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[ScienceDirect Publication: Acta Materialia] Inverse Design of High-Performance Glasses Through an Encoder-Decoder Machine Learning Approach Toward Materials Discovery: Application to Oxynitride Glasses

ScienceDirect Publication: Acta Materialia — Tue, 30 Dec 2025 18:31:09 GMT

Publication date: Available online 29 December 2025

Source: Acta Materialia

Author(s): Alexis Duval, Eric Robin, Patrick Houizot, Tanguy Rouxel

[ScienceDirect Publication: Journal of Energy Storage] Machine learning-aided prediction and optimization of specific capacitance in functionalized GO-based Mn/Fe co-doped Bi₂O₃ nanocomposites

ScienceDirect Publication: Journal of Energy Storage — Tue, 30 Dec 2025 12:42:28 GMT

Publication date: 10 February 2026

Source: Journal of Energy Storage, Volume 146

Author(s): Vijay A. Mane, Kartik M. Chavan, Sushant S. Munde, Dnyaneshwar V. Dake, Nita D. Raskar, Ramprasad B. Sonpir, Pravin V. Dhole, Ketan P. Gattu, Sandeep B. Somvanshi, Pavan R. Kayande, Jagruti S. Pawar, Babasaheb N. Dole

[ScienceDirect Publication: Journal of Energy Storage] Time-resolved impedance spectroscopy analysis of stable lithium iron phosphate cathode with enhanced electronic/ionic conductivity and ion diffusion characteristics

ScienceDirect Publication: Journal of Energy Storage — Tue, 30 Dec 2025 12:42:28 GMT

Publication date: 10 February 2026

Source: Journal of Energy Storage, Volume 146

Author(s): Jiguo Tu, Yan Li, Libo Chen, Dongbai Sun

[cond-mat updates on arXiv.org] Thermodynamic Phase Stability, Structural, Mechanical, Optoelectronic, and Thermoelectric Properties of the III-V Semiconductor AlSb for Energy Conversion Applications

ScienceDirect Publication: Acta Materialia — Tue, 30 Dec 2025 18:31:09 GMT

arXiv:2512.22277v1 Announce Type: new +My Customized Papers (Auto-Filtered)https://github.com/your_username/your_repoAggregated research papers based on keywords

[ScienceDirect Publication: Journal of Energy Storage] Machine learning-aided prediction and optimization of specific capacitance in functionalized GO-based Mn/Fe co-doped Bi₂O₃ nanocomposites

ScienceDirect Publication: Journal of Energy Storage — Tue, 30 Dec 2025 12:42:28 GMT

Publication date: 10 February 2026

Source: Journal of Energy Storage, Volume 146

[ScienceDirect Publication: Journal of Energy Storage] Time-resolved impedance spectroscopy analysis of stable lithium iron phosphate cathode with enhanced electronic/ionic conductivity and ion diffusion characteristics

ScienceDirect Publication: Journal of Energy Storage — Tue, 30 Dec 2025 12:42:28 GMT

Publication date: 10 February 2026

Source: Journal of Energy Storage, Volume 146

Author(s): Jiguo Tu, Yan Li, Libo Chen, Dongbai Sun

[cond-mat updates on arXiv.org] Thermodynamic Phase Stability, Structural, Mechanical, Optoelectronic, and Thermoelectric Properties of the III-V Semiconductor AlSb for Energy Conversion Applications

cond-mat updates on arXiv.org — Tue, 30 Dec 2025 05:00:00 GMT

arXiv:2512.22277v1 Announce Type: new Abstract: This study presents a first principles investigation of the structural, thermodynamic, electronic, optical and thermoelectric properties of aluminum antimonide (AlSb) in its cubic (F-43m) and hexagonal (P63mc) phases. Both structures are dynamically and mechanically stable, as confirmed by phonon calculations and the Born Huang criteria. The lattice constants obtained using the SCAN and PBEsol functionals show good agreement with experimental data. The cubic phase exhibits a direct band gap of 1.66 to 1.78 eV, while the hexagonal phase shows a band gap of 1.48 to 1.59 eV, as confirmed by mBJ and HSE06 calculations. Under external pressure, the band gap decreases in the cubic phase and increases in the hexagonal phase due to different s p orbital hybridization mechanisms. The optical absorption coefficient reaches 1e6 cm-1, which is comparable to or higher than values reported for other III V semiconductors. The Seebeck coefficient exceeds 1500 microV per K under intrinsic conditions, and the thermoelectric performance improves above 600 K due to enhanced phonon scattering and lattice anharmonicity. The calculated formation energies (-1.316 eV for F-43m and -1.258 eV for P63mc) confirm that the cubic phase is thermodynamically more stable. The hexagonal phase exhibits higher anisotropy and lower lattice stiffness, which is favorable for thermoelectric applications. These results demonstrate the strong interplay between crystal symmetry, phonon behavior and charge transport, and provide useful guidance for the design of AlSb based materials for optoelectronic and energy conversion technologies.

[cond-mat updates on arXiv.org] The Role of THz Phonons in the Ionic Conduction Mechanism of $Li_7La_3Zr_2O_{12}$ Polymorphs

cond-mat updates on arXiv.org — Tue, 30 Dec 2025 05:00:00 GMT

arXiv:2512.22427v1 Announce Type: new Abstract: Superionic conduction in solid-state materials is governed not only by static factors, such as structure and composition, but also by dynamic interactions between the mobile ion and the crystal lattice. Specifically, the dynamics of lattice vibrations, or phonons, have attracted interest because of their hypothesized ability to facilitate superionic conduction. However, direct experimental measurement of the role of phonons in ionic conduction is challenging due to the fast intrinsic timescales of ion hopping and the difficulty of driving relevant phonon modes, which often lie in the low-energy THz regime. To overcome these limitations, we use laser-driven ultrafast impedance spectroscopy (LUIS). LUIS resonantly excites phonons using a THz field and probes ion hopping with picosecond time resolution. We apply LUIS to understand the dynamical role of phonons in $Li_7La_3Zr_2O_{12}$ (LLZO). When in its cubic phase (c-LLZO), this garnet-type solid electrolyte has an ionic conductivity two orders of magnitude greater than its tetragonal phase (t-LLZO). T-LLZO is characterized by an ordered and filled $Li^+$ sublattice necessitating synchronous ion hopping. In contrast, c-LLZO is characterized by a disordered and vacancy-rich $Li^+$ sublattice, and has a conduction mechanism dominated by single hops. We find that, upon excitation of phonons in the 0.5-7.5 THz range, the impedance of t-LLZO experiences a longer ion hopping decay signal in comparison to c-LLZO. The results suggest that phonon-mediated ionic conduction by THz modes may lead to larger ion displacements in ordered and fully occupied mobile ion sublattices as opposed to those that are disordered and vacancy-rich. Overall, this work highlights the interplay between static and dynamic factors that enables improved ionic conductivity in otherwise poorly conducting inorganic solids.

[cond-mat updates on arXiv.org] Thermally Activated Non-Affine Rearrangements in Amorphous Glass: Emergence of Intrinsic Length Scales

cond-mat updates on arXiv.org — Tue, 30 Dec 2025 05:00:00 GMT

arXiv:2512.22530v1 Announce Type: new Abstract: We present a systematic study of temperature-driven nonaffine rearrangements in a model amorphous solid across the full thermodynamic range, from a high-temperature liquid, through supercooled and sub-glass regimes, into deep glassy states. The central result is a quantitative characterisation of the componentwise nonaffine residual displacements, obtained by subtracting local affine maps from particle displacements. For each state point the tails of the probability distributions of these nonaffine components display clear exponential decay; linear fits to the logarithm of the tail region yield characteristic nonaffine length scales {\xi}NA,x and {\xi}NA,y , which quantify the spatial extent of purely nonaffine, local rearrangements. To compare with other length scales, we compute van Hove distributions Gx(ux), Gy (uy ) which capture the full particle displacement field (coherent affine-like motion plus residuals). A robust, key finding is that the van Hove length scale consistently exceeds the filtered nonaffine length scale, i.e. {\xi}VH > {\xi}NA, across all temperatures, state points, and densities we studied. The nonaffine length {\xi}NA quantifies the distance over which complex deformation occurs, specifically nonlinear and anharmonic responses, irreversible (plastic) rearrangements, topological non-recoverable particle rearrangements, and other residual motions that cannot be represented by a local affine map. Moreover, near equality of {\xi}NA,x and {\xi}NA,y in all conditions provides further evidence that nonaffine rearrangements propagate isotropically under thermally driven deformation in contrast to externally driven shear.

[cond-mat updates on arXiv.org] Fast and accurate Fe-H machine-learning interatomic potential for elucidating hydrogen embrittlement mechanisms

cond-mat updates on arXiv.org — Tue, 23 Dec 2025 05:00:00 GMT

arXiv:2512.22934v1 Announce Type: new @@ -63,4 +63,4 @@ Abstract: Reinforcement Learning from Verifiable Rewards (RLVR) has emerged as a Abstract: Nonreciprocal active matter systems typically feature an asymmetric role among interacting agents, such as a pursuer-evader relationship. We propose a multi-species nonreciprocal active matter model that is invariant under permutations of the particle species. The nonreciprocal, yet symmetric, interactions emerge from a constant phase shift in the velocity alignment interactions, rather than from an asymmetric coupling matrix. This system possessing permutation symmetry displays rich collective behaviors, including a species-mixed chiral phase with quasi-long-range polar order and a species separation phase characterized by vortex cells. The system also displays a coexistence phase of the chiral and the species separation phases, in which intriguing dynamic patterns emerge. These rich collective behaviors are a consequence of the interplay between nonreciprocity and permutation symmetry.

[cond-mat updates on arXiv.org] Enhanced sinterability and in vitro bioactivity of diopside through fluoride doping

cond-mat updates on arXiv.org — Tue, 23 Dec 2025 05:00:00 GMT

arXiv:2512.19014v1 Announce Type: new Abstract: In this work, diopside (CaMgSi2O6) was doped with fluoride at a level of 1 mol.%, without the formation of any second phase, by a wet chemical precipitation method. The sintered structure of the synthesized nanopowders was studied by X-ray diffraction, Fourier transform infrared spectroscopy and field-emission scanning electron microscopy. Also, the samples' in vitro apatite-forming ability in a simulated body fluid was comparatively evaluated by electron microscopy, inductively coupled plasma spectroscopy and Fourier transform infrared spectroscopy. According to the results, the material's sinterability was improved by fluoride doping, as realized from the further development of sintering necks. It was also found that compared to the undoped bioceramic, a higher amount of apatite was deposited on the surface of the doped sample. It is concluded that fluoride can be considered as a doping agent in magnesium-containing silicates to improve biological, particularly bioactivity, behaviors.

[cond-mat updates on arXiv.org] Bridging the divide: Economic exchange and segregation in dual-income cities

cond-mat updates on arXiv.org — Tue, 23 Dec 2025 05:00:00 GMT

arXiv:2512.18680v1 Announce Type: cross Abstract: Segregation is a growing concern around the world. One of its main manifestations is the creation of ghettos, whose inhabitants have difficult access to well-paid jobs, which are often located far from their homes. In order to study this phenomenon, we propose an extension of Schelling's model of segregation to take into account the existence of economic exchanges. To approximate a geographical model of the city, we consider a small-world network with a defined real estate market. The evolution of the system has also been studied, finding that economic exchanges follow exponential laws and relocations are approximated by power laws. In addition to this, we consider the existence of delays in the actions of the agents, which mainly affect the happiness of those with fewer economic resources. Besides, the size of the economic exchange plays a crucial role in overall segregation. Despite its simplicity, we find that our model reproduces real-world situations such as the separation between favoured and handicapped economic areas, the importance of economic contacts between them to improve the distribution of wealth, and the existence of efficient and cheap transport to break the poverty cycles typical of disadvantaged zones.

[cond-mat updates on arXiv.org] Information Supercurrents in Chiral Active Matter

cond-mat updates on arXiv.org — Tue, 23 Dec 2025 05:00:00 GMT

arXiv:2512.16884v2 Announce Type: replace -Abstract: Recent minimalist modeling has demonstrated that overdamped polar chiral active matter can support emergent, inviscid Euler turbulence, despite the system's strictly dissipative microscopic nature. In this letter, we establish the statistical mechanical foundation for this emergent inertial regime by deriving a formal isomorphism between the model's agent dynamics and the overdamped Langevin equation for disordered Josephson junctions. We identify the trapped agent state as carrying non-dissipative (phase rigidity) information supercurrents, analogous to a macroscopic superconducting phase governed by the Adler equation. The validity of this mapping is confirmed analytically and empirically by demonstrating a disorder-broadened Adler-Ohmic crossover in the system's slip velocity, corresponding to the saddle-node bifurcation of phase-locking systems. These results define the new minimal chiral flocking model as a motile, disordered Josephson array, bridging active turbulence and superconductivity.

[Communications Materials] In situ polymerization for high performance solid-state lithium-sulfur batteries

Communications Materials — Tue, 23 Dec 2025 00:00:00 GMT

Communications Materials, Published online: 23 December 2025; doi:10.1038/s43246-025-01035-3

Solid-state lithium-sulfur batteries promise high energy density, long-term performance, and enhanced safety, but face challenges with interfacial issues due to poor solid–solid contact. Here, the authors review the benefits and challenges of in situ polymerization, discussing its potential to enhance electrode-electrolyte integration and improve battery performance, and proposing future prospects for multifunctional polymer solid-state electrolytes.

[ChemRxiv] Molecular Dynamics Simulations for Organic Chemists – It’s About Time!

ChemRxiv — Tue, 23 Dec 2025 00:00:00 GMT

Molecular dynamics simulations model chemical reactions as continuous changes in molecular structure over time in-stead of static minima and transition states. This perspective argues that time-dependent structural change is a crucial, but often overlooked, mechanistic feature as many reactions simply do not follow a single, equilibrated minimum-energy path. We highlight examples where traditional transition state theory fails, typically cases involving short-lived interme-diates, non-equilibrium solvation, momentum-controlled selectivity, post-transition state bifurcations, and “hidden” dy-namic intermediates and show how molecular dynamics can reveal the actual sequence of structural change which gov-erns a reaction outcome. We also discuss emerging machine learning-based molecular dynamics which have found appli-cations in photochemistry and solvent modelling. While molecular dynamics will not replace methods based on transi-tion state theory, it offers organic chemists a time-resolved view of molecular structure which can be crucial to under-standing a given reaction. However, a central barrier for organic chemists is to understand when and why to apply an ad-vanced computational technique such as molecular dynamics simulations. In this perspective, we aim to introduce the methodology in sufficient detail to enable organic chemists to make this assessment and gain an appreciation for the im-portance of time in reaction mechanisms.

[ChemRxiv] Characterisation and immobilisation study of the Haloperoxidase from Curvularia inaequalis: application to phenol derivatives

ChemRxiv — Tue, 23 Dec 2025 00:00:00 GMT

In the past decades, usage of enzymes to catalyse halogenation reactions has emerged as a greener approach compared to usual ones using toxic reagents and yielding to a bad atom economy. Vanadium dependent haloperoxidases (VDHals) are the most commonly used enzymes for such transformations in organic chemistry due to their robustness. Among them, haloperoxidase from Curvularia inaequalis (CiVCPO) is the most cited in the literature but only barely characterized aside from its substrate spectrum and kinetic parameters. In the present study, we evaluated the melting temperature, thermostability, thermoactivity and solvent stability of CiVCPO in order to have a better overview of its potential in organic synthesis. We have also performed the first immobilisation study of this enzyme on 3 types of supports: 3 EziG™ glass beads coated with different polymers, 5 Relizyme™ polymethacrylate beads with different functional groups, the commercial Amberlite IRA900 and Dowex 50WX8, and 3 metal-organic frameworks from the UiO-66(Zr) family. As a result, we could retain 50% of total immobilized activity on 2 Relizyme supports (ethylamine (EA403) & iminodiacetic (IDA403), with 55% activity kept over 5 recycling steps. The unconventional UiO-66(Zr) family also proved to be an interesting material for this enzyme. Finally, we show that free enzyme and supported enzyme are suitable for bromination and chlorination of a range of phenolic compounds with excellent yields with up to 65% conversion in 24 h in the tested conditions.

[Nature Nanotechnology] Nanostructured niobium-doped nickel-rich multiphase positive electrode active material for high-power lithium-based batteries

Nature Nanotechnology — Tue, 23 Dec 2025 00:00:00 GMT

Nature Nanotechnology, Published online: 23 December 2025; doi:10.1038/s41565-025-02092-y

A two-step doping strategy for preparing Nb-doped Ni-rich positive electrode active materials forms nanosized grains and enables reversible multiphase transitions, improving lithium-ion transport and high-power performance of Li-based batteries.

[ChemRxiv] Study of anion transport by amide-based macrocycles of different sizes

ChemRxiv — Tue, 23 Dec 2025 00:00:00 GMT

Synthetic anion receptors can transport anions across lipid bilayer membranes. Many anion transporters have been reported, including macrocyclic compounds. However, there are no systematic studies on how the size of macrocycles impacts their anion transport activity and selectivity. Therefore, we prepared eight amide-based macrocyclic compounds with ring sizes ranging from 18 to 26 atoms, as well as four bis-amides. We studied these compounds as anion receptors using chloride titrations and molecular modelling, and as anion transporters using liposomes with various fluorescent probes. Neither the size of the macrocycles nor the affinity for chloride were found to be determining factors for chloride transport activity; preorganisation appears to play a more important role. Fluorination was found to have a clear positive effect on anion transport rates, with the bis-amides performing surprisingly well compared to the macrocycles. The smallest non-fluorinated macrocycle exhibited selectivity for chloride over hydroxide and nitrate, whereas the pentafluorophenyl bis-amide demonstrated effective transport of bicarbonate and nitrate, likely due to anion-pi interactions in addition to hydrogen bonding. The insights from this study will shape the design of future anionophores.

[ChemRxiv] Ion-Conductive Vitrimers Based on Backbone-Type Triazolium Poly(ionic liquid)s: Counterion-Dependent Dynamics and Backbone Flexibility

ChemRxiv — Tue, 23 Dec 2025 00:00:00 GMT

To simultaneously achieve high ionic conductivity and recyclability, vitrimers were prepared using backbone-type triazolium poly(ionic liquid)s (TPILs) that integrate ionic transport with dynamic network rearrangement via trans-N-alkylation. TPIL elastomers bearing I⁻, BF₄⁻, PF₆⁻, and TFSI⁻ counteranions were synthesized from “clickable” ionic liquid monomers, and their glass transition temperature (Tg), ionic conductivity, and vitrimeric dynamics were compared. Only the I⁻-based network exhibited stress relaxation at 170 °C, indicating that nucleophilic anions are important for bond exchange. However, a trade-off was observed between ionic transport and dynamic network rearrangement. Furthermore, mixed-anion TPIL elastomers using I⁻+TFSI⁻ exhibited lower Tg and higher ionic conductivity than I⁻-based elastomer, while still maintaining vitrimer-like relaxation. The segmental relaxation was decoupled from Arrhenius-type bond-exchange dynamics. Ionic conduction was dominated by segmental motion, with minimal contribution from cross-link exchange. This design combining flexible polymer backbones and cooperative anion engineering can create recyclable, highly conductive polymer electrolytes.

[ChemRxiv] Advances in Calcium Isotope Purification and Analysis Using Cutting-Edge Signal Amplifiers for Matrix-Diverse Reference Materials

ChemRxiv — Tue, 23 Dec 2025 00:00:00 GMT

Stable calcium (Ca) isotopes are increasingly applied across geosciences, medical sciences, ecology, paleontology, and archaeology. However, the deployment speed of Ca isotope applications worldwide is hampered by three major challenges: 1) the necessity for complex Ca purification procedures prior to analysis; 2) expensive instrumentation (typically TIMS or ICP-MS) requiring specific configurations and fine-tuning to generate reliable data; and 3) the exhaustion of some of the most widely used reference materials for cross-laboratory comparisons. In this study we present methodological advances aimed at lifting some of these barriers. First, we refined existing chromatography methods for purifying Ca by developing a branching procedure based on commercially available labware to allow faster method transfer and to minimize resin and reagent consumption for a variety of sample matrices. Our adjustments drastically improved strontium (Sr) separation from Ca, including for Sr-rich samples such as seawater. Second, we explored the potential of 10¹³Ω Faraday cup amplifiers for improving Ca isotope measurements. Our results show improved precision in 43Ca measurements under low ionic transmission configurations with δ43/42Ca standard deviation value reduced by half. This expands the list of ICP-MS configurations capable of producing reliable Ca isotope measurements and delineates a path for less sample-destructive methods (i.e., lower Ca analytical requirements). These amplifiers also markedly enhanced the correction of Sr²⁺ interferences typically affecting Ca ion beams. In this configuration, accurate and precise Ca isotopic measurements were obtained without prior Sr removal for Sr/Ca concentration ratios up to 10⁻². Lastly, using these technical advancements we analyzed existing and new international certified reference materials (SRM1486, SRM1400, IAPSO, CACB-1, DOLT-5, DORM-5, TORT-3), complementing existing and out-of-stock standards of the Ca isotope toolbox, notably for Ca carbonate and marine soft tissues. Together, these advances open the door of Ca isotope research to more laboratories and pave the way for future developments and applications.

[ChemRxiv] Predicting Sequence Dependent Fluorescence with Classic Machine Learning Models

ChemRxiv — Tue, 23 Dec 2025 00:00:00 GMT

Terminally labeled DNA oligonucleotides have wide applications in modern biology and biotechnological applications. It has been observed that the fluorescent intensity of light released from these fluorescent labels is heavily influenced by the terminal sequence of nucleotides. Recent studies have assayed and published the raw fluorescent values of Cy3 and Cy5 as a function of the most adjacent 5 nucleotides resulting in 1024 data points. While experimentally tractable, an increase in the sequence space will vastly increase the experimental and time cost. Machine Learning is well suited to addressing the issue of experimental tractability however there is a wide design space in the choice of algorithms. In this work we use classic machine learning models such as Support Vector Machine, Multilayer Perceptrons and Random Forests to both predict the raw intensity value and classify the intensity magnitude of the fluorophore using the sequence as input. We demonstrate that the performance of these models is heavily dependent on the numerical transformation of the sequence and that Random Forest consistently outperforms all other models in both regression and classification tasks irrespective of the sequence transformation.

[ChemRxiv] Machine learning driven advances in molecular dynamics of bulk and interfacial aqueous systems

ChemRxiv — Tue, 23 Dec 2025 00:00:00 GMT

Molecular dynamics (MD) simulations have been widely applied to investigate various physical and chemical processes in aqueous and interfacial environments, which are crucial for the design of energy materials and for understanding several chemical processes at the heart of life itself. However, the applicability of MD simulations has been constrained by several inherent challenges, including the accuracy of force fields, limitations in simulation size and timescales. One promising solution to these challenges is the integration of machine learning (ML) methods, both for improved description of the nature of interactions in aqueous systems as well as for enhanced sampling. In this review, we discuss the principles, implementation, and applications of ML force fields (MLFFs) and ML enhanced sampling methods to the study of aqueous, interfacial systems. We discuss five key categories of applications that use MLFFs, ML-enhanced sampling, and ML-driven data analytics. We first discuss how MLFFs are enabling quantum level accuracy at classical level cost for large scale simulations of complex aqueous and interfacial systems, and then highlight how coupling them with enhanced sampling and advanced data analytics, especially graph based approaches for featurizing such systems, can be used both for enhancing simulations and for understanding them by yielding reliable low dimensional reaction coordinates that improve the interpretation of high dimensional MD data. The discussed applications include investigations into the structure and dynamics of bulk water and aqueous interfaces, proton transfer, catalysis, phase transitions, and the prediction of vibrational spectra. In each case, we highlight how ML-based methods enable simulations that were previously computationally prohibitive and provide new physical insights into aqueous solutions and interfaces. For instance, MLFFs allow nanosecond-scale simulations with thousands of atoms while maintaining quantum chemistry accuracy. Additionally, ML-enhanced sampling facilitates the crossing of large reaction barriers and enables the exploration of extensive configuration spaces. Moreover, ML models trained on simulation data uncover previously overlooked factors, such as the role of solvent dynamics in phase transitions. The combination of MLFFs with enhanced sampling techniques makes the calculation of high-dimensional free energy surfaces feasible, significantly improving our understanding of chemical reactions. Finally, we discuss the current challenges in this field and outline potential future research directions to further advance the integration of ML in MD simulations.

[RSC - Chem. Sci. latest articles] Automated Closed-Loop Continuous Flow Block Copolymer Synthesizer

RSC - Chem. Sci. latest articles — Tue, 23 Dec 2025 00:00:00 GMT

Chem. Sci., 2026, Accepted Manuscript
DOI: 10.1039/D5SC07307C, Edge Article

Open Access

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence.

WeiNian Wong, Daniel Phillips, MD Taifur Rahman, Tanja Junkers
A fully automated continuous flow synthesizer for diblock copolymer (BCP) synthesis was constructed comprising elements of flow chemistry, automation, machine learning and in-line monitoring. A new method using in-line FTIR...
The content of this RSS Feed (c) The Royal Society of Chemistry

[RSC - Chem. Sci. latest articles] Node-Equivariant Message Passing for Efficient and Accurate Machine Learning Interatomic Potentials

RSC - Chem. Sci. latest articles — Tue, 23 Dec 2025 00:00:00 GMT

Chem. Sci., 2026, Accepted Manuscript
DOI: 10.1039/D5SC07248D, Edge Article

Open Access

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence.

Yaolong Zhang, Hua Guo
Machine learned interatomic potentials, particularly equivariant message-passing (MP) models, have demonstrated high fidelity in representing first-principles data, revolutionizing computational studies in materials science, biophysics, and catalysis. However, these equivariant MP...
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[RSC - Chem. Sci. latest articles] Robust Janus-Faced Quasi-Solid-State Electrolytes Mimicking Honeycomb for Fast Transport and Adequate Supply of Sodium Ions

RSC - Chem. Sci. latest articles — Tue, 23 Dec 2025 00:00:00 GMT

Chem. Sci., 2026, Accepted Manuscript
DOI: 10.1039/D5SC08536E, Edge Article

Open Access

This article is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported Licence.

Fang Chen, Yadan Xie, Zhoubin Yu, Na Li, Xiang Ding, Yu Qiao
Quasi-solid-state electrolytes are one of the most promising alternative candidate for traditional liquid state electrolytes with fast ion transport rate, high mechanical strength and wide temperature adaptation. Here we designed...
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[Joule] Machine learning-driven interface material design for high-performance perovskite solar cells with scalability and band-gap universality

Joule — Tue, 23 Dec 2025 00:00:00 GMT

Machine learning-driven molecular design integrating correlation analysis, clustering, and LASSO regression discovers BIPA, an efficient interface modifier that concurrently passivates defects, optimizes band alignment, and enhances perovskite crystallinity. This strategy enables high-efficiency, scalable, and stable perovskite solar cells across a wide band-gap range (1.55–1.85 eV).

[Cell Reports Physical Science] A global thermodynamic-kinetic model capturing the hallmarks of liquid-liquid phase separation and amyloid aggregation

Cell Reports Physical Science — Tue, 23 Dec 2025 00:00:00 GMT

Bhandari et al. develop a unified thermodynamic-kinetic framework that integrates liquid-liquid phase separation (LLPS) with amyloid aggregation. By considering oligomerization and fibrillization in both protein-poor and protein-rich phases, the model reproduces concentration-dependent aggregation kinetics and rationalizes the seemingly contradictory reports on whether LLPS accelerates or suppresses fibril formation.

[ChemRxiv] Maximizing Machine Learning Interatomic Potential Transferability for the Discovery of the Novel Stellated Octadecagon Bi18-Pt24 Cage Structure

ChemRxiv — Tue, 23 Dec 2025 00:00:00 GMT

Achieving true transferability remains the central challenge for Machine Learning Interatomic Potentials (ML-IAPs) in modeling complex bimetallic nanoclusters across their vast potential energy surfaces. We systematically investi- gate data selection strategies to optimize the Chebyshev Interaction Model for Efficient Simulation (ChIMES) po- tential for the Bi-Pt nanoclusters by comparing three innovative sampling methods: Principal Component Analysis (PCA)/k-means (structural diversity), t-distributed Stochastic Neighbor Embedding (t-SNE)/k-means (force-space di- versity), and hierarchical clustering. Quantitatively, the PCA/k-means strategy proved most effective for global ac- curacy, yielding the lowest force errors and achieving energy root mean square errors (RMSE) values competitive with DFT, demonstrating excellent accuracy (19.16 meV/atom). Structural validation on 34 unique DFT-optimized isomers further confirmed the potential’s high fidelity, with the best model PCA/k-means reproducing structures with an average root mean square deviation (RMSD) of 0.10 Å. However, the t-SNE methods, by maximizing diversity in the force space, demonstrated superior extrapolative power, leading to the more precise prediction of a novel stel- lated octadecagon Bi18Pt24 cage structure, demonstrating the potential for exploring previously unseen morphologies. Our results establish a clear methodology for strategic data sampling that successfully maximizes ML-IAP transfer- ability, providing an accurate and computationally efficient tool that accelerates the theoretical discovery of complex bimetallic architectures.

[ChemRxiv] High-Performance Semiempirical Excited-State Molecular Dynamics: A Step Toward Data-Driven Photodynamics

ChemRxiv — Tue, 23 Dec 2025 00:00:00 GMT

We introduce excited-state molecular dynamics (ESMD) in PYSEQM, a GPU-accelerated semiempirical quantum chemistry engine implemented in PyTorch. The new module enables Born-Oppenheimer (single-surface) dynamics using configuration-interaction singles and random phase approximation for excited-states, allowing long trajectories and large statistical ensembles to be simulated efficiently on a single GPU. We also implement an extended-Lagrangian ESMD (XL-ESMD) scheme that propagates auxiliary electronic variables, enabling relaxed ground and excited-state convergence thresholds without compromising energy conservation. The ESMD implementation scales smoothly from small chromophores to a nearly 900-atom dendrimer (taking 6.5 s per ESMD step). PYSEQM also supports batched execution, allowing many geometries or trajectories to be evaluated in a single GPU launch, substantially increasing throughput and making ensemble-based protocols routine. As a demonstration, we compute absorption, emission, and infrared spectra from trajectories propagated on the ground and first excited states, illustrating practical utility of PYSEQM. The XL-ESMD scheme yields identical spectra at significantly lower computational cost, establishing the role of extended Lagrangian based dynamics for efficient ESMD simulations. Beyond raw performance, PYSEQM’s Pytorch foundation provides automatic differentiation for forces, efficient GPU batching, and seamless interfacing with machine learning models. These capabilities position PYSEQM as practical platform for machine learning-augmented excited-state dynamics and lay the foundation for future data-driven nonadiabatic ESMD modeling of ultrafast spectroscopic probes.

[Applied Physics Letters Current Issue] Mixed ionic–electronic conductor based on B 16 framework

Applied Physics Letters Current Issue — Tue, 23 Dec 2025 00:00:00 GMT

Mixed ionic–electronic conductors (MIECs) are essential materials for next-generation energy storage and conversion systems. However, several limitations—including the scarcity of intrinsic MIEC materials, low ionic conductivity, and a narrow operational temperature range—restrict their practical use. Based on the experimentally synthesized MgB₄ crystal, this study designs a B₁₆ covalent framework with three-dimensionally connected channels by theoretically removing Mg atoms through computational methods. Using first-principles calculations and machine learning molecular dynamics simulations, we systematically explore its compounds' potential as intrinsic MIEC materials. The results indicate that the B₁₆ framework can stably host and transport Li⁺, Be²⁺, and Al³⁺ ions with different valences. The formations of LiB₂, BeB₄, and AlB₈ enter superionic states at 1200, 1700, and 1400 K, respectively, with ionic conductivities reaching 10⁻² S/cm, and the optimal electronic conductivities approaching 10⁴ S/cm. The framework shows good structural stability: the volume change after ion insertion is less than 12.4%, and its mechanical properties (for example, a shear modulus of 47.8 GPa) are comparable to those of traditional electrode materials like LiFePO₄ and NCM. Through defect engineering, LiB₂ with 12.5% crystal defects can lower the superionic transition temperature to 400 K while maintaining a high ionic conductivity of 1.65 × 10⁻¹ S/cm. This study offers a viable approach to designing MIEC materials and demonstrates significant potential for applications such as high-temperature solid-state batteries and electrochemical sensors.

[iScience] A Multicenter Multimodel Habitat Radiomics Model for Predicting Immunotherapy Response in Advanced NSCLC

iScience — Tue, 23 Dec 2025 00:00:00 GMT

Robust predictive biomarker is critical for identifying NSCLC patients who may benefit from immunotherapy. This study developed a CT-based habitat model using 590 advanced NSCLC cases. The model was constructed in contrast-enhanced CT images and validated on an independent cohort with non-contrast CT. Tumor volumes were segmented into three subregions via K-means clustering. Radiomic features were extracted from each habitat and used to build predictive models with six machine learning classifiers.The ExtraTrees-based habitat model demonstrated superior predictive performance in the test cohort(AUC = 0.814).

[ACS Nano: Latest Articles (ACS Publications)] [ASAP] Regulating Solvation Structure and Ion Transport via Lewis-Base Dual-Functional Covalent Organic Polymer Separators for Dendrite-Free Li-Metal Anodes

ACS Nano: Latest Articles (ACS Publications) — Mon, 22 Dec 2025 20:52:05 GMT

ACS Nano

DOI: 10.1021/acsnano.5c14722

[ACS Nano: Latest Articles (ACS Publications)] [ASAP] Highly Selective Lithium-Ion Separation by Regulating Ion Transport Energy Barriers of Vermiculite Membranes

ACS Nano: Latest Articles (ACS Publications) — Mon, 22 Dec 2025 18:30:41 GMT

ACS Nano

DOI: 10.1021/acsnano.5c17718

[Wiley: Advanced Intelligent Discovery: Table of Contents] A Physics Constrained Machine Learning Pipeline for Young's Modulus Prediction in Multimaterial Hyperelastic Cylinders Guided by Contact Mechanics

Wiley: Advanced Intelligent Discovery: Table of Contents — Mon, 22 Dec 2025 17:43:04 GMT

Advanced Intelligent Discovery, EarlyView.

[ACS Nano: Latest Articles (ACS Publications)] [ASAP] Multianion Synergism Boosts High-Performance All-Solid-State Lithium Batteries

ACS Nano: Latest Articles (ACS Publications) — Mon, 22 Dec 2025 14:37:35 GMT

ACS Nano

DOI: 10.1021/acsnano.5c12987

[Wiley: Advanced Functional Materials: Table of Contents] Sulfur‐Doped Bi2O3 Nanorods with Asymmetric S−Bi−O Active Sites for Highly Efficient Electrosynthesis of Formic Acid

Wiley: Advanced Functional Materials: Table of Contents — Mon, 22 Dec 2025 14:14:10 GMT

Advanced Functional Materials, EarlyView.

[The Journal of Physical Chemistry C: Latest Articles (ACS Publications)] [ASAP] Density Effects on the Thermal Decomposition of LLM-105 Explored by Neural Network Potential

The Journal of Physical Chemistry C: Latest Articles (ACS Publications) — Mon, 22 Dec 2025 14:01:00 GMT

The Journal of Physical Chemistry C

DOI: 10.1021/acs.jpcc.5c06140

[Accounts of Chemical Research: Latest Articles (ACS Publications)] [ASAP] Accelerating Materials Discovery Through Sparse Gaussian Process Machine Learning Potentials

Accounts of Chemical Research: Latest Articles (ACS Publications) — Mon, 22 Dec 2025 13:59:15 GMT

Accounts of Chemical Research

DOI: 10.1021/acs.accounts.5c00667

[Wiley: Small: Table of Contents] Revealing Electronic Structure–Chemisorption Relationships for Accelerated Discovery of Aqueous Zinc Battery Additives Through Machine Learning

Wiley: Small: Table of Contents — Mon, 22 Dec 2025 12:24:02 GMT

Small, EarlyView.

[Wiley: Small: Table of Contents] Ultra‐High Capacity Density Lithium Metal Battery is Effectuated via Coupling Single Lithium‐Ion Conductor and Lithium‐Ion Sieve Within Yttrium‐Organic Framework

Wiley: Small: Table of Contents — Mon, 22 Dec 2025 11:34:32 GMT

Small, EarlyView.

[Wiley: Small: Table of Contents] Boosting Gaseous Mercury Detection via Photooxidation‐Enrichment Fluorescent Membrane with Machine Learning

Wiley: Small: Table of Contents — Mon, 22 Dec 2025 11:29:41 GMT

Small, EarlyView.

[Recent Articles in Phys. Rev. Lett.] Gate-Tunable Spectrum and Charge Dispersion Mitigation in a Graphene Superconducting Qubit

Recent Articles in Phys. Rev. Lett. — Mon, 22 Dec 2025 10:00:00 GMT

Author(s): Nicolas Aparicio, Simon Messelot, Edgar Bonet-Orozco, Eric Eyraud, Kenji Watanabe, Takashi Taniguchi, Johann Coraux, and Julien Renard

Controlling the energy spectrum of quantum-coherent superconducting circuits, i.e., the energies of excited states, the circuit anharmonicity, and the states’ charge dispersion, is essential for designing performant qubits. This control is usually achieved by adjusting the circuit’s geometry. In sit…

[Phys. Rev. Lett. 135, 266001] Published Mon Dec 22, 2025

[Proceedings of the National Academy of Sciences: Physical Sciences] SR-LLM: An incremental symbolic regression framework driven by LLM-based retrieval-augmented generation

Proceedings of the National Academy of Sciences: Physical Sciences — Mon, 22 Dec 2025 08:00:00 GMT

Proceedings of the National Academy of Sciences, Volume 122, Issue 52, December 2025.
SignificanceScientists have long sought to derive models from extensive observational input–output data, ensuring these models accurately capture the underlying mapping from inputs to outputs while remaining interpretable to humans through clear meanings. ...

[Wiley: Angewandte Chemie International Edition: Table of Contents] Potential‐Tailored Aryl–Sodium Reagent with Moderate Ionic Binding Strength Enables Precise yet Fast Hard Carbon Presodiation

Wiley: Angewandte Chemie International Edition: Table of Contents — Mon, 22 Dec 2025 05:36:53 GMT

Angewandte Chemie International Edition, EarlyView.

[npj Computational Materials] Machine learning interatomic potential can infer electrical response

npj Computational Materials — Mon, 22 Dec 2025 00:00:00 GMT

npj Computational Materials, Published online: 22 December 2025; doi:10.1038/s41524-025-01911-z

Machine learning interatomic potential can infer electrical response

[Applied Physics Letters Open Issues] High-throughput sensing of single-cell properties using parallel multi-stage cell deformation

Applied Physics Letters Open Issues — Mon, 22 Dec 2025 00:00:00 GMT

Biophysical properties of single cells serve as label-free, noninvasive biomarkers for phenotyping. However, most techniques measure quantities dependent on multiple biophysical properties rather than individual ones, limiting their biological/clinical relevance. Here, we present a single-cell biophysical phenotyping technique that quantifies size (Dc) and elastic modulus (E) of cells deforming at different levels along constriction microchannels. A physical model is developed to resolve features of multiple deformation stages into Dc and E. Parallel-channel device design achieves a reasonably high throughput of ∼10⁴ cells/min. The measurement employs lock-in amplification-assisted electrokinetic sensing via embedded electrodes across three channel sections with varying constriction widths, inducing distinct cell deformations. We demonstrate the technique by profiling normal and cancerous breast cell lines (MCF-10A, MCF-7, and MDA-MB-231), as well as drug-treated cancer cells (cytochalasin D, cetuximab, and lysophosphatidic acid). The biophysical phenotyping enables cell classification with high accuracy (>95.45% via principal component analysis; >97.32% via machine learning). This approach offers robust and high-throughput cell classification, with potential applications in basic research and clinical diagnostics.

[Applied Physics Letters Open Issues] Coherent phonon tunneling-driven ultralow and non-monotonic thermal conductivity in quasi-0D Cs 3 Cu 2 I 5

Applied Physics Letters Open Issues — Mon, 22 Dec 2025 00:00:00 GMT

Low-dimensional copper halides have emerged as promising thermoelectric materials due to their phonon-glass electron-crystal behavior, yet their thermal transport mechanisms remain insufficiently understood. Using ab initio calculations and a unified thermal transport theory, we identify that Cs₃Cu₂I₅ possesses an ultralow lattice thermal conductivity (κ_L) of 0.126 W/(m K) at room temperature (RT)—one of the lowest among metal halides. Above RT, coherent phonon tunneling dominates over particle-like propagation, resulting in glass-like κ_L in all directions. Intriguingly, the competing contributions of coherent and incoherent terms induce an anomalous non-monotonic temperature dependence of κ_L along the c axis, with an initial decrease followed by an unexpected rise. This behavior arises from strong anharmonicity and dense flat phonon dispersions, driven by hierarchical bonding and structural complexity. Our work uncovers unconventional heat transport mechanisms in complex crystals with strong anharmonicity.

[Applied Physics Letters Open Issues] Machine learning-assisted performance prediction of ZnMSnO-based thin-film transistors

Applied Physics Letters Open Issues — Mon, 22 Dec 2025 00:00:00 GMT

Amorphous oxide semiconductors (AOS) are highly promising for optoelectronic devices due to their exceptional electrical properties and optical transparency. However, a significant barrier to their development is the lack of a comprehensive materials database, which hinders systematic studies and the discovery of emergent AOS materials. This study addresses this gap by constructing a dedicated database of zinc-tin-based doped oxide semiconductors (Zn–M–Sn–O) and their thin-film transistor (TFT) performance parameters, compiled from an extensive review of existing literature. Our research aims to perform a systematic analysis of the correlations between key material properties and device performance. We summarize and analyze existing Zn–M–Sn–O based optoelectronic devices, extracting key features such as material compositions, processing parameters, and performance metrics. These features are then used to construct feature vectors. By applying a machine learning algorithm to this dataset, we establish a performance prediction model for Zn–M–Sn–O TFTs. This machine learning-assisted approach allows us to efficiently screen materials and predict the optimal M element for high-performance devices. This methodology significantly accelerates the discovery and development of advanced AOS materials, paving the way for next-generation optoelectronic technologies.

[Applied Physics Reviews Current Issue] Thermal conductivity limits of MoS 2 and MoSe 2 : Revisiting high-order anharmonic lattice dynamics with machine learning potentials

Applied Physics Reviews Current Issue — Mon, 22 Dec 2025 00:00:00 GMT

Group-VI transition metal dichalcogenides (TMDs), MoS₂ and MoSe₂, have emerged as prototypical low-dimensional systems with distinctive phononic and electronic properties, making them attractive for applications in nanoelectronics, optoelectronics, and thermoelectrics. However, their reported lattice thermal conductivities ( κ) remain highly inconsistent, with experimental values and theoretical predictions differing by more than an order of magnitude. These discrepancies stem from uncertainties in measurement techniques, variations in computational protocols, and ambiguities in the treatment of higher-order anharmonic processes. In this study, we critically review these inconsistencies, first by mapping the spread of experimental and modeling results, and then by identifying the methodological origins of divergence. To this end, we bridge first-principles calculations, molecular dynamics simulations, and state-of-the-art machine learning force fields (MLFFs), including recently developed foundation models. We train and benchmark GAP, MACE, NEP, and HIPHIVE against density functional theory and rigorously evaluate the impact of third- and fourth-order phonon scattering processes on κ. The computational efficiency of MLFFs enables us to extend convergence tests beyond conventional limits and to validate predictions through homogeneous nonequilibrium molecular dynamics as well. Our analysis demonstrates that, contrary to some recent claims, fully converged four-phonon processes contribute negligibly to the intrinsic thermal conductivity of both MoS₂ and MoSe₂. These findings not only refine the intrinsic transport limits of 2D TMDs but also establish MLFF-based approaches as a robust and scalable framework for predictive modeling of phonon-mediated thermal transport in low-dimensional materials.

[ChemRxiv] Missense mutations in cancer: in silico predictions, developing treatments, and overcoming cell resistance.

ChemRxiv — Mon, 22 Dec 2025 00:00:00 GMT

Targeted therapies built around specific genetic driver mutations have become a cornerstone of precision oncology. These mutations, often found in oncogenes such as KRAS or tumor suppressors such as TP53, contribute to tumor initiation, progression, and therapeutic resistance. Recent successes with KRAS inhibitors targeting G12C and G12D mutations highlight the clinical potential of mutation-specific drug design. Concurrently, advances in machine learning have enhanced the prediction of missense variant effects by integrating amino acid dynamics, structural perturbations, and pathogenicity scoring. This review synthesizes current computational tools and emerging therapeutic strategies, including small-molecule inhibitors, protein degraders, proximity-based therapeutics, and gene or cellular therapies, to provide a comprehensive framework linking structure–function relationships to the rational design of next-generation cancer treatments.

[ChemRxiv] Domain Oriented Universal Machine Learning Potential Enables Fast Exploration of Chemical Space of Battery Electrolytes

ChemRxiv — Mon, 22 Dec 2025 00:00:00 GMT

Li-ion batteries, widely used in electronic devices, electric vehicles, and aviation, demand high energy density, fast charging capabilities, and broad operating temperature ranges. Computations combined with experiments have gained increasing attention for electrolyte development. However, the inherent complexity of electrolytes poses a significant challenge. Classical molecular dynamics often fails due to inaccuracies in force field parameters, while ab initio calculationsarelimitedbyhighcomputationalcosts. Recently, machinelearning molecular dynamics has emerged as an efficient and accurate alternative. However, its application is hindered by limited transferability of machine learning potentials. In this work, we developed a universal machine learning potential for electrolytes using an iterative training approach on randomly composed datasets, enabling the accurate computation of key properties for a broad range of electrolytes via molecular dynamics. Furthermore, coordination dynamics analysis of Li ion, by quantifying the coordination lifetime, provides a direct, quantitative measure of solvation strength. The universal machine learning potential for electrolytes facilitates the prediction and optimization of electrolyte properties, offering a powerful tool for electrolyte design.

[ChemRxiv] Large-scale structure- and sequence-based comparative analysis enables functional annotation of animal venom peptides

ChemRxiv — Mon, 22 Dec 2025 00:00:00 GMT

Animal venoms constitute one of the most chemically diverse and pharmacologically rich peptide repertoires in nature, yet the vast majority of venom peptides remain structurally and functionally unannotated due to limited material availability and a paucity of experimentally solved structures. This knowledge gap has significantly constrained both mechanistic understanding and translational applications of venom-derived molecules. Here we conduct a comprehensive structure- and sequence-based comparative analysis of close to 4,000 venom peptides (i.e. teretoxins and conotoxins) from marine snails using AlphaFold2. While conotoxins have been studied for over six decades, teretoxins remain largely unexplored. Our study provides the first comprehensive structural classification and functional annotation of the entire known teretoxin repertoire, substantially expanding the venom peptide landscape. Structural clustering analysis revealed that both teretoxins and conotoxins form a large number of structural clusters (225 and 307 clusters, respectively), with each cluster characterized by conserved cysteine frameworks and disulfide connectivity. Importantly, combining structural clusters with phylogenetic analysis revealed that structure prediction together with cysteine frameworks offer an improved strategy for venom peptide classification. We used predicted disulfide connectivity from derived from AlphaFold2 models to annotate the majority of uncharacterized conotoxins on ConoServer database, addressing a long-standing classification bottleneck in venom peptide classification efforts. As a concrete demonstration of functional prediction, co-clustering of predicted teretoxin and conotoxin structures led to the identification of teretoxins structurally homologous to conotoxins with described activities, suggesting shared functional activities such as Kunitz-type peptide activity, neurotoxicity, and ion channel inhibition. Using docking and molecular dynamics (MD) simulations on our Kunitz-type peptide co-cluster, we observed that conotoxin P07849 and teretoxin Tar2.9 engage trypsin in a manner similar to the Kunitz Domain 1 (KD1) of the Alzheimer’s amyloid beta-protein precursor (APPI), a previously unappreciated protease inhibitory role for this venom peptide family. Overall, this work establishes a scalable, structure-centric framework that combines structure prediction, structural clustering, co-clustering, and phylogenetics for deorphanizing venom peptides, enabling predicted annotation and functional inference for future experimental, pharmacological, and therapeutic exploration.

[ChemRxiv] Performance of dispersion models in predicting ambient hydrocarbon concentrations at a regional air quality monitor in an oil and gas producing region

ChemRxiv — Mon, 22 Dec 2025 00:00:00 GMT

The performance of four widely used dispersion models (AERMOD, a single equation Gaussian formulation, and two versions of CALPUFF) for predicting ambient hydrocarbon concentrations at a regional air quality monitor in the Eagle Ford Shale oil and gas production region was assessed. Model performance is found to vary considerably based on the performance objective, meteorological conditions, and temporal resolution. Among the models evaluated in this work, the methods used to estimate the dispersion coefficients and whether the model was plume- or puff-based strongly influenced model performance. Uncertainties in meteorological and emissions inputs also played an important role in model performance, but the significance of their impact varied depending on the performance objective. Techniques to identify and address model uncertainties and for selecting the best performing model for a given application are suggested.

[ChemRxiv] Machine Learning-Guided Scope Selection to Balance Performance and Substrate Similarity

ChemRxiv — Mon, 22 Dec 2025 00:00:00 GMT

The determination of a reaction substrate scope enables downstream users to decide whether the reaction in question is suitable for their envisioned application. The information content of the scope, as demonstrated by its performance and diversity, is crucial to inform the quality of this decision. Herein, we report a broadly applicable and easy to use machine learning algorithm, ScopeBO, for the selection of scopes that balance these two aspects. We use the Vendi score as a metric for scope diversity and establish a scope score that quantifies scope performance within the context of a specific chemical search space. The hyperparameters of ScopeBO are optimized using these metrics, and its performance is validated with several reaction datasets, demonstrating favorable performance against that of alternative selection methods. Through this quantitative optimization, ScopeBO provides an approach towards objective and standardized scope selection that maximizes the information content of the evaluated substrates.

[ChemRxiv] Relationship Between Local Disorder and Atomic Motion in an Antiperovskite Solid Electrolyte

ChemRxiv — Mon, 22 Dec 2025 00:00:00 GMT

Solid-state electrolytes are an alternative to conventional liquid systems for safer and more efficient batteries, whereas a shift from Li to Na would unlock systems with increased resource availability and simplified supply chains. Antiperovskite Na2[NH2][BH4] recently emerged as a candidate that showcases that internal polyanion dynamics can facilitate Na transport. However, experimental validation of the predicted mechanisms of atomic motion remains scarce. To this end, we investigate the intricate relationship between local atomic disorder and dynamic motion. Maps of atomic disorder from total scattering data reproduce the predictions of polyanion rotation and Na translation by ab initio molecular dynamics (AIMD). The comparison also reveals the concurrence of BD4- translations, which were overlooked in previous analyses, and the existence of static disorder due to the different degrees of freedom of each anion, even while maintaining their ideal shape. This complex interplay refines mechanisms governing ion dynamics that determine solid-state electrolyte functionality. Realistic design strategies for rotor-based electrolytes must explicitly account for polyanion translation and static disorder, rather than optimizing rotational freedom in isolation. The combination of total scattering experiments with AIMD provides a route to screen potential polyanion-based candidates for favorable multi-modal disorder, thus steering the discovery of new phases with transformational ionic conductivity.

[ChemRxiv] Multi-Objective Catalyst Discovery in High-Entropy Alloy Composition Space: The Role of Noble Metals on the Pareto Front for Oxygen Reduction Reaction

ChemRxiv — Mon, 22 Dec 2025 00:00:00 GMT

Discovering new materials for electrocatalytic energy conversion reactions is a key step toward energy sustainability. However, for catalysts to be viable in practice, they must perform in multiple, potentially conflicting objectives. We demonstrate this challenge for the acidic oxygen reduction reaction (ORR), where activity, stability, and material cost must be balanced. Using the continuous composition space of high-entropy alloys (HEAs) together with our established models for activity and dissolution, we identify a Pareto-optimal set of ORR catalysts within the Ag–Au–Cu–Ir–Pd–Pt–Rh–Ru system via multi-objective Bayesian optimization. Additionally, we introduce a fine-tuned machine learning model that predicts adsorption energies for alloys spanning 12 elements and 9 adsorbates. Our results show that alloying expands the hypervolume spanned by the Pareto front, consisting of low- to medium-entropy alloys composed primarily of Ag, Au, Cu, Pd, and Pt. We further propose an approach for analyzing the Pareto front by quantifying the loss in hypervolume when critical elements (Au, Pd, and Pt) are removed, clarifying their relative contributions to optimal performance. This work highlights the need to consider all relevant objectives in catalyst optimization and the advantage of HEAs as a powerful platform for multi-objective catalyst discovery.

[ChemRxiv] Agent-based framework for modeling hyperlocal urban air quality

ChemRxiv — Mon, 22 Dec 2025 00:00:00 GMT

Urban air quality exhibits significant spatial and temporal heterogeneity at hyperlocal scales, necessitating advanced modeling paradigms that can bridge the gap between computationally intensive physics-based models and empirically-driven statistical approaches. This paper introduces a novel agent-based modeling framework specifically designed for hyperlocal air quality assessment, capable of providing descriptive, predictive, and prescriptive analysis. The proposed framework discretizes urban environments into interacting agents, with pollutant dynamics governed by a parameterized mass balance that preserves fundamental physics while maintaining computational efficiency. The framework is demonstrated through a case study in Chennai, India, using mobile monitoring data across a 25 km route with 250 m spatial resolution. Geospatial features (traffic, land use, meteorology) are encoded as agent properties through physically interpretable parameters. This enables transparent attribution of pollution sources and transport pathways, thereby strengthening the framework’s descriptive capabilities. The approach successfully captures complex spatio-temporal pollution dynamics and describes pollution hotspots by attributing them to source and transport influences. Predictive capabilities are demonstrated through spatio-temporal interpolation and temporal forecasting. Spatio-temporal formulation of the framework enables it to outperform regular unidimensional methods. The discrete agent structure facilitates prescriptive applications, demonstrated here through identification of least-exposure routes between locations. The unification of descriptive, predictive and prescriptive capabilities within a single interpretable framework makes it a potentially valuable tool for urban environmental management and real-time decision support systems.

[iScience] Widely Targeted Metabolomics and Machine Learning Identify Succinate as a Key Metabolite in Sepsis-Associated Encephalopathy

iScience — Mon, 22 Dec 2025 00:00:00 GMT

Sepsis-associated encephalopathy (SAE) is a common and serious complication of sepsis that leads to acute brain dysfunction and long-term cognitive impairment. We used widely targeted LC–MS/MS plasma metabolomics in 29 healthy controls, 32 sepsis patients, and 27 SAE patients, combined with machine learning, to define metabolic patterns across these groups. This approach identified 12 discriminatory metabolites, with succinate showing a stepwise increase from health to sepsis to SAE and associations with clinical severity scores.

[ACS Nano: Latest Articles (ACS Publications)] [ASAP] Feature-Selective Preprocessing with Electrically Robust Boron Nitride-Based Dynamic Memristors for Reliable Lightweight Neural Networks

ACS Nano: Latest Articles (ACS Publications) — Sun, 21 Dec 2025 18:05:25 GMT

ACS Nano

DOI: 10.1021/acsnano.5c16967

[Journal of the American Chemical Society: Latest Articles (ACS Publications)] [ASAP] Interpreting X-ray Diffraction Patterns of Metal–Organic Frameworks via Generative Artificial Intelligence

Journal of the American Chemical Society: Latest Articles (ACS Publications) — Sat, 20 Dec 2025 15:03:45 GMT

Journal of the American Chemical Society

DOI: 10.1021/jacs.5c16416

[npj Computational Materials] Free-energy perturbation in the exchange-correlation space accelerated by machine learning: application to silica polymorphs

npj Computational Materials — Sat, 20 Dec 2025 00:00:00 GMT

npj Computational Materials, Published online: 20 December 2025; doi:10.1038/s41524-025-01874-1

Free-energy perturbation in the exchange-correlation space accelerated by machine learning: application to silica polymorphs

[Journal of the American Chemical Society: Latest Articles (ACS Publications)] [ASAP] A Transformative Molecular Muscle Solid Electrolyte

Journal of the American Chemical Society: Latest Articles (ACS Publications) — Fri, 19 Dec 2025 20:12:03 GMT

Journal of the American Chemical Society

DOI: 10.1021/jacs.5c18427

[Wiley: Small Structures: Table of Contents] Li6−xFe1−xAlxCl8 Solid Electrolytes for Cost‐Effective All‐Solid‐State LiFePO4 Batteries

Wiley: Small Structures: Table of Contents — Fri, 19 Dec 2025 18:40:34 GMT

Small Structures, EarlyView.

[Wiley: Small: Table of Contents] Unravelling Electronic Structure and Molecular Vibrations of Proteins in Virus Using Novel Correlated Plasmon‐Enhanced Raman Spectroscopy With Machine Learning

Wiley: Small: Table of Contents — Fri, 19 Dec 2025 11:08:23 GMT

Small, EarlyView.

[Recent Articles in Phys. Rev. B] Vision transformer neural quantum states for impurity models

Recent Articles in Phys. Rev. B — Fri, 19 Dec 2025 10:00:00 GMT

Author(s): Xiaodong Cao, Zhicheng Zhong, and Yi Lu

Transformer neural networks, known for their ability to recognize complex patterns in high-dimensional data, offer a promising framework for capturing many-body correlations in quantum systems. We employ an adapted vision transformer (ViT) architecture to model quantum impurity models, optimizing it…

[Phys. Rev. B 112, 235155] Published Fri Dec 19, 2025

[Recent Articles in Phys. Rev. B] Renormalized quantum anharmonicity enhanced electron-phonon coupling in the ambient-pressure compound $\mathrm{Rb}{\mathrm{H}}_{6}$

Recent Articles in Phys. Rev. B — Fri, 19 Dec 2025 10:00:00 GMT

Author(s): Zhongyu Wan, Guo-Hua Zhong, Ruiqin Zhang, and Hai-Qing Lin

Hydrogen-based compounds are promising candidates for room-temperature superconductivity. However, hydrogen-related anharmonic quantum effects have created a huge gap between experiments and theories. The compound $\mathrm{Rb}{\mathrm{H}}_{6}$ exemplifies the impacts of quantum fluctuations and latt…

[Phys. Rev. B 112, L220504] Published Fri Dec 19, 2025

[Wiley: Angewandte Chemie International Edition: Table of Contents] Dual‐Function Antibacterial and Antibiofilm Agent Based on a Confinement‐Activated Fluorescent System in Water

Wiley: Angewandte Chemie International Edition: Table of Contents — Fri, 19 Dec 2025 05:42:28 GMT

Angewandte Chemie International Edition, EarlyView.

[Wiley: Advanced Science: Table of Contents] Quantifying Additive Manufacturing Vapor Plumes Using Laser‐Induced Breakdown Spectroscopy, Synchrotron X‐Ray Radiography and Simulations

Wiley: Advanced Science: Table of Contents — Fri, 19 Dec 2025 03:30:01 GMT

Advanced Science, EarlyView.

[npj Computational Materials] Publisher Correction: Machine learning potentials for alloys: a detailed workflow to predict phase diagrams and benchmark accuracy

npj Computational Materials — Fri, 19 Dec 2025 00:00:00 GMT

npj Computational Materials, Published online: 19 December 2025; doi:10.1038/s41524-025-01913-x

Publisher Correction: Machine learning potentials for alloys: a detailed workflow to predict phase diagrams and benchmark accuracy

[npj Computational Materials] Alloy design integrating natural language processing and machine learning: breakthrough development of low-cost, high-performance Ni-based single-crystal superalloys

npj Computational Materials — Fri, 19 Dec 2025 00:00:00 GMT

npj Computational Materials, Published online: 19 December 2025; doi:10.1038/s41524-025-01906-w

Alloy design integrating natural language processing and machine learning: breakthrough development of low-cost, high-performance Ni-based single-crystal superalloys

[Joule] Boosting ionic conductivity of fluoride electrolytes by polyanion coordination chemistry enabling 5 V-Class all-solid-state batteries

Joule — Fri, 19 Dec 2025 00:00:00 GMT

This study developed a novel class of highly conductive amorphous fluoride solid-state electrolytes (SSEs) LixTi(PO4)x/3F4, using a polyanion coordination strategy. The optimized Li1.3Ti(PO4)1.3/3F4 achieves a Li+ conductivity of 1.16 × 10−5 S cm−1, two orders of magnitude higher than that of analogous Li2TiF6. Combining the inherent high-voltage stability of fluoride and the excellent ionic conductivity of Li1.3Ti(PO4)1.3/3F4, this material enables superior 5 V-class all-solid-state battery performance. This work opens a new avenue for designing high-conductivity fluoride SSEs and advancing the performance of 5 V-class all-solid-state batteries.

[RSC - Digital Discovery latest articles] Adsorb-Agent: Autonomous Identification of Stable Adsorption Configurations via Large Language Model Agent

RSC - Digital Discovery latest articles — Fri, 19 Dec 2025 00:00:00 GMT

Digital Discovery, 2025, Accepted Manuscript
DOI: 10.1039/D5DD00298B, Paper

Open Access

This article is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported Licence.

Janghoon Ock, Radheesh Sharma Meda, Tirtha Vinchurkar, Yayati Jadhav, Amir Barati Farimani
Adsorption energy is a key reactivity descriptor in catalysis. Determining adsorption energy requires evaluating numerous adsorbate-catalyst configurations, making it computationally intensive. Current methods rely on exhaustive sampling, which does not...
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[The Journal of Physical Chemistry C: Latest Articles (ACS Publications)] [ASAP] Instant Prediction of Moire Superlattice Relaxation in Twisted Bilayers of Transition Metal Dichalcogenides Using Different Neural Network Architectures

The Journal of Physical Chemistry C: Latest Articles (ACS Publications) — Thu, 18 Dec 2025 11:50:58 GMT

The Journal of Physical Chemistry C

DOI: 10.1021/acs.jpcc.5c07169

[Recent Articles in Phys. Rev. Lett.] Variational Machine Learning Model for Electronic Structure Optimization via the Density Matrix

Recent Articles in Phys. Rev. Lett. — Thu, 18 Dec 2025 10:00:00 GMT

Author(s): Luqi Dong, Shuxiang Yang, Su-Huai Wei, and Yunhao Lu

We present a novel approach that combines machine learning with direct variational energy optimization via the density matrix to solve the Kohn-Sham equation in density functional theory. Instead of relying on the conventional self-consistent field method, our approach directly optimizes the ground …

[Phys. Rev. Lett. 135, 256403] Published Thu Dec 18, 2025

[Recent Articles in Phys. Rev. B] One-defect one-potential strategy for accurate machine learning prediction of phonons in defect-containing supercells

Recent Articles in Phys. Rev. B — Thu, 18 Dec 2025 10:00:00 GMT

Author(s): Junjie Zhou, Xinpeng Li, Menglin Huang, and Shiyou Chen

Atomic vibrations play a critical role in phonon-assisted electronic transitions at defects in solids. However, accurate phonon calculations in defect-laden systems are often hindered by the high computational cost of large-supercell first-principles calculations. Recently, foundation models, such a…

[Phys. Rev. B 112, 235205] Published Thu Dec 18, 2025

[Wiley: Advanced Science: Table of Contents] Polymorphism Crystal Structure Prediction with Adaptive Space Group Diversity Control

Wiley: Advanced Science: Table of Contents — Thu, 18 Dec 2025 09:38:21 GMT

Advanced Science, Volume 12, Issue 47, December 18, 2025.

[Wiley: Advanced Science: Table of Contents] Computationally‐Guided Development of Sulfide Solid Electrolyte Powder Coatings for Enhanced Stability and Performance of Solid‐State Batteries

Wiley: Advanced Science: Table of Contents — Thu, 18 Dec 2025 09:38:21 GMT

Advanced Science, Volume 12, Issue 47, December 18, 2025.

[Proceedings of the National Academy of Sciences: Physical Sciences] Uncovering inequalities in new knowledge learning by large language models across different languages

Proceedings of the National Academy of Sciences: Physical Sciences — Thu, 18 Dec 2025 08:00:00 GMT

Proceedings of the National Academy of Sciences, Volume 122, Issue 51, December 2025.
SignificanceLarge language models (LLMs) are transforming daily life, yet users across different languages may not benefit equally. Our study shows that LLMs face greater challenges in learning new knowledge and resisting incorrect or misleading ...

[Proceedings of the National Academy of Sciences: Physical Sciences] Heavy-tailed update distributions arise from information-driven self-organization in nonequilibrium learning

Proceedings of the National Academy of Sciences: Physical Sciences — Thu, 18 Dec 2025 08:00:00 GMT

Proceedings of the National Academy of Sciences, Volume 122, Issue 51, December 2025.
SignificanceArtificial neural networks can adapt to tasks while freely exploring possible solutions, similar to how humans balance curiosity with goal-driven behavior. We show that during training, such networks naturally operate near a critical state. ...

[AAAS: Science: Table of Contents] State-independent ionic conductivity

AAAS: Science: Table of Contents — Thu, 18 Dec 2025 07:00:11 GMT

Science, Volume 390, Issue 6779, Page 1254-1258, December 2025.

[AAAS: Science: Table of Contents] Scientific production in the era of large language models

AAAS: Science: Table of Contents — Thu, 18 Dec 2025 07:00:11 GMT

Science, Volume 390, Issue 6779, Page 1240-1243, December 2025.

[Wiley: Advanced Functional Materials: Table of Contents] Homogeneous Microphase Structure and Polymer‐Dominated Ion Transport Network Enable Durable Quasi‐Solid‐State Sodium Metal Batteries

Wiley: Advanced Functional Materials: Table of Contents — Thu, 18 Dec 2025 05:55:56 GMT

Advanced Functional Materials, EarlyView.

[Nature Machine Intelligence] A psychometric framework for evaluating and shaping personality traits in large language models

Nature Machine Intelligence — Thu, 18 Dec 2025 00:00:00 GMT

Nature Machine Intelligence, Published online: 18 December 2025; doi:10.1038/s42256-025-01115-6

Serapio-García, Safdari and colleagues develop a method based on psychometric tests to measure and validate personality-like traits in LLMs. Large, instruction-tuned models give reliable personality measurement results, and specific personality profiles can be mimicked in downstream tasks.

[Wiley: Small: Table of Contents] Probing Lattice Anharmonicity and Thermal Transport in Ultralow‐κ Materials Using Machine Learning Interatomic Potentials

Wiley: Small: Table of Contents — Wed, 17 Dec 2025 20:22:25 GMT

Small, EarlyView.

[Wiley: Small: Table of Contents] Ion Migration Control in Lead‐Free Halide Perovskite Transistors for Logic and Neuromorphic Circuits

Wiley: Small: Table of Contents — Wed, 17 Dec 2025 19:52:40 GMT

Small, EarlyView.

[Journal of the American Chemical Society: Latest Articles (ACS Publications)] [ASAP] Convergent Evolution: Self-Assembly of Small Molecule, Polymeric, and Inorganic Contrast Agents toward Advanced MRI

Journal of the American Chemical Society: Latest Articles (ACS Publications) — Wed, 17 Dec 2025 19:33:22 GMT

Journal of the American Chemical Society

DOI: 10.1021/jacs.4c11767

[ACS Nano: Latest Articles (ACS Publications)] [ASAP] van Hove Source for Ultralow Power Field-Effect Transistors

ACS Nano: Latest Articles (ACS Publications) — Wed, 17 Dec 2025 18:12:49 GMT

ACS Nano

DOI: 10.1021/acsnano.5c17157

[ACS Nano: Latest Articles (ACS Publications)] [ASAP] An Ultralong-Circulating Tantalum-Based Computed Tomography Contrast Agent for Vascular Imaging in Large Animals

ACS Nano: Latest Articles (ACS Publications) — Wed, 17 Dec 2025 17:49:52 GMT

ACS Nano

DOI: 10.1021/acsnano.5c13773

[Wiley: Advanced Functional Materials: Table of Contents] Machine Learning‐assisted Ultrasensitive SERS Immunoassays Across Wide Concentration Ranges Toward Clinical Ovarian Cancer Diagnosis

Wiley: Advanced Functional Materials: Table of Contents — Wed, 17 Dec 2025 14:49:25 GMT

Advanced Functional Materials, Volume 35, Issue 51, December 16, 2025.

[Wiley: Advanced Functional Materials: Table of Contents] Prediction and Fine Screening of Small Molecular Passivation Materials for High‐Efficiency Perovskite Solar Cells Via an Enhanced Machine Learning Workflow

Wiley: Advanced Functional Materials: Table of Contents — Wed, 17 Dec 2025 14:49:25 GMT

Advanced Functional Materials, Volume 35, Issue 51, December 16, 2025.

[Wiley: Advanced Materials: Table of Contents] Tailoring Graphite Interlayers with Electron‐Acceptor Bridges Raises Ion Diffusion Kinetics for Ultrafast Charging Batteries

Wiley: Advanced Materials: Table of Contents — Wed, 17 Dec 2025 14:13:34 GMT

Advanced Materials, Volume 37, Issue 50, December 17, 2025.

[Wiley: Small: Table of Contents] Interfacial Catalysis Engineering of Solid Electrolyte Interphase Toward High‐Performance Batteries

Wiley: Small: Table of Contents — Wed, 17 Dec 2025 12:51:53 GMT

Small, Volume 21, Issue 50, December 17, 2025.

[Wiley: Small: Table of Contents] In Situ Construction of Dual‐Functional UiO‐66‐NH2 Coated Li1.3Al0.3Ti1.7(PO4)3 to Achieve Lithium Metal Cells with Efficient Ion Transport in Quasi‐Solid Electrolytes

Wiley: Small: Table of Contents — Wed, 17 Dec 2025 12:51:53 GMT

Small, Volume 21, Issue 50, December 17, 2025.

[Wiley: Small: Table of Contents] 1D Lithium‐Ion Transport in a LiMn2O4 Nanowire Cathode during Charge–Discharge Cycles

Wiley: Small: Table of Contents — Wed, 17 Dec 2025 12:51:53 GMT

Small, Volume 21, Issue 50, December 17, 2025.

[Wiley: Small: Table of Contents] A Reversible Zinc Metal Anode with an Inorganic/Organic Solid Electrolyte Interphase Enriched for Epitaxial Deposition Along the Zn (101) Plane

Wiley: Small: Table of Contents — Wed, 17 Dec 2025 12:51:53 GMT

Small, Volume 21, Issue 50, December 17, 2025.

[Proceedings of the National Academy of Sciences: Proceedings of the National Academy of Sciences: Table of Contents] Learning to learn ecosystems from limited data

Wed, 17 Dec 2025 08:00:00 GMT

Proceedings of the National Academy of Sciences, Volume 122, Issue 51, December 2025.
SignificanceIn recent years, machine learning has been successfully applied to complex and nonlinear dynamical systems for improved prediction of the future state, but ecological systems represent a great challenge because of the scarcity of the ...

[Wiley: Advanced Functional Materials: Table of Contents] Smart Wound Management System Capable of On‐Chip Machine Learning and Closed‐Loop Therapeutic Feedback

Wiley: Advanced Functional Materials: Table of Contents — Wed, 17 Dec 2025 06:06:36 GMT

Advanced Functional Materials, EarlyView.

[Nature Materials] Probing frozen solid electrolyte interphases

Nature Materials — Wed, 17 Dec 2025 00:00:00 GMT

Nature Materials, Published online: 17 December 2025; doi:10.1038/s41563-025-02443-z

Probing frozen solid electrolyte interphases

[Cell Reports Physical Science] Accelerated inorganic materials design with generative AI agents

Cell Reports Physical Science — Wed, 17 Dec 2025 00:00:00 GMT

Takahara et al. introduce MatAgent, a generative AI agent for inorganic materials design that integrates large language model reasoning with diffusion-based generation and property prediction. The human-inspired reasoning process facilitates interpretable and property-directed discovery of inorganic materials.

[ACS Energy Letters: Latest Articles (ACS Publications)] [ASAP] Fluorinated Halide Solid Electrolytes for High-Voltage All-Solid-State Sodium-Ion Batteries Enabling Reversible Oxygen Redox

ACS Energy Letters: Latest Articles (ACS Publications) — Tue, 16 Dec 2025 20:00:00 GMT

ACS Energy Letters

DOI: 10.1021/acsenergylett.5c03248

[Journal of the American Chemical Society: Latest Articles (ACS Publications)] [ASAP] Highly Accurate and Fast Prediction of MOF Free Energy via Machine Learning

Journal of the American Chemical Society: Latest Articles (ACS Publications) — Tue, 16 Dec 2025 17:08:56 GMT

Journal of the American Chemical Society

DOI: 10.1021/jacs.5c13960

[Wiley: Angewandte Chemie International Edition: Table of Contents] Mechanically Robust Bilayer Solid Electrolyte Interphase Enabled by Sequential Decomposition Mechanism for High‐Performance Micron‐Sized SiOx Anodes

Wiley: Angewandte Chemie International Edition: Table of Contents — Tue, 16 Dec 2025 15:14:44 GMT

Angewandte Chemie International Edition, Volume 64, Issue 51, December 15, 2025.

[Wiley: Angewandte Chemie International Edition: Table of Contents] Machine Learning‐Driven Automated Synthesis of Polysubstituted Gentisaldehydes

Wiley: Angewandte Chemie International Edition: Table of Contents — Tue, 16 Dec 2025 15:14:44 GMT

Angewandte Chemie International Edition, Volume 64, Issue 51, December 15, 2025.

[Wiley: Angewandte Chemie International Edition: Table of Contents] Uphill Anion Transporters with Ultrahigh Efficiency Based on N‐Heterocyclic Carbene Metal Complexes

Wiley: Angewandte Chemie International Edition: Table of Contents — Tue, 16 Dec 2025 15:14:44 GMT

Angewandte Chemie International Edition, Volume 64, Issue 51, December 15, 2025.

[The Journal of Physical Chemistry C: Latest Articles (ACS Publications)] [ASAP] Ionic Liquids in Quasi-Solid-State Li–S Batteries with Sulfide-Based Solid Electrolytes: A Density Functional Theory and Ab Initio Molecular Dynamics Study

The Journal of Physical Chemistry C: Latest Articles (ACS Publications) — Tue, 16 Dec 2025 14:13:16 GMT

The Journal of Physical Chemistry C

DOI: 10.1021/acs.jpcc.5c05916

[Wiley: Advanced Energy Materials: Table of Contents] How Machine Learning Has Driven the Development of Rechargeable Ion Batteries

Wiley: Advanced Energy Materials: Table of Contents — Tue, 16 Dec 2025 10:18:19 GMT

Advanced Energy Materials, Volume 15, Issue 47, December 16, 2025.

[Wiley: Advanced Energy Materials: Table of Contents] Interplay Between the Dissolved Mn2+ and Solid Electrolyte Interphases of Graphite Anode

Wiley: Advanced Energy Materials: Table of Contents — Tue, 16 Dec 2025 10:18:19 GMT

Advanced Energy Materials, Volume 15, Issue 47, December 16, 2025.

[Wiley: Advanced Energy Materials: Table of Contents] From HF Scavenging to Li‐Ion Transport Enhancement: Multifunctional Separator Enabling Stable Li Metal Batteries in Carbonate‐Based Electrolytes

Wiley: Advanced Energy Materials: Table of Contents — Tue, 16 Dec 2025 09:58:08 GMT

Advanced Energy Materials, EarlyView.

[Wiley: Advanced Energy Materials: Table of Contents] Insight Into All‐Solid‐State Lithium‐Sulfur Batteries: Challenges and Interface Engineering at the Electrode‐Sulfide Solid Electrolyte Interface

Wiley: Advanced Energy Materials: Table of Contents — Tue, 16 Dec 2025 09:45:18 GMT

Advanced Energy Materials, EarlyView.

[Proceedings of the National Academy of Sciences: Physical Sciences] Designing strongly coupled polaritonic structures via statistical machine learning

Proceedings of the National Academy of Sciences: Physical Sciences — Tue, 16 Dec 2025 08:00:00 GMT

Proceedings of the National Academy of Sciences, Volume 122, Issue 51, December 2025.
SignificanceStrong coupling photonics enables precise control of light at subwavelength scales, offering transformative potential in energy conversion and optical information processing. However, designing these systems remains a significant challenge due ...

[Applied Physics Letters Current Issue] Ultrafast laser-induced anharmonic lattice dynamics and nonlinear optical modulation in croconic acid

Applied Physics Letters Current Issue — Tue, 16 Dec 2025 00:00:00 GMT

Ultrafast laser excitation offers a powerful means to modulate material properties on femtosecond timescales. Here, we investigate croconic acid, a hydrogen-bonded organic ferroelectric, using real-time time-dependent density functional theory to uncover the microscopic mechanisms of light-induced structural transitions and nonlinear optical responses. High-order harmonic generation in croconic acid is found to be highly sensitive to proton displacement within hydrogen bonds, with polarization switching reshaping internal electronic asymmetry and modulating intersite electron currents. Subangstrom-scale lattice distortions induce marked enhancements or suppressions in the harmonics, highlighting the extreme sensitivity of the nonlinear response to hydrogen-bond configuration. These results reveal a light-driven electron–proton–lattice interaction mechanism in organic ferroelectrics, providing a route toward tunable ultrafast photonic and optoelectronic devices based on molecular materials.

[Applied Physics Letters Current Issue] Spin-splitting-torque-driven field-free perpendicular magnetization switching in RuO 2 /synthetic antiferromagnet heterostructures for spintronic convolutional neural networks

Applied Physics Letters Current Issue — Tue, 16 Dec 2025 00:00:00 GMT

With the growing demand for low-power and high-speed spintronic devices, the development of advanced material systems with efficient spin control capabilities has emerged as a central focus in spintronics research. Here, we propose a fully antiferromagnetic device architecture based on a magnetically compensated RuO₂/synthetic antiferromagnet heterostructure, achieving fully electrical writing and reading functionalities. This design, characterized by its negligible stray field and deterministic field-free switching, is inherently suitable for large-scale neuromorphic integration. In a proof-of-concept demonstration, we showcase the implementation of an all-spintronic convolutional neural network using this architecture, achieving a high recognition accuracy of 98.7% on the handwritten digit classification task.

[iScience] What Makes a Scent Trigger a Memory? A Cognitive Decomposition of Odor-Evoked Retrieval

iScience — Tue, 16 Dec 2025 00:00:00 GMT

A single scent can unlock vivid memories. This study investigates the factors that make some odors more evocative than others. We examined odor-evoked episodic memory in 106 participants who experienced odors embedded in distinct visuospatial contexts, and whose memory was tested 24–72 hours later. The protocol empirically dissociates odor recognition (“I’ve already smelled this scent”) and associative memory (“It evokes a memory”) processes. Using machine learning with SHapley Additive exPlanations, we identified distinct predictors for each process.

[iScience] Integrative Analysis of Transcriptomic Data Reveals a Predictive Gene Signature for Chemoradiotherapy Response in Rectal Cancer

iScience — Tue, 16 Dec 2025 00:00:00 GMT

Locally advanced rectal cancer (LARC) is treated with neoadjuvant chemoradiotherapy (nCRT), but only a minority of patients achieve a pathological complete response (pCR). Predictive biomarkers of response could help guide treatment decisions, yet none have reached clinical practice. In this exploratory study, we integrated six publicly available transcriptomic datasets and applied machine learning to derive a 186-gene signature predictive of nCRT response. The signature showed good performance in cross-validation (AUC 0.80) and was associated with consensus molecular (CMS4) and immune (iCMS3) subtypes enriched in responders.

[iScience] Combining DNA Methylation Features and Clinical Characteristics Predicts Ketamine Treatment Response for PTSD

iScience — Tue, 16 Dec 2025 00:00:00 GMT

Post-traumatic stress disorder (PTSD) exhibits extensive clinical and biological variability, making treatment challenging. The Consortium to Alleviate PTSD (CAP)-ketamine trial, the largest randomized study of ketamine for PTSD, found no overall benefit of ketamine over placebo, underscoring the necessity to identify responsive subgroups. Using pre-treatment blood DNA methylation profiles and clinical measures from the CAP-ketamine trial, we applied machine learning to predict treatment response.

[Chem] In situ cryogenic X-ray photoelectron spectroscopy unveils metastable components of the solid electrolyte interphase in Li-ion batteries

Chem — Tue, 16 Dec 2025 00:00:00 GMT

Nguyen et al. integrate cryogenic X-ray photoelectron spectroscopy (XPS) with residual gas analysis to study the solid electrolyte interphase (SEI) on graphite anodes in Li-ion batteries. The cryo-state preserves metastable SEI components, such as LiPOxFy, which decompose into stable products, such as LiF, with gas release upon warming. Discussions highlight critical XPS conditions, including ultrahigh vacuum exposure, X-ray-induced damage, and neutralizer settings, which could alter the detection and characterization of SEI components.

[The Journal of Physical Chemistry Letters: Latest Articles (ACS Publications)] [ASAP] Anharmonic Coupling in a Strong Intramolecular H-Bond System: Contributions to Static and Time-Resolved Vibrational Spectra

The Journal of Physical Chemistry Letters: Latest Articles (ACS Publications) — Mon, 15 Dec 2025 17:03:38 GMT

The Journal of Physical Chemistry Letters

DOI: 10.1021/acs.jpclett.5c03487

[Journal of the American Chemical Society: Latest Articles (ACS Publications)] [ASAP] Rhodium-Catalyzed Atroposelective Alkyne Oxyamidation Using Non-Nitrene NH Acyloxyamide Reagents

Journal of the American Chemical Society: Latest Articles (ACS Publications) — Mon, 15 Dec 2025 15:14:00 GMT

Journal of the American Chemical Society

DOI: 10.1021/jacs.5c18495

[Proceedings of the National Academy of Sciences: Physical Sciences] CHARGE-MAP: An integrated framework to study the multicriteria EV charging infrastructure expansion problem

Proceedings of the National Academy of Sciences: Physical Sciences — Mon, 15 Dec 2025 08:00:00 GMT

Proceedings of the National Academy of Sciences, Volume 122, Issue 51, December 2025.
SignificanceThe surge in electric vehicle (EV) adoption has presented us the challenge of developing accessible and cost-effective charging infrastructures. To address this challenge, we present a frameworkcharge-map. It consists of: i) an agent-based ...

[Wiley: Chinese Journal of Chemistry: Table of Contents] 2‐Trifluoromethyl‐Benzimidazolium Salt as a Dual‐Function Reagent for Deoxytrifluoromethylation of Benzyl Alcohols

Wiley: Chinese Journal of Chemistry: Table of Contents — Mon, 15 Dec 2025 07:33:14 GMT

Chinese Journal of Chemistry, Volume 44, Issue 2, Page 177-182, 15 January 2026.

[Applied Physics Letters Current Issue] Covalent bond chemistry enabling M 2 CN 2 MXenes as anode materials for halide-ion batteries

Applied Physics Letters Current Issue — Mon, 15 Dec 2025 00:00:00 GMT

The development of halide-ion batteries is limited by the lack of efficient electrode materials. Two-dimensional M₂CN₂ MXenes are promising anode candidates due to their structural flexibility and low molar mass, yet their stability and storage mechanism remain unclear. Using first-principles calculations, we identify Ti₂CN₂, Nb₂CN₂, and Ta₂CN₂ as stable MXenes. Ti₂CN₂ exhibits excellent performance with low voltages (0.07 V for F⁻) and high specific capacities (394.8 mAh/g for F⁻). The storage mechanism involves covalent bonding between surface N and halide-ions, where adsorption strength is governed by the energy difference between occupied σ^* and unoccupied π^* orbitals and their electron overlap. Moreover, O or Zr doping significantly enhances halide-ion diffusion kinetics. This work elucidates the covalent bond-mediated storage in M₂CN₂ MXenes and guides the design of high-performance halide-ion battery electrodes.

[Applied Physics Letters Current Issue] Measurement of multiple mechanical properties from multi-dimensional signals in nanosecond laser ablation via PINN

Applied Physics Letters Current Issue — Mon, 15 Dec 2025 00:00:00 GMT

Accurate evaluation of mechanical properties in steels under ageing or service conditions remains a major challenge. We propose a thermo-mechanical coupling framework for nanosecond laser ablation based on energy conservation, which is embedded into a physics-informed neural network (PINN) to enable simultaneous inversion of multiple mechanical properties. A thermo-mechanical coupling coefficient is defined to uniformly describe the dynamic allocation of input laser energy among thermal diffusion, mechanical work, and plasma shielding across different deformation stages under laser irradiation. Furthermore, hard-to-measure physical characteristics in the coupled equation are replaced with experimentally accessible features obtained through the simultaneous acquisition of spectroscopic, shockwave, and surface-wave signals. Using 210 experimental datasets, the framework simultaneously recovers Young's modulus, yield strength, ultimate tensile strength, and micro-Vickers hardness with high accuracy (R² = 0.9927, 0.9912, 0.9916, and 0.9959, respectively), significantly outperforming the baseline method (ultrasonic velocity regression for E, R² = 0.0012). Comparisons with linear normalization and unconstrained neural networks demonstrate that PINN achieves near-unity accuracy through the embedding of conservation-law constraints. Partial dependency analysis further uncovers the nonlinear coupling laws between input features and mechanical properties. The proposed paradigm, integrating conservation laws, measurable features, and physics-informed learning, offers a universal approach for non-contact, high-precision, and physically consistent multi-to-multi inversion of multiple material properties under nanosecond laser ablation conditions.

[RSC - Digital Discovery latest articles] Deep learning based SEM image analysis for predicting ionic conductivity in LiZr2(PO4)3-based solid electrolytes

RSC - Digital Discovery latest articles — Mon, 15 Dec 2025 00:00:00 GMT

Digital Discovery, 2026, Advance Article
DOI: 10.1039/D5DD00232J, Paper

Open Access

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence.

Kento Murakami, Yudai Yamaguchi, Yo Kato, Kazuki Ishikawa, Naoto Tanibata, Hayami Takeda, Masanobu Nakayama, Masayuki Karasuyama
Lithium-ion-conductive oxide materials have attracted considerable attention as solid electrolytes for all-solid-state batteries.
To cite this article before page numbers are assigned, use the DOI form of citation above.
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[RSC - Digital Discovery latest articles] Hierarchical Attention Graph Learning with LLMs Enhancement for Molecular Solubility Prediction

RSC - Digital Discovery latest articles — Mon, 15 Dec 2025 00:00:00 GMT

Digital Discovery, 2025, Accepted Manuscript
DOI: 10.1039/D5DD00407A, Paper

Open Access

This article is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported Licence.

Yangxin Fan, Yinghui Wu, Roger French, Danny Perez, Michael Taylor, Ping Yang
Solubility quantifies the concentration of a molecule that can dissolve in a given solvent. Accurate prediction of solubility is essential for optimizing drug efficacy, improving chemical and separation processes, waste...
The content of this RSS Feed (c) The Royal Society of Chemistry

[iScience] Interpretable Machine Learning for Accessible Dysphagia Screening and Staging in Older Adults

iScience — Mon, 15 Dec 2025 00:00:00 GMT

Dysphagia in older adults causes serious complications, and efficient and scalable screening are needed. This prospective multicenter study developed interpretable machine learning (ML) models for the early identification and staging of dysphagia. Nine ML models were built using the clinical data from 1,235 patients and externally validated on 720 patients. All patients were older adults from seven Suzhou hospitals whose dysphagia was confirmed via Videofluoroscopic Swallowing Studies. Features were selected via random forest, and model interpretability was analyzed with SHapley Additive exPlanations (SHAP).

[Joule] Dendrite suppression in garnet electrolytes via thermally induced compressive stress

Joule — Mon, 15 Dec 2025 00:00:00 GMT

Thermal gradients induce compressive stress in garnet solid electrolytes, mechanically toughening them against lithium penetration. The resulting 3-fold increase in critical current density demonstrates that stress engineering can increase critical current densities in solid-state batteries and isolates the role of mechanical stress as a dominant factor in dendrite suppression.

[Journal of the American Chemical Society: Latest Articles (ACS Publications)] [ASAP] Unraveling the Humidity-Induced Phase Transition in CALF-20 via Machine Learning Potentials

Journal of the American Chemical Society: Latest Articles (ACS Publications) — Sat, 13 Dec 2025 14:29:51 GMT

Journal of the American Chemical Society

DOI: 10.1021/jacs.5c18944

[Wiley: Advanced Energy Materials: Table of Contents] Machine Learning Descriptors for Mapping Structure‐Property‐Performance Relationships of Perovskite Solar Cells

Wiley: Advanced Energy Materials: Table of Contents — Sat, 13 Dec 2025 07:01:43 GMT

Advanced Energy Materials, EarlyView.

[Journal of the American Chemical Society: Latest Articles (ACS Publications)] [ASAP] Vinylsilanes as Chain-Transfer Agents in Ethylene Polymerization: Direct Synthesis of Heterotelechelic Polyolefins

Journal of the American Chemical Society: Latest Articles (ACS Publications) — Fri, 12 Dec 2025 16:44:30 GMT

Journal of the American Chemical Society

DOI: 10.1021/jacs.5c15808

[The Journal of Physical Chemistry Letters: Latest Articles (ACS Publications)] [ASAP] Compression-Induced Lattice Tilting Quenches Ion Migration at Metal Halide Perovskite Grain Boundaries: A Machine Learning Molecular Dynamics Study

The Journal of Physical Chemistry Letters: Latest Articles (ACS Publications) — Fri, 12 Dec 2025 15:21:13 GMT

The Journal of Physical Chemistry Letters

DOI: 10.1021/acs.jpclett.5c03637

[Journal of the American Chemical Society: Latest Articles (ACS Publications)] [ASAP] Machine Learning-Assisted Crystal Structure Prediction of Solid-State Electrolytes Reveals Superior Ionic Conductivity in Metastable Edge-Sharing Phases

Journal of the American Chemical Society: Latest Articles (ACS Publications) — Fri, 12 Dec 2025 14:36:09 GMT

Journal of the American Chemical Society

DOI: 10.1021/jacs.5c15665

[ACS Materials Letters: Latest Articles (ACS Publications)] [ASAP] Reaction Pathway Informed Strategy for Fast Solid-State Synthesis of Garnet-Type Solid Electrolyte

ACS Materials Letters: Latest Articles (ACS Publications) — Fri, 12 Dec 2025 14:10:55 GMT

ACS Materials Letters

DOI: 10.1021/acsmaterialslett.5c01262

[ACS Energy Letters: Latest Articles (ACS Publications)] [ASAP] Structural Aspects, Ionic Conductivity, and Electrochemical Properties of New Bromine-Substituted Alkali-Based Crystalline Phases MTa(Nb)X6–yBry (M = Li, Na, K; X = Cl, F)

ACS Energy Letters: Latest Articles (ACS Publications) — Fri, 12 Dec 2025 13:47:45 GMT

ACS Energy Letters

DOI: 10.1021/acsenergylett.5c02904

[Proceedings of the National Academy of Sciences: Proceedings of the National Academy of Sciences: Table of Contents] Spiking world model with multicompartment neurons for model-based reinforcement learning

Fri, 12 Dec 2025 08:00:00 GMT

Proceedings of the National Academy of Sciences, Volume 122, Issue 50, December 2025.
SignificanceDendritic computation is key to the brain’s ability to integrate information over long timescales. Inspired by this, this study proposes a spiking neural network model that embeds dendritic mechanisms to enhance long-term memory and planning. ...

[APL Machine Learning Current Issue] Smart detection of plant nutrient deficiencies using machine learning and image fusion

APL Machine Learning Current Issue — Fri, 12 Dec 2025 00:00:00 GMT

Plant nutrient deficiencies are a continual challenge for enhancing global crop output and food security. Historically, manual inspections have been plagued by subjectivity, inefficiency, and restricted scalability, necessitating the development of enhanced detection algorithms. This research introduces a novel approach utilizing image processing and machine learning to enhance detection accuracy and practical applicability. This strategy promotes classification stability by integrating machine learning classifiers, including k-Nearest Neighbors, Artificial Neural Networks, Decision Trees, and Linear Discriminant Analysis, with fusion techniques such as Majority Voting and Mean Fusion. The experiments utilize Leave-One-Out Cross-Validation for model evaluation to address dataset variability and deliver thorough assessments. The study’s results indicate that the suggested system surpasses existing systems in accuracy, precision, recall, and F1 score, attaining an overall accuracy of 98.17%. The method is effective across various noise and resolution parameters, allowing for scalability in precision agriculture applications. This discovery not only enhances the diagnosis of plant nutrient deficiencies but also enables further investigations into real-time plant health monitoring.

[Nature Machine Intelligence] LLM use in scholarly writing poses a provenance problem

Nature Machine Intelligence — Fri, 12 Dec 2025 00:00:00 GMT

Nature Machine Intelligence, Published online: 12 December 2025; doi:10.1038/s42256-025-01159-8

LLM use in scholarly writing poses a provenance problem

[RSC - Digital Discovery latest articles] PEMD: a high-throughput simulation and analysis framework for solid polymer electrolytes

RSC - Digital Discovery latest articles — Fri, 12 Dec 2025 00:00:00 GMT

Digital Discovery, 2026, Advance Article
DOI: 10.1039/D5DD00454C, Paper

Open Access

This article is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported Licence.

Shendong Tan, Bochun Liang, Dexin Lu, Chaoyuan Ji, Wenke Ji, Zihui Li, Tingzheng Hou
PEMD is an open-source Python framework that integrates polymer construction, force-field parameterization, multiscale simulation, and property analysis, with standardized workflows for screening and data-driven design of solid polymer electrolytes.
To cite this article before page numbers are assigned, use the DOI form of citation above.
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[AI for Science - latest papers] Investigating CO adsorption on Cu(111) and Rh(111) surfaces using machine learning exchange-correlation functionals

AI for Science - latest papers — Fri, 12 Dec 2025 00:00:00 GMT

The ‘CO adsorption puzzle’, a persistent failure of utilizing generalized gradient approximations in density functional theory to replicate CO’s experimental preference for top-site adsorption on transition-metal surfaces, remains a critical barrier in surface chemistry. While hybrid functionals such as HSE06 partially resolve this discrepancy, their prohibitive computational cost limits broader applications. We tackle this issue by adopting the Deep Kohn–Sham (DeePKS) method to train machine-learned exchange-correlation functionals. Principal component analysis reveals that the input descriptors for electronic structures separate distinctly across different chemical environments, enabling the DeePKS models to generalize to multi-element systems. We train system-specific DeePKS models for transition-metal surfaces Cu(111) and Rh(111). These models successfully recover experimental site preferences, yielding adsorption energy differences of about 10 meV compared to HSE06, and can be applied to study unseen adsorbate coverages. Furthermore, a single model for the two surfaces is trained, and the model achieves comparable accuracy in predicting not only adsorption energies and site preference but also potential energy surfaces and relaxed surface adsorption structures. The work demonstrates a promising path towards universal models, enabling catalyst exploration with hybrid functional accuracy at substantially reduced cost.

[iScience] Contextualized biomedical language processing enhances ICU survival prediction

iScience — Fri, 12 Dec 2025 00:00:00 GMT

Accurate prediction of intensive care unit (ICU) survival remains challenging due to heterogeneous clinical data. This study shows that contextualized biomedical language processing markedly enhances ICU survival prediction. Multimodal models integrating structured laboratory data with unstructured text (chief complaints and ICD entries) were trained and validated using MIMIC-IV, MIMIC-III, and eICU datasets. The BioBERT-enhanced convolutional neural network achieved AUROCs of 0.889 (Strict Cohort, n=5,795) and 0.974 (Lenient Cohort, n=58,615) during external validation.

[iScience] Consensus machine learning identifies cell death gene signature for carotid artery stenosis diagnosis

iScience — Fri, 12 Dec 2025 00:00:00 GMT

Carotid artery stenosis (CAS) is a major contributor to ischemic stroke, and molecular tools for its early detection remain limited. To address this need, we integrated one in-house RNA-seq cohort with eight public datasets comprising 696 samples, together with proteomic profiling, qRT-PCR, single-cell sequencing, and FYCO1 silencing experiments. From 1,258 curated cell death–related genes, candidates were filtered by logistic regression across cohorts, and ten machine learning algorithms were combined into 105 model configurations to derive a consensus diagnostic classifier.

[The Journal of Physical Chemistry C: Latest Articles (ACS Publications)] [ASAP] Dual Structure-Directing Agents for Superstructure Formation in PtCoCu Ternary Alloy Electrocatalysts

The Journal of Physical Chemistry C: Latest Articles (ACS Publications) — Thu, 11 Dec 2025 15:46:59 GMT

The Journal of Physical Chemistry C

DOI: 10.1021/acs.jpcc.5c06519

[Wiley: Advanced Science: Table of Contents] A Cost‐Effective and Scalable Machine Learning Approach for Quality Assessment of Fresh Maize Kernel Using NIR Spectroscopy

Wiley: Advanced Science: Table of Contents — Thu, 11 Dec 2025 09:23:00 GMT

Advanced Science, Volume 12, Issue 46, December 11, 2025.

[Wiley: Advanced Science: Table of Contents] High‐Performance Zinc–Bromine Rechargeable Batteries Enabled by In‐Situ Formed Solid Electrolyte Interphase

Wiley: Advanced Science: Table of Contents — Thu, 11 Dec 2025 09:23:00 GMT

Advanced Science, Volume 12, Issue 46, December 11, 2025.

[Wiley: Advanced Science: Table of Contents] Nonalcoholic Fatty Liver Disease Exacerbates the Advancement of Renal Fibrosis by Modulating Renal CCR2+PIRB+ Macrophages Through the ANGPTL8/PIRB/ALOX5AP Axis

Wiley: Advanced Science: Table of Contents — Thu, 11 Dec 2025 09:23:00 GMT

Advanced Science, Volume 12, Issue 46, December 11, 2025.

[Wiley: Advanced Science: Table of Contents] Inverse Design of Metal‐Organic Frameworks for CH4/N2 Separation Enabled by Coupled Machine Learning and Genetic Algorithms

Wiley: Advanced Science: Table of Contents — Thu, 11 Dec 2025 09:23:00 GMT

Advanced Science, Volume 12, Issue 46, December 11, 2025.

[Wiley: Advanced Science: Table of Contents] Synergistic Effect of Dual‐Functional Groups in MOF‐Modified Separators for Efficient Lithium‐Ion Transport and Polysulfide Management of Lithium‐Sulfur Batteries

Wiley: Advanced Science: Table of Contents — Thu, 11 Dec 2025 09:23:00 GMT

Advanced Science, Volume 12, Issue 46, December 11, 2025.

[Wiley: Advanced Science: Table of Contents] H2S Is a Potential Universal Reducing Agent for Prx6‐Type Peroxiredoxins

Wiley: Advanced Science: Table of Contents — Thu, 11 Dec 2025 09:23:00 GMT

Advanced Science, Volume 12, Issue 46, December 11, 2025.

[Wiley: Advanced Science: Table of Contents] Luminescent Nanocucurbits Enable Spatiotemporal Co‐Delivery of Hydrophilic and Hydrophobic Chemotherapeutic Agents

Wiley: Advanced Science: Table of Contents — Thu, 11 Dec 2025 09:23:00 GMT

Advanced Science, Volume 12, Issue 46, December 11, 2025.

[Proceedings of the National Academy of Sciences: Proceedings of the National Academy of Sciences: Table of Contents] Evaluating large language models in biomedical data science challenges through a classroom experiment

Thu, 11 Dec 2025 08:00:00 GMT

Proceedings of the National Academy of Sciences, Volume 122, Issue 50, December 2025.
SignificanceLarge language models (LLMs) are increasingly used in science and engineering, yet their real-world effectiveness in data analysis remains unclear. In this study, graduate students used LLMs to tackle biomedical data challenges on Kaggle, a ...

[Wiley: Advanced Functional Materials: Table of Contents] Red Phosphorus@SnSe0.5S0.5 Core‐Shell Heterostructure Enables Superior Sodium Storage via Synergistic Ion Diffusion and Polyphosphides Trapping

Wiley: Advanced Functional Materials: Table of Contents — Thu, 11 Dec 2025 06:58:45 GMT

Advanced Functional Materials, Volume 35, Issue 50, December 9, 2025.

[Wiley: Advanced Functional Materials: Table of Contents] Dual‐Site Ni Nanoparticles‐Ru Clusters Anchored on Hierarchical Carbon with Decoupled Gas and Ion Diffusion Channels Enabling Low‐Overpotential, Highly Stable Li‐CO2 Batteries

Wiley: Advanced Functional Materials: Table of Contents — Thu, 11 Dec 2025 06:58:45 GMT

Advanced Functional Materials, Volume 35, Issue 50, December 9, 2025.

[Wiley: Advanced Functional Materials: Table of Contents] Surface Fluidic Microneedle Patches for Lymphatic Delivery of Diagnostic and Therapeutic Agents (Adv. Funct. Mater. 50/2025)

Wiley: Advanced Functional Materials: Table of Contents — Thu, 11 Dec 2025 06:58:45 GMT

Advanced Functional Materials, Volume 35, Issue 50, December 9, 2025.

[Wiley: Advanced Functional Materials: Table of Contents] Bonyzymes: Efficient Anti‐Inflammatory, Antibacterial and Osteogenic Agents for Peri‐Implantitis Reconstruction Treatment

Wiley: Advanced Functional Materials: Table of Contents — Thu, 11 Dec 2025 06:58:45 GMT

Advanced Functional Materials, Volume 35, Issue 50, December 9, 2025.

[Wiley: Advanced Functional Materials: Table of Contents] Surface Fluidic Microneedle Patches for Lymphatic Delivery of Diagnostic and Therapeutic Agents

Wiley: Advanced Functional Materials: Table of Contents — Thu, 11 Dec 2025 06:58:45 GMT

Advanced Functional Materials, Volume 35, Issue 50, December 9, 2025.

[RSC - Digital Discovery latest articles] Toward smart CO2 capture by the synthesis of metal organic frameworks using large language models

RSC - Digital Discovery latest articles — Thu, 11 Dec 2025 00:00:00 GMT

Digital Discovery, 2026, Advance Article
DOI: 10.1039/D5DD00446B, Paper

Open Access

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence.

Hossein Mashhadimoslem, Mohammad Ali Abdol, Kourosh Zanganeh, Ahmed Shafeen, Encheng Liu, Sohrab Zendehboudi, Ali Elkamel, Aiping Yu
This research focuses on collecting experimental CO₂ adsorption data from 433 scientific papers to address the challenges of MOF synthesis methods and the correlation of MOF structure and the effect of their structure on CO₂ adsorption using LLMs.
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[Journal of Chemical Theory and Computation: Latest Articles (ACS Publications)] [ASAP] A Universal Augmentation Framework for Long-Range Electrostatics in Machine Learning Interatomic Potentials

Journal of Chemical Theory and Computation: Latest Articles (ACS Publications) — Wed, 10 Dec 2025 10:12:04 GMT

Journal of Chemical Theory and Computation

DOI: 10.1021/acs.jctc.5c01400

[Wiley: ENERGY & ENVIRONMENTAL MATERIALS: Table of Contents] Tailoring Thermophysical Properties and Multiscale Machine Learning Modeling of 2D Nanomaterial‐Infused Beeswax as a Green NePCM for Sustainable Thermal Management Systems

Wiley: ENERGY & ENVIRONMENTAL MATERIALS: Table of Contents — Wed, 10 Dec 2025 09:54:56 GMT

ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.

[Applied Physics Reviews Current Issue] Construction of polar topological nanodevices for neuromorphic computing

Applied Physics Reviews Current Issue — Wed, 10 Dec 2025 00:00:00 GMT

The research field of polar topological domains has witnessed rapid expansion in recent years, inspired by the vast application potentials for future topological electronic devices. Nonetheless, such topological devices remain elusive. In this study, we implemented the polar topological domain structures as neuromorphic computing elements, and present 12-state non-volatile ferroelectric topological nanodevices that demonstrate exceptional neuromorphic computing capabilities through the controlled formation and erasure of walls. These nanodevices exhibit near-linear long-term potentiation and long-term depression characteristics under repetitive voltage pulses, achieving a remarkable dynamic range. Simulations using a convolutional neural network model with these devices attain 95% recognition accuracy on the Modified National Institute of Standards and Technology handwritten digits dataset within 100 epochs. These results expand the functional scope of polar topological electronic devices to future neuromorphic computing systems.

[RSC - Digital Discovery latest articles] Optimizing Data Extraction from Materials Science Literature: A Study of Tools Using Large Language Models

RSC - Digital Discovery latest articles — Wed, 10 Dec 2025 00:00:00 GMT

Digital Discovery, 2025, Accepted Manuscript
DOI: 10.1039/D5DD00482A, Paper

Open Access

This article is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported Licence.

Wenkai Ning, Jeffrey Robert Reimers, Musen Li, Rika Kobayashi
Large Language Models (LLMs) are increasingly utilized for large-scale extraction and organization of unstructured data owing to their exceptional Natural Language Processing (NLP) capabilities. Empowering materials design, vast amounts of...
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[Journal of the American Chemical Society: Latest Articles (ACS Publications)] [ASAP] Machine Learning-Guided Decoding Bioelectronic Signals of Photosynthetic Cyanobacterial Cells by Conducting Polymers

Journal of the American Chemical Society: Latest Articles (ACS Publications) — Tue, 09 Dec 2025 15:33:56 GMT

Journal of the American Chemical Society

DOI: 10.1021/jacs.5c13150

[Recent Articles in Phys. Rev. Lett.] Connection between Memory Performance and Optical Absorption in Quantum Reservoir Computing

Recent Articles in Phys. Rev. Lett. — Tue, 09 Dec 2025 10:00:00 GMT

Author(s): Niclas Götting, Steffen Wilksen, Alexander Steinhoff, Frederik Lohof, and Christopher Gies

Quantum reservoir computing (QRC) offers a promising paradigm for harnessing quantum systems for machine learning tasks, especially in the era of noisy intermediate-scale quantum devices. While information-theoretical benchmarks like short-term memory capacity (STMC) are widely used to evaluate QRC …

[Phys. Rev. Lett. 135, 240403] Published Tue Dec 09, 2025

[Wiley: Advanced Energy Materials: Table of Contents] Ultrahigh‐Rate Lithium Storage in MoS2 Enabled by Isotropic Ion Transport and Fe‐Atomic Site Conversion

Wiley: Advanced Energy Materials: Table of Contents — Tue, 09 Dec 2025 08:32:12 GMT

Advanced Energy Materials, EarlyView.

[Wiley: Advanced Energy Materials: Table of Contents] Prediction of Structural Stability of Layered Oxide Cathode Materials: Combination of Machine Learning and Ab Initio Thermodynamics

Wiley: Advanced Energy Materials: Table of Contents — Tue, 09 Dec 2025 07:26:17 GMT

Advanced Energy Materials, EarlyView.

[Wiley: Advanced Intelligent Discovery: Table of Contents] Enhancing Synaptic Plasticity in Strontium Titanate‐Based Sensory Processing Devices: A Study on Oxygen Vacancy Modulation and Performance in Artificial Neural Networks

Wiley: Advanced Intelligent Discovery: Table of Contents — Tue, 09 Dec 2025 01:16:19 GMT

Advanced Intelligent Discovery, Volume 1, Issue 3, December 2025.

[RSC - Digital Discovery latest articles] Multi-agentic AI framework for end-to-end atomistic simulations

RSC - Digital Discovery latest articles — Tue, 09 Dec 2025 00:00:00 GMT

Digital Discovery, 2026, Advance Article
DOI: 10.1039/D5DD00435G, Paper

Open Access

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence.

Aikaterini Vriza, Uma Kornu, Aditya Koneru, Henry Chan, Subramanian K. R. S. Sankaranarayanan
Autonomous multi-agent AI system coordinates specialized agents to perform complex materials property calculations from natural language prompts.
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[Journal of the American Chemical Society: Latest Articles (ACS Publications)] [ASAP] Quantifying Phase Contributions to Ion Transport in Organic–Inorganic Composite Electrolytes

Journal of the American Chemical Society: Latest Articles (ACS Publications) — Mon, 08 Dec 2025 19:45:10 GMT

Journal of the American Chemical Society

DOI: 10.1021/jacs.5c11634

[Proceedings of the National Academy of Sciences: Proceedings of the National Academy of Sciences: Table of Contents] Chatbot Voting Advice Applications inform but seldom sway young unaligned voters

Mon, 08 Dec 2025 08:00:00 GMT

Proceedings of the National Academy of Sciences, Volume 122, Issue 50, December 2025.
SignificanceMany people struggle to identify where political parties stand on the issues that matter most to them. This study introduces a Voting Advice Application (VAA) Bot powered by generative AI, that provides information about party positions using ...

[RSC - Chem. Sci. latest articles] A solid composite electrolyte based on three-dimensional structured zeolite networks for high-performance solid-state lithium metal batteries

RSC - Chem. Sci. latest articles — Sun, 07 Dec 2025 00:00:00 GMT

Chem. Sci., 2026, Advance Article
DOI: 10.1039/D5SC05786H, Edge Article

Open Access

This article is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported Licence.

Zhaodi Luo, Yuxin Cui, Zixuan Zhang, Malin Li, Jihong Yu
We report a composite solid electrolyte, 3D Zeo/PEO, constructed by integrating a 3D zeolite network into a LiTFSI–PEO matrix, which boosts the performance of batteries by regulating the Li⁺ conduction and deposition, as well as SEI formation.
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[Proceedings of the National Academy of Sciences: Physical Sciences] Local equations describe unreasonably efficient stochastic algorithms in random K-SAT

Proceedings of the National Academy of Sciences: Physical Sciences — Fri, 05 Dec 2025 08:00:00 GMT

Proceedings of the National Academy of Sciences, Volume 122, Issue 49, December 2025.
SignificanceThe difficulties of algorithmic dynamics in highly nonconvex landscapes are central in several research areas, from hard combinatorial optimization to machine learning. However, it is unclear why and how some particular algorithms find ...

[ACS Materials Letters: Latest Articles (ACS Publications)] [ASAP] Beyond Conventional Sodium Superionic Conductor: Fe-Substituted Na3V2(PO4)2F3 Cathodes with Accelerated Charge Transport via Polyol Reflux for Sodium-Ion Batteries

ACS Materials Letters: Latest Articles (ACS Publications) — Thu, 04 Dec 2025 13:33:58 GMT

ACS Materials Letters

DOI: 10.1021/acsmaterialslett.5c01502

[Wiley: Advanced Science: Table of Contents] Non‐Monotonic Ion Conductivity in Lithium‐Aluminum‐Chloride Glass Solid‐State Electrolytes Explained by Cascading Hopping

Wiley: Advanced Science: Table of Contents — Thu, 04 Dec 2025 08:00:00 GMT

Advanced Science, Volume 12, Issue 45, December 4, 2025.

[Wiley: Advanced Science: Table of Contents] Re‐Purposing a Modular Origami Manipulator Into an Adaptive Physical Computer for Machine Learning and Robotic Perception

Wiley: Advanced Science: Table of Contents — Thu, 04 Dec 2025 08:00:00 GMT

Advanced Science, Volume 12, Issue 45, December 4, 2025.

[Wiley: Advanced Materials: Table of Contents] Ultrastable Calcium Metal Anodes Enabled by a Strongly Coordinated Electrolyte Derived Bilayer Solid Electrolyte Interphase

Wiley: Advanced Materials: Table of Contents — Thu, 04 Dec 2025 07:04:36 GMT

Advanced Materials, Volume 37, Issue 48, December 3, 2025.

[APL Machine Learning Current Issue] Multi-resolution physics-aware recurrent convolutional neural network for complex flows

APL Machine Learning Current Issue — Thu, 04 Dec 2025 00:00:00 GMT

We present MRPARCv2, Multi-resolution Physics-Aware Recurrent Convolutional Neural Network, designed to model complex flows by embedding the structure of advection–diffusion–reaction equations and leveraging a multi-resolution architecture. MRPARCv2 introduces hierarchical discretization and cross-resolution feature communication to improve the accuracy and efficiency of flow simulations. We evaluate the model on a challenging 2D turbulent radiative layer dataset from The Well multi-physics benchmark repository and demonstrate significant improvements when compared to the single resolution baseline model, in both Variance Scaled Root Mean Squared Error and physics-driven metrics, including turbulent kinetic energy spectra and mass–temperature distributions. Despite having 30% fewer trainable parameters, MRPARCv2 outperforms its predecessor by up to 50% in roll-out prediction error and 86% in spectral error. A preliminary study on uncertainty quantification was performed, and we also analyzed the model’s performance under different levels of abstractions of the flow, specifically on sampling subsets of field variables. We find that the absence of physical constraints on the equation of state (EOS) in the network architecture leads to degraded accuracy. A variable substitution experiment confirms that this issue persists regardless of which physical quantity is predicted directly. Our findings highlight the advantages of multi-resolution inductive bias for capturing multi-scale flow dynamics and suggest the need for future PIML models to embed EOS knowledge to enhance physical fidelity.

[RSC - Digital Discovery latest articles] Understanding and mitigating distribution shifts for universal machine learning interatomic potentials

RSC - Digital Discovery latest articles — Thu, 04 Dec 2025 00:00:00 GMT

Digital Discovery, 2026, Advance Article
DOI: 10.1039/D5DD00260E, Paper

Open Access

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence.

Tobias Kreiman, Aditi S. Krishnapriyan
We find common distribution shifts that pose challenges for universal machine learning interatomic potentials (MLIPs). We develop test-time refinement strategies that mitigate the shifts and provide insights into why MLIPs struggle to generalize.
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[iScience] Physical Cognition in Altered Gravity: Link Between Sensorimotor and Cognitive Adaptability

iScience — Thu, 04 Dec 2025 00:00:00 GMT

A hallmark of human intelligence is rapid adaptation to changing environments. Yet the link between sensorimotor recalibration to new physical conditions and cognitive updating of internal models remains unclear. We addressed this using altered gravity as a model system. In a within-subject study, 25 adults completed a virtual-reality task requiring motor adjustment to non-terrestrial gravities and an online problem-solving task requiring physical reasoning under matched gravity manipulations. Adaptability in each domain was computed relative to performance under terrestrial gravity.

[iScience] Meteorological and Socioeconomic Impacts on China Ozone Past and Future Analysis

iScience — Thu, 04 Dec 2025 00:00:00 GMT

Chen et al. quantify seasonal ozone dynamics across China using machine learning and climate projections, revealing northern warm‑season O3 peaks driven by temperature, humidity, and mid‑tropospheric winds, and regionally divergent future trajectories under SSPs, highlighting the need for location‑specific, climate‑aware ozone control.

[Applied Physics Reviews Current Issue] Gate-tunable dual-mode BiOI photodetector for precise object identification

Applied Physics Reviews Current Issue — Thu, 04 Dec 2025 00:00:00 GMT

The controllable growth of large-sized and high-quality semiconductor single crystals is an important guarantee for the realization of high-performance electronic and optoelectronic devices. Herein, we synthesized layered BiOI transparent single crystals through a tellurium-assisted chemical vapor transport strategy. Systematic investigation reveals that tellurium acts as a critical transport agent, directly modulating the crystallization dynamics and enabling the growth of high-quality 1-cm single crystals with precise size control. The layered BiOI crystals demonstrate excellent broadband (254–940 nm) photoresponse performance, achieving a remarkable responsivity of 123.7 A·W⁻¹ and specific detectivity of 7.2 × 10¹³ Jones. Notably, the implementation of gate voltage regulation allows dynamic control of carrier transport mechanisms, achieving efficient regulation of the photoresponse of the device. This unique gate-tunable characteristic enables dual-mode operation in image recognition systems, simultaneously supporting both high-sensitivity detection and programmable contrast enhancement. The combination of scalable crystal growth and multifunctional optoelectronic properties positions BiOI as a promising candidate for next-generation intelligent photodetection technologies.

[Wiley: Small: Table of Contents] Label‐Free Detection of Nuclear Envelope Nucleoporation using 2D Morphological Embeddings and Machine Learning

Wiley: Small: Table of Contents — Wed, 03 Dec 2025 15:24:49 GMT

Small, Volume 21, Issue 48, December 3, 2025.

[Wiley: Small: Table of Contents] Reagentless Real‐Time ATP Monitoring with New DNA Aptamers

Wiley: Small: Table of Contents — Wed, 03 Dec 2025 15:24:49 GMT

Small, Volume 21, Issue 48, December 3, 2025.

[Wiley: Advanced Functional Materials: Table of Contents] Machine Learning‐Enabled Polymer Discovery for Enhanced Pulmonary siRNA Delivery

Wiley: Advanced Functional Materials: Table of Contents — Wed, 03 Dec 2025 08:00:00 GMT

Advanced Functional Materials, Volume 35, Issue 49, December 2, 2025.

[Wiley: Advanced Functional Materials: Table of Contents] Enhanced Potassium Ion Diffusion and Interface Stability Enabled by Potassiophilic rGO/CNTs/NaF Micro‐Lattice Aerogel for High‐Performance Potassium Metal Batteries

Wiley: Advanced Functional Materials: Table of Contents — Wed, 03 Dec 2025 08:00:00 GMT

Advanced Functional Materials, Volume 35, Issue 49, December 2, 2025.

[Nature Reviews Physics] Predicting high-entropy alloy phases with machine learning

Nature Reviews Physics — Wed, 03 Dec 2025 00:00:00 GMT

Nature Reviews Physics, Published online: 03 December 2025; doi:10.1038/s42254-025-00903-8

Omokhuwele Umoru explains how generative adversarial networks can help to predict the phases of high-entropy alloys.

[RSC - Digital Discovery latest articles] Evaluating the transfer learning from metals to oxides with GAME-Net-Ox

RSC - Digital Discovery latest articles — Wed, 03 Dec 2025 00:00:00 GMT

Digital Discovery, 2026, Advance Article
DOI: 10.1039/D5DD00331H, Paper

Open Access

This article is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported Licence.

Thomas Van Hout, Oliver Loveday, Jordi Morales-Vidal, Santiago Morandi, Núria López
GAME-Net-Ox, an extension of the GAME-Net graph neural network, enables fast prediction of adsorption energies for molecules with key organic functional groups on conductive and semiconductive rutile metal oxides and metal surfaces.
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[iScience] United multi-omics and machine learning refine regulatory T cell-defined hepatocellular carcinoma subtypes

iScience — Wed, 03 Dec 2025 00:00:00 GMT

Hepatocellular carcinoma (HCC) is highly heterogeneous and aggressive, and the absence of precision individual treatment regimen enables repeated immune escape. Exploiting Treg-marker genes as key classifiers, we used 10 clustering algorithms to integrate the multi-omics HCC patients data and combined with 10 machine learning (ML) algorithms to delineate molecular subtypes to define molecular subtypes predictive of prognosis and immune response. We identified two cancer subtypes (CSs) that are associated with prognosis, with the second subtype (CS2) showing the most favourable prognostic outcomes.

[iScience] ABCA1 acts as a protective modulator in amyotrophic lateral sclerosis

iScience — Wed, 03 Dec 2025 00:00:00 GMT

Amyotrophic lateral sclerosis (ALS) is a progressive motor neuron disease lacking reliable biomarkers and effective therapeutic targets. We performed an integrative multiscale analysis combining global epidemiology, whole-blood transcriptomics, machine learning, and Mendelian randomization (MR). We developed a nine-gene diagnostic signature (AUC = 0.75 in external validation) and identified ATP-binding cassette transporter A1 (ABCA1) as a central feature. MR analyses supported a protective causal relationship between increased ABCA1 expression and reduced ALS risk (OR = 0.93, p = 0.02).

[Matter] Unknowium, beyond the banana, and AI discovery in materials science

Matter — Wed, 03 Dec 2025 00:00:00 GMT

Recently, the proportion of papers implementing some sort of artificial intelligence (AI) or machine learning (ML) methods in materials science has been growing. It’s hard to ignore such a powerful and exciting tool. Relatedly, I have just returned from the Pujiang Innovation Forum held in Shanghai, China, where I participated in the “AI for Materials Science” session (Figure 1A), speaking as a lowly editor among global experts in the field.

[Wiley: Advanced Energy Materials: Table of Contents] Taming Metal–Solid Electrolyte Interface Instability via Metal Strain Hardening

Wiley: Advanced Energy Materials: Table of Contents — Tue, 02 Dec 2025 13:55:59 GMT

Advanced Energy Materials, Volume 15, Issue 45, December 2, 2025.

[Wiley: Advanced Energy Materials: Table of Contents] Self‐Liquefying Conformal Nanocoatings via Phase‐Convertible Ion Conductors for Stable All‐Solid‐State Batteries (Adv. Energy Mater. 45/2025)

Wiley: Advanced Energy Materials: Table of Contents — Tue, 02 Dec 2025 13:55:59 GMT

Advanced Energy Materials, Volume 15, Issue 45, December 2, 2025.

[Wiley: Advanced Energy Materials: Table of Contents] Multiscale Design Strategies of Interface‐Stabilized Solid Electrolytes and Dynamic Interphase Decoding from Atomic‐to‐Macroscopic Perspectives

Wiley: Advanced Energy Materials: Table of Contents — Tue, 02 Dec 2025 13:55:59 GMT

Advanced Energy Materials, Volume 15, Issue 45, December 2, 2025.

[Wiley: Advanced Energy Materials: Table of Contents] Self‐Liquefying Conformal Nanocoatings via Phase‐Convertible Ion Conductors for Stable All‐Solid‐State Batteries

Wiley: Advanced Energy Materials: Table of Contents — Tue, 02 Dec 2025 13:55:59 GMT

Advanced Energy Materials, Volume 15, Issue 45, December 2, 2025.

[Chinese Chemical Society: CCS Chemistry: Table of Contents] LoRA-Chem: Modular Machine Learning for Multitask Prediction in Organic Reactions

Chinese Chemical Society: CCS Chemistry: Table of Contents — Tue, 02 Dec 2025 04:48:31 GMT

CCS Chemistry, Ahead of Print.

DOI:10.31635/ccschem.025.202506542

The prediction of organic chemical reactions has historically presented significant challenges owing to the inherent complexity and mechanistic diversity of reaction processes. In this work, we present LoRA-Chem, an innovative modular framework that ...

[iScience] Dimensionality modulated generative AI for safe biomedical dataset augmentation

iScience — Tue, 02 Dec 2025 00:00:00 GMT

Generative artificial intelligence can expand small biomedical datasets but may amplify noise and distort statistical relationships. We developed genESOM, a framework integrating an error control system into a generative AI method based on emergent self-organizing maps. By separating structure learning from data synthesis, genESOM enables dimensionality modulation and injection of engineered diagnostic features, i.e., permuted versions of real variables, as negative controls that track feature importance stability.

[Wiley: Advanced Intelligent Discovery: Table of Contents] Advances in Thermal Modeling and Simulation of Lithium‐Ion Batteries with Machine Learning Approaches

Wiley: Advanced Intelligent Discovery: Table of Contents — Mon, 01 Dec 2025 22:39:43 GMT

Advanced Intelligent Discovery, EarlyView.

[APL Machine Learning Current Issue] RTNinja : A generalized machine learning framework for analyzing random telegraph noise signals in nanoelectronic devices

APL Machine Learning Current Issue — Mon, 01 Dec 2025 00:00:00 GMT

Random telegraph noise is a prevalent variability phenomenon in nanoelectronic devices, arising from stochastic carrier exchange at defect sites and critically impacting device reliability and performance. Conventional analysis techniques often rely on restrictive assumptions or manual interventions, limiting their applicability to complex, noisy datasets. Here, we introduce RTNinja, a generalized, fully automated machine learning framework for the unsupervised analysis of random telegraph noise signals. RTNinja deconvolves complex signals to identify the number and characteristics of hidden individual sources without requiring prior knowledge of the system. The framework comprises two modular components: LevelsExtractor, which uses Bayesian inference and model selection to denoise and discretize the signal, and SourcesMapper, which infers source configurations through probabilistic clustering and optimization. To evaluate performance, we developed a Monte Carlo simulator that generates labeled datasets spanning broad signal-to-noise ratios and source complexities; across 7000 such datasets, RTNinja consistently demonstrated high-fidelity signal reconstruction and accurate extraction of source amplitudes and activity patterns. Our results demonstrate that RTNinja offers a robust, scalable, and device-agnostic tool for random telegraph noise characterization, enabling large-scale statistical benchmarking, reliability-centric technology qualification, predictive failure modeling, and device physics exploration in next-generation nanoelectronics.

[iScience] A pilot study: Incorporating Treponema pallidum antigens into machine learning models for accurate syphilis treatment outcome assessment

iScience — Mon, 01 Dec 2025 00:00:00 GMT

Health informatics; disease; artificial intelligence applications

[iScience] Bathymetry of the Philippine Sea with Convolution Neural Network from Multisource Marine Geodetic Data

iScience — Fri, 28 Nov 2025 00:00:00 GMT

This study developed a deep learning-based method for high resolution bathymetry prediction in the Philippine Sea, aiming to improve the accuracy of seafloor depth estimation using multi-source marine geodetic data. The method integrates geographic coordinates with auxiliary features such as bathymetry, sea-land marks, seafloor slope and orientation, gravity anomaly, vertical gravity gradient, mean dynamic topography, deflection of the vertical, mean sea surface and sedimentary thickness. These inputs were extracted from an 8×8 arcminute region around each training point and the model was trained to predict depth residuals.

[Wiley: Small Methods: Table of Contents] Water‐Dispersible Metal Oxide Nanoparticles Synthesized Via Hydrogen‐Bond‐Mediated Aqueous Solution: Gd2O3 for High‐Performance T1 Magnetic Resonance Imaging Contrast Agent

Wiley: Small Methods: Table of Contents — Thu, 27 Nov 2025 07:52:59 GMT

Small Methods, EarlyView.

[iScience] Interpretable Machine Learning for Urothelial Cells Classification and Risk Scoring in Urine Cytology

iScience — Thu, 27 Nov 2025 00:00:00 GMT

Urine cytology is widely used for detecting urothelial carcinoma (UC), though its performance is constrained by limited sensitivity and substantial inter-observer variability. An interpretable machine learning framework was developed to classify urothelial cells and to estimate slide-level risk of high-grade urothelial carcinoma. 10,230 expert-annotated urothelial cells were used to extract 20 quantitiative feature representing cytomorphologic criteric defined by the Paris System. Ordinal logistic regression and random forest models were trained and validated, achiving over 90% accuracy for classifying cells into Normal, Atypical, or Suspicious categories.

[Wiley: Advanced Intelligent Discovery: Table of Contents] Machine Learning‐Assisted Second‐Order Perturbation Theory for Chemical Potential Correction Toward Hubbard U Determination

Wiley: Advanced Intelligent Discovery: Table of Contents — Wed, 26 Nov 2025 03:49:32 GMT

Advanced Intelligent Discovery, EarlyView.

[RSC - Digital Discovery latest articles] Toward accelerating rare-earth metal extraction using equivariant neural networks

RSC - Digital Discovery latest articles — Wed, 26 Nov 2025 00:00:00 GMT

Digital Discovery, 2026, Advance Article
DOI: 10.1039/D5DD00286A, Paper

Open Access

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence.

Ankur K. Gupta, Caitlin V. Hetherington, Wibe A. de Jong
A high-throughput workflow leveraging equivariant GNNs and a diverse dataset of rare-earth complexes to predict binding affinities and accelerate critical metal separation.
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[RSC - Digital Discovery latest articles] Automated synthesis and fragment descriptor-based machine learning for retention time prediction in supercritical fluid chromatography

RSC - Digital Discovery latest articles — Wed, 26 Nov 2025 00:00:00 GMT

Digital Discovery, 2026, Advance Article
DOI: 10.1039/D5DD00437C, Paper

Open Access

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence.

Sitanan Sartyoungkul, Balasubramaniyan Sakthivel, Pavel Sidorov, Yuuya Nagata
Integration of automated synthesis and fragment descriptor-based machine learning enables accurate prediction of SFC retention times and accelerates column characterization.
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The content of this RSS Feed (c) The Royal Society of Chemistry

[RSC - Digital Discovery latest articles] Mol2Raman: a graph neural network model for predicting Raman spectra from SMILES representations

RSC - Digital Discovery latest articles — Tue, 25 Nov 2025 00:00:00 GMT

Digital Discovery, 2025, Advance Article
DOI: 10.1039/D5DD00210A, Paper

Open Access

This article is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported Licence.

Salvatore Sorrentino, Alessandro Gussoni, Francesco Calcagno, Gioele Pasotti, Davide Avagliano, Ivan Rivalta, Marco Garavelli, Dario Polli
Mol2Raman is a graph neural network that predicts Raman spectra from molecular SMILES. Trained on >31k DFT-calculated spectra, it localizes peaks within 15 cm⁻¹ with 64% accuracy, outperforming current SOTA deep learning algorithms on Raman spectra.
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[RSC - Chem. Sci. latest articles] Data-driven approach to elucidate the correlation between photocatalytic activity and rate constants from excited states

RSC - Chem. Sci. latest articles — Tue, 25 Nov 2025 00:00:00 GMT

Chem. Sci., 2026, Advance Article
DOI: 10.1039/D5SC06465A, Edge Article

Open Access

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence.

Ryuga Kunisada, Manami Hayashi, Tabea Rohlfs, Taiki Nagano, Koki Sano, Naoto Inai, Naoki Noto, Takuya Ogaki, Yasunori Matsui, Hiroshi Ikeda, Olga García Mancheño, Takeshi Yanai, Susumu Saito
A data-driven framework integrating machine learning and quantum chemical calculations enables elucidation of how rate constants from excited states govern the photocatalytic activity of organic photosensitizers.
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[Cell Reports Physical Science] Repurposing clinical iron oxide agents for mild hyperthermia-assisted cancer therapy

Cell Reports Physical Science — Tue, 25 Nov 2025 00:00:00 GMT

Zha et al. have developed a photothermal- or ultrasound-assisted therapeutic platform that endows a clinically approved iron oxide reagent with profound anticancer efficacy. The platform can induce immunogenic cell death in multiple xenograft models, reverse immunosuppressive tumor microenvironments, and trigger robust anticancer immune responses with enhanced immunological memory.

[JACS Au: Latest Articles (ACS Publications)] [ASAP] Constant-Potential MD with Neural Network Potentials Reveals Cation Effects on CO2 Reduction at Au-Water Interfaces

JACS Au: Latest Articles (ACS Publications) — Mon, 24 Nov 2025 12:22:43 GMT

JACS Au

DOI: 10.1021/jacsau.5c01198

[Proceedings of the National Academy of Sciences: Physical Sciences] Modeling feasible locomotion of nanobots for cancer detection and treatment

Proceedings of the National Academy of Sciences: Physical Sciences — Mon, 24 Nov 2025 08:00:00 GMT

Proceedings of the National Academy of Sciences, Volume 122, Issue 48, December 2025.
SignificanceWe present a mathematical model of nanorobots moving in a colloidal environment within the human body to locate a single, targeted cancer site and deliver localized treatment. The capabilities and behavior of individual agents are inspired by ...

[Wiley: Chinese Journal of Chemistry: Table of Contents] Locked Coplanar Conformation Boosts Rapid Electron/Ion Transport in Linear Polyimide Cathodes for Sodium‐Ion Storage

Wiley: Chinese Journal of Chemistry: Table of Contents — Mon, 24 Nov 2025 07:33:36 GMT

Chinese Journal of Chemistry, EarlyView.

[APL Machine Learning Current Issue] A hybrid neural architecture: Online attosecond x-ray characterization

APL Machine Learning Current Issue — Fri, 21 Nov 2025 00:00:00 GMT

The emergence of high-repetition-rate x-ray free-electron lasers (XFELs), such as SLAC’s LCLS-II, serves as our canonical example for autonomous controls that necessitate high-throughput diagnostics paired with streaming computational pipelines capable of single-shot analysis with extremely low latency. We present the deterministic characterization with an integrated parallelizable hybrid resolver architecture, a hybrid machine learning framework designed for fast, accurate analysis of XFEL diagnostics using angular streaking-based sinogram images. This architecture integrates convolutional neural networks and bidirectional long short-term memory models to denoise input, identify x-ray sub-spike features, and extract sub-spike relative delays with sub-30 attosecond temporal resolution. Deployed on low-latency hardware, it achieves over 10 kHz throughput with 168.3 μs inference latency, indicating scalability to 14 kHz with field-programmable gate array integration. By transforming regression tasks into classification problems and leveraging optimized error encoding, we achieve high precision with low-latency performance that is critical for real-time streaming event selection and experimental control feedback signals. This represents a key development in real-time control pipelines for next-generation autonomous science, generally, and high repetition-rate x-ray experiments in particular.

[Joule] Accelerated discovery of CO2-to-C3-hydrocarbon electrocatalysts with human-in-the-loop

Joule — Fri, 21 Nov 2025 00:00:00 GMT

Despite advances in automation and AI, accelerating discovery in heterogeneous electrocatalysts remains hindered by the experimental challenges of building integrated platforms for synthesis and evaluation, as well as limited performance-relevant data. This work integrates accelerated experimentation, machine learning, and domain expertise to efficiently explore CO2-to-C3 electrocatalysts, adding new mechanistic and data-driven insights to energy science.

[Joule] Redox-mediated solid-state doping of Spiro-OMeTAD for efficient and robust perovskite photovoltaics

Joule — Fri, 21 Nov 2025 00:00:00 GMT

The volatile and unstable nature of conventional dopants severely limits the performance and operational lifetime of perovskite solar cells. Here, we demonstrate a solid-state doping strategy, enabling a uniform nanoscale doping profile while effectively suppressing ion migration. This strategy yields perovskite solar cells with a certified efficiency of 26.34% and high device stability.

[AI for Science - latest papers] Learning to be simple

AI for Science - latest papers — Thu, 20 Nov 2025 00:00:00 GMT

In this work we employ machine learning to understand structured mathematical data involving finite groups and derive a theorem about necessary properties of generators of finite simple groups. We create a database of all two-generated subgroups of the symmetric group on n-objects and conduct a classification of finite simple groups among them using shallow feed-forward neural networks. We show that this neural network classifier can decipher the property of simplicity with varying accuracies depending on the features. Our neural network model leads to a natural conjecture concerning the generators of a finite simple group. We subsequently prove this conjecture. This new toy theorem comments on the necessary properties of generators of finite simple groups. We show this explicitly for a class of sporadic groups for which the result holds. Our work further makes the case for a machine motivated study of algebraic structures in pure mathematics and highlights the possibility of generating new conjectures and theorems in mathematics with the aid of machine learning.

[RSC - Chem. Sci. latest articles] Development of a glutamine-responsive MRI contrast agent

RSC - Chem. Sci. latest articles — Thu, 20 Nov 2025 00:00:00 GMT

Chem. Sci., 2026, Advance Article
DOI: 10.1039/D5SC05987A, Edge Article

Open Access

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence.

Charles A. Wilson, Austin T. Bruchs, Saman Fatima, David G. Boggs, Jennifer Bridwell-Rabb, Lisa Olshansky
This report details the development of a conformationally switchable artificial metalloprotein (swArM) that provides differential MRI contrast signal in the presence and absence of the key biomarker glutamine.
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[Wiley: Advanced Intelligent Discovery: Table of Contents] Taguchi–Bayesian Sampling: A Roadmap for Polymer Database Construction Toward Small Representative Machine Learning

Wiley: Advanced Intelligent Discovery: Table of Contents — Wed, 19 Nov 2025 05:00:22 GMT

Advanced Intelligent Discovery, EarlyView.

[RSC - Digital Discovery latest articles] Democratizing machine learning in chemistry with community-engaged test sets

RSC - Digital Discovery latest articles — Wed, 19 Nov 2025 00:00:00 GMT

Digital Discovery, 2026, Advance Article
DOI: 10.1039/D5DD00424A, Paper

Open Access

This article is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported Licence.

Jason L. Wu, David M. Friday, Changhyun Hwang, Seungjoo Yi, Tiara C. Torres-Flores, Martin D. Burke, Ying Diao, Charles M. Schroeder, Nicholas E. Jackson
Machine learning (ML) is increasingly central to chemical discovery, yet most efforts remain confined to distributed and isolated research groups, limiting external validation and community engagement.
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The content of this RSS Feed (c) The Royal Society of Chemistry

[iScience] An Explainable Machine Learning Model Predicts 30-Day Readmission after Vertebral Augmentation

iScience — Wed, 19 Nov 2025 00:00:00 GMT

Osteoporotic vertebral compression fracture (OVCF) patients face high 30-day readmission risks after vertebral augmentation procedures (VAPs). Using electronic health records (EHRs) of 3,947 OVCF patients who underwent VAPs (2019–2024), we developed an interpretable machine learning model to identify readmission predictors. Eight algorithms were evaluated via 10-fold cross-validation, and XGBoost showed the best performance (area under the curve [AUC], sensitivity, specificity, F1 score, and decision curve analysis).

[Wiley: SmartMat: Table of Contents] Machine Learning Design of Soft Magnetoresponsive Materials With Multidirectional Fields

Wiley: SmartMat: Table of Contents — Tue, 18 Nov 2025 08:00:00 GMT

SmartMat, Volume 6, Issue 6, December 2025.

[RSC - Digital Discovery latest articles] Advancing metal organic framework and covalent organic framework design via the digital-intelligent paradigm

RSC - Digital Discovery latest articles — Tue, 18 Nov 2025 00:00:00 GMT

Digital Discovery, 2026, Advance Article
DOI: 10.1039/D5DD00401B, Review Article

Open Access

This article is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported Licence.

Bing Ma, Na Qin, Qianqian Yan, Wei Zhou, Sheng Zhang, Xiao Wang, Lipiao Bao, Xing Lu
AI and machine learning combined with multiscale simulations accelerate framework materials design. This review summarizes AI-assisted strategies for synthesis prediction, condition optimization, and inverse functional design.
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The content of this RSS Feed (c) The Royal Society of Chemistry

[RSC - Digital Discovery latest articles] Application-specific machine-learned interatomic potentials: exploring the trade-off between DFT convergence, MLIP expressivity, and computational cost

RSC - Digital Discovery latest articles — Tue, 18 Nov 2025 00:00:00 GMT

Digital Discovery, 2026, Advance Article
DOI: 10.1039/D5DD00294J, Paper

Open Access

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence.

Ilgar Baghishov, Jan Janssen, Graeme Henkelman, Danny Perez
Simultaneously tuning DFT convergence, data selection, and energy-force weights reveals a Pareto front of optimal MLIPs. This minimizes costs by tailoring the MLIP to the specific accuracy requirements of the target application.
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[Applied Physics Reviews Current Issue] Synergistic integration of metasurfaces and quantum photonics: Pathways to next-generation technologies

Applied Physics Reviews Current Issue — Mon, 17 Nov 2025 00:00:00 GMT

The convergence of metamaterials and quantum optics heralds a transformative era in photonic technologies, poised to revolutionize applications ranging from information processing and imaging to sensing and beyond. This review explores the synergistic integration of metasurfaces—engineered sub-wavelength planar structures—and quantum optics, which exploits quantum mechanical principles to manipulate light at the most granular level. We outline the design principles, fabrication processes, and computational challenges involved in creating quantum metasurfaces, discussing both forward and inverse design approaches. Advances in nanofabrication and intelligent optimization techniques, such as machine learning and topology optimization, have enabled the development of metasurfaces with unparalleled control over electromagnetic waves. We examine recent progress in using quantum metasurfaces for single-photon and multi-photon generation, quantum imaging, and quantum sensing, showcasing how these innovations achieve unprecedented precision and novel functionalities. Additionally, we highlight the integration of metasurfaces into quantum light manipulation, emphasizing their role in enhancing wavefront shaping and entanglement control. By providing a comprehensive survey of current advancements and future research directions, this review highlights the vast potential of metasurfaces and quantum optics at the crossroads, setting the stage for next-generation technological innovations that will define the forthcoming decade.

[AI for Science - latest papers] Universal machine learning potentials for systems with reduced dimensionality

AI for Science - latest papers — Mon, 17 Nov 2025 00:00:00 GMT

We present a benchmark designed to evaluate the predictive capabilities of universal machine learning interatomic potentials (MLIPs) across systems of varying dimensionality. Specifically, our benchmark tests zero- (molecules, atomic clusters, etc), one- (nanowires, nanoribbons, nanotubes, etc), two- (atomic layers and slabs) and three-dimensional (3D) (bulk materials) compounds. The benchmark reveals that while all tested models demonstrate excellent performance for 3D systems, accuracy degrades progressively for lower-dimensional structures. The best performing models for geometry optimization are orbital version 2, equiformerV2, and the equivariant Smooth Energy Network, with the equivariant Smooth Energy Network also providing the most accurate energies. Our results indicate that the best models yield, on average, errors in the atomic positions in the range of 0.01–0.02 Å and errors in the energy below 10 meV atom−1 across all dimensionalities. These results demonstrate that state-of-the-art universal MLIPs have reached sufficient accuracy to serve as direct replacements for density functional theory calculations, at a small fraction of the computational cost, in simulations spanning the full range from isolated atoms to bulk solids. More significantly, the best performing models already enable efficient simulations of complex systems containing subsystems of mixed dimensionality, opening new possibilities for modeling realistic materials and interfaces.

[Cell Reports Physical Science] Conjugated polyelectrolyte-aptamer hybrid for organic-electrochemical-transistor-based sensing

Cell Reports Physical Science — Mon, 17 Nov 2025 00:00:00 GMT

Jiang et al. present biofunctionalized organic mixed ionic-electronic conductors (OMIECs), specifically single-component materials that integrate high specificity with semiconducting properties, exemplified by p(NDI-T-ZI/EG)-aptamer. This hybrid design enables covalent attachment of diverse functional units, thereby expanding the library of sensory OMIECs for future diagnostic applications.

[Cell Reports Physical Science] CatBench framework for benchmarking machine learning interatomic potentials in adsorption energy predictions for heterogeneous catalysis

Cell Reports Physical Science — Mon, 17 Nov 2025 00:00:00 GMT

Moon et al. introduce CatBench, a framework that systematically evaluates machine learning interatomic potentials for predicting molecular adsorption from small to large molecules on catalyst surfaces. Testing 13 state-of-the-art models across ≥47,000 reactions, they identify optimal accuracy-speed trade-offs and provide quantitative guidance for selecting models for practical catalyst discovery.

[Journal of the American Chemical Society: Latest Articles (ACS Publications)] [ASAP] An O2-Independent Copper(II) Phototherapeutic Agent for Photoactivating H2O2 to Enhance Antitumor Immunotherapy

Journal of the American Chemical Society: Latest Articles (ACS Publications) — Sun, 16 Nov 2025 13:54:08 GMT

Journal of the American Chemical Society

DOI: 10.1021/jacs.5c14960

[Wiley: ENERGY & ENVIRONMENTAL MATERIALS: Table of Contents] Liquid‐Phase Synthesis of Halide Solid Electrolytes for All‐Solid‐State Batteries Using Organic Solvents

Wiley: ENERGY & ENVIRONMENTAL MATERIALS: Table of Contents — Fri, 14 Nov 2025 14:05:17 GMT

ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.

[Proceedings of the National Academy of Sciences: Physical Sciences] How public involvement can improve the science of AI

Proceedings of the National Academy of Sciences: Physical Sciences — Fri, 14 Nov 2025 08:00:00 GMT

Proceedings of the National Academy of Sciences, Volume 122, Issue 48, December 2025.
As AI systems from decision-making algorithms to generative AI are deployed more widely, computer scientists and social scientists alike are being called on to provide trustworthy quantitative evaluations of AI safety and reliability. These calls have ...

[AI for Science - latest papers] TorchSim: an efficient atomistic simulation engine in PyTorch

AI for Science - latest papers — Fri, 14 Nov 2025 00:00:00 GMT

We introduce TorchSim, an open-source atomistic simulation engine tailored for the machine learned interatomic potential (MLIP) era. By rewriting core atomistic simulation primitives in PyTorch, TorchSim can achieve orders of magnitude acceleration for popular MLIPs. Unlike existing molecular dynamics (MD) packages, which simulate one system at a time, TorchSim performs batched simulations that efficiently utilize modern GPUs by evolving multiple systems concurrently. TorchSim supports MD integrators, structural relaxation optimizers, both machine-learned and classical interatomic potentials (such as Lennard–Jones, Morse, soft-sphere), batching with automatic memory management, differentiable simulation, and integration with popular materials informatics tools.

[AI for Science - latest papers] Graph learning metallic glass discovery from Wikipedia

AI for Science - latest papers — Fri, 14 Nov 2025 00:00:00 GMT

Synthesizing new materials efficiently is highly demanded in various research fields. However, this process is usually slow and expensive, especially for metallic glasses, whose formation strongly depends on the optimal combinations of multiple elements to resist crystallization. This constraint renders only several thousands of candidates explored in the vast material space since 1960. Recently, data-driven approaches armed by advanced machine learning techniques provided alternative routes for intelligent materials design. Due to data scarcity and immature material encoding, the conventional tabular data is usually mined by statistical learning algorithms, giving limited model predictability and generalizability. Here, we propose sophisticated data learning from material network representations. The node elements are encoded from the Wikipedia by a language model. Graph neural networks with versatile architectures are designed to serve as recommendation systems to explore hidden relationships among materials. By employing Wikipedia embeddings from different languages, we assess the capability of natural languages in materials design. Our study proposes a new paradigm to harvesting new amorphous materials and beyond with artificial intelligence.

[ACS Materials Au: Latest Articles (ACS Publications)] [ASAP] Molecular Modeling-Based Machine Learning for Accurate Prediction of Gas Diffusivity and Permeability in Metal–Organic Frameworks

ACS Materials Au: Latest Articles (ACS Publications) — Wed, 12 Nov 2025 18:15:35 GMT

ACS Materials Au

DOI: 10.1021/acsmaterialsau.5c00111

[Recent Articles in PRX Energy] Dynamic Vacancy Levels in ${\mathrm{Cs}\mathrm{Pb}\mathrm{Cl}}_{3}$ Obey Equilibrium Defect Thermodynamics

Recent Articles in PRX Energy — Wed, 12 Nov 2025 10:00:00 GMT

Author(s): Irea Mosquera-Lois and Aron Walsh

This study of halide perovskites uses advanced molecular dynamics simulations with machine learning force fields to identify dynamic defect levels and their impact on the material’s optoelectronic properties.

[PRX Energy 4, 043008] Published Wed Nov 12, 2025

[Wiley: Advanced Intelligent Discovery: Table of Contents] Accelerating Primary Screening of USP8 Inhibitors from Drug Repurposing Databases with Tree‐Based Machine Learning

Wiley: Advanced Intelligent Discovery: Table of Contents — Tue, 11 Nov 2025 04:16:54 GMT

Advanced Intelligent Discovery, EarlyView.

[RSC - Digital Discovery latest articles] Design of simple-structured conjugated polymers for organic solar cells by machine learning-assisted structural modification and experimental validation

RSC - Digital Discovery latest articles — Tue, 11 Nov 2025 00:00:00 GMT

Digital Discovery, 2025, 4,3774-3781
DOI: 10.1039/D5DD00418G, Paper

Open Access

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence.

Shogo Tadokoro, Ryosuke Kamimura, Fumitaka Ishiwari, Akinori Saeki
We explore simple-structured p-type polymers for organic photovoltaics using machine learning (ML) based on the primitive use of the molecular size and synthetic accessibility. Experimental validation shows good agreement with the ML prediction.
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[Joule] Entropy-guided discovery of denary trirutile antimonates for electrocatalytic chlorine evolution

Joule — Tue, 11 Nov 2025 00:00:00 GMT

Entropy-guided trirutile antimonates are developed as highly efficient catalysts for the chlorine evolution reaction. By integrating machine learning, DFT calculations, and operando experiments, this work uncovers atomic-level mechanisms governing catalytic activity and stability.

[AI for Science - latest papers] Surface stability modeling with universal machine learning interatomic potentials: a comprehensive cleavage energy benchmarking study

AI for Science - latest papers — Fri, 07 Nov 2025 00:00:00 GMT

Machine learning interatomic potentials (MLIPs) have revolutionized computational materials science by bridging the gap between quantum mechanical accuracy and classical simulation efficiency, enabling unprecedented exploration of materials properties across the periodic table. Despite their remarkable success in predicting bulk properties, no systematic evaluation has assessed how well these universal MLIPs (uMLIPs) can predict cleavage energies, a critical property governing fracture, catalysis, surface stability, and interfacial phenomena. Here, we present a comprehensive benchmark of 19 state-of-the-art uMLIPs for cleavage energy prediction using our previously established density functional theory database of 36 718 slab structures spanning elemental, binary, and ternary metallic compounds. We evaluate diverse architectural paradigms, analyzing their performance across chemical compositions, crystal systems, thickness, and surface orientations. Our zero-shot evaluation results reveal that training data composition dominates architectural sophistication: models trained on the Open Materials 2024 (OMat24) dataset, which emphasizes non-equilibrium configurations, achieve mean absolute percentage errors below 6% and correctly identify the thermodynamically most stable surface terminations in 87% of cases, without any explicit surface energy training. In contrast, architecturally identical models trained on equilibrium-only datasets show five-fold higher errors, while models trained on surface-adsorbate data fail catastrophically with a 17-fold degradation. Remarkably, simpler architectures trained on appropriate data achieve comparable accuracy to complex transformers while offering 10–100× computational speedup. These findings fundamentally reframe MLIP development priorities: highlighting that strategic training-data generation with appropriate non-equilibrium sampling deserves equal or greater attention than architectural complexity.

[Joule] Li–Si compound anodes enabling high-performance all-solid-state Li-ion batteries

Joule — Fri, 07 Nov 2025 00:00:00 GMT

Li–Si compound anodes, exemplified by Li2.33Si, overcome the degradation issues of conventional Si anodes by combining high ionic and electronic conductivity, favorable mechanical properties, and a negligible-volume-change Li-storage mechanism (Li2.33 + αSi, 0 < α < 0.92), thereby enabling high areal capacity, long cycle life, and fast rate capability in all-solid-state Li-ion batteries.

[ACS Physical Chemistry Au: Latest Articles (ACS Publications)] [ASAP] Machine Learning as a Method for Retrieving Pressure Values by Analyzing Spectral Line Parameters: The Hydrochloric Acid Case

ACS Physical Chemistry Au: Latest Articles (ACS Publications) — Tue, 04 Nov 2025 19:09:10 GMT

ACS Physical Chemistry Au

DOI: 10.1021/acsphyschemau.5c00097

[Chinese Chemical Society: CCS Chemistry: Table of Contents] Near-Infrared-II Aggregation-Induced Emission Photosensitizers with Mitochondrial Respiration Perturbation Activity Amplifies Ferroptosis, Necroptosis, and Apoptosis for Cancer Immunotherapy

Chinese Chemical Society: CCS Chemistry: Table of Contents — Tue, 04 Nov 2025 04:36:34 GMT

CCS Chemistry, Ahead of Print.

DOI:10.31635/ccschem.025.202505952

Activation of programmed cell death (PCD) networks in cancer cells represents an emerging paradigm in precision oncology. However, conventional antitumor agents remain constrained by insufficient cellular targeting and limited capacity to engage multiple ...

[Applied Physics Reviews Current Issue] Dynamic landscape of chemiresistive breathomic nanosensors based on fifth-generation chips for complex disease diagnosis and healthcare monitoring

Applied Physics Reviews Current Issue — Tue, 04 Nov 2025 00:00:00 GMT

The growing global population is overwhelming the existing medical infrastructure, demanding a pressing need for the advancement of early-stage and point-of-care disease diagnostics. Conventional techniques are mostly invasive, time-consuming, expensive, sophisticated, and centered at urban facilities. Moreover, they are unable to address the biological complexities related to critical diseases, disorders, and pandemics, resulting in associated high morbidity and mortality. To address this gap, miniaturized fifth-generation sensing chips provide alternatives in terms of accessibility, affordability, and adaptability, being point-of-care and minimally invasive diagnostics. In this context, Breathomic chips based on nanoscale semiconductors have shown their potential for noninvasive, personalized, and on-site operation, offering the capability to identify volatile organic compounds/gases as disease biomarkers from exhaled breath and enabling early disease detection. However, the practical implementation of these sensors in real-time medical contexts remains challenging due to factors including the lack of clinical trials, dedicated data analysis, understanding of the complexities, public awareness, scalability, and accessibility. This comprehensive review critically summarizes the landscape of breath biomarkers detecting fifth-generation chemiresistive chips for human disease diagnosis, methodically outlining associated challenges, alternative strategies, and prospects for clinical implementations and commercial advancement. It details the biological origins of biomarkers, the diverse sensing modalities, and the underlying mechanisms pertaining to breathomic biomarker diagnosis. Furthermore, it highlights the integration of digital-age technologies, including nanotechnology, artificial intelligence, bioinformatics, and machine learning, for high-performance breathomic chips. These next-generation smart sensory chips have the potential to revolutionize medical healthcare facilities, improving patient outcomes, understanding prognosis, and aiding the UN's sustainable development goals.

[RSC - Digital Discovery latest articles] Machine learning of polyurethane prepolymer viscosity: a comparison of chemical and physicochemical approaches

RSC - Digital Discovery latest articles — Tue, 04 Nov 2025 00:00:00 GMT

Digital Discovery, 2025, 4,3652-3661
DOI: 10.1039/D5DD00287G, Paper

Open Access

This article is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported Licence.

Joseph A. Pugar, Calvin Gang, Isabelle Millan, Karl Haider, Newell R. Washburn
A dual machine learning framework predicts polyurethane prepolymer viscosity using either chemical composition or physicochemical descriptors, balancing accuracy for known chemistries with generalizability to new formulations.
The content of this RSS Feed (c) The Royal Society of Chemistry

[Chinese Chemical Society: CCS Chemistry: Table of Contents] Biodegradable Cesium Nanosalts Activating Antitumor Immunity via Inducing Cellular Pyroptosis and Interfering with Metabolism

Chinese Chemical Society: CCS Chemistry: Table of Contents — Mon, 03 Nov 2025 01:13:27 GMT

CCS Chemistry, Ahead of Print.

DOI:10.31635/ccschem.025.202506187

Nanosalts deserve to be taken seriously as an important kind of superior antitumor agent. However, nanosalts for tumor therapy are still a little-touched “Blue Ocean.” Broadening the material library of nanosalts is particularly important to extend their ...

[tandf: Materials Research Letters: Table of Contents] Machine learning-assisted design of strong and ductile BCC high-entropy alloys

tandf: Materials Research Letters: Table of Contents — Thu, 30 Oct 2025 12:22:23 GMT

Volume 13, Issue 12, December 2025, Page 1260-1268
.

[RSC - Digital Discovery latest articles] FFLAME: a fragment-to-framework learning approach for MOF potentials

RSC - Digital Discovery latest articles — Thu, 30 Oct 2025 00:00:00 GMT

Digital Discovery, 2025, 4,3466-3477
DOI: 10.1039/D5DD00321K, Paper

Open Access

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence.

Xiaoqi Zhang, Yutao Li, Xin Jin, Berend Smit
FFLAME, a fragment-centric strategy for training transferable MOF machine learning potentials, learns from building blocks, lowers data needs, and achieves near-target accuracy with minimal fine-tuning even for unseen MOFs.
The content of this RSS Feed (c) The Royal Society of Chemistry

[RSC - Digital Discovery latest articles] Machine learning generalised DFT+U projectors in a numerical atom-centred orbital framework

RSC - Digital Discovery latest articles — Thu, 30 Oct 2025 00:00:00 GMT

Digital Discovery, 2025, 4,3701-3727
DOI: 10.1039/D5DD00292C, Paper

Open Access

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence.

Amit Chaudhari, Kushagra Agrawal, Andrew J. Logsdail
We present machine learning-based workflows using symbolic regression and support vector machines to simultaneously optimise Hubbard U values and projectors, enabling accurate and efficient simulations of defects and polarons in complex metal oxides.
The content of this RSS Feed (c) The Royal Society of Chemistry

[RSC - Digital Discovery latest articles] Leveraging large language models for enzymatic reaction prediction and characterization

RSC - Digital Discovery latest articles — Thu, 30 Oct 2025 00:00:00 GMT

Digital Discovery, 2025, 4,3588-3609
DOI: 10.1039/D5DD00187K, Paper

Open Access

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence.

Lorenzo Di Fruscia, Jana M. Weber
We present a systematic study of multitask Large Language Models, fine-tuned to predict enzyme commission numbers and to perform forward and retrosynthesis of enzymatic reactions.
The content of this RSS Feed (c) The Royal Society of Chemistry

[RSC - Digital Discovery latest articles] Cross-laboratory validation of machine learning models for copper nanocluster synthesis using cloud-based automated platforms

RSC - Digital Discovery latest articles — Thu, 30 Oct 2025 00:00:00 GMT

Digital Discovery, 2025, 4,3683-3692
DOI: 10.1039/D5DD00335K, Paper

Open Access

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence.

Ricardo Montoya-Gonzalez, Rosa de Guadalupe González-Huerta, Martha Leticia Hernández-Pichardo, Subha R. Das
Cloud laboratory robotic synthesis of copper nanoclusters combined with ML enables predictive models from just 40 experiments
The content of this RSS Feed (c) The Royal Society of Chemistry

[Wiley: InfoMat: Table of Contents] Delicate design of lithium‐ion bridges in hybrid solid electrolyte for wide‐temperature adaptive solid‐state lithium metal batteries

Wiley: InfoMat: Table of Contents — Wed, 29 Oct 2025 00:36:10 GMT

InfoMat, EarlyView.

[APL Machine Learning Current Issue] Building an affordable self-driving lab: Practical machine learning experiments for physics education using Internet-of-Things

APL Machine Learning Current Issue — Wed, 29 Oct 2025 00:00:00 GMT

Machine learning (ML) is transforming modern physics research, but practical, hands-on experience with ML techniques remains limited due to cost and complexity barriers. To address this gap, we introduce an affordable, autonomous, Internet-of-Things (IoT)-enabled experimental platform designed specifically for applied physics education. Utilizing an Arduino microcontroller, a customizable multi-wavelength light emitting diode array, and photosensors, our setup generates diverse, real-time optical datasets ideal for training and evaluating foundational ML algorithms, including traversal methods, Bayesian inference, and deep learning. The platform facilitates a closed-loop, self-driving experimental workflow, encompassing automated data collection, preprocessing, model training, and validation. Through systematic performance comparisons, we demonstrate the superior ability of deep learning to capture complex nonlinear relationships compared to traversal and Bayesian methods. At ∼$60, this open-source IoT platform provides an accessible, practical pathway for students to master advanced ML concepts, promoting deeper conceptual insights and essential technical skills required for the next generation of physicists and engineers.

[APL Machine Learning Current Issue] Data integration and data fusion approaches in self-driving labs: A perspective

APL Machine Learning Current Issue — Wed, 29 Oct 2025 00:00:00 GMT

Self-driving laboratories (SDLs) are transforming materials discovery by combining automation, machine learning, and real-time feedback. Yet, their success depends on robust data integration and fusion methods capable of handling materials data that are heterogeneous, sparse, and multi-scale. Such data span theoretical models, simulations, and experimental techniques across diverse spatial and temporal scales, creating significant challenges for interoperability and analysis. This perspective reviews the state-of-the-art techniques, including knowledge graphs, structured pipelines, multimodal machine learning, and physics-informed models, that are enabling materials science and SDLs to unify and learn from disparate data sources, identify critical challenges, and propose forward-looking directions to enhance data readiness, interoperability, and predictive power in SDLs. We also highlight emerging methods such as transformer architectures, zero-shot learning, and real-time stream processing, and discuss the critical need for more scalable, interpretable, and adaptive solutions to fully realize autonomous materials innovation. By mapping out both the current landscape and future opportunities, we argue that next-generation data integration and fusion are not just enablers but essential pillars for achieving fully autonomous, adaptive, and intelligent SDL systems capable of addressing the complexities of hierarchical and multifunctional materials.

[RSC - Digital Discovery latest articles] Machine learning anomaly detection of automated HPLC experiments in the cloud laboratory

RSC - Digital Discovery latest articles — Wed, 29 Oct 2025 00:00:00 GMT

Digital Discovery, 2025, 4,3445-3454
DOI: 10.1039/D5DD00253B, Paper

Open Access

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence.

Filipp Gusev, Benjamin C. Kline, Ryan Quinn, Anqin Xu, Ben Smith, Brian Frezza, Olexandr Isayev
Autonomous experiments are vulnerable to unforeseen adverse events. We developed a transferable ML framework that flags affected HPLC runs in real time and provides expert-level quality control without human oversight.
The content of this RSS Feed (c) The Royal Society of Chemistry

[Applied Physics Reviews Current Issue] Strain engineering of van Hove singularity and coupled itinerant ferromagnetism in quasi-2D oxide superlattices

Applied Physics Reviews Current Issue — Tue, 28 Oct 2025 00:00:00 GMT

Engineering van Hove singularities (vHss) near the Fermi level, if feasible, offers a powerful route to control exotic quantum phases in electronic and magnetic behaviors. However, conventional approaches rely primarily on chemical and electrical doping and focus mainly on local electrical or optical measurements, limiting their applicability to coupled functionalities. In this study, a vHs-induced insulator-metal transition coupled with a ferromagnetic phase transition was empirically achieved in atomically designed quasi-2D SrRuO₃ (SRO) superlattices via epitaxial strain engineering, which has not been observed in conventional 3D SRO systems. Theoretical calculations revealed that epitaxial strain effectively modulates the strength and energy positions of vHs of specific Ru orbitals, driving correlated phase transitions in the electronic and magnetic ground states. X-ray absorption spectroscopy confirmed the anisotropic electronic structure of quasi-2D SRO modulated by epitaxial strain. Magneto-optic Kerr effect and electrical transport measurements demonstrated modulated magnetic and electronic phases. Furthermore, magneto-electrical measurements detected significant anomalous Hall effect signals and ferromagnetic magnetoresistance, indicating the presence of magnetically coupled charge carriers in the 2D metallic regime. This study establishes strain engineering as a promising platform for tuning vHss and resultant itinerant ferromagnetism of low-dimensional correlated quantum systems.

[Wiley: Advanced Intelligent Discovery: Table of Contents] Machine Learning‐Enhanced Random Matrix Theory Design for Human Immunodeficiency Virus Vaccine Development

Wiley: Advanced Intelligent Discovery: Table of Contents — Mon, 27 Oct 2025 03:21:44 GMT

Advanced Intelligent Discovery, EarlyView.

[RSC - Digital Discovery latest articles] An improved machine learning strategy using structural features to predict the glass transition temperature of oxide glasses

RSC - Digital Discovery latest articles — Thu, 23 Oct 2025 23:00:00 GMT

Digital Discovery, 2025, 4,3764-3773
DOI: 10.1039/D5DD00326A, Paper

Open Access

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence.

Satwinder Singh Danewalia, Kulvir Singh
We present a physics-informed machine learning approach to predict the glass transition temperature (T_g) of sodium borosilicate glasses.
The content of this RSS Feed (c) The Royal Society of Chemistry

[Applied Physics Reviews Current Issue] 3D-printed lithium-metal batteries: Multiscale architectures, hybrid technologies, and monolithic integration for next-generation energy storage

Applied Physics Reviews Current Issue — Thu, 23 Oct 2025 00:00:00 GMT

Lithium-metal anodes, with their unmatched theoretical capacity (3860 mAh g⁻¹) and ultra-low electrochemical potential (−3.04 V vs standard hydrogen electrode), are pivotal for next-generation high-energy-density batteries. However, their practical deployment is hindered by persistent challenges—dendritic growth, unstable solid electrolyte interphases (SEIs), and severe volumetric expansion. Emerging as a transformative solution, three-dimensional (3D) printing enables the rational design of multiscale architectures (e.g., micro-lattice anodes and gradient-porous cathodes) and hybrid solid-state electrolytes to address these limitations. This review presents a pioneering synthesis of 3D printing's role in lithium-metal battery engineering, focusing on its capacity to regulate lithium-ion flux, stabilize SEIs, and suppress dendrite proliferation through hierarchical structural control. We systematically analyze four key additive manufacturing technologies (inkjet printing, direct ink writing, fused deposition modeling, and stereolithography), delineating their unique advantages in tailoring ion transport pathways and mechanical robustness. Furthermore, we propose multi-material co-printing strategies to resolve interfacial incompatibilities in monolithic lithium-metal batteries, a critical barrier in current research. By bridging additive manufacturing with electrochemical fundamentals, this work outlines a roadmap to harness 3D printing's full potential, addressing scalability challenges and advancing applications in aerospace, wearables, and biomedical devices where energy density and safety are paramount.

[Wiley: Advanced Intelligent Discovery: Table of Contents] Harnessing Large Language Models to Advance Microbiome Research: From Sequence Analysis to Clinical Applications

Wiley: Advanced Intelligent Discovery: Table of Contents — Tue, 21 Oct 2025 05:48:44 GMT

Advanced Intelligent Discovery, EarlyView.

[RSC - Digital Discovery latest articles] GoFlow: efficient transition state geometry prediction with flow matching and E(3)-equivariant neural networks

RSC - Digital Discovery latest articles — Mon, 20 Oct 2025 23:00:00 GMT

Digital Discovery, 2025, 4,3492-3501
DOI: 10.1039/D5DD00283D, Paper

Open Access

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence.

Leonard Galustian, Konstantin Mark, Johannes Karwounopoulos, Maximilian P.-P. Kovar, Esther Heid
We introduce GoFlow, a package to generate 3D transition state geometries using flow matching.
The content of this RSS Feed (c) The Royal Society of Chemistry

[AI for Science - latest papers] AInstein: numerical Einstein metrics via machine learning

AI for Science - latest papers — Thu, 16 Oct 2025 23:00:00 GMT

A new semi-supervised machine learning package is introduced which successfully solves the Euclidean vacuum Einstein equations with a cosmological constant, without any symmetry assumptions. The model architecture contains subnetworks for each patch in the manifold-defining atlas. Each subnetwork predicts the components of a metric in its associated patch, with the relevant Einstein conditions of the form being used as independent loss components (here , where n is the dimension of the Riemannian manifold, and the Einstein constant ). To ensure the consistency of the global structure of the manifold, another loss component is introduced across the patch subnetworks which enforces the coordinate transformation between the patches, , for an appropriate analytically known Jacobian J. We test our method for the case of spheres represented by a pair of patches in dimensions 2, 3, 4, and 5. In dimensions 2 and 3, the geometries have been fully classified. However, it is unknown whether a Ricci-flat metric can exist on spheres in dimensions 4 and 5. This work hints against the existence of such a metric.

[Matter] SpectroGen: A physically informed generative artificial intelligence for accelerated cross-modality spectroscopic materials characterization

Matter — Tue, 14 Oct 2025 00:00:00 GMT

SpectroGen seamlessly couples physics-driven distribution models with a variable autoencoder to generate synthetic spectra indistinguishable from real data. By speeding up high-throughput screening, it closes the gap between AI-based materials discovery and experimental confirmation. Its flexible architecture accommodates diverse spectroscopic techniques, extending its utility across multiple scientific domains. The synergy of rapid AI-driven design and swift AI-enabled characterization expedites validation of innovative materials, bridging lab-based discovery and industry-ready applications to address urgent societal needs.

[Chem] Precisely modulating Li2CO3 coverage on Ni-rich cathode boosts sulfide solid-state lithium battery performance

Chem — Tue, 14 Oct 2025 00:00:00 GMT

It is of great importance to address the issues of stability and charge transfer at the cathode/electrolyte interface in all-solid-state lithium batteries (ASSLBs). We proposed a CO2 atmosphere treatment to precisely modulate Li2CO3 coverage on Ni-rich layered oxide cathodes (NRLOs) with minimal damage, effectively utilizing the advantageous effect while avoiding the harmful effect of surficial Li2CO3 on the interface. This fundamental mechanism offers insights for optimizing the NRLO/sulfide solid electrolyte interface and advancing high-energy-density ASSLBs.

[RSC - Digital Discovery latest articles] Do Llamas understand the periodic table?

RSC - Digital Discovery latest articles — Mon, 13 Oct 2025 23:00:00 GMT

Digital Discovery, 2025, 4,3455-3465
DOI: 10.1039/D5DD00374A, Paper

Open Access

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence.

Ge Lei, Samuel J. Cooper
We observe a 3D spiral structure in the hidden states of LLMs that aligns with the conceptual structure of the periodic table.
The content of this RSS Feed (c) The Royal Society of Chemistry

[Applied Physics Reviews Current Issue] Carbon-based memristors for neuromorphic computing

Applied Physics Reviews Current Issue — Mon, 13 Oct 2025 00:00:00 GMT

Driven by the rapid advancement of the Internet of Things and artificial intelligence, computational power demands have experienced an exponential surge, thereby accentuating the inherent limitations of the conventional von Neumann architecture. Neuromorphic computing memristors are emerging as a promising solution to overcome this bottleneck. Among various material-based memristors, carbon-based memristors (CBMs) are particularly attractive due to their biocompatibility, flexibility, and stability, which make them well suited for next-generation neuromorphic applications. This review summarizes the recent advancements in CBMs and proposes potential application scenarios in neuromorphic computing. Representative CBMs and preparation methods of carbon-based materials in different dimensions (0D, 1D, 2D, and 3D) are presented, followed by structural, storage, and synaptic plasticity testing and switching mechanisms. The neural network architecture built by CBMs is summarized for image processing, wearable electronics, and three-dimensional integration. Finally, the future challenges and application prospects of CBMs are reviewed and summarized.

[Matter] Dynamic pressure mapping of infant cervical spines using a wearable magnetoelastic patch

Matter — Fri, 10 Oct 2025 00:00:00 GMT

To enable continuous monitoring of infant cervical motion, we present a kirigami-inspired soft magnetoelastic patch that conforms intimately to the cervical position without compromising comfort. By leveraging passive magnetic sensing and flexible structural design, the patch captures subtle biomechanical changes during cervical movements. Integrated with machine learning classification, it enables intelligent recognition of stress patterns, providing a non-invasive and adaptive solution for early assessment of infant cervical motion.

[Matter] Machine learning-driven ligand engineering decodes and controls structural distortions in 2D perovskites

Matter — Fri, 10 Oct 2025 00:00:00 GMT

This work deciphers how ligand molecular descriptors (i.e., nitrogen content, hydrogen bonding, and π-conjugation) govern structural distortions and optoelectronic properties in 2D perovskites. The authors demonstrate that machine learning can quantitatively correlate these descriptors with octahedral distortions (92.6% prediction accuracy) and enable the targeted synthesis of six new perovskites with tunable band gaps (1.91–2.39 eV). The established structure-property relationships and machine learning-driven design paradigm represent a transformative approach for accelerating the discovery of functional perovskites, bridging computational prediction with experimental validation for optoelectronic applications.

[Applied Physics Reviews Current Issue] The enduring legacy of scanning spreading resistance microscopy: Overview, advancements, and future directions

Applied Physics Reviews Current Issue — Wed, 08 Oct 2025 00:00:00 GMT

Scanning spreading resistance microscopy (SSRM) has recently celebrated 30 years of existence when counting from the original patent of 1994. In this time, the technique has experienced an incredible journey with substantial evolutions that transformed SSRM from a small-scale experiment into a staple for chip manufacturing laboratories for physical analysis of materials, failure analysis, and process development of integrated circuits. As the nanoelectronics industry is ready for a new inflection point, with the introduction of nanosheet field-effect transistor to replace FinFETs and cell track scaling architectures such as the complementary field-effect transistors, SSRM is once again at a turning point. This review aims to highlight the state-of-the-art while discussing the emerging challenges introduced by the ever-increasing complexity in complementary metal–oxide–semiconductor (CMOS) manufacturing. We start by illustrating the unique capability of the SSRM technique, its origin, and its evolution. Next, we continue by showing the considerable research effort that enabled SSRM to transition to a tomographic sensing method in support of FinFET transistors. Here, the high aspect ratio fin geometry and the complex contacts technology have imposed important modifications to the original method. Later, we elaborate on some of the key challenges introduced by the upcoming device transition from three-sided channel FinFETs into nanosheet FETs, i.e., offering a four-sided electrostatic control of the channel. Finally, we present the use of machine learning for automation in carrier calibration with increased accuracy. We close by introducing some of the concepts that we consider promising for further extension of SSRM to obtain sub-nm structural information and doping profiles in the area of advanced FinFETs and nanosheet FET technologies, including (a) correlative analysis flow, (b) liquid-assisted probing, and (c) top–down and bottom–up multi-probe sensing schemes to merge low- and high-pressure SSRM scans.

[Chinese Chemical Society: CCS Chemistry: Table of Contents] Oxygen Vacancy-Modulated Molybdenum Oxide/Montmorillonite Heterointerface Nanoarchitectures for Plasmon-Enhanced Solar-Osmotic Energy Harvesting

Chinese Chemical Society: CCS Chemistry: Table of Contents — Mon, 06 Oct 2025 03:22:16 GMT

CCS Chemistry, Ahead of Print.

DOI:10.31635/ccschem.025.202506132

Two-dimensional (2D) nanofluidic membranes with precise ion transport kinetics hold transformative potential for next-generation ion-selective membranes, yet their practical implementation in osmotic energy conversion remains constrained by inherent ...

[RSC - Digital Discovery latest articles] Constructing and explaining machine learning models for the exploration and design of boron-based Lewis acids

RSC - Digital Discovery latest articles — Sun, 05 Oct 2025 23:00:00 GMT

Digital Discovery, 2025, 4,3623-3634
DOI: 10.1039/D5DD00212E, Paper

Open Access

This article is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported Licence.

Juliette Fenogli, Laurence Grimaud, Rodolphe Vuilleumier
Bridging ML and chemical intuition, interpretable models predict Lewis acidity with high accuracy and reveal design rules for tailoring boron-based Lewis acids.
The content of this RSS Feed (c) The Royal Society of Chemistry

[APL Machine Learning Current Issue] Deep learning model of myofilament cooperative activation and cross-bridge cycling in cardiac muscle

APL Machine Learning Current Issue — Fri, 03 Oct 2025 00:00:00 GMT

Cardiac muscle contraction is driven by the cross-bridge cycle, where myosin heads generate force by cyclically attaching to and pulling on actin filaments using energy from ATP. Modeling this process is central to understanding cardiac sarcomere mechanics. In this study, we developed supervised machine learning (ML) models using artificial neural networks (ANNs) to simulate cross-bridge cycling and muscle behavior under isosarcometric, isometric, and isotonic conditions. Trained on synthetic data, the ANN captured nonlinear dependencies among calcium concentration, stiffness, sarcomere length, temperature, and force output. Error analysis through histograms and unity-line scatterplots validated prediction accuracy and identified underfitting and overfitting patterns. Comparisons across ANN architectures showed how hidden layer complexity affects model generalization. The present deep learning models accurately reproduced key physiological behaviors, including steady-state force–Ca²⁺ relations, sarcomere length changes, and force–velocity relations, and matched theoretical results. This work demonstrates the potential of ML tools to enhance cardiac muscle modeling and exploit existing experimental datasets for improved prediction of cardiac muscle diseases.

[RSC - Digital Discovery latest articles] ReactPyR: a python workflow for ReactIR allows for quantification of the stability of sensitive compounds in air

RSC - Digital Discovery latest articles — Thu, 02 Oct 2025 23:00:00 GMT

Digital Discovery, 2025, 4,3533-3539
DOI: 10.1039/D5DD00305A, Paper

Open Access

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence.

Nicola L. Bell, Emanuele Berardi, Marina Gladkikh, Richard Drummond Turnbull, Freya Turton
ReactPyR enables automated ReactIR workflows to quantify air-sensitivity in organometallic reagents, delivering reproducible kinetic insights and guiding stabilisation strategies for safer, more efficient handling of highly reactive species.
The content of this RSS Feed (c) The Royal Society of Chemistry

[Applied Physics Reviews Current Issue] Extracellular vesicles as the drug delivery vehicle for gene-based therapy

Applied Physics Reviews Current Issue — Wed, 01 Oct 2025 00:00:00 GMT

Extracellular vesicles (EVs) are membrane-bound nanoparticles naturally secreted by cells, playing a vital role in intercellular communication and holding significant promise as therapeutic agents. These natural carriers deliver various molecules into cells, including proteins and nucleic acids. There are numerous methods to load and modify EVs, encompassing physical, chemical, and biological approaches. EVs demonstrate the capacity to target specific cells within organs, even requiring blood–tissue transition. The protein corona significantly influences EV availability and cargo delivery, with biomolecules residing both within and conjugated to the EV membrane. Furthermore, embedding EVs within biomaterials such as hydrogels, scaffolds, and nanofibers can enhance their stability, targeting specificity, and therapeutic potential. By addressing cargo loading and cell/tissue-specific targeting, EVs offer a novel therapeutic strategy for various diseases, including cancer, autoimmune disorders, and neurodegenerative diseases. Furthermore, EVs show promise as vaccination tools, delivering messenger RNA and proteins of various pathogens. Advances in EV biology and engineering would provide improved strategies for vesicle targeting, enhanced cargo loading, and safe and effective delivery. The convergence of technological advancements, interdisciplinary collaboration, and an enhanced understanding of EVs promises to revolutionize therapeutic approaches to a wide range of diseases, establishing EV-based treatments as a cornerstone of future medicine.

[Wiley: Advanced Intelligent Discovery: Table of Contents] Discovery of Novel Materials with Giant Dielectric Constants via First‐Principles Phonon Calculations and Machine Learning

Wiley: Advanced Intelligent Discovery: Table of Contents — Tue, 30 Sep 2025 06:30:24 GMT

Advanced Intelligent Discovery, EarlyView.

[AI for Science - latest papers] FastTrack: a fast method to evaluate mass transport in solid leveraging universal machine learning interatomic potential

AI for Science - latest papers — Mon, 29 Sep 2025 23:00:00 GMT

We introduce a rapid, accurate framework for computing atomic migration barriers in crystals by combining universal machine‐learning force fields (MLFFs) with 3D potential‐energy‐surface sampling and interpolation. Our method suppresses periodic self‐interactions via supercell expansion, builds a continuous potential energy surface (PES) from MLFF energies on a spatial grid, and extracts minimum‐energy pathways without predefined nudged elastic band (NEB) images. For a benchmark set of twelve electrode and electrolyte materials, including LiCoO2, LiFePO4, and Li10GeP2S12, our MLFF‐derived barriers lie within tens of meV of density functional theory (DFT) and experiment values, while achieving a ∼100-fold speedup over standard DFT‐NEB calculations. We benchmark GPTFF, CHGNet, and MACE, showing that fine‐tuning on PBE/PBE + U data further enhances accuracy. Ultimately, we introduce an open‐source package for high‐throughput materials screening and interactive PES visualization.

[Wiley: Advanced Intelligent Discovery: Table of Contents] Artificial Intelligence‐Driven Insights into Electrospinning: Machine Learning Models to Predict Cotton‐Wool‐Like Structure of Electrospun Fibers

Wiley: Advanced Intelligent Discovery: Table of Contents — Wed, 24 Sep 2025 13:21:08 GMT

Advanced Intelligent Discovery, EarlyView.

[AI for Science - latest papers] 4D-MISR: a unified model for low-dose super-resolution imaging via feature fusion

AI for Science - latest papers — Wed, 17 Sep 2025 23:00:00 GMT

While an electron microscope offers crucial atomic-resolution insights into structure–property relationships, radiation damage severely limits its use on beam-sensitive materials like proteins and 2D materials. To overcome this challenge, we push beyond the electron dose limits of the conventional method by adapting principles from multi-image super-resolution that had been widely used in remote sensing. Our method fuses multiple low-resolution, sub-pixel-shifted views and enhances this reconstruction with a convolutional neural network that integrates features from synthetic, multi-angle observations. We developed a dual-path, attention-guided network for four-dimensional scanning transmission electron microscopy (4D-STEM) that achieves atomic-scale super-resolution from ultra-low-dose data. This provides robust atomic-scale visualization across amorphous, semi-crystalline, and crystalline beam-sensitive specimens. Systematic evaluations on representative materials demonstrate the comparable spatial resolution to conventional ptychography under ultra low-dose conditions. Our work one-step expands the capabilities of 4D-STEM, offering a new and generalizable method for the structural analysis of any radiation-vulnerable material.

[Recent Articles in PRX Energy] Thermodynamic Modeling of Complex Solid Solutions in the $\mathrm{Lu}$-$\mathrm{H}$-$\mathrm{N}$ System via Graph Neural Network Accelerated Monte Carlo Simulations

Recent Articles in PRX Energy — Tue, 02 Sep 2025 10:00:00 GMT

Author(s): Pin-Wen Guan, Catalin D. Spataru, Vitalie Stavila, Reese Jones, Peter A. Sharma, and Matthew D. Witman

A thermodynamic modeling framework captures interstitial lattice disorder in complex metal hydrides, yielding pressure- and temperature-dependent phase diagrams that align with experiments and show how nitrogen doping can lower dehydrogenation temperatures for optimized hydrogen-storage alloys.

[PRX Energy 4, 033013] Published Tue Sep 02, 2025

[Recent Articles in PRX Energy] Reconstructions and Dynamics of $β$-Lithium Thiophosphate Surfaces

Recent Articles in PRX Energy — Tue, 26 Aug 2025 10:00:00 GMT

Author(s): Hanna Türk, Davide Tisi, and Michele Ceriotti

Machine-learning-based molecular dynamics simulations of the solid electrolyte $β$ -Li $_{3}$ PS $_{4}$ under realistic conditions reveal dynamic surface structure and reactivity.

[PRX Energy 4, 033010] Published Tue Aug 26, 2025

[Wiley: Advanced Intelligent Discovery: Table of Contents] Application of Neural Networks for Advanced Ir Spectroscopy Characterization of Ceria Catalysts Surfaces

Wiley: Advanced Intelligent Discovery: Table of Contents — Mon, 25 Aug 2025 07:01:05 GMT

Advanced Intelligent Discovery, EarlyView.

[Chem] Photocatalytic hydrogenation of alkenes using ammonia-borane

Chem — Mon, 25 Aug 2025 00:00:00 GMT

Hydrogenation of olefins is a key reaction in chemistry; however, it typically requires the use of flammable hydrogen gas with transition metal catalysis. This work presents a novel approach employing ammonia-borane, a stable and non-toxic reagent, as a hydrogen surrogate material under photocatalytic conditions, which efficiently circumvents the use of hydrogen and metal catalysis.

[Chem] Stereoselective C(sp3)-Si/Ge bond formation via nickel-catalyzed decarboxylative couplings

Chem — Thu, 21 Aug 2025 00:00:00 GMT

A long-standing gap in the catalytic synthesis of Si- and Ge-glycosides—particularly Ge analogs—has been filled by a stereoselective Ni-catalyzed decarboxylative coupling. This strategy enables selective C(sp³)–Si/Ge bond formation from redox-active esters and (silyl/germyl) zinc reagents, operating through a distinct Ni(0)/Ni(I)/Ni(II) cycle involving SET-mediated N–O bond cleavage. Ge- and Si-glycosides demonstrated promising bioactivity for the first time. These findings expand the synthetic repertoire for bioactive glycomimetics and provide new mechanistic insights into NHPI ester activation in cross-coupling chemistry.

[Matter] CGformer: Transformer-enhanced crystal graph network with global attention for material property prediction

Matter — Wed, 20 Aug 2025 00:00:00 GMT

Designing new materials for better batteries is a major challenge, especially for complex “high-entropy” materials with countless atomic combinations. We developed a novel AI model, CGformer, that looks at the entire crystal structure to accurately predict material properties. By screening nearly 150,000 candidates, our AI identified promising new sodium-ion solid electrolytes. We successfully synthesized these materials, and they showed excellent performance, validating our AI-driven discovery pipeline. This work provides a powerful tool to accelerate the design of next-generation energy materials.

[Chem] Organosilicon precursors for efficient aromatic copper-mediated radiocyanation

Chem — Wed, 20 Aug 2025 00:00:00 GMT

We present a copper-mediated labeling of aryl silanes with carbon-11, a radioactive isotope used in positron emission tomography imaging. The approach enables late-stage and efficient tagging of organic molecules, helping to accelerate the development of new imaging agents for biomedical imaging.

[Chem] Manganese low-energy photocatalysis for remodeling nitrogenation of alkenes

Chem — Tue, 19 Aug 2025 00:00:00 GMT

A manganese low-energy photoredox catalytic platform via the in situ assembly of a manganese(II) salt, a bidentate N ligand, a nucleophilic azide reagent, and an alcohol is established. This catalytic platform enables the oxidative remodeling nitrogenation of alkenes, efficiently synthesizing ketonitriles, ketones, or nitriles with excellent functional group tolerance. Additionally, the feasibility for late-stage functionalization of drug molecule derivatives and streamlined synthesis of anabasine demonstrates the potential applications of this protocol in synthetic organic chemistry and biomedicine.

[Recent Articles in PRX Energy] Large-Scale Simulation Unveiled Superior Potassium-Based Solid Electrolyte with High Ionic Conductivity and Excellent Electrochemical Stability in ${M}_{5}{\mathrm{YSi}}_{4}{\mathrm{O}}_{12}$ ($M=\mathrm{Li},\mathrm{K}$)

Recent Articles in PRX Energy — Thu, 14 Aug 2025 10:00:00 GMT

Author(s): Zhao Li, Jiaxiang Li, Congwei Xie, Keith Butler, Fei Du, and Yu Xie

Advanced computational modeling predicts the ionic conductivity and electrochemical stability of a promising potassium-based solid electrolyte. The approach highlights the importance of longer length and time scales during simulations, achievable with machine learning potentials.

[PRX Energy 4, 033007] Published Thu Aug 14, 2025

[Wiley: Advanced Intelligent Discovery: Table of Contents] Interpretable Machine Learning for Solvent‐Dependent Carrier Mobility in Solution‐Processed Organic Thin Films

Wiley: Advanced Intelligent Discovery: Table of Contents — Fri, 08 Aug 2025 09:54:45 GMT

Advanced Intelligent Discovery, EarlyView.

[Wiley: Advanced Intelligent Discovery: Table of Contents] Macrophage Phenotype Detection Methodology on Textured Surfaces via Nuclear Morphology Using Machine Learning

Wiley: Advanced Intelligent Discovery: Table of Contents — Fri, 01 Aug 2025 08:40:28 GMT

Advanced Intelligent Discovery, EarlyView.

[Wiley: Advanced Intelligent Discovery: Table of Contents] CrossMatAgent: AI‐Assisted Design of Manufacturable Metamaterial Patterns via Multi‐Agent Generative Framework

Wiley: Advanced Intelligent Discovery: Table of Contents — Fri, 25 Jul 2025 08:24:33 GMT

Advanced Intelligent Discovery, EarlyView.

[Wiley: Advanced Intelligent Discovery: Table of Contents] Topology‐Aware Machine Learning for High‐Throughput Screening of MOFs in C8 Aromatic Separation

Wiley: Advanced Intelligent Discovery: Table of Contents — Thu, 24 Jul 2025 10:45:19 GMT

Advanced Intelligent Discovery, EarlyView.

[Recent Articles in PRX Energy] Origin of Intrinsically Low Thermal Conductivity in a Garnet-Type Solid Electrolyte: Linking Lattice and Ionic Dynamics with Thermal Transport

Recent Articles in PRX Energy — Thu, 17 Jul 2025 10:00:00 GMT

Author(s): Yitian Wang, Yaokun Su, Jesús Carrete, Huanyu Zhang, Nan Wu, Yutao Li, Hongze Li, Jiaming He, Youming Xu, Shucheng Guo, Qingan Cai, Douglas L. Abernathy, Travis Williams, Kostiantyn V. Kravchyk, Maksym V. Kovalenko, Georg K.H. Madsen, Chen Li, and Xi Chen

Using a comprehensive experimental and computational approach, this work analyzes the intrinsically low thermal conductivity of solid ionic conductor Li $_{6.5}$ La $_{3}$ Zr $_{1.5}$ Ta $_{0.5}$ O $_{12}$ , a promising electrolyte for all-solid-state batteries.

[PRX Energy 4, 033004] Published Thu Jul 17, 2025

[Recent Articles in PRX Energy] A Comparative Study of Solid Electrolyte Interphase Evolution in Ether and Ester-Based Electrolytes for $\mathrm{Na}$-ion Batteries

Recent Articles in PRX Energy — Tue, 15 Jul 2025 10:00:00 GMT

Author(s): Liang Zhao, Sara I.R. Costa, Yue Chen, Jack R. Fitzpatrick, Andrew J. Naylor, Oleg Kolosov, and Nuria Tapia-Ruiz

Diglyme-based electrolytes promote a thin, uniform, and stable solid electrolyte interphase that can extend the lifespan of sodium-ion batteries, as shown using advanced spectroscopic and electrochemical techniques.

[PRX Energy 4, 033002] Published Tue Jul 15, 2025

[Chinese Chemical Society: CCS Chemistry: Table of Contents] Metalloligand Enabling Cobalt-Catalyzed anti-Markovnikov Hydrosilylation of Alkynes with Tertiary Silanes

Chinese Chemical Society: CCS Chemistry: Table of Contents — Tue, 15 Jul 2025 04:05:27 GMT

CCS Chemistry, Ahead of Print.

DOI:10.31635/ccschem.025.202505983

Metal-catalyzed hydrosilylation of alkynes with hydrosilanes is a useful method for the preparation of vinylsilanes that are useful reagents in organic synthesis and the silicone industry. 3d metal catalysts affecting the hydrosilylation reactions of ...

[Wiley: Advanced Intelligent Discovery: Table of Contents] Deep Learning Prediction of Surface Roughness in Multi‐Stage Microneedle Fabrication: A Long Short‐Term Memory‐Recurrent Neural Network Approach

Wiley: Advanced Intelligent Discovery: Table of Contents — Mon, 14 Jul 2025 15:08:07 GMT

Advanced Intelligent Discovery, EarlyView.

[Chinese Chemical Society: CCS Chemistry: Table of Contents] Inorganic Iodide Catalyzed Alkylation of Amines with Primary Alcohols

Chinese Chemical Society: CCS Chemistry: Table of Contents — Fri, 11 Jul 2025 03:57:49 GMT

CCS Chemistry, Ahead of Print.

DOI:10.31635/ccschem.025.202505864

Alkylation of amines with readily accessible reagents is one of the most efficient strategies for synthesizing substituted amines. Primary alcohols, being widely abundant, are excellent electrophiles that can undergo dehydration to react with various ...

[Wiley: Advanced Intelligent Discovery: Table of Contents] Autonomous Machine Learning‐Based Classification and Arrangement of Submillimeter Objects Using a Capillary Force Gripper

Wiley: Advanced Intelligent Discovery: Table of Contents — Wed, 09 Jul 2025 08:01:30 GMT

Advanced Intelligent Discovery, EarlyView.

[Wiley: Advanced Intelligent Discovery: Table of Contents] Universally Accurate or Specifically Inadequate? Stress‐Testing General Purpose Machine Learning Interatomic Potentials

Wiley: Advanced Intelligent Discovery: Table of Contents — Wed, 09 Jul 2025 07:56:18 GMT

Advanced Intelligent Discovery, EarlyView.

[Wiley: Advanced Intelligent Discovery: Table of Contents] A Machine Learning Model for Interpretable PECVD Deposition Rate Prediction

Wiley: Advanced Intelligent Discovery: Table of Contents — Fri, 27 Jun 2025 08:27:19 GMT

Advanced Intelligent Discovery, EarlyView.

[Wiley: Advanced Intelligent Discovery: Table of Contents] Feature Selection for Machine Learning‐Driven Accelerated Discovery and Optimization in Emerging Photovoltaics: A Review

Wiley: Advanced Intelligent Discovery: Table of Contents — Fri, 27 Jun 2025 08:15:35 GMT

Advanced Intelligent Discovery, EarlyView.

[ACS Materials Au: Latest Articles (ACS Publications)] [ASAP] Historical Data Mining Deep Dive into Machine Learning-Aided 2D Materials Research in Electrochemical Applications

ACS Materials Au: Latest Articles (ACS Publications) — Mon, 23 Jun 2025 15:22:16 GMT

ACS Materials Au

DOI: 10.1021/acsmaterialsau.5c00030

[Wiley: Advanced Intelligent Discovery: Table of Contents] Machine Learning‐Assisted Infectious Disease Detection in Low‐Income Areas: Toward Rapid Triage of Dengue and Zika Virus Using Open‐Source Hardware

Wiley: Advanced Intelligent Discovery: Table of Contents — Mon, 23 Jun 2025 08:20:28 GMT

Advanced Intelligent Discovery, EarlyView.

[Wiley: Advanced Intelligent Discovery: Table of Contents] What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Wiley: Advanced Intelligent Discovery: Table of Contents — Fri, 20 Jun 2025 08:36:19 GMT

Advanced Intelligent Discovery, EarlyView.

[Wiley: Advanced Intelligent Discovery: Table of Contents] Predicting High‐Resolution Spatial and Spectral Features in Mass Spectrometry Imaging with Machine Learning and Multimodal Data Fusion

Wiley: Advanced Intelligent Discovery: Table of Contents — Wed, 18 Jun 2025 08:10:58 GMT

Advanced Intelligent Discovery, EarlyView.

[Wiley: Advanced Intelligent Discovery: Table of Contents] A Machine Learning Perspective on the Brønsted–Evans–Polanyi Relation in Water‐Gas Shift Catalysis on MXenes

Wiley: Advanced Intelligent Discovery: Table of Contents — Wed, 18 Jun 2025 08:09:26 GMT

Advanced Intelligent Discovery, EarlyView.

[Chinese Chemical Society: CCS Chemistry: Table of Contents] Efficient Pure Organic Near-Infrared Room-Temperature Phosphorescence Based on n/π Orbital Decoupling

Chinese Chemical Society: CCS Chemistry: Table of Contents — Sat, 14 Jun 2025 05:08:51 GMT

CCS Chemistry, Ahead of Print.

DOI:10.31635/ccschem.025.202405319

Developing pure organic room-temperature phosphorescence (RTP) materials remains an enormous challenge, especially for efficient near-infrared (NIR) RTP materials. Herein, a functional unit combination strategy is employed to design a series of pure ...

[Chinese Chemical Society: CCS Chemistry: Table of Contents] Identification of Cu-N2 Sites for Zn-Air Batteries in Harsh Electrolytes: Computer Virtual Screening, Machine Learning, and Practical Application

Chinese Chemical Society: CCS Chemistry: Table of Contents — Sat, 14 Jun 2025 04:39:17 GMT

CCS Chemistry, Ahead of Print.

DOI:10.31635/ccschem.025.202505577

Nonprecious-metal catalysts possess great potential to replace noble metals in catalysis; however, selecting efficient candidates through experiments is time-consuming and costly. Herein, we employed a data-driven virtual screening (VS) method to discover ...

[Recent Articles in PRX Energy] Correlating Local Morphology and Charge Dynamics via Kelvin Probe Force Microscopy to Explain Photoelectrode Performance

Recent Articles in PRX Energy — Mon, 09 Jun 2025 10:00:00 GMT

Author(s): Maryam Pourmahdavi, Mauricio Schieda, Ragle Raudsepp, Steffen Fengler, Jiri Kollmann, Yvonne Pieper, Thomas Dittrich, Thomas Klassen, and Francesca M. Toma

Charge transport in photoelectrodes for photoelectrochemical cells is influenced by microstructural variations; here, the authors use Kelvin Probe Force Microscopy to correlate local morphology with optoelectronic properties toward optimizing materials toward material optimization.

[PRX Energy 4, 023010] Published Mon Jun 09, 2025

[Chinese Chemical Society: CCS Chemistry: Table of Contents] Radical Amidoalkynylation of Electron-Rich Alkenes with Bifunctional Alkynylsulfonamide Reagents

Chinese Chemical Society: CCS Chemistry: Table of Contents — Mon, 09 Jun 2025 02:05:34 GMT

CCS Chemistry, Ahead of Print.

DOI:10.31635/ccschem.025.202505686

Radical amidoalkynylations of olefins offer a powerful platform for the rapid construction of both C–N and C–O bonds, generating vicinal aminoalkynes which are frequently found in biologically active molecules. Herein, we developed a practical two-...

[Chinese Chemical Society: CCS Chemistry: Table of Contents] Development of Nanomolar Affinity Miniprotein Inhibitors Targeting α-Synuclein Aggregation as Promising Therapeutic Agents for Parkinson’s Disease

Chinese Chemical Society: CCS Chemistry: Table of Contents — Tue, 03 Jun 2025 05:02:30 GMT

CCS Chemistry, Ahead of Print.

DOI:10.31635/ccschem.025.202505587

Parkinson’s disease (PD) is a debilitating neurodegenerative disorder characterized by the accumulation of α-synuclein (α-syn) aggregates in the brain. Developing effective therapies targeting α-syn has been challenging due to its intrinsically disordered ...

[Chinese Chemical Society: CCS Chemistry: Table of Contents] Harnessing Photoredox Cascade to Enhance Photodynamic Oncotherapy by Nanoformulated Macrocyclic Photosensitizer

Chinese Chemical Society: CCS Chemistry: Table of Contents — Tue, 03 Jun 2025 04:56:28 GMT

CCS Chemistry, Ahead of Print.

DOI:10.31635/ccschem.025.202505567

Optically active nanoagents hold a dominant position in advanced phototheranostics, but there remain challenges in structural optimization and performance maximization for biomedical applications. Herein, a π-extended triphenylamine-containing ...

[Chinese Chemical Society: CCS Chemistry: Table of Contents] Minimal Sulfur-Grafted Graphite Anode with Accelerated Interfacial Kinetics for Fast-Charging Lithium-Ion Batteries

Chinese Chemical Society: CCS Chemistry: Table of Contents — Wed, 28 May 2025 08:32:07 GMT

CCS Chemistry, Ahead of Print.

DOI:10.31635/ccschem.025.202505705

The significant capacity decay and undesired metallic Li plating of graphite anode resulting from sluggish Li-ion diffusion kinetics at the graphite/electrolyte interface have largely hindered the fast-charging capability of lithium-ion batteries (LIBs). ...

[Chinese Chemical Society: CCS Chemistry: Table of Contents] Enantioconvergent Negishi Cross-Coupling of Racemic sec-Alkylzinc Reagent with Aryl Halides Enabled by Bulky N-Heterocyclic Carbene-Pd Catalyst

Chinese Chemical Society: CCS Chemistry: Table of Contents — Mon, 19 May 2025 04:21:11 GMT

CCS Chemistry, Ahead of Print.

DOI:10.31635/ccschem.025.202505591

Transition-metal-catalyzed cross-coupling reactions have revolutionized synthetic approaches for forging C–C bonds. However, catalytic enantioconvergent couplings of racemic secondary organometallics with aryl electrophiles remain a significant challenge. ...

[Recent Articles in PRX Energy] Resolving the Solvation Structure and Transport Properties of Aqueous Zinc Electrolytes from Salt-in-Water to Water-in-Salt Using Neural Network Potential

Recent Articles in PRX Energy — Fri, 11 Apr 2025 10:00:00 GMT

Author(s): Chuntian Cao, Arun Kingan, Ryan C. Hill, Jason Kuang, Lei Wang, Chunyi Zhang, Matthew R. Carbone, Hubertus van Dam, Shinjae Yoo, Shan Yan, Esther S. Takeuchi, Kenneth J. Takeuchi, Xifan Wu, AM Milinda Abeykoon, Amy C. Marschilok, and Deyu Lu

A neural network potential model is developed for ZnCl $_{2}$ electrolytes that provides atomic scale insights into the solvation structure and ionic conductivity. The results agree well with experiment and shed light on the performance of aqueous zinc-ion batteries across a wide concentration range of ZnCl $_{2}$ electrolytes.

[PRX Energy 4, 023004] Published Fri Apr 11, 2025

[Recent Articles in PRX Energy] Crystal Structure Prediction and Phase Stability in Highly Anharmonic Silver-Based Chalcohalide Antiperovskites

Recent Articles in PRX Energy — Thu, 03 Apr 2025 10:00:00 GMT

Author(s): Pol Benítez, Cibrán López, Cong Liu, Ivan Caño, Josep-Lluís Tamarit, Edgardo Saucedo, and Claudio Cazorla

Using theoretical first-principles methods, stable and metastable phases of silver-based chalcohalide anti-perovskites are predicted, offering insight into their stability for potential energy and optoelectronic applications.

[PRX Energy 4, 023002] Published Thu Apr 03, 2025

[Recent Articles in PRX Energy] Unraveling Temperature-Induced Vacancy Clustering in Tungsten: From Direct Microscopy to Atomistic Insights via Data-Driven Bayesian Sampling

Recent Articles in PRX Energy — Tue, 25 Feb 2025 10:00:00 GMT

Author(s): Anruo Zhong, Clovis Lapointe, Alexandra M. Goryaeva, Kazuto Arakawa, Manuel Athènes, and Mihai-Cosmin Marinica

This study reveals how anharmonic, entropy-driven stabilization of di-vacancies at elevated temperatures reconcile theoretical predictions with experimental observations of vacancy clustering in tungsten, a prime candidate material for fusion reactors.

[PRX Energy 4, 013008] Published Tue Feb 25, 2025

[Recent Articles in PRX Energy] Constant-Current Nonequilibrium Molecular Dynamics Approach for Accelerated Computation of Ionic Conductivity Including Ion-Ion Correlation

Recent Articles in PRX Energy — Wed, 19 Feb 2025 10:00:00 GMT

Author(s): Ryoma Sasaki, Yoshitaka Tateyama, and Debra J. Searles

A new “constant-current” nonequilibrium molecular dynamics simulation method accelerates ionic conductivity calculations by up to two orders of magnitude while accurately capturing ion-ion correlations, enabling more efficient screening of solid electrolytes and revealing important low-temperature conduction behaviors.

[PRX Energy 4, 013005] Published Wed Feb 19, 2025

[Recent Articles in PRX Energy] Detecting Attacks and Estimating States of Power Grids from Partial Observations with Machine Learning

Recent Articles in PRX Energy — Tue, 04 Feb 2025 10:00:00 GMT

Author(s): Zheng-Meng Zhai, Mohammadamin Moradi, and Ying-Cheng Lai

Using data-driven machine learning models, this work demonstrates a method to map the dynamical state of a full power grid from limited observations, enabling the user to locate disruptions with information only from other areas of the grid.

[PRX Energy 4, 013003] Published Tue Feb 04, 2025

[Recent Articles in PRX Energy] 3D Reconstruction of a Nuclear Reactor by Muon Tomography: Structure Validation and Anomaly Detection

Recent Articles in PRX Energy — Tue, 28 Jan 2025 10:00:00 GMT

Author(s): Baptiste Lefevre, Julien Vogel, Héctor Gomez, David Attié, Laurent Gallego, Philippe Gonzales, Bertrand Lesage, Philippe Mas, and Daniel Pomarède

Muon tomography, a non-invasive technique that can be used to image large, inaccessible structures, is combined with machine learning to create a 3D reconstruction of a historical nuclear reactor that reveals material density variations, including potential anomalies in the graphite core.

[PRX Energy 4, 013002] Published Tue Jan 28, 2025

[Recent Articles in PRX Energy] Determining Parameters of Metal-Halide Perovskites Using Photoluminescence with Bayesian Inference

Recent Articles in PRX Energy — Tue, 14 Jan 2025 10:00:00 GMT

Author(s): Manuel Kober-Czerny, Akash Dasgupta, Seongrok Seo, Florine M. Rombach, David P. McMeekin, Heon Jin, and Henry J. Snaith

Experiment and machine learning are combined to extract key material parameters and insight into charge carrier transport in metal halide perovskites for solar cell applications.

[PRX Energy 4, 013001] Published Tue Jan 14, 2025

[Recent Articles in PRX Energy] Learning Molecular Mixture Property Using Chemistry-Aware Graph Neural Network

Recent Articles in PRX Energy — Wed, 12 Jun 2024 10:00:00 GMT

Author(s): Hengrui Zhang (张恒睿), Tianxing Lai (来天行), Jie Chen, Arumugam Manthiram, James M. Rondinelli, and Wei Chen

MolSets, a machine learning model that integrates graph neural networks with permutation invariant architecture, addresses multilevel complexity for effective prediction of molecular mixture properties, thus accelerating lithium battery electrolyte design.

[PRX Energy 3, 023006] Published Wed Jun 12, 2024

[Recent Articles in PRX Energy] Temperature Impact on Lithium Metal Morphology in Lithium Reservoir-Free Solid-State Batteries

Recent Articles in PRX Energy — Fri, 17 May 2024 10:00:00 GMT

Author(s): Min-Gi Jeong, Kelsey B. Hatzell, Sourim Banerjee, Bairav S. Vishnugopi, and Partha P. Mukherjee

Toward enhancing performance in reservoir-free solid-state batteries, confocal imaging experiments are combined with meso-scale modeling to unveil vertical and horizontal growth mechanisms at varying temperatures of lithium metal at an agyrodite solid electrolyte|stainless steel interface.

[PRX Energy 3, 023003] Published Fri May 17, 2024

[Recent Articles in Rev. Mod. Phys.] Colloquium: Advances in automation of quantum dot devices control

Recent Articles in Rev. Mod. Phys. — Fri, 17 Feb 2023 10:00:00 GMT

Author(s): Justyna P. Zwolak and Jacob M. Taylor

A promising platform for quantum computing consists of arrays of quantum dots. However, operating these devices presents a challenging control problem, since the location of the dots and the charges they contain must be reliably and reproducibly matched with the gate voltages. This Colloquium explains how automated control protocols that make use of machine learning techniques can succeed in systems where heuristic control is not feasible.

[Rev. Mod. Phys. 95, 011006] Published Fri Feb 17, 2023

[PRB: Dynamics, dynamical systems, lattice effects, quantum solids] Hydrogen as promoter and inhibitor of superionicity: A case study on Li-N-H systems

PRB: Dynamics, dynamical systems, lattice effects, quantum solids — Mon, 26 Jul 2010 10:00:00 GMT

Author(s): Andreas Blomqvist, C. Moysés Araújo, Ralph H. Scheicher, Pornjuk Srepusharawoot, Wen Li, Ping Chen, and Rajeev Ahuja

Materials which possess a high lithium ion conductivity are very attractive for battery and fuel cell applications. Hydrogenation of the fast-ion conductor lithium nitride $({\text{Li}}_{3}\text{N})$ leads to the formation of lithium imide $({\text{Li}}_{2}\text{NH})$ and subsequently of lithium ami…

[Phys. Rev. B 82, 024304] Published Mon Jul 26, 2010

[PRB: Dynamics, dynamical systems, lattice effects, quantum solids] Nonadiabatic effects of rattling phonons and $4f$ excitations in $\text{Pr}{({\text{Os}}_{1−x}{\text{Ru}}_{x})}_{4}{\text{Sb}}_{12}$

PRB: Dynamics, dynamical systems, lattice effects, quantum solids — Fri, 18 Jun 2010 10:00:00 GMT

Author(s): Peter Thalmeier

In the skutterudite compounds the anharmonic “rattling” oscillations of $4f$-guest ions in the surrounding ${\text{Sb}}_{12}$ host cages are found to have significant influence on the low-temperature properties. Recently specific-heat analysis of $\text{Pr}{({\text{Os}}_{1−x}{\text{Ru}}_{x})}_{4}{\t…

[Phys. Rev. B 81, 224305] Published Fri Jun 18, 2010

[PRB: Dynamics, dynamical systems, lattice effects, quantum solids] Ionic conductivity of nanocrystalline yttria-stabilized zirconia: Grain boundary and size effects

PRB: Dynamics, dynamical systems, lattice effects, quantum solids — Mon, 10 May 2010 10:00:00 GMT

Author(s): O. J. Durá, M. A. López de la Torre, L. Vázquez, J. Chaboy, R. Boada, A. Rivera-Calzada, J. Santamaria, and C. Leon

We report on the effect of grain size on the ionic conductivity of yttria-stabilized zirconia samples synthesized by ball milling. Complex impedance measurements, as a function of temperature and frequency are performed on $10\text{ }\text{mol}\text{ }\mathrm{%}$ yttria-stabilized zirconia nanocryst…

[Phys. Rev. B 81, 184301] Published Mon May 10, 2010

[PRB: Dynamics, dynamical systems, lattice effects, quantum solids] Calculating the anharmonic free energy from first principles

PRB: Dynamics, dynamical systems, lattice effects, quantum solids — Fri, 07 May 2010 10:00:00 GMT

Author(s): Zhongqing Wu

We developed a method to calculate the anharmonic free energy without requiring any adjustable parameter. The requisite computations are first-principles quasiharmonic calculations plus an additional Canonical (NVT) ensemble first-principles molecular-dynamics simulation and, therefore, are affordab…

[Phys. Rev. B 81, 172301] Published Fri May 07, 2010

[PRB: Dynamics, dynamical systems, lattice effects, quantum solids] Phason dynamics in one-dimensional lattices

PRB: Dynamics, dynamical systems, lattice effects, quantum solids — Thu, 25 Feb 2010 10:00:00 GMT

Author(s): Hansjörg Lipp, Michael Engel, Steffen Sonntag, and Hans-Rainer Trebin

In quasicrystals, the phason degree of freedom and the inherent anharmonic potentials lead to complex dynamics, which cannot be described by the usual phonon modes of motion. We have constructed simple one-dimensional model systems, the dynamic Fibonacci chain, and approximants thereof. They allow u…

[Phys. Rev. B 81, 064302] Published Thu Feb 25, 2010

[PRB: Dynamics, dynamical systems, lattice effects, quantum solids] Ab initio construction of interatomic potentials for uranium dioxide across all interatomic distances

PRB: Dynamics, dynamical systems, lattice effects, quantum solids — Wed, 25 Nov 2009 10:00:00 GMT

Author(s): P. Tiwary, A. van de Walle, and N. Grønbech-Jensen

We provide a methodology for generating interatomic potentials for use in classical molecular-dynamics simulations of atomistic phenomena occurring at energy scales ranging from lattice vibrations to crystal defects to high-energy collisions. A rigorous method to objectively determine the shape of a…

[Phys. Rev. B 80, 174302] Published Wed Nov 25, 2009

[PRB: Dynamics, dynamical systems, lattice effects, quantum solids] One-dimensional nanostructure-guided chain reactions: Harmonic and anharmonic interactions

PRB: Dynamics, dynamical systems, lattice effects, quantum solids — Fri, 13 Nov 2009 10:00:00 GMT

Author(s): Nitish Nair and Michael S. Strano

We have performed a parametric study of self-propagating chain reactions along a one-dimensional bead-spring array. The coupling between beads is modeled using harmonic and anharmonic Fermi-Pasta-Ulam (FPU)-$β$ and ${φ}^{4}$ potentials. The parameters that define the system are the activation energy…

[Phys. Rev. B 80, 174301] Published Fri Nov 13, 2009

[Communications Materials] In situ polymerization for high performance solid-state lithium-sulfur batteries

Communications Materials — Tue, 23 Dec 2025 00:00:00 GMT

Communications Materials, Published online: 23 December 2025; doi:10.1038/s43246-025-01035-3

[ChemRxiv] Molecular Dynamics Simulations for Organic Chemists – It’s About Time!

ChemRxiv — Tue, 23 Dec 2025 00:00:00 GMT

[ChemRxiv] Characterisation and immobilisation study of the Haloperoxidase from Curvularia inaequalis: application to phenol derivatives

ChemRxiv — Tue, 23 Dec 2025 00:00:00 GMT

[Nature Nanotechnology] Nanostructured niobium-doped nickel-rich multiphase positive electrode active material for high-power lithium-based batteries

Nature Nanotechnology — Tue, 23 Dec 2025 00:00:00 GMT

Nature Nanotechnology, Published online: 23 December 2025; doi:10.1038/s41565-025-02092-y

[ChemRxiv] Study of anion transport by amide-based macrocycles of different sizes

ChemRxiv — Tue, 23 Dec 2025 00:00:00 GMT

[ChemRxiv] Ion-Conductive Vitrimers Based on Backbone-Type Triazolium Poly(ionic liquid)s: Counterion-Dependent Dynamics and Backbone Flexibility

ChemRxiv — Tue, 23 Dec 2025 00:00:00 GMT

[ChemRxiv] Advances in Calcium Isotope Purification and Analysis Using Cutting-Edge Signal Amplifiers for Matrix-Diverse Reference Materials

ChemRxiv — Tue, 23 Dec 2025 00:00:00 GMT

[ChemRxiv] Predicting Sequence Dependent Fluorescence with Classic Machine Learning Models

ChemRxiv — Tue, 23 Dec 2025 00:00:00 GMT

[ChemRxiv] Machine learning driven advances in molecular dynamics of bulk and interfacial aqueous systems

ChemRxiv — Tue, 23 Dec 2025 00:00:00 GMT

[RSC - Chem. Sci. latest articles] Automated Closed-Loop Continuous Flow Block Copolymer Synthesizer

RSC - Chem. Sci. latest articles — Tue, 23 Dec 2025 00:00:00 GMT

Chem. Sci., 2026, Accepted Manuscript
DOI: 10.1039/D5SC07307C, Edge Article

Open Access

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence.

[RSC - Chem. Sci. latest articles] Node-Equivariant Message Passing for Efficient and Accurate Machine Learning Interatomic Potentials

RSC - Chem. Sci. latest articles — Tue, 23 Dec 2025 00:00:00 GMT

Chem. Sci., 2026, Accepted Manuscript
DOI: 10.1039/D5SC07248D, Edge Article

Open Access

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence.

[RSC - Chem. Sci. latest articles] Robust Janus-Faced Quasi-Solid-State Electrolytes Mimicking Honeycomb for Fast Transport and Adequate Supply of Sodium Ions

RSC - Chem. Sci. latest articles — Tue, 23 Dec 2025 00:00:00 GMT

Chem. Sci., 2026, Accepted Manuscript
DOI: 10.1039/D5SC08536E, Edge Article

Open Access

This article is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported Licence.

[Joule] Machine learning-driven interface material design for high-performance perovskite solar cells with scalability and band-gap universality

Joule — Tue, 23 Dec 2025 00:00:00 GMT

[Cell Reports Physical Science] A global thermodynamic-kinetic model capturing the hallmarks of liquid-liquid phase separation and amyloid aggregation

Cell Reports Physical Science — Tue, 23 Dec 2025 00:00:00 GMT

[ChemRxiv] Maximizing Machine Learning Interatomic Potential Transferability for the Discovery of the Novel Stellated Octadecagon Bi18-Pt24 Cage Structure

ChemRxiv — Tue, 23 Dec 2025 00:00:00 GMT

[ChemRxiv] High-Performance Semiempirical Excited-State Molecular Dynamics: A Step Toward Data-Driven Photodynamics

ChemRxiv — Tue, 23 Dec 2025 00:00:00 GMT

[Applied Physics Letters Current Issue] Mixed ionic–electronic conductor based on B 16 framework

Applied Physics Letters Current Issue — Tue, 23 Dec 2025 00:00:00 GMT

[iScience] A Multicenter Multimodel Habitat Radiomics Model for Predicting Immunotherapy Response in Advanced NSCLC

iScience — Tue, 23 Dec 2025 00:00:00 GMT

[ACS Nano: Latest Articles (ACS Publications)] [ASAP] Regulating Solvation Structure and Ion Transport via Lewis-Base Dual-Functional Covalent Organic Polymer Separators for Dendrite-Free Li-Metal Anodes

ACS Nano: Latest Articles (ACS Publications) — Mon, 22 Dec 2025 20:52:05 GMT

ACS Nano

DOI: 10.1021/acsnano.5c14722

[ACS Nano: Latest Articles (ACS Publications)] [ASAP] Highly Selective Lithium-Ion Separation by Regulating Ion Transport Energy Barriers of Vermiculite Membranes

ACS Nano: Latest Articles (ACS Publications) — Mon, 22 Dec 2025 18:30:41 GMT

ACS Nano

DOI: 10.1021/acsnano.5c17718

[Wiley: Advanced Intelligent Discovery: Table of Contents] A Physics Constrained Machine Learning Pipeline for Young's Modulus Prediction in Multimaterial Hyperelastic Cylinders Guided by Contact Mechanics

Wiley: Advanced Intelligent Discovery: Table of Contents — Mon, 22 Dec 2025 17:43:04 GMT

Advanced Intelligent Discovery, EarlyView.

[ACS Nano: Latest Articles (ACS Publications)] [ASAP] Multianion Synergism Boosts High-Performance All-Solid-State Lithium Batteries

ACS Nano: Latest Articles (ACS Publications) — Mon, 22 Dec 2025 14:37:35 GMT

ACS Nano

DOI: 10.1021/acsnano.5c12987

[Wiley: Advanced Functional Materials: Table of Contents] Sulfur‐Doped Bi2O3 Nanorods with Asymmetric S−Bi−O Active Sites for Highly Efficient Electrosynthesis of Formic Acid

Wiley: Advanced Functional Materials: Table of Contents — Mon, 22 Dec 2025 14:14:10 GMT

Advanced Functional Materials, EarlyView.

[The Journal of Physical Chemistry C: Latest Articles (ACS Publications)] [ASAP] Density Effects on the Thermal Decomposition of LLM-105 Explored by Neural Network Potential

The Journal of Physical Chemistry C: Latest Articles (ACS Publications) — Mon, 22 Dec 2025 14:01:00 GMT

The Journal of Physical Chemistry C

DOI: 10.1021/acs.jpcc.5c06140

[Accounts of Chemical Research: Latest Articles (ACS Publications)] [ASAP] Accelerating Materials Discovery Through Sparse Gaussian Process Machine Learning Potentials

Accounts of Chemical Research: Latest Articles (ACS Publications) — Mon, 22 Dec 2025 13:59:15 GMT

Accounts of Chemical Research

DOI: 10.1021/acs.accounts.5c00667

[Wiley: Small: Table of Contents] Revealing Electronic Structure–Chemisorption Relationships for Accelerated Discovery of Aqueous Zinc Battery Additives Through Machine Learning

Wiley: Small: Table of Contents — Mon, 22 Dec 2025 12:24:02 GMT

Small, EarlyView.

[Wiley: Small: Table of Contents] Ultra‐High Capacity Density Lithium Metal Battery is Effectuated via Coupling Single Lithium‐Ion Conductor and Lithium‐Ion Sieve Within Yttrium‐Organic Framework

Wiley: Small: Table of Contents — Mon, 22 Dec 2025 11:34:32 GMT

Small, EarlyView.

[Wiley: Small: Table of Contents] Boosting Gaseous Mercury Detection via Photooxidation‐Enrichment Fluorescent Membrane with Machine Learning

Wiley: Small: Table of Contents — Mon, 22 Dec 2025 11:29:41 GMT

Small, EarlyView.

[Recent Articles in Phys. Rev. Lett.] Gate-Tunable Spectrum and Charge Dispersion Mitigation in a Graphene Superconducting Qubit

Recent Articles in Phys. Rev. Lett. — Mon, 22 Dec 2025 10:00:00 GMT

Author(s): Nicolas Aparicio, Simon Messelot, Edgar Bonet-Orozco, Eric Eyraud, Kenji Watanabe, Takashi Taniguchi, Johann Coraux, and Julien Renard

[Phys. Rev. Lett. 135, 266001] Published Mon Dec 22, 2025

[Proceedings of the National Academy of Sciences: Physical Sciences] SR-LLM: An incremental symbolic regression framework driven by LLM-based retrieval-augmented generation

Proceedings of the National Academy of Sciences: Physical Sciences — Mon, 22 Dec 2025 08:00:00 GMT

[Wiley: Angewandte Chemie International Edition: Table of Contents] Potential‐Tailored Aryl–Sodium Reagent with Moderate Ionic Binding Strength Enables Precise yet Fast Hard Carbon Presodiation

Wiley: Angewandte Chemie International Edition: Table of Contents — Mon, 22 Dec 2025 05:36:53 GMT

Angewandte Chemie International Edition, EarlyView.

[npj Computational Materials] Machine learning interatomic potential can infer electrical response

npj Computational Materials — Mon, 22 Dec 2025 00:00:00 GMT

npj Computational Materials, Published online: 22 December 2025; doi:10.1038/s41524-025-01911-z

Machine learning interatomic potential can infer electrical response

[Applied Physics Letters Open Issues] High-throughput sensing of single-cell properties using parallel multi-stage cell deformation

Applied Physics Letters Open Issues — Mon, 22 Dec 2025 00:00:00 GMT

[Applied Physics Letters Open Issues] Coherent phonon tunneling-driven ultralow and non-monotonic thermal conductivity in quasi-0D Cs 3 Cu 2 I 5

Applied Physics Letters Open Issues — Mon, 22 Dec 2025 00:00:00 GMT

[Applied Physics Letters Open Issues] Machine learning-assisted performance prediction of ZnMSnO-based thin-film transistors

Applied Physics Letters Open Issues — Mon, 22 Dec 2025 00:00:00 GMT

[Applied Physics Reviews Current Issue] Thermal conductivity limits of MoS 2 and MoSe 2 : Revisiting high-order anharmonic lattice dynamics with machine learning potentials

Applied Physics Reviews Current Issue — Mon, 22 Dec 2025 00:00:00 GMT

[ChemRxiv] Missense mutations in cancer: in silico predictions, developing treatments, and overcoming cell resistance.

ChemRxiv — Mon, 22 Dec 2025 00:00:00 GMT

[ChemRxiv] Domain Oriented Universal Machine Learning Potential Enables Fast Exploration of Chemical Space of Battery Electrolytes

ChemRxiv — Mon, 22 Dec 2025 00:00:00 GMT

[ChemRxiv] Large-scale structure- and sequence-based comparative analysis enables functional annotation of animal venom peptides

ChemRxiv — Mon, 22 Dec 2025 00:00:00 GMT

[ChemRxiv] Performance of dispersion models in predicting ambient hydrocarbon concentrations at a regional air quality monitor in an oil and gas producing region

ChemRxiv — Mon, 22 Dec 2025 00:00:00 GMT

[ChemRxiv] Machine Learning-Guided Scope Selection to Balance Performance and Substrate Similarity

ChemRxiv — Mon, 22 Dec 2025 00:00:00 GMT

[ChemRxiv] Relationship Between Local Disorder and Atomic Motion in an Antiperovskite Solid Electrolyte

ChemRxiv — Mon, 22 Dec 2025 00:00:00 GMT

[ChemRxiv] Multi-Objective Catalyst Discovery in High-Entropy Alloy Composition Space: The Role of Noble Metals on the Pareto Front for Oxygen Reduction Reaction

ChemRxiv — Mon, 22 Dec 2025 00:00:00 GMT

[ChemRxiv] Agent-based framework for modeling hyperlocal urban air quality

ChemRxiv — Mon, 22 Dec 2025 00:00:00 GMT

[iScience] Widely Targeted Metabolomics and Machine Learning Identify Succinate as a Key Metabolite in Sepsis-Associated Encephalopathy

iScience — Mon, 22 Dec 2025 00:00:00 GMT

[ACS Nano: Latest Articles (ACS Publications)] [ASAP] Feature-Selective Preprocessing with Electrically Robust Boron Nitride-Based Dynamic Memristors for Reliable Lightweight Neural Networks

ACS Nano: Latest Articles (ACS Publications) — Sun, 21 Dec 2025 18:05:25 GMT

ACS Nano

DOI: 10.1021/acsnano.5c16967

[Journal of the American Chemical Society: Latest Articles (ACS Publications)] [ASAP] Interpreting X-ray Diffraction Patterns of Metal–Organic Frameworks via Generative Artificial Intelligence

Journal of the American Chemical Society: Latest Articles (ACS Publications) — Sat, 20 Dec 2025 15:03:45 GMT

Journal of the American Chemical Society

DOI: 10.1021/jacs.5c16416

[npj Computational Materials] Free-energy perturbation in the exchange-correlation space accelerated by machine learning: application to silica polymorphs

npj Computational Materials — Sat, 20 Dec 2025 00:00:00 GMT

npj Computational Materials, Published online: 20 December 2025; doi:10.1038/s41524-025-01874-1

Free-energy perturbation in the exchange-correlation space accelerated by machine learning: application to silica polymorphs

[Journal of the American Chemical Society: Latest Articles (ACS Publications)] [ASAP] A Transformative Molecular Muscle Solid Electrolyte

Journal of the American Chemical Society: Latest Articles (ACS Publications) — Fri, 19 Dec 2025 20:12:03 GMT

Journal of the American Chemical Society

DOI: 10.1021/jacs.5c18427

[Wiley: Small Structures: Table of Contents] Li6−xFe1−xAlxCl8 Solid Electrolytes for Cost‐Effective All‐Solid‐State LiFePO4 Batteries

Wiley: Small Structures: Table of Contents — Fri, 19 Dec 2025 18:40:34 GMT

Small Structures, EarlyView.

[Wiley: Small: Table of Contents] Unravelling Electronic Structure and Molecular Vibrations of Proteins in Virus Using Novel Correlated Plasmon‐Enhanced Raman Spectroscopy With Machine Learning

Wiley: Small: Table of Contents — Fri, 19 Dec 2025 11:08:23 GMT

Small, EarlyView.

[Recent Articles in Phys. Rev. B] Vision transformer neural quantum states for impurity models

Recent Articles in Phys. Rev. B — Fri, 19 Dec 2025 10:00:00 GMT

Author(s): Xiaodong Cao, Zhicheng Zhong, and Yi Lu

[Phys. Rev. B 112, 235155] Published Fri Dec 19, 2025

[Recent Articles in Phys. Rev. B] Renormalized quantum anharmonicity enhanced electron-phonon coupling in the ambient-pressure compound $\mathrm{Rb}{\mathrm{H}}_{6}$

Recent Articles in Phys. Rev. B — Fri, 19 Dec 2025 10:00:00 GMT

Author(s): Zhongyu Wan, Guo-Hua Zhong, Ruiqin Zhang, and Hai-Qing Lin

[Phys. Rev. B 112, L220504] Published Fri Dec 19, 2025

[Wiley: Angewandte Chemie International Edition: Table of Contents] Dual‐Function Antibacterial and Antibiofilm Agent Based on a Confinement‐Activated Fluorescent System in Water

Wiley: Angewandte Chemie International Edition: Table of Contents — Fri, 19 Dec 2025 05:42:28 GMT

Angewandte Chemie International Edition, EarlyView.

[Wiley: Advanced Science: Table of Contents] Quantifying Additive Manufacturing Vapor Plumes Using Laser‐Induced Breakdown Spectroscopy, Synchrotron X‐Ray Radiography and Simulations

Wiley: Advanced Science: Table of Contents — Fri, 19 Dec 2025 03:30:01 GMT

Advanced Science, EarlyView.

[npj Computational Materials] Publisher Correction: Machine learning potentials for alloys: a detailed workflow to predict phase diagrams and benchmark accuracy

npj Computational Materials — Fri, 19 Dec 2025 00:00:00 GMT

npj Computational Materials, Published online: 19 December 2025; doi:10.1038/s41524-025-01913-x

Publisher Correction: Machine learning potentials for alloys: a detailed workflow to predict phase diagrams and benchmark accuracy

[npj Computational Materials] Alloy design integrating natural language processing and machine learning: breakthrough development of low-cost, high-performance Ni-based single-crystal superalloys

npj Computational Materials — Fri, 19 Dec 2025 00:00:00 GMT

npj Computational Materials, Published online: 19 December 2025; doi:10.1038/s41524-025-01906-w

Alloy design integrating natural language processing and machine learning: breakthrough development of low-cost, high-performance Ni-based single-crystal superalloys

[Joule] Boosting ionic conductivity of fluoride electrolytes by polyanion coordination chemistry enabling 5 V-Class all-solid-state batteries

Joule — Fri, 19 Dec 2025 00:00:00 GMT

[RSC - Digital Discovery latest articles] Adsorb-Agent: Autonomous Identification of Stable Adsorption Configurations via Large Language Model Agent

RSC - Digital Discovery latest articles — Fri, 19 Dec 2025 00:00:00 GMT

Digital Discovery, 2025, Accepted Manuscript
DOI: 10.1039/D5DD00298B, Paper

Open Access

This article is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported Licence.

[The Journal of Physical Chemistry C: Latest Articles (ACS Publications)] [ASAP] Instant Prediction of Moire Superlattice Relaxation in Twisted Bilayers of Transition Metal Dichalcogenides Using Different Neural Network Architectures

The Journal of Physical Chemistry C: Latest Articles (ACS Publications) — Thu, 18 Dec 2025 11:50:58 GMT

The Journal of Physical Chemistry C

DOI: 10.1021/acs.jpcc.5c07169

[Recent Articles in Phys. Rev. Lett.] Variational Machine Learning Model for Electronic Structure Optimization via the Density Matrix

Recent Articles in Phys. Rev. Lett. — Thu, 18 Dec 2025 10:00:00 GMT

Author(s): Luqi Dong, Shuxiang Yang, Su-Huai Wei, and Yunhao Lu

[Phys. Rev. Lett. 135, 256403] Published Thu Dec 18, 2025

[Recent Articles in Phys. Rev. B] One-defect one-potential strategy for accurate machine learning prediction of phonons in defect-containing supercells

Recent Articles in Phys. Rev. B — Thu, 18 Dec 2025 10:00:00 GMT

Author(s): Junjie Zhou, Xinpeng Li, Menglin Huang, and Shiyou Chen

[Phys. Rev. B 112, 235205] Published Thu Dec 18, 2025

[Wiley: Advanced Science: Table of Contents] Polymorphism Crystal Structure Prediction with Adaptive Space Group Diversity Control

Wiley: Advanced Science: Table of Contents — Thu, 18 Dec 2025 09:38:21 GMT

Advanced Science, Volume 12, Issue 47, December 18, 2025.

[Wiley: Advanced Science: Table of Contents] Computationally‐Guided Development of Sulfide Solid Electrolyte Powder Coatings for Enhanced Stability and Performance of Solid‐State Batteries

Wiley: Advanced Science: Table of Contents — Thu, 18 Dec 2025 09:38:21 GMT

Advanced Science, Volume 12, Issue 47, December 18, 2025.

[Proceedings of the National Academy of Sciences: Physical Sciences] Uncovering inequalities in new knowledge learning by large language models across different languages

Proceedings of the National Academy of Sciences: Physical Sciences — Thu, 18 Dec 2025 08:00:00 GMT

[Proceedings of the National Academy of Sciences: Physical Sciences] Heavy-tailed update distributions arise from information-driven self-organization in nonequilibrium learning

Proceedings of the National Academy of Sciences: Physical Sciences — Thu, 18 Dec 2025 08:00:00 GMT

[AAAS: Science: Table of Contents] State-independent ionic conductivity

AAAS: Science: Table of Contents — Thu, 18 Dec 2025 07:00:11 GMT

Science, Volume 390, Issue 6779, Page 1254-1258, December 2025.

[AAAS: Science: Table of Contents] Scientific production in the era of large language models

AAAS: Science: Table of Contents — Thu, 18 Dec 2025 07:00:11 GMT

Science, Volume 390, Issue 6779, Page 1240-1243, December 2025.

[Wiley: Advanced Functional Materials: Table of Contents] Homogeneous Microphase Structure and Polymer‐Dominated Ion Transport Network Enable Durable Quasi‐Solid‐State Sodium Metal Batteries

Wiley: Advanced Functional Materials: Table of Contents — Thu, 18 Dec 2025 05:55:56 GMT

Advanced Functional Materials, EarlyView.

[Nature Machine Intelligence] A psychometric framework for evaluating and shaping personality traits in large language models

Nature Machine Intelligence — Thu, 18 Dec 2025 00:00:00 GMT

Nature Machine Intelligence, Published online: 18 December 2025; doi:10.1038/s42256-025-01115-6

[Wiley: Small: Table of Contents] Probing Lattice Anharmonicity and Thermal Transport in Ultralow‐κ Materials Using Machine Learning Interatomic Potentials

Wiley: Small: Table of Contents — Wed, 17 Dec 2025 20:22:25 GMT

Small, EarlyView.

[Wiley: Small: Table of Contents] Ion Migration Control in Lead‐Free Halide Perovskite Transistors for Logic and Neuromorphic Circuits

Wiley: Small: Table of Contents — Wed, 17 Dec 2025 19:52:40 GMT

Small, EarlyView.

[Journal of the American Chemical Society: Latest Articles (ACS Publications)] [ASAP] Convergent Evolution: Self-Assembly of Small Molecule, Polymeric, and Inorganic Contrast Agents toward Advanced MRI

Journal of the American Chemical Society: Latest Articles (ACS Publications) — Wed, 17 Dec 2025 19:33:22 GMT

Journal of the American Chemical Society

DOI: 10.1021/jacs.4c11767

[ACS Nano: Latest Articles (ACS Publications)] [ASAP] van Hove Source for Ultralow Power Field-Effect Transistors

ACS Nano: Latest Articles (ACS Publications) — Wed, 17 Dec 2025 18:12:49 GMT

ACS Nano

DOI: 10.1021/acsnano.5c17157

[ACS Nano: Latest Articles (ACS Publications)] [ASAP] An Ultralong-Circulating Tantalum-Based Computed Tomography Contrast Agent for Vascular Imaging in Large Animals

ACS Nano: Latest Articles (ACS Publications) — Wed, 17 Dec 2025 17:49:52 GMT

ACS Nano

DOI: 10.1021/acsnano.5c13773

[Wiley: Advanced Functional Materials: Table of Contents] Machine Learning‐assisted Ultrasensitive SERS Immunoassays Across Wide Concentration Ranges Toward Clinical Ovarian Cancer Diagnosis

Wiley: Advanced Functional Materials: Table of Contents — Wed, 17 Dec 2025 14:49:25 GMT

Advanced Functional Materials, Volume 35, Issue 51, December 16, 2025.

[Wiley: Advanced Functional Materials: Table of Contents] Prediction and Fine Screening of Small Molecular Passivation Materials for High‐Efficiency Perovskite Solar Cells Via an Enhanced Machine Learning Workflow

Wiley: Advanced Functional Materials: Table of Contents — Wed, 17 Dec 2025 14:49:25 GMT

Advanced Functional Materials, Volume 35, Issue 51, December 16, 2025.

[Wiley: Advanced Materials: Table of Contents] Tailoring Graphite Interlayers with Electron‐Acceptor Bridges Raises Ion Diffusion Kinetics for Ultrafast Charging Batteries

Wiley: Advanced Materials: Table of Contents — Wed, 17 Dec 2025 14:13:34 GMT

Advanced Materials, Volume 37, Issue 50, December 17, 2025.

[Wiley: Small: Table of Contents] Interfacial Catalysis Engineering of Solid Electrolyte Interphase Toward High‐Performance Batteries

Wiley: Small: Table of Contents — Wed, 17 Dec 2025 12:51:53 GMT

Small, Volume 21, Issue 50, December 17, 2025.

[Wiley: Small: Table of Contents] In Situ Construction of Dual‐Functional UiO‐66‐NH2 Coated Li1.3Al0.3Ti1.7(PO4)3 to Achieve Lithium Metal Cells with Efficient Ion Transport in Quasi‐Solid Electrolytes

Wiley: Small: Table of Contents — Wed, 17 Dec 2025 12:51:53 GMT

Small, Volume 21, Issue 50, December 17, 2025.

[Wiley: Small: Table of Contents] 1D Lithium‐Ion Transport in a LiMn2O4 Nanowire Cathode during Charge–Discharge Cycles

Wiley: Small: Table of Contents — Wed, 17 Dec 2025 12:51:53 GMT

Small, Volume 21, Issue 50, December 17, 2025.

[Wiley: Small: Table of Contents] A Reversible Zinc Metal Anode with an Inorganic/Organic Solid Electrolyte Interphase Enriched for Epitaxial Deposition Along the Zn (101) Plane

Wiley: Small: Table of Contents — Wed, 17 Dec 2025 12:51:53 GMT

Small, Volume 21, Issue 50, December 17, 2025.

[Proceedings of the National Academy of Sciences: Proceedings of the National Academy of Sciences: Table of Contents] Learning to learn ecosystems from limited data

Wed, 17 Dec 2025 08:00:00 GMT

[Wiley: Advanced Functional Materials: Table of Contents] Smart Wound Management System Capable of On‐Chip Machine Learning and Closed‐Loop Therapeutic Feedback

Wiley: Advanced Functional Materials: Table of Contents — Wed, 17 Dec 2025 06:06:36 GMT

Advanced Functional Materials, EarlyView.

[Nature Materials] Probing frozen solid electrolyte interphases

Nature Materials — Wed, 17 Dec 2025 00:00:00 GMT

Nature Materials, Published online: 17 December 2025; doi:10.1038/s41563-025-02443-z

Probing frozen solid electrolyte interphases

[Cell Reports Physical Science] Accelerated inorganic materials design with generative AI agents

Cell Reports Physical Science — Wed, 17 Dec 2025 00:00:00 GMT

[ACS Energy Letters: Latest Articles (ACS Publications)] [ASAP] Fluorinated Halide Solid Electrolytes for High-Voltage All-Solid-State Sodium-Ion Batteries Enabling Reversible Oxygen Redox

ACS Energy Letters: Latest Articles (ACS Publications) — Tue, 16 Dec 2025 20:00:00 GMT

ACS Energy Letters

DOI: 10.1021/acsenergylett.5c03248

[Journal of the American Chemical Society: Latest Articles (ACS Publications)] [ASAP] Highly Accurate and Fast Prediction of MOF Free Energy via Machine Learning

Journal of the American Chemical Society: Latest Articles (ACS Publications) — Tue, 16 Dec 2025 17:08:56 GMT

Journal of the American Chemical Society

DOI: 10.1021/jacs.5c13960

[Wiley: Angewandte Chemie International Edition: Table of Contents] Mechanically Robust Bilayer Solid Electrolyte Interphase Enabled by Sequential Decomposition Mechanism for High‐Performance Micron‐Sized SiOx Anodes

Wiley: Angewandte Chemie International Edition: Table of Contents — Tue, 16 Dec 2025 15:14:44 GMT

Angewandte Chemie International Edition, Volume 64, Issue 51, December 15, 2025.

[Wiley: Angewandte Chemie International Edition: Table of Contents] Machine Learning‐Driven Automated Synthesis of Polysubstituted Gentisaldehydes

Wiley: Angewandte Chemie International Edition: Table of Contents — Tue, 16 Dec 2025 15:14:44 GMT

Angewandte Chemie International Edition, Volume 64, Issue 51, December 15, 2025.

[Wiley: Angewandte Chemie International Edition: Table of Contents] Uphill Anion Transporters with Ultrahigh Efficiency Based on N‐Heterocyclic Carbene Metal Complexes

Wiley: Angewandte Chemie International Edition: Table of Contents — Tue, 16 Dec 2025 15:14:44 GMT

Angewandte Chemie International Edition, Volume 64, Issue 51, December 15, 2025.

[The Journal of Physical Chemistry C: Latest Articles (ACS Publications)] [ASAP] Ionic Liquids in Quasi-Solid-State Li–S Batteries with Sulfide-Based Solid Electrolytes: A Density Functional Theory and Ab Initio Molecular Dynamics Study

The Journal of Physical Chemistry C: Latest Articles (ACS Publications) — Tue, 16 Dec 2025 14:13:16 GMT

The Journal of Physical Chemistry C

DOI: 10.1021/acs.jpcc.5c05916

[Wiley: Advanced Energy Materials: Table of Contents] How Machine Learning Has Driven the Development of Rechargeable Ion Batteries

Wiley: Advanced Energy Materials: Table of Contents — Tue, 16 Dec 2025 10:18:19 GMT

Advanced Energy Materials, Volume 15, Issue 47, December 16, 2025.

[Wiley: Advanced Energy Materials: Table of Contents] Interplay Between the Dissolved Mn2+ and Solid Electrolyte Interphases of Graphite Anode

Wiley: Advanced Energy Materials: Table of Contents — Tue, 16 Dec 2025 10:18:19 GMT

Advanced Energy Materials, Volume 15, Issue 47, December 16, 2025.

[Wiley: Advanced Energy Materials: Table of Contents] From HF Scavenging to Li‐Ion Transport Enhancement: Multifunctional Separator Enabling Stable Li Metal Batteries in Carbonate‐Based Electrolytes

Wiley: Advanced Energy Materials: Table of Contents — Tue, 16 Dec 2025 09:58:08 GMT

Advanced Energy Materials, EarlyView.

[Wiley: Advanced Energy Materials: Table of Contents] Insight Into All‐Solid‐State Lithium‐Sulfur Batteries: Challenges and Interface Engineering at the Electrode‐Sulfide Solid Electrolyte Interface

Wiley: Advanced Energy Materials: Table of Contents — Tue, 16 Dec 2025 09:45:18 GMT

Advanced Energy Materials, EarlyView.

[Proceedings of the National Academy of Sciences: Physical Sciences] Designing strongly coupled polaritonic structures via statistical machine learning

Proceedings of the National Academy of Sciences: Physical Sciences — Tue, 16 Dec 2025 08:00:00 GMT

[Applied Physics Letters Current Issue] Ultrafast laser-induced anharmonic lattice dynamics and nonlinear optical modulation in croconic acid

Applied Physics Letters Current Issue — Tue, 16 Dec 2025 00:00:00 GMT

[Applied Physics Letters Current Issue] Spin-splitting-torque-driven field-free perpendicular magnetization switching in RuO 2 /synthetic antiferromagnet heterostructures for spintronic convolutional neural networks

Applied Physics Letters Current Issue — Tue, 16 Dec 2025 00:00:00 GMT

[iScience] What Makes a Scent Trigger a Memory? A Cognitive Decomposition of Odor-Evoked Retrieval

iScience — Tue, 16 Dec 2025 00:00:00 GMT

[iScience] Integrative Analysis of Transcriptomic Data Reveals a Predictive Gene Signature for Chemoradiotherapy Response in Rectal Cancer

iScience — Tue, 16 Dec 2025 00:00:00 GMT

[iScience] Combining DNA Methylation Features and Clinical Characteristics Predicts Ketamine Treatment Response for PTSD

iScience — Tue, 16 Dec 2025 00:00:00 GMT

[Chem] In situ cryogenic X-ray photoelectron spectroscopy unveils metastable components of the solid electrolyte interphase in Li-ion batteries

Chem — Tue, 16 Dec 2025 00:00:00 GMT

[The Journal of Physical Chemistry Letters: Latest Articles (ACS Publications)] [ASAP] Anharmonic Coupling in a Strong Intramolecular H-Bond System: Contributions to Static and Time-Resolved Vibrational Spectra

The Journal of Physical Chemistry Letters: Latest Articles (ACS Publications) — Mon, 15 Dec 2025 17:03:38 GMT

The Journal of Physical Chemistry Letters

DOI: 10.1021/acs.jpclett.5c03487

[Journal of the American Chemical Society: Latest Articles (ACS Publications)] [ASAP] Rhodium-Catalyzed Atroposelective Alkyne Oxyamidation Using Non-Nitrene NH Acyloxyamide Reagents

Journal of the American Chemical Society: Latest Articles (ACS Publications) — Mon, 15 Dec 2025 15:14:00 GMT

Journal of the American Chemical Society

DOI: 10.1021/jacs.5c18495

[Proceedings of the National Academy of Sciences: Physical Sciences] CHARGE-MAP: An integrated framework to study the multicriteria EV charging infrastructure expansion problem

Proceedings of the National Academy of Sciences: Physical Sciences — Mon, 15 Dec 2025 08:00:00 GMT

[Wiley: Chinese Journal of Chemistry: Table of Contents] 2‐Trifluoromethyl‐Benzimidazolium Salt as a Dual‐Function Reagent for Deoxytrifluoromethylation of Benzyl Alcohols

Wiley: Chinese Journal of Chemistry: Table of Contents — Mon, 15 Dec 2025 07:33:14 GMT

Chinese Journal of Chemistry, Volume 44, Issue 2, Page 177-182, 15 January 2026.

[Applied Physics Letters Current Issue] Covalent bond chemistry enabling M 2 CN 2 MXenes as anode materials for halide-ion batteries

Applied Physics Letters Current Issue — Mon, 15 Dec 2025 00:00:00 GMT

[Applied Physics Letters Current Issue] Measurement of multiple mechanical properties from multi-dimensional signals in nanosecond laser ablation via PINN

Applied Physics Letters Current Issue — Mon, 15 Dec 2025 00:00:00 GMT

[RSC - Digital Discovery latest articles] Deep learning based SEM image analysis for predicting ionic conductivity in LiZr2(PO4)3-based solid electrolytes

RSC - Digital Discovery latest articles — Mon, 15 Dec 2025 00:00:00 GMT

Digital Discovery, 2026, Advance Article
DOI: 10.1039/D5DD00232J, Paper

Open Access

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[RSC - Digital Discovery latest articles] Hierarchical Attention Graph Learning with LLMs Enhancement for Molecular Solubility Prediction

RSC - Digital Discovery latest articles — Mon, 15 Dec 2025 00:00:00 GMT

Digital Discovery, 2025, Accepted Manuscript
DOI: 10.1039/D5DD00407A, Paper

Open Access

This article is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported Licence.

[iScience] Interpretable Machine Learning for Accessible Dysphagia Screening and Staging in Older Adults

iScience — Mon, 15 Dec 2025 00:00:00 GMT

[Joule] Dendrite suppression in garnet electrolytes via thermally induced compressive stress

Joule — Mon, 15 Dec 2025 00:00:00 GMT

[Journal of the American Chemical Society: Latest Articles (ACS Publications)] [ASAP] Unraveling the Humidity-Induced Phase Transition in CALF-20 via Machine Learning Potentials

Journal of the American Chemical Society: Latest Articles (ACS Publications) — Sat, 13 Dec 2025 14:29:51 GMT

Journal of the American Chemical Society

DOI: 10.1021/jacs.5c18944

[Wiley: Advanced Energy Materials: Table of Contents] Machine Learning Descriptors for Mapping Structure‐Property‐Performance Relationships of Perovskite Solar Cells

Wiley: Advanced Energy Materials: Table of Contents — Sat, 13 Dec 2025 07:01:43 GMT

Advanced Energy Materials, EarlyView.

[Journal of the American Chemical Society: Latest Articles (ACS Publications)] [ASAP] Vinylsilanes as Chain-Transfer Agents in Ethylene Polymerization: Direct Synthesis of Heterotelechelic Polyolefins

Journal of the American Chemical Society: Latest Articles (ACS Publications) — Fri, 12 Dec 2025 16:44:30 GMT

Journal of the American Chemical Society

DOI: 10.1021/jacs.5c15808

[The Journal of Physical Chemistry Letters: Latest Articles (ACS Publications)] [ASAP] Compression-Induced Lattice Tilting Quenches Ion Migration at Metal Halide Perovskite Grain Boundaries: A Machine Learning Molecular Dynamics Study

The Journal of Physical Chemistry Letters: Latest Articles (ACS Publications) — Fri, 12 Dec 2025 15:21:13 GMT

The Journal of Physical Chemistry Letters

DOI: 10.1021/acs.jpclett.5c03637

[Journal of the American Chemical Society: Latest Articles (ACS Publications)] [ASAP] Machine Learning-Assisted Crystal Structure Prediction of Solid-State Electrolytes Reveals Superior Ionic Conductivity in Metastable Edge-Sharing Phases

Journal of the American Chemical Society: Latest Articles (ACS Publications) — Fri, 12 Dec 2025 14:36:09 GMT

Journal of the American Chemical Society

DOI: 10.1021/jacs.5c15665

[ACS Materials Letters: Latest Articles (ACS Publications)] [ASAP] Reaction Pathway Informed Strategy for Fast Solid-State Synthesis of Garnet-Type Solid Electrolyte

ACS Materials Letters: Latest Articles (ACS Publications) — Fri, 12 Dec 2025 14:10:55 GMT

ACS Materials Letters

DOI: 10.1021/acsmaterialslett.5c01262

[ACS Energy Letters: Latest Articles (ACS Publications)] [ASAP] Structural Aspects, Ionic Conductivity, and Electrochemical Properties of New Bromine-Substituted Alkali-Based Crystalline Phases MTa(Nb)X6–yBry (M = Li, Na, K; X = Cl, F)

ACS Energy Letters: Latest Articles (ACS Publications) — Fri, 12 Dec 2025 13:47:45 GMT

ACS Energy Letters

DOI: 10.1021/acsenergylett.5c02904

[Proceedings of the National Academy of Sciences: Proceedings of the National Academy of Sciences: Table of Contents] Spiking world model with multicompartment neurons for model-based reinforcement learning

Fri, 12 Dec 2025 08:00:00 GMT

[APL Machine Learning Current Issue] Smart detection of plant nutrient deficiencies using machine learning and image fusion

APL Machine Learning Current Issue — Fri, 12 Dec 2025 00:00:00 GMT

[Nature Machine Intelligence] LLM use in scholarly writing poses a provenance problem

Nature Machine Intelligence — Fri, 12 Dec 2025 00:00:00 GMT

Nature Machine Intelligence, Published online: 12 December 2025; doi:10.1038/s42256-025-01159-8

LLM use in scholarly writing poses a provenance problem

[RSC - Digital Discovery latest articles] PEMD: a high-throughput simulation and analysis framework for solid polymer electrolytes

RSC - Digital Discovery latest articles — Fri, 12 Dec 2025 00:00:00 GMT

Digital Discovery, 2026, Advance Article
DOI: 10.1039/D5DD00454C, Paper

Open Access

This article is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported Licence.

[AI for Science - latest papers] Investigating CO adsorption on Cu(111) and Rh(111) surfaces using machine learning exchange-correlation functionals

AI for Science - latest papers — Fri, 12 Dec 2025 00:00:00 GMT

[iScience] Contextualized biomedical language processing enhances ICU survival prediction

iScience — Fri, 12 Dec 2025 00:00:00 GMT

[iScience] Consensus machine learning identifies cell death gene signature for carotid artery stenosis diagnosis

iScience — Fri, 12 Dec 2025 00:00:00 GMT

[The Journal of Physical Chemistry C: Latest Articles (ACS Publications)] [ASAP] Dual Structure-Directing Agents for Superstructure Formation in PtCoCu Ternary Alloy Electrocatalysts

The Journal of Physical Chemistry C: Latest Articles (ACS Publications) — Thu, 11 Dec 2025 15:46:59 GMT

The Journal of Physical Chemistry C

DOI: 10.1021/acs.jpcc.5c06519

[Wiley: Advanced Science: Table of Contents] A Cost‐Effective and Scalable Machine Learning Approach for Quality Assessment of Fresh Maize Kernel Using NIR Spectroscopy

Wiley: Advanced Science: Table of Contents — Thu, 11 Dec 2025 09:23:00 GMT

Advanced Science, Volume 12, Issue 46, December 11, 2025.

[Wiley: Advanced Science: Table of Contents] High‐Performance Zinc–Bromine Rechargeable Batteries Enabled by In‐Situ Formed Solid Electrolyte Interphase

Wiley: Advanced Science: Table of Contents — Thu, 11 Dec 2025 09:23:00 GMT

Advanced Science, Volume 12, Issue 46, December 11, 2025.

[Wiley: Advanced Science: Table of Contents] Nonalcoholic Fatty Liver Disease Exacerbates the Advancement of Renal Fibrosis by Modulating Renal CCR2+PIRB+ Macrophages Through the ANGPTL8/PIRB/ALOX5AP Axis

Wiley: Advanced Science: Table of Contents — Thu, 11 Dec 2025 09:23:00 GMT

Advanced Science, Volume 12, Issue 46, December 11, 2025.

[Wiley: Advanced Science: Table of Contents] Inverse Design of Metal‐Organic Frameworks for CH4/N2 Separation Enabled by Coupled Machine Learning and Genetic Algorithms

Wiley: Advanced Science: Table of Contents — Thu, 11 Dec 2025 09:23:00 GMT

Advanced Science, Volume 12, Issue 46, December 11, 2025.

[Wiley: Advanced Science: Table of Contents] Synergistic Effect of Dual‐Functional Groups in MOF‐Modified Separators for Efficient Lithium‐Ion Transport and Polysulfide Management of Lithium‐Sulfur Batteries

Wiley: Advanced Science: Table of Contents — Thu, 11 Dec 2025 09:23:00 GMT

Advanced Science, Volume 12, Issue 46, December 11, 2025.

[Wiley: Advanced Science: Table of Contents] H2S Is a Potential Universal Reducing Agent for Prx6‐Type Peroxiredoxins

Wiley: Advanced Science: Table of Contents — Thu, 11 Dec 2025 09:23:00 GMT

Advanced Science, Volume 12, Issue 46, December 11, 2025.

[Wiley: Advanced Science: Table of Contents] Luminescent Nanocucurbits Enable Spatiotemporal Co‐Delivery of Hydrophilic and Hydrophobic Chemotherapeutic Agents

Wiley: Advanced Science: Table of Contents — Thu, 11 Dec 2025 09:23:00 GMT

Advanced Science, Volume 12, Issue 46, December 11, 2025.

[Proceedings of the National Academy of Sciences: Proceedings of the National Academy of Sciences: Table of Contents] Evaluating large language models in biomedical data science challenges through a classroom experiment

Thu, 11 Dec 2025 08:00:00 GMT

[Wiley: Advanced Functional Materials: Table of Contents] Red Phosphorus@SnSe0.5S0.5 Core‐Shell Heterostructure Enables Superior Sodium Storage via Synergistic Ion Diffusion and Polyphosphides Trapping

Wiley: Advanced Functional Materials: Table of Contents — Thu, 11 Dec 2025 06:58:45 GMT

Advanced Functional Materials, Volume 35, Issue 50, December 9, 2025.

[Wiley: Advanced Functional Materials: Table of Contents] Dual‐Site Ni Nanoparticles‐Ru Clusters Anchored on Hierarchical Carbon with Decoupled Gas and Ion Diffusion Channels Enabling Low‐Overpotential, Highly Stable Li‐CO2 Batteries

Wiley: Advanced Functional Materials: Table of Contents — Thu, 11 Dec 2025 06:58:45 GMT

Advanced Functional Materials, Volume 35, Issue 50, December 9, 2025.

[Wiley: Advanced Functional Materials: Table of Contents] Surface Fluidic Microneedle Patches for Lymphatic Delivery of Diagnostic and Therapeutic Agents (Adv. Funct. Mater. 50/2025)

Wiley: Advanced Functional Materials: Table of Contents — Thu, 11 Dec 2025 06:58:45 GMT

Advanced Functional Materials, Volume 35, Issue 50, December 9, 2025.

[Wiley: Advanced Functional Materials: Table of Contents] Bonyzymes: Efficient Anti‐Inflammatory, Antibacterial and Osteogenic Agents for Peri‐Implantitis Reconstruction Treatment

Wiley: Advanced Functional Materials: Table of Contents — Thu, 11 Dec 2025 06:58:45 GMT

Advanced Functional Materials, Volume 35, Issue 50, December 9, 2025.

[Wiley: Advanced Functional Materials: Table of Contents] Surface Fluidic Microneedle Patches for Lymphatic Delivery of Diagnostic and Therapeutic Agents

Wiley: Advanced Functional Materials: Table of Contents — Thu, 11 Dec 2025 06:58:45 GMT

Advanced Functional Materials, Volume 35, Issue 50, December 9, 2025.

[RSC - Digital Discovery latest articles] Toward smart CO2 capture by the synthesis of metal organic frameworks using large language models

RSC - Digital Discovery latest articles — Thu, 11 Dec 2025 00:00:00 GMT

Digital Discovery, 2026, Advance Article
DOI: 10.1039/D5DD00446B, Paper

Open Access

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence.

[Journal of Chemical Theory and Computation: Latest Articles (ACS Publications)] [ASAP] A Universal Augmentation Framework for Long-Range Electrostatics in Machine Learning Interatomic Potentials

Journal of Chemical Theory and Computation: Latest Articles (ACS Publications) — Wed, 10 Dec 2025 10:12:04 GMT

Journal of Chemical Theory and Computation

DOI: 10.1021/acs.jctc.5c01400

[Wiley: ENERGY & ENVIRONMENTAL MATERIALS: Table of Contents] Tailoring Thermophysical Properties and Multiscale Machine Learning Modeling of 2D Nanomaterial‐Infused Beeswax as a Green NePCM for Sustainable Thermal Management Systems

Wiley: ENERGY & ENVIRONMENTAL MATERIALS: Table of Contents — Wed, 10 Dec 2025 09:54:56 GMT

ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.

[Applied Physics Reviews Current Issue] Construction of polar topological nanodevices for neuromorphic computing

Applied Physics Reviews Current Issue — Wed, 10 Dec 2025 00:00:00 GMT

[RSC - Digital Discovery latest articles] Optimizing Data Extraction from Materials Science Literature: A Study of Tools Using Large Language Models

RSC - Digital Discovery latest articles — Wed, 10 Dec 2025 00:00:00 GMT

Digital Discovery, 2025, Accepted Manuscript
DOI: 10.1039/D5DD00482A, Paper

Open Access

This article is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported Licence.

[Journal of the American Chemical Society: Latest Articles (ACS Publications)] [ASAP] Machine Learning-Guided Decoding Bioelectronic Signals of Photosynthetic Cyanobacterial Cells by Conducting Polymers

Journal of the American Chemical Society: Latest Articles (ACS Publications) — Tue, 09 Dec 2025 15:33:56 GMT

Journal of the American Chemical Society

DOI: 10.1021/jacs.5c13150

[Recent Articles in Phys. Rev. Lett.] Connection between Memory Performance and Optical Absorption in Quantum Reservoir Computing

Recent Articles in Phys. Rev. Lett. — Tue, 09 Dec 2025 10:00:00 GMT

Author(s): Niclas Götting, Steffen Wilksen, Alexander Steinhoff, Frederik Lohof, and Christopher Gies

[Phys. Rev. Lett. 135, 240403] Published Tue Dec 09, 2025

[Wiley: Advanced Energy Materials: Table of Contents] Ultrahigh‐Rate Lithium Storage in MoS2 Enabled by Isotropic Ion Transport and Fe‐Atomic Site Conversion

Wiley: Advanced Energy Materials: Table of Contents — Tue, 09 Dec 2025 08:32:12 GMT

Advanced Energy Materials, EarlyView.

[Wiley: Advanced Energy Materials: Table of Contents] Prediction of Structural Stability of Layered Oxide Cathode Materials: Combination of Machine Learning and Ab Initio Thermodynamics

Wiley: Advanced Energy Materials: Table of Contents — Tue, 09 Dec 2025 07:26:17 GMT

Advanced Energy Materials, EarlyView.

[Wiley: Advanced Intelligent Discovery: Table of Contents] Enhancing Synaptic Plasticity in Strontium Titanate‐Based Sensory Processing Devices: A Study on Oxygen Vacancy Modulation and Performance in Artificial Neural Networks

Wiley: Advanced Intelligent Discovery: Table of Contents — Tue, 09 Dec 2025 01:16:19 GMT

Advanced Intelligent Discovery, Volume 1, Issue 3, December 2025.

[RSC - Digital Discovery latest articles] Multi-agentic AI framework for end-to-end atomistic simulations

RSC - Digital Discovery latest articles — Tue, 09 Dec 2025 00:00:00 GMT

Digital Discovery, 2026, Advance Article
DOI: 10.1039/D5DD00435G, Paper

Open Access

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence.

[Journal of the American Chemical Society: Latest Articles (ACS Publications)] [ASAP] Quantifying Phase Contributions to Ion Transport in Organic–Inorganic Composite Electrolytes

Journal of the American Chemical Society: Latest Articles (ACS Publications) — Mon, 08 Dec 2025 19:45:10 GMT

Journal of the American Chemical Society

DOI: 10.1021/jacs.5c11634

[Proceedings of the National Academy of Sciences: Proceedings of the National Academy of Sciences: Table of Contents] Chatbot Voting Advice Applications inform but seldom sway young unaligned voters

Mon, 08 Dec 2025 08:00:00 GMT

[RSC - Chem. Sci. latest articles] A solid composite electrolyte based on three-dimensional structured zeolite networks for high-performance solid-state lithium metal batteries

RSC - Chem. Sci. latest articles — Sun, 07 Dec 2025 00:00:00 GMT

Chem. Sci., 2026, Advance Article
DOI: 10.1039/D5SC05786H, Edge Article

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[Proceedings of the National Academy of Sciences: Physical Sciences] Local equations describe unreasonably efficient stochastic algorithms in random K-SAT

Proceedings of the National Academy of Sciences: Physical Sciences — Fri, 05 Dec 2025 08:00:00 GMT

[ACS Materials Letters: Latest Articles (ACS Publications)] [ASAP] Beyond Conventional Sodium Superionic Conductor: Fe-Substituted Na3V2(PO4)2F3 Cathodes with Accelerated Charge Transport via Polyol Reflux for Sodium-Ion Batteries

ACS Materials Letters: Latest Articles (ACS Publications) — Thu, 04 Dec 2025 13:33:58 GMT

ACS Materials Letters

DOI: 10.1021/acsmaterialslett.5c01502

[Wiley: Advanced Science: Table of Contents] Non‐Monotonic Ion Conductivity in Lithium‐Aluminum‐Chloride Glass Solid‐State Electrolytes Explained by Cascading Hopping

Wiley: Advanced Science: Table of Contents — Thu, 04 Dec 2025 08:00:00 GMT

Advanced Science, Volume 12, Issue 45, December 4, 2025.

[Wiley: Advanced Science: Table of Contents] Re‐Purposing a Modular Origami Manipulator Into an Adaptive Physical Computer for Machine Learning and Robotic Perception

Wiley: Advanced Science: Table of Contents — Thu, 04 Dec 2025 08:00:00 GMT

Advanced Science, Volume 12, Issue 45, December 4, 2025.

[Wiley: Advanced Materials: Table of Contents] Ultrastable Calcium Metal Anodes Enabled by a Strongly Coordinated Electrolyte Derived Bilayer Solid Electrolyte Interphase

Wiley: Advanced Materials: Table of Contents — Thu, 04 Dec 2025 07:04:36 GMT

Advanced Materials, Volume 37, Issue 48, December 3, 2025.

[APL Machine Learning Current Issue] Multi-resolution physics-aware recurrent convolutional neural network for complex flows

APL Machine Learning Current Issue — Thu, 04 Dec 2025 00:00:00 GMT

[RSC - Digital Discovery latest articles] Understanding and mitigating distribution shifts for universal machine learning interatomic potentials

RSC - Digital Discovery latest articles — Thu, 04 Dec 2025 00:00:00 GMT

Digital Discovery, 2026, Advance Article
DOI: 10.1039/D5DD00260E, Paper

Open Access

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[iScience] Physical Cognition in Altered Gravity: Link Between Sensorimotor and Cognitive Adaptability

iScience — Thu, 04 Dec 2025 00:00:00 GMT

[iScience] Meteorological and Socioeconomic Impacts on China Ozone Past and Future Analysis

iScience — Thu, 04 Dec 2025 00:00:00 GMT

[Applied Physics Reviews Current Issue] Gate-tunable dual-mode BiOI photodetector for precise object identification

Applied Physics Reviews Current Issue — Thu, 04 Dec 2025 00:00:00 GMT

[Wiley: Small: Table of Contents] Label‐Free Detection of Nuclear Envelope Nucleoporation using 2D Morphological Embeddings and Machine Learning

Wiley: Small: Table of Contents — Wed, 03 Dec 2025 15:24:49 GMT

Small, Volume 21, Issue 48, December 3, 2025.

[Wiley: Small: Table of Contents] Reagentless Real‐Time ATP Monitoring with New DNA Aptamers

Wiley: Small: Table of Contents — Wed, 03 Dec 2025 15:24:49 GMT

Small, Volume 21, Issue 48, December 3, 2025.

[Wiley: Advanced Functional Materials: Table of Contents] Machine Learning‐Enabled Polymer Discovery for Enhanced Pulmonary siRNA Delivery

Wiley: Advanced Functional Materials: Table of Contents — Wed, 03 Dec 2025 08:00:00 GMT

Advanced Functional Materials, Volume 35, Issue 49, December 2, 2025.

[Wiley: Advanced Functional Materials: Table of Contents] Enhanced Potassium Ion Diffusion and Interface Stability Enabled by Potassiophilic rGO/CNTs/NaF Micro‐Lattice Aerogel for High‐Performance Potassium Metal Batteries

Wiley: Advanced Functional Materials: Table of Contents — Wed, 03 Dec 2025 08:00:00 GMT

Advanced Functional Materials, Volume 35, Issue 49, December 2, 2025.

[Nature Reviews Physics] Predicting high-entropy alloy phases with machine learning

Nature Reviews Physics — Wed, 03 Dec 2025 00:00:00 GMT

Nature Reviews Physics, Published online: 03 December 2025; doi:10.1038/s42254-025-00903-8

Omokhuwele Umoru explains how generative adversarial networks can help to predict the phases of high-entropy alloys.

[RSC - Digital Discovery latest articles] Evaluating the transfer learning from metals to oxides with GAME-Net-Ox

RSC - Digital Discovery latest articles — Wed, 03 Dec 2025 00:00:00 GMT

Digital Discovery, 2026, Advance Article
DOI: 10.1039/D5DD00331H, Paper

Open Access

This article is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported Licence.

[iScience] United multi-omics and machine learning refine regulatory T cell-defined hepatocellular carcinoma subtypes

iScience — Wed, 03 Dec 2025 00:00:00 GMT

[iScience] ABCA1 acts as a protective modulator in amyotrophic lateral sclerosis

iScience — Wed, 03 Dec 2025 00:00:00 GMT

[Matter] Unknowium, beyond the banana, and AI discovery in materials science

Matter — Wed, 03 Dec 2025 00:00:00 GMT

[iScience] AI enhancing differential diagnosis of acute chronic obstructive pulmonary disease and acute heart failure

iScience — Wed, 03 Dec 2025 00:00:00 GMT

Cardiovascular medicine; Respiratory medicine; Machine learning

[Wiley: Advanced Energy Materials: Table of Contents] Taming Metal–Solid Electrolyte Interface Instability via Metal Strain Hardening

Wiley: Advanced Energy Materials: Table of Contents — Tue, 02 Dec 2025 13:55:59 GMT

Advanced Energy Materials, Volume 15, Issue 45, December 2, 2025.

[Wiley: Advanced Energy Materials: Table of Contents] Self‐Liquefying Conformal Nanocoatings via Phase‐Convertible Ion Conductors for Stable All‐Solid‐State Batteries (Adv. Energy Mater. 45/2025)

Wiley: Advanced Energy Materials: Table of Contents — Tue, 02 Dec 2025 13:55:59 GMT

Advanced Energy Materials, Volume 15, Issue 45, December 2, 2025.

[Wiley: Advanced Energy Materials: Table of Contents] Multiscale Design Strategies of Interface‐Stabilized Solid Electrolytes and Dynamic Interphase Decoding from Atomic‐to‐Macroscopic Perspectives

Wiley: Advanced Energy Materials: Table of Contents — Tue, 02 Dec 2025 13:55:59 GMT

Advanced Energy Materials, Volume 15, Issue 45, December 2, 2025.

[Wiley: Advanced Energy Materials: Table of Contents] Self‐Liquefying Conformal Nanocoatings via Phase‐Convertible Ion Conductors for Stable All‐Solid‐State Batteries

Wiley: Advanced Energy Materials: Table of Contents — Tue, 02 Dec 2025 13:55:59 GMT

Advanced Energy Materials, Volume 15, Issue 45, December 2, 2025.

[Chinese Chemical Society: CCS Chemistry: Table of Contents] LoRA-Chem: Modular Machine Learning for Multitask Prediction in Organic Reactions

Chinese Chemical Society: CCS Chemistry: Table of Contents — Tue, 02 Dec 2025 04:48:31 GMT

CCS Chemistry, Ahead of Print.

DOI:10.31635/ccschem.025.202506542

[iScience] Dimensionality modulated generative AI for safe biomedical dataset augmentation

iScience — Tue, 02 Dec 2025 00:00:00 GMT

[Wiley: Advanced Intelligent Discovery: Table of Contents] Advances in Thermal Modeling and Simulation of Lithium‐Ion Batteries with Machine Learning Approaches

Wiley: Advanced Intelligent Discovery: Table of Contents — Mon, 01 Dec 2025 22:39:43 GMT

Advanced Intelligent Discovery, EarlyView.

[APL Machine Learning Current Issue] RTNinja : A generalized machine learning framework for analyzing random telegraph noise signals in nanoelectronic devices

APL Machine Learning Current Issue — Mon, 01 Dec 2025 00:00:00 GMT

[iScience] A pilot study: Incorporating Treponema pallidum antigens into machine learning models for accurate syphilis treatment outcome assessment

iScience — Mon, 01 Dec 2025 00:00:00 GMT

Health informatics; disease; artificial intelligence applications

[iScience] Bathymetry of the Philippine Sea with Convolution Neural Network from Multisource Marine Geodetic Data

iScience — Fri, 28 Nov 2025 00:00:00 GMT

[Wiley: Small Methods: Table of Contents] Water‐Dispersible Metal Oxide Nanoparticles Synthesized Via Hydrogen‐Bond‐Mediated Aqueous Solution: Gd2O3 for High‐Performance T1 Magnetic Resonance Imaging Contrast Agent

Wiley: Small Methods: Table of Contents — Thu, 27 Nov 2025 07:52:59 GMT

Small Methods, EarlyView.

[iScience] Interpretable Machine Learning for Urothelial Cells Classification and Risk Scoring in Urine Cytology

iScience — Thu, 27 Nov 2025 00:00:00 GMT

[Wiley: Advanced Intelligent Discovery: Table of Contents] Machine Learning‐Assisted Second‐Order Perturbation Theory for Chemical Potential Correction Toward Hubbard U Determination

Wiley: Advanced Intelligent Discovery: Table of Contents — Wed, 26 Nov 2025 03:49:32 GMT

Advanced Intelligent Discovery, EarlyView.

[RSC - Digital Discovery latest articles] Toward accelerating rare-earth metal extraction using equivariant neural networks

RSC - Digital Discovery latest articles — Wed, 26 Nov 2025 00:00:00 GMT

Digital Discovery, 2026, Advance Article
DOI: 10.1039/D5DD00286A, Paper

Open Access

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[RSC - Digital Discovery latest articles] Automated synthesis and fragment descriptor-based machine learning for retention time prediction in supercritical fluid chromatography

RSC - Digital Discovery latest articles — Wed, 26 Nov 2025 00:00:00 GMT

Digital Discovery, 2026, Advance Article
DOI: 10.1039/D5DD00437C, Paper

Open Access

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence.

[RSC - Digital Discovery latest articles] Mol2Raman: a graph neural network model for predicting Raman spectra from SMILES representations

RSC - Digital Discovery latest articles — Tue, 25 Nov 2025 00:00:00 GMT

Digital Discovery, 2025, Advance Article
DOI: 10.1039/D5DD00210A, Paper

Open Access

This article is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported Licence.

[RSC - Chem. Sci. latest articles] Data-driven approach to elucidate the correlation between photocatalytic activity and rate constants from excited states

RSC - Chem. Sci. latest articles — Tue, 25 Nov 2025 00:00:00 GMT

Chem. Sci., 2026, Advance Article
DOI: 10.1039/D5SC06465A, Edge Article

Open Access

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence.

[Cell Reports Physical Science] Repurposing clinical iron oxide agents for mild hyperthermia-assisted cancer therapy

Cell Reports Physical Science — Tue, 25 Nov 2025 00:00:00 GMT

[JACS Au: Latest Articles (ACS Publications)] [ASAP] Constant-Potential MD with Neural Network Potentials Reveals Cation Effects on CO2 Reduction at Au-Water Interfaces

JACS Au: Latest Articles (ACS Publications) — Mon, 24 Nov 2025 12:22:43 GMT

JACS Au

DOI: 10.1021/jacsau.5c01198

[Proceedings of the National Academy of Sciences: Physical Sciences] Modeling feasible locomotion of nanobots for cancer detection and treatment

Proceedings of the National Academy of Sciences: Physical Sciences — Mon, 24 Nov 2025 08:00:00 GMT

[Wiley: Chinese Journal of Chemistry: Table of Contents] Locked Coplanar Conformation Boosts Rapid Electron/Ion Transport in Linear Polyimide Cathodes for Sodium‐Ion Storage

Wiley: Chinese Journal of Chemistry: Table of Contents — Mon, 24 Nov 2025 07:33:36 GMT

Chinese Journal of Chemistry, EarlyView.

[APL Machine Learning Current Issue] A hybrid neural architecture: Online attosecond x-ray characterization

APL Machine Learning Current Issue — Fri, 21 Nov 2025 00:00:00 GMT

[Joule] Accelerated discovery of CO2-to-C3-hydrocarbon electrocatalysts with human-in-the-loop

Joule — Fri, 21 Nov 2025 00:00:00 GMT

[Joule] Redox-mediated solid-state doping of Spiro-OMeTAD for efficient and robust perovskite photovoltaics

Joule — Fri, 21 Nov 2025 00:00:00 GMT

[AI for Science - latest papers] Learning to be simple

AI for Science - latest papers — Thu, 20 Nov 2025 00:00:00 GMT

[RSC - Chem. Sci. latest articles] Development of a glutamine-responsive MRI contrast agent

RSC - Chem. Sci. latest articles — Thu, 20 Nov 2025 00:00:00 GMT

Chem. Sci., 2026, Advance Article
DOI: 10.1039/D5SC05987A, Edge Article

Open Access

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[Wiley: Advanced Intelligent Discovery: Table of Contents] Taguchi–Bayesian Sampling: A Roadmap for Polymer Database Construction Toward Small Representative Machine Learning

Wiley: Advanced Intelligent Discovery: Table of Contents — Wed, 19 Nov 2025 05:00:22 GMT

Advanced Intelligent Discovery, EarlyView.

[RSC - Digital Discovery latest articles] Democratizing machine learning in chemistry with community-engaged test sets

RSC - Digital Discovery latest articles — Wed, 19 Nov 2025 00:00:00 GMT

Digital Discovery, 2026, Advance Article
DOI: 10.1039/D5DD00424A, Paper

Open Access

This article is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported Licence.

[iScience] An Explainable Machine Learning Model Predicts 30-Day Readmission after Vertebral Augmentation

iScience — Wed, 19 Nov 2025 00:00:00 GMT

[Wiley: SmartMat: Table of Contents] Machine Learning Design of Soft Magnetoresponsive Materials With Multidirectional Fields

Wiley: SmartMat: Table of Contents — Tue, 18 Nov 2025 08:00:00 GMT

SmartMat, Volume 6, Issue 6, December 2025.

[RSC - Digital Discovery latest articles] Advancing metal organic framework and covalent organic framework design via the digital-intelligent paradigm

RSC - Digital Discovery latest articles — Tue, 18 Nov 2025 00:00:00 GMT

Digital Discovery, 2026, Advance Article
DOI: 10.1039/D5DD00401B, Review Article

Open Access

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[RSC - Digital Discovery latest articles] Application-specific machine-learned interatomic potentials: exploring the trade-off between DFT convergence, MLIP expressivity, and computational cost

RSC - Digital Discovery latest articles — Tue, 18 Nov 2025 00:00:00 GMT

Digital Discovery, 2026, Advance Article
DOI: 10.1039/D5DD00294J, Paper

Open Access

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence.

[Applied Physics Reviews Current Issue] Synergistic integration of metasurfaces and quantum photonics: Pathways to next-generation technologies

Applied Physics Reviews Current Issue — Mon, 17 Nov 2025 00:00:00 GMT

[AI for Science - latest papers] Universal machine learning potentials for systems with reduced dimensionality

AI for Science - latest papers — Mon, 17 Nov 2025 00:00:00 GMT

[Cell Reports Physical Science] Conjugated polyelectrolyte-aptamer hybrid for organic-electrochemical-transistor-based sensing

Cell Reports Physical Science — Mon, 17 Nov 2025 00:00:00 GMT

[Cell Reports Physical Science] CatBench framework for benchmarking machine learning interatomic potentials in adsorption energy predictions for heterogeneous catalysis

Cell Reports Physical Science — Mon, 17 Nov 2025 00:00:00 GMT

[Journal of the American Chemical Society: Latest Articles (ACS Publications)] [ASAP] An O2-Independent Copper(II) Phototherapeutic Agent for Photoactivating H2O2 to Enhance Antitumor Immunotherapy

Journal of the American Chemical Society: Latest Articles (ACS Publications) — Sun, 16 Nov 2025 13:54:08 GMT

Journal of the American Chemical Society

DOI: 10.1021/jacs.5c14960

[Wiley: ENERGY & ENVIRONMENTAL MATERIALS: Table of Contents] Liquid‐Phase Synthesis of Halide Solid Electrolytes for All‐Solid‐State Batteries Using Organic Solvents

Wiley: ENERGY & ENVIRONMENTAL MATERIALS: Table of Contents — Fri, 14 Nov 2025 14:05:17 GMT

ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.

[Proceedings of the National Academy of Sciences: Physical Sciences] How public involvement can improve the science of AI

Proceedings of the National Academy of Sciences: Physical Sciences — Fri, 14 Nov 2025 08:00:00 GMT

[AI for Science - latest papers] TorchSim: an efficient atomistic simulation engine in PyTorch

AI for Science - latest papers — Fri, 14 Nov 2025 00:00:00 GMT

[AI for Science - latest papers] Graph learning metallic glass discovery from Wikipedia

AI for Science - latest papers — Fri, 14 Nov 2025 00:00:00 GMT

[ACS Materials Au: Latest Articles (ACS Publications)] [ASAP] Molecular Modeling-Based Machine Learning for Accurate Prediction of Gas Diffusivity and Permeability in Metal–Organic Frameworks

ACS Materials Au: Latest Articles (ACS Publications) — Wed, 12 Nov 2025 18:15:35 GMT

ACS Materials Au

DOI: 10.1021/acsmaterialsau.5c00111

[Recent Articles in PRX Energy] Dynamic Vacancy Levels in ${\mathrm{Cs}\mathrm{Pb}\mathrm{Cl}}_{3}$ Obey Equilibrium Defect Thermodynamics

Recent Articles in PRX Energy — Wed, 12 Nov 2025 10:00:00 GMT

Author(s): Irea Mosquera-Lois and Aron Walsh

[PRX Energy 4, 043008] Published Wed Nov 12, 2025

[Wiley: Advanced Intelligent Discovery: Table of Contents] Accelerating Primary Screening of USP8 Inhibitors from Drug Repurposing Databases with Tree‐Based Machine Learning

Wiley: Advanced Intelligent Discovery: Table of Contents — Tue, 11 Nov 2025 04:16:54 GMT

Advanced Intelligent Discovery, EarlyView.

[RSC - Digital Discovery latest articles] Design of simple-structured conjugated polymers for organic solar cells by machine learning-assisted structural modification and experimental validation

RSC - Digital Discovery latest articles — Tue, 11 Nov 2025 00:00:00 GMT

Digital Discovery, 2025, 4,3774-3781
DOI: 10.1039/D5DD00418G, Paper

Open Access

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence.

[Joule] Entropy-guided discovery of denary trirutile antimonates for electrocatalytic chlorine evolution

Joule — Tue, 11 Nov 2025 00:00:00 GMT

[AI for Science - latest papers] Surface stability modeling with universal machine learning interatomic potentials: a comprehensive cleavage energy benchmarking study

AI for Science - latest papers — Fri, 07 Nov 2025 00:00:00 GMT

[Joule] Li–Si compound anodes enabling high-performance all-solid-state Li-ion batteries

Joule — Fri, 07 Nov 2025 00:00:00 GMT

[ACS Physical Chemistry Au: Latest Articles (ACS Publications)] [ASAP] Machine Learning as a Method for Retrieving Pressure Values by Analyzing Spectral Line Parameters: The Hydrochloric Acid Case

ACS Physical Chemistry Au: Latest Articles (ACS Publications) — Tue, 04 Nov 2025 19:09:10 GMT

ACS Physical Chemistry Au

DOI: 10.1021/acsphyschemau.5c00097

[Chinese Chemical Society: CCS Chemistry: Table of Contents] Near-Infrared-II Aggregation-Induced Emission Photosensitizers with Mitochondrial Respiration Perturbation Activity Amplifies Ferroptosis, Necroptosis, and Apoptosis for Cancer Immunotherapy

Chinese Chemical Society: CCS Chemistry: Table of Contents — Tue, 04 Nov 2025 04:36:34 GMT

CCS Chemistry, Ahead of Print.

DOI:10.31635/ccschem.025.202505952

[Applied Physics Reviews Current Issue] Dynamic landscape of chemiresistive breathomic nanosensors based on fifth-generation chips for complex disease diagnosis and healthcare monitoring

Applied Physics Reviews Current Issue — Tue, 04 Nov 2025 00:00:00 GMT

[RSC - Digital Discovery latest articles] Machine learning of polyurethane prepolymer viscosity: a comparison of chemical and physicochemical approaches

RSC - Digital Discovery latest articles — Tue, 04 Nov 2025 00:00:00 GMT

Digital Discovery, 2025, 4,3652-3661
DOI: 10.1039/D5DD00287G, Paper

Open Access

This article is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported Licence.

[Chinese Chemical Society: CCS Chemistry: Table of Contents] Biodegradable Cesium Nanosalts Activating Antitumor Immunity via Inducing Cellular Pyroptosis and Interfering with Metabolism

Chinese Chemical Society: CCS Chemistry: Table of Contents — Mon, 03 Nov 2025 01:13:27 GMT

CCS Chemistry, Ahead of Print.

DOI:10.31635/ccschem.025.202506187

[tandf: Materials Research Letters: Table of Contents] Machine learning-assisted design of strong and ductile BCC high-entropy alloys

tandf: Materials Research Letters: Table of Contents — Thu, 30 Oct 2025 12:22:23 GMT

Volume 13, Issue 12, December 2025, Page 1260-1268
.

[RSC - Digital Discovery latest articles] FFLAME: a fragment-to-framework learning approach for MOF potentials

RSC - Digital Discovery latest articles — Thu, 30 Oct 2025 00:00:00 GMT

Digital Discovery, 2025, 4,3466-3477
DOI: 10.1039/D5DD00321K, Paper

Open Access

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence.

[RSC - Digital Discovery latest articles] Machine learning generalised DFT+U projectors in a numerical atom-centred orbital framework

RSC - Digital Discovery latest articles — Thu, 30 Oct 2025 00:00:00 GMT

Digital Discovery, 2025, 4,3701-3727
DOI: 10.1039/D5DD00292C, Paper

Open Access

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence.

[RSC - Digital Discovery latest articles] Leveraging large language models for enzymatic reaction prediction and characterization

RSC - Digital Discovery latest articles — Thu, 30 Oct 2025 00:00:00 GMT

Digital Discovery, 2025, 4,3588-3609
DOI: 10.1039/D5DD00187K, Paper

Open Access

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence.

[RSC - Digital Discovery latest articles] Cross-laboratory validation of machine learning models for copper nanocluster synthesis using cloud-based automated platforms

RSC - Digital Discovery latest articles — Thu, 30 Oct 2025 00:00:00 GMT

Digital Discovery, 2025, 4,3683-3692
DOI: 10.1039/D5DD00335K, Paper

Open Access

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence.

[Wiley: InfoMat: Table of Contents] Delicate design of lithium‐ion bridges in hybrid solid electrolyte for wide‐temperature adaptive solid‐state lithium metal batteries

Wiley: InfoMat: Table of Contents — Wed, 29 Oct 2025 00:36:10 GMT

InfoMat, EarlyView.

[APL Machine Learning Current Issue] Building an affordable self-driving lab: Practical machine learning experiments for physics education using Internet-of-Things

APL Machine Learning Current Issue — Wed, 29 Oct 2025 00:00:00 GMT

[APL Machine Learning Current Issue] Data integration and data fusion approaches in self-driving labs: A perspective

APL Machine Learning Current Issue — Wed, 29 Oct 2025 00:00:00 GMT

[RSC - Digital Discovery latest articles] Machine learning anomaly detection of automated HPLC experiments in the cloud laboratory

RSC - Digital Discovery latest articles — Wed, 29 Oct 2025 00:00:00 GMT

Digital Discovery, 2025, 4,3445-3454
DOI: 10.1039/D5DD00253B, Paper

Open Access

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence.

[Applied Physics Reviews Current Issue] Strain engineering of van Hove singularity and coupled itinerant ferromagnetism in quasi-2D oxide superlattices

Applied Physics Reviews Current Issue — Tue, 28 Oct 2025 00:00:00 GMT

[Wiley: Advanced Intelligent Discovery: Table of Contents] Machine Learning‐Enhanced Random Matrix Theory Design for Human Immunodeficiency Virus Vaccine Development

Wiley: Advanced Intelligent Discovery: Table of Contents — Mon, 27 Oct 2025 03:21:44 GMT

Advanced Intelligent Discovery, EarlyView.

[RSC - Digital Discovery latest articles] An improved machine learning strategy using structural features to predict the glass transition temperature of oxide glasses

RSC - Digital Discovery latest articles — Thu, 23 Oct 2025 23:00:00 GMT

Digital Discovery, 2025, 4,3764-3773
DOI: 10.1039/D5DD00326A, Paper

Open Access

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence.

[Applied Physics Reviews Current Issue] 3D-printed lithium-metal batteries: Multiscale architectures, hybrid technologies, and monolithic integration for next-generation energy storage

Applied Physics Reviews Current Issue — Thu, 23 Oct 2025 00:00:00 GMT

[Wiley: Advanced Intelligent Discovery: Table of Contents] Harnessing Large Language Models to Advance Microbiome Research: From Sequence Analysis to Clinical Applications

Wiley: Advanced Intelligent Discovery: Table of Contents — Tue, 21 Oct 2025 05:48:44 GMT

Advanced Intelligent Discovery, EarlyView.

[RSC - Digital Discovery latest articles] GoFlow: efficient transition state geometry prediction with flow matching and E(3)-equivariant neural networks

RSC - Digital Discovery latest articles — Mon, 20 Oct 2025 23:00:00 GMT

Digital Discovery, 2025, 4,3492-3501
DOI: 10.1039/D5DD00283D, Paper

Open Access

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence.

[AI for Science - latest papers] AInstein: numerical Einstein metrics via machine learning

AI for Science - latest papers — Thu, 16 Oct 2025 23:00:00 GMT

[Matter] SpectroGen: A physically informed generative artificial intelligence for accelerated cross-modality spectroscopic materials characterization

Matter — Tue, 14 Oct 2025 00:00:00 GMT

[Chem] Precisely modulating Li2CO3 coverage on Ni-rich cathode boosts sulfide solid-state lithium battery performance

Chem — Tue, 14 Oct 2025 00:00:00 GMT

[RSC - Digital Discovery latest articles] Do Llamas understand the periodic table?

RSC - Digital Discovery latest articles — Mon, 13 Oct 2025 23:00:00 GMT

Digital Discovery, 2025, 4,3455-3465
DOI: 10.1039/D5DD00374A, Paper

Open Access

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence.

[Applied Physics Reviews Current Issue] Carbon-based memristors for neuromorphic computing

Applied Physics Reviews Current Issue — Mon, 13 Oct 2025 00:00:00 GMT

[Matter] Dynamic pressure mapping of infant cervical spines using a wearable magnetoelastic patch

Matter — Fri, 10 Oct 2025 00:00:00 GMT

[Matter] Machine learning-driven ligand engineering decodes and controls structural distortions in 2D perovskites

Matter — Fri, 10 Oct 2025 00:00:00 GMT

[Applied Physics Reviews Current Issue] The enduring legacy of scanning spreading resistance microscopy: Overview, advancements, and future directions

Applied Physics Reviews Current Issue — Wed, 08 Oct 2025 00:00:00 GMT

[Chinese Chemical Society: CCS Chemistry: Table of Contents] Oxygen Vacancy-Modulated Molybdenum Oxide/Montmorillonite Heterointerface Nanoarchitectures for Plasmon-Enhanced Solar-Osmotic Energy Harvesting

Chinese Chemical Society: CCS Chemistry: Table of Contents — Mon, 06 Oct 2025 03:22:16 GMT

CCS Chemistry, Ahead of Print.

DOI:10.31635/ccschem.025.202506132

[RSC - Digital Discovery latest articles] Constructing and explaining machine learning models for the exploration and design of boron-based Lewis acids

RSC - Digital Discovery latest articles — Sun, 05 Oct 2025 23:00:00 GMT

Digital Discovery, 2025, 4,3623-3634
DOI: 10.1039/D5DD00212E, Paper

Open Access

This article is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported Licence.

[APL Machine Learning Current Issue] Deep learning model of myofilament cooperative activation and cross-bridge cycling in cardiac muscle

APL Machine Learning Current Issue — Fri, 03 Oct 2025 00:00:00 GMT

[RSC - Digital Discovery latest articles] ReactPyR: a python workflow for ReactIR allows for quantification of the stability of sensitive compounds in air

RSC - Digital Discovery latest articles — Thu, 02 Oct 2025 23:00:00 GMT

Digital Discovery, 2025, 4,3533-3539
DOI: 10.1039/D5DD00305A, Paper

Open Access

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence.

[Applied Physics Reviews Current Issue] Extracellular vesicles as the drug delivery vehicle for gene-based therapy

Applied Physics Reviews Current Issue — Wed, 01 Oct 2025 00:00:00 GMT

[Wiley: Advanced Intelligent Discovery: Table of Contents] Discovery of Novel Materials with Giant Dielectric Constants via First‐Principles Phonon Calculations and Machine Learning

Wiley: Advanced Intelligent Discovery: Table of Contents — Tue, 30 Sep 2025 06:30:24 GMT

Advanced Intelligent Discovery, EarlyView.

[AI for Science - latest papers] FastTrack: a fast method to evaluate mass transport in solid leveraging universal machine learning interatomic potential

AI for Science - latest papers — Mon, 29 Sep 2025 23:00:00 GMT

[Wiley: Advanced Intelligent Discovery: Table of Contents] Artificial Intelligence‐Driven Insights into Electrospinning: Machine Learning Models to Predict Cotton‐Wool‐Like Structure of Electrospun Fibers

Wiley: Advanced Intelligent Discovery: Table of Contents — Wed, 24 Sep 2025 13:21:08 GMT

Advanced Intelligent Discovery, EarlyView.

[AI for Science - latest papers] 4D-MISR: a unified model for low-dose super-resolution imaging via feature fusion

AI for Science - latest papers — Wed, 17 Sep 2025 23:00:00 GMT

[Recent Articles in PRX Energy] Thermodynamic Modeling of Complex Solid Solutions in the $\mathrm{Lu}$-$\mathrm{H}$-$\mathrm{N}$ System via Graph Neural Network Accelerated Monte Carlo Simulations

Recent Articles in PRX Energy — Tue, 02 Sep 2025 10:00:00 GMT

Author(s): Pin-Wen Guan, Catalin D. Spataru, Vitalie Stavila, Reese Jones, Peter A. Sharma, and Matthew D. Witman

[PRX Energy 4, 033013] Published Tue Sep 02, 2025

[Recent Articles in PRX Energy] Reconstructions and Dynamics of $β$-Lithium Thiophosphate Surfaces

Recent Articles in PRX Energy — Tue, 26 Aug 2025 10:00:00 GMT

Author(s): Hanna Türk, Davide Tisi, and Michele Ceriotti

Machine-learning-based molecular dynamics simulations of the solid electrolyte $β$ -Li $_{3}$ PS $_{4}$ under realistic conditions reveal dynamic surface structure and reactivity.

[PRX Energy 4, 033010] Published Tue Aug 26, 2025

[Wiley: Advanced Intelligent Discovery: Table of Contents] Application of Neural Networks for Advanced Ir Spectroscopy Characterization of Ceria Catalysts Surfaces

Wiley: Advanced Intelligent Discovery: Table of Contents — Mon, 25 Aug 2025 07:01:05 GMT

Advanced Intelligent Discovery, EarlyView.

[Chem] Photocatalytic hydrogenation of alkenes using ammonia-borane

Chem — Mon, 25 Aug 2025 00:00:00 GMT

[Chem] Stereoselective C(sp3)-Si/Ge bond formation via nickel-catalyzed decarboxylative couplings

Chem — Thu, 21 Aug 2025 00:00:00 GMT

[Matter] CGformer: Transformer-enhanced crystal graph network with global attention for material property prediction

Matter — Wed, 20 Aug 2025 00:00:00 GMT

[Chem] Organosilicon precursors for efficient aromatic copper-mediated radiocyanation

Chem — Wed, 20 Aug 2025 00:00:00 GMT

[Chem] Manganese low-energy photocatalysis for remodeling nitrogenation of alkenes

Chem — Tue, 19 Aug 2025 00:00:00 GMT

[Recent Articles in PRX Energy] Large-Scale Simulation Unveiled Superior Potassium-Based Solid Electrolyte with High Ionic Conductivity and Excellent Electrochemical Stability in ${M}_{5}{\mathrm{YSi}}_{4}{\mathrm{O}}_{12}$ ($M=\mathrm{Li},\mathrm{K}$)

Recent Articles in PRX Energy — Thu, 14 Aug 2025 10:00:00 GMT

Author(s): Zhao Li, Jiaxiang Li, Congwei Xie, Keith Butler, Fei Du, and Yu Xie

[PRX Energy 4, 033007] Published Thu Aug 14, 2025

[Wiley: Advanced Intelligent Discovery: Table of Contents] Interpretable Machine Learning for Solvent‐Dependent Carrier Mobility in Solution‐Processed Organic Thin Films

Wiley: Advanced Intelligent Discovery: Table of Contents — Fri, 08 Aug 2025 09:54:45 GMT

Advanced Intelligent Discovery, EarlyView.

[Wiley: Advanced Intelligent Discovery: Table of Contents] Macrophage Phenotype Detection Methodology on Textured Surfaces via Nuclear Morphology Using Machine Learning

Wiley: Advanced Intelligent Discovery: Table of Contents — Fri, 01 Aug 2025 08:40:28 GMT

Advanced Intelligent Discovery, EarlyView.

[Wiley: Advanced Intelligent Discovery: Table of Contents] CrossMatAgent: AI‐Assisted Design of Manufacturable Metamaterial Patterns via Multi‐Agent Generative Framework

Wiley: Advanced Intelligent Discovery: Table of Contents — Fri, 25 Jul 2025 08:24:33 GMT

Advanced Intelligent Discovery, EarlyView.

[Wiley: Advanced Intelligent Discovery: Table of Contents] Topology‐Aware Machine Learning for High‐Throughput Screening of MOFs in C8 Aromatic Separation

Wiley: Advanced Intelligent Discovery: Table of Contents — Thu, 24 Jul 2025 10:45:19 GMT

Advanced Intelligent Discovery, EarlyView.

[Recent Articles in PRX Energy] Origin of Intrinsically Low Thermal Conductivity in a Garnet-Type Solid Electrolyte: Linking Lattice and Ionic Dynamics with Thermal Transport

Recent Articles in PRX Energy — Thu, 17 Jul 2025 10:00:00 GMT

[PRX Energy 4, 033004] Published Thu Jul 17, 2025

[Recent Articles in PRX Energy] A Comparative Study of Solid Electrolyte Interphase Evolution in Ether and Ester-Based Electrolytes for $\mathrm{Na}$-ion Batteries

Recent Articles in PRX Energy — Tue, 15 Jul 2025 10:00:00 GMT

Author(s): Liang Zhao, Sara I.R. Costa, Yue Chen, Jack R. Fitzpatrick, Andrew J. Naylor, Oleg Kolosov, and Nuria Tapia-Ruiz

[PRX Energy 4, 033002] Published Tue Jul 15, 2025

[Chinese Chemical Society: CCS Chemistry: Table of Contents] Metalloligand Enabling Cobalt-Catalyzed anti-Markovnikov Hydrosilylation of Alkynes with Tertiary Silanes

Chinese Chemical Society: CCS Chemistry: Table of Contents — Tue, 15 Jul 2025 04:05:27 GMT

CCS Chemistry, Ahead of Print.

DOI:10.31635/ccschem.025.202505983

[Wiley: Advanced Intelligent Discovery: Table of Contents] Deep Learning Prediction of Surface Roughness in Multi‐Stage Microneedle Fabrication: A Long Short‐Term Memory‐Recurrent Neural Network Approach

Wiley: Advanced Intelligent Discovery: Table of Contents — Mon, 14 Jul 2025 15:08:07 GMT

Advanced Intelligent Discovery, EarlyView.

[Chinese Chemical Society: CCS Chemistry: Table of Contents] Inorganic Iodide Catalyzed Alkylation of Amines with Primary Alcohols

Chinese Chemical Society: CCS Chemistry: Table of Contents — Fri, 11 Jul 2025 03:57:49 GMT

CCS Chemistry, Ahead of Print.

DOI:10.31635/ccschem.025.202505864

[Wiley: Advanced Intelligent Discovery: Table of Contents] Autonomous Machine Learning‐Based Classification and Arrangement of Submillimeter Objects Using a Capillary Force Gripper

Wiley: Advanced Intelligent Discovery: Table of Contents — Wed, 09 Jul 2025 08:01:30 GMT

Advanced Intelligent Discovery, EarlyView.

[Wiley: Advanced Intelligent Discovery: Table of Contents] Universally Accurate or Specifically Inadequate? Stress‐Testing General Purpose Machine Learning Interatomic Potentials

Wiley: Advanced Intelligent Discovery: Table of Contents — Wed, 09 Jul 2025 07:56:18 GMT

Advanced Intelligent Discovery, EarlyView.

[Wiley: Advanced Intelligent Discovery: Table of Contents] A Machine Learning Model for Interpretable PECVD Deposition Rate Prediction

Wiley: Advanced Intelligent Discovery: Table of Contents — Fri, 27 Jun 2025 08:27:19 GMT

Advanced Intelligent Discovery, EarlyView.

[Wiley: Advanced Intelligent Discovery: Table of Contents] Feature Selection for Machine Learning‐Driven Accelerated Discovery and Optimization in Emerging Photovoltaics: A Review

Wiley: Advanced Intelligent Discovery: Table of Contents — Fri, 27 Jun 2025 08:15:35 GMT

Advanced Intelligent Discovery, EarlyView.

[ACS Materials Au: Latest Articles (ACS Publications)] [ASAP] Historical Data Mining Deep Dive into Machine Learning-Aided 2D Materials Research in Electrochemical Applications

ACS Materials Au: Latest Articles (ACS Publications) — Mon, 23 Jun 2025 15:22:16 GMT

ACS Materials Au

DOI: 10.1021/acsmaterialsau.5c00030

[Wiley: Advanced Intelligent Discovery: Table of Contents] Machine Learning‐Assisted Infectious Disease Detection in Low‐Income Areas: Toward Rapid Triage of Dengue and Zika Virus Using Open‐Source Hardware

Wiley: Advanced Intelligent Discovery: Table of Contents — Mon, 23 Jun 2025 08:20:28 GMT

Advanced Intelligent Discovery, EarlyView.

[Wiley: Advanced Intelligent Discovery: Table of Contents] What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Wiley: Advanced Intelligent Discovery: Table of Contents — Fri, 20 Jun 2025 08:36:19 GMT

Advanced Intelligent Discovery, EarlyView.

[Wiley: Advanced Intelligent Discovery: Table of Contents] Predicting High‐Resolution Spatial and Spectral Features in Mass Spectrometry Imaging with Machine Learning and Multimodal Data Fusion

Wiley: Advanced Intelligent Discovery: Table of Contents — Wed, 18 Jun 2025 08:10:58 GMT

Advanced Intelligent Discovery, EarlyView.

[Wiley: Advanced Intelligent Discovery: Table of Contents] A Machine Learning Perspective on the Brønsted–Evans–Polanyi Relation in Water‐Gas Shift Catalysis on MXenes

Wiley: Advanced Intelligent Discovery: Table of Contents — Wed, 18 Jun 2025 08:09:26 GMT

Advanced Intelligent Discovery, EarlyView.

[Chinese Chemical Society: CCS Chemistry: Table of Contents] Efficient Pure Organic Near-Infrared Room-Temperature Phosphorescence Based on n/π Orbital Decoupling

Chinese Chemical Society: CCS Chemistry: Table of Contents — Sat, 14 Jun 2025 05:08:51 GMT

CCS Chemistry, Ahead of Print.

DOI:10.31635/ccschem.025.202405319

[Chinese Chemical Society: CCS Chemistry: Table of Contents] Identification of Cu-N2 Sites for Zn-Air Batteries in Harsh Electrolytes: Computer Virtual Screening, Machine Learning, and Practical Application

Chinese Chemical Society: CCS Chemistry: Table of Contents — Sat, 14 Jun 2025 04:39:17 GMT

CCS Chemistry, Ahead of Print.

DOI:10.31635/ccschem.025.202505577

[Recent Articles in PRX Energy] Correlating Local Morphology and Charge Dynamics via Kelvin Probe Force Microscopy to Explain Photoelectrode Performance

Recent Articles in PRX Energy — Mon, 09 Jun 2025 10:00:00 GMT

Author(s): Maryam Pourmahdavi, Mauricio Schieda, Ragle Raudsepp, Steffen Fengler, Jiri Kollmann, Yvonne Pieper, Thomas Dittrich, Thomas Klassen, and Francesca M. Toma

[PRX Energy 4, 023010] Published Mon Jun 09, 2025

[Chinese Chemical Society: CCS Chemistry: Table of Contents] Radical Amidoalkynylation of Electron-Rich Alkenes with Bifunctional Alkynylsulfonamide Reagents

Chinese Chemical Society: CCS Chemistry: Table of Contents — Mon, 09 Jun 2025 02:05:34 GMT

CCS Chemistry, Ahead of Print.

DOI:10.31635/ccschem.025.202505686

[Chinese Chemical Society: CCS Chemistry: Table of Contents] Development of Nanomolar Affinity Miniprotein Inhibitors Targeting α-Synuclein Aggregation as Promising Therapeutic Agents for Parkinson’s Disease

Chinese Chemical Society: CCS Chemistry: Table of Contents — Tue, 03 Jun 2025 05:02:30 GMT

CCS Chemistry, Ahead of Print.

DOI:10.31635/ccschem.025.202505587

[Chinese Chemical Society: CCS Chemistry: Table of Contents] Harnessing Photoredox Cascade to Enhance Photodynamic Oncotherapy by Nanoformulated Macrocyclic Photosensitizer

Chinese Chemical Society: CCS Chemistry: Table of Contents — Tue, 03 Jun 2025 04:56:28 GMT

CCS Chemistry, Ahead of Print.

DOI:10.31635/ccschem.025.202505567

[Chinese Chemical Society: CCS Chemistry: Table of Contents] Minimal Sulfur-Grafted Graphite Anode with Accelerated Interfacial Kinetics for Fast-Charging Lithium-Ion Batteries

Chinese Chemical Society: CCS Chemistry: Table of Contents — Wed, 28 May 2025 08:32:07 GMT

CCS Chemistry, Ahead of Print.

DOI:10.31635/ccschem.025.202505705

[Chinese Chemical Society: CCS Chemistry: Table of Contents] Enantioconvergent Negishi Cross-Coupling of Racemic sec-Alkylzinc Reagent with Aryl Halides Enabled by Bulky N-Heterocyclic Carbene-Pd Catalyst

Chinese Chemical Society: CCS Chemistry: Table of Contents — Mon, 19 May 2025 04:21:11 GMT

CCS Chemistry, Ahead of Print.

DOI:10.31635/ccschem.025.202505591

[Recent Articles in PRX Energy] Resolving the Solvation Structure and Transport Properties of Aqueous Zinc Electrolytes from Salt-in-Water to Water-in-Salt Using Neural Network Potential

Recent Articles in PRX Energy — Fri, 11 Apr 2025 10:00:00 GMT

[PRX Energy 4, 023004] Published Fri Apr 11, 2025

[Recent Articles in PRX Energy] Crystal Structure Prediction and Phase Stability in Highly Anharmonic Silver-Based Chalcohalide Antiperovskites

Recent Articles in PRX Energy — Thu, 03 Apr 2025 10:00:00 GMT

Author(s): Pol Benítez, Cibrán López, Cong Liu, Ivan Caño, Josep-Lluís Tamarit, Edgardo Saucedo, and Claudio Cazorla

[PRX Energy 4, 023002] Published Thu Apr 03, 2025

[Recent Articles in PRX Energy] Unraveling Temperature-Induced Vacancy Clustering in Tungsten: From Direct Microscopy to Atomistic Insights via Data-Driven Bayesian Sampling

Recent Articles in PRX Energy — Tue, 25 Feb 2025 10:00:00 GMT

Author(s): Anruo Zhong, Clovis Lapointe, Alexandra M. Goryaeva, Kazuto Arakawa, Manuel Athènes, and Mihai-Cosmin Marinica

[PRX Energy 4, 013008] Published Tue Feb 25, 2025

[Recent Articles in PRX Energy] Constant-Current Nonequilibrium Molecular Dynamics Approach for Accelerated Computation of Ionic Conductivity Including Ion-Ion Correlation

Recent Articles in PRX Energy — Wed, 19 Feb 2025 10:00:00 GMT

Author(s): Ryoma Sasaki, Yoshitaka Tateyama, and Debra J. Searles

[PRX Energy 4, 013005] Published Wed Feb 19, 2025

[Recent Articles in PRX Energy] Detecting Attacks and Estimating States of Power Grids from Partial Observations with Machine Learning

Recent Articles in PRX Energy — Tue, 04 Feb 2025 10:00:00 GMT

Author(s): Zheng-Meng Zhai, Mohammadamin Moradi, and Ying-Cheng Lai

[PRX Energy 4, 013003] Published Tue Feb 04, 2025

[Recent Articles in PRX Energy] 3D Reconstruction of a Nuclear Reactor by Muon Tomography: Structure Validation and Anomaly Detection

Recent Articles in PRX Energy — Tue, 28 Jan 2025 10:00:00 GMT

Author(s): Baptiste Lefevre, Julien Vogel, Héctor Gomez, David Attié, Laurent Gallego, Philippe Gonzales, Bertrand Lesage, Philippe Mas, and Daniel Pomarède

[PRX Energy 4, 013002] Published Tue Jan 28, 2025

[Recent Articles in PRX Energy] Determining Parameters of Metal-Halide Perovskites Using Photoluminescence with Bayesian Inference

Recent Articles in PRX Energy — Tue, 14 Jan 2025 10:00:00 GMT

Author(s): Manuel Kober-Czerny, Akash Dasgupta, Seongrok Seo, Florine M. Rombach, David P. McMeekin, Heon Jin, and Henry J. Snaith

Experiment and machine learning are combined to extract key material parameters and insight into charge carrier transport in metal halide perovskites for solar cell applications.

[PRX Energy 4, 013001] Published Tue Jan 14, 2025

[Recent Articles in PRX Energy] Learning Molecular Mixture Property Using Chemistry-Aware Graph Neural Network

Recent Articles in PRX Energy — Wed, 12 Jun 2024 10:00:00 GMT

Author(s): Hengrui Zhang (张恒睿), Tianxing Lai (来天行), Jie Chen, Arumugam Manthiram, James M. Rondinelli, and Wei Chen

[PRX Energy 3, 023006] Published Wed Jun 12, 2024

[Recent Articles in PRX Energy] Temperature Impact on Lithium Metal Morphology in Lithium Reservoir-Free Solid-State Batteries

Recent Articles in PRX Energy — Fri, 17 May 2024 10:00:00 GMT

Author(s): Min-Gi Jeong, Kelsey B. Hatzell, Sourim Banerjee, Bairav S. Vishnugopi, and Partha P. Mukherjee

[PRX Energy 3, 023003] Published Fri May 17, 2024

[Recent Articles in Rev. Mod. Phys.] Colloquium: Advances in automation of quantum dot devices control

Recent Articles in Rev. Mod. Phys. — Fri, 17 Feb 2023 10:00:00 GMT

Author(s): Justyna P. Zwolak and Jacob M. Taylor

[Rev. Mod. Phys. 95, 011006] Published Fri Feb 17, 2023

[PRB: Dynamics, dynamical systems, lattice effects, quantum solids] Hydrogen as promoter and inhibitor of superionicity: A case study on Li-N-H systems

PRB: Dynamics, dynamical systems, lattice effects, quantum solids — Mon, 26 Jul 2010 10:00:00 GMT

Author(s): Andreas Blomqvist, C. Moysés Araújo, Ralph H. Scheicher, Pornjuk Srepusharawoot, Wen Li, Ping Chen, and Rajeev Ahuja

[Phys. Rev. B 82, 024304] Published Mon Jul 26, 2010

[PRB: Dynamics, dynamical systems, lattice effects, quantum solids] Nonadiabatic effects of rattling phonons and $4f$ excitations in $\text{Pr}{({\text{Os}}_{1−x}{\text{Ru}}_{x})}_{4}{\text{Sb}}_{12}$

PRB: Dynamics, dynamical systems, lattice effects, quantum solids — Fri, 18 Jun 2010 10:00:00 GMT

Author(s): Peter Thalmeier

[Phys. Rev. B 81, 224305] Published Fri Jun 18, 2010

[PRB: Dynamics, dynamical systems, lattice effects, quantum solids] Ionic conductivity of nanocrystalline yttria-stabilized zirconia: Grain boundary and size effects

PRB: Dynamics, dynamical systems, lattice effects, quantum solids — Mon, 10 May 2010 10:00:00 GMT

Author(s): O. J. Durá, M. A. López de la Torre, L. Vázquez, J. Chaboy, R. Boada, A. Rivera-Calzada, J. Santamaria, and C. Leon

[Phys. Rev. B 81, 184301] Published Mon May 10, 2010

[PRB: Dynamics, dynamical systems, lattice effects, quantum solids] Calculating the anharmonic free energy from first principles

PRB: Dynamics, dynamical systems, lattice effects, quantum solids — Fri, 07 May 2010 10:00:00 GMT

Author(s): Zhongqing Wu

[Phys. Rev. B 81, 172301] Published Fri May 07, 2010

[PRB: Dynamics, dynamical systems, lattice effects, quantum solids] Phason dynamics in one-dimensional lattices

PRB: Dynamics, dynamical systems, lattice effects, quantum solids — Thu, 25 Feb 2010 10:00:00 GMT

Author(s): Hansjörg Lipp, Michael Engel, Steffen Sonntag, and Hans-Rainer Trebin

[Phys. Rev. B 81, 064302] Published Thu Feb 25, 2010

[PRB: Dynamics, dynamical systems, lattice effects, quantum solids] Ab initio construction of interatomic potentials for uranium dioxide across all interatomic distances

PRB: Dynamics, dynamical systems, lattice effects, quantum solids — Wed, 25 Nov 2009 10:00:00 GMT

Author(s): P. Tiwary, A. van de Walle, and N. Grønbech-Jensen

[Phys. Rev. B 80, 174302] Published Wed Nov 25, 2009

[PRB: Dynamics, dynamical systems, lattice effects, quantum solids] One-dimensional nanostructure-guided chain reactions: Harmonic and anharmonic interactions

PRB: Dynamics, dynamical systems, lattice effects, quantum solids — Fri, 13 Nov 2009 10:00:00 GMT

Author(s): Nitish Nair and Michael S. Strano

[Phys. Rev. B 80, 174301] Published Fri Nov 13, 2009

My Customized Papers (Auto-Filtered)

[ScienceDirect Publication: Acta Materialia] Inverse Design of High-Performance Glasses Through an Encoder-Decoder Machine Learning Approach Toward Materials Discovery: Application to Oxynitride Glasses

[ScienceDirect Publication: Journal of Energy Storage] Machine learning-aided prediction and optimization of specific capacitance in functionalized GO-based Mn/Fe co-doped Bi2O3 nanocomposites

[ScienceDirect Publication: Journal of Energy Storage] Time-resolved impedance spectroscopy analysis of stable lithium iron phosphate cathode with enhanced electronic/ionic conductivity and ion diffusion characteristics

[cond-mat updates on arXiv.org] Thermodynamic Phase Stability, Structural, Mechanical, Optoelectronic, and Thermoelectric Properties of the III-V Semiconductor AlSb for Energy Conversion Applications

[ScienceDirect Publication: Journal of Energy Storage] Machine learning-aided prediction and optimization of specific capacitance in functionalized GO-based Mn/Fe co-doped Bi2O3 nanocomposites

[ScienceDirect Publication: Journal of Energy Storage] Time-resolved impedance spectroscopy analysis of stable lithium iron phosphate cathode with enhanced electronic/ionic conductivity and ion diffusion characteristics

[cond-mat updates on arXiv.org] Thermodynamic Phase Stability, Structural, Mechanical, Optoelectronic, and Thermoelectric Properties of the III-V Semiconductor AlSb for Energy Conversion Applications

[cond-mat updates on arXiv.org] The Role of THz Phonons in the Ionic Conduction Mechanism of $Li_7La_3Zr_2O_{12}$ Polymorphs

[cond-mat updates on arXiv.org] Thermally Activated Non-Affine Rearrangements in Amorphous Glass: Emergence of Intrinsic Length Scales

[cond-mat updates on arXiv.org] Fast and accurate Fe-H machine-learning interatomic potential for elucidating hydrogen embrittlement mechanisms

[cond-mat updates on arXiv.org] Enhanced sinterability and in vitro bioactivity of diopside through fluoride doping

[cond-mat updates on arXiv.org] Bridging the divide: Economic exchange and segregation in dual-income cities

[cond-mat updates on arXiv.org] Information Supercurrents in Chiral Active Matter

[Communications Materials] In situ polymerization for high performance solid-state lithium-sulfur batteries

[ChemRxiv] Molecular Dynamics Simulations for Organic Chemists – It’s About Time!

[ChemRxiv] Characterisation and immobilisation study of the Haloperoxidase from Curvularia inaequalis: application to phenol derivatives

[Nature Nanotechnology] Nanostructured niobium-doped nickel-rich multiphase positive electrode active material for high-power lithium-based batteries

[ChemRxiv] Study of anion transport by amide-based macrocycles of different sizes

[ChemRxiv] Ion-Conductive Vitrimers Based on Backbone-Type Triazolium Poly(ionic liquid)s: Counterion-Dependent Dynamics and Backbone Flexibility

[ChemRxiv] Advances in Calcium Isotope Purification and Analysis Using Cutting-Edge Signal Amplifiers for Matrix-Diverse Reference Materials

[ChemRxiv] Predicting Sequence Dependent Fluorescence with Classic Machine Learning Models

[ChemRxiv] Machine learning driven advances in molecular dynamics of bulk and interfacial aqueous systems

[RSC - Chem. Sci. latest articles] Automated Closed-Loop Continuous Flow Block Copolymer Synthesizer

[RSC - Chem. Sci. latest articles] Node-Equivariant Message Passing for Efficient and Accurate Machine Learning Interatomic Potentials

[RSC - Chem. Sci. latest articles] Robust Janus-Faced Quasi-Solid-State Electrolytes Mimicking Honeycomb for Fast Transport and Adequate Supply of Sodium Ions

[Joule] Machine learning-driven interface material design for high-performance perovskite solar cells with scalability and band-gap universality

[Cell Reports Physical Science] A global thermodynamic-kinetic model capturing the hallmarks of liquid-liquid phase separation and amyloid aggregation

[ChemRxiv] Maximizing Machine Learning Interatomic Potential Transferability for the Discovery of the Novel Stellated Octadecagon Bi18-Pt24 Cage Structure

[ChemRxiv] High-Performance Semiempirical Excited-State Molecular Dynamics: A Step Toward Data-Driven Photodynamics

[Applied Physics Letters Current Issue] Mixed ionic–electronic conductor based on B 16 framework

[iScience] A Multicenter Multimodel Habitat Radiomics Model for Predicting Immunotherapy Response in Advanced NSCLC

[ACS Nano: Latest Articles (ACS Publications)] [ASAP] Regulating Solvation Structure and Ion Transport via Lewis-Base Dual-Functional Covalent Organic Polymer Separators for Dendrite-Free Li-Metal Anodes

[ACS Nano: Latest Articles (ACS Publications)] [ASAP] Highly Selective Lithium-Ion Separation by Regulating Ion Transport Energy Barriers of Vermiculite Membranes

[Wiley: Advanced Intelligent Discovery: Table of Contents] A Physics Constrained Machine Learning Pipeline for Young's Modulus Prediction in Multimaterial Hyperelastic Cylinders Guided by Contact Mechanics

[ACS Nano: Latest Articles (ACS Publications)] [ASAP] Multianion Synergism Boosts High-Performance All-Solid-State Lithium Batteries

[Wiley: Advanced Functional Materials: Table of Contents] Sulfur‐Doped Bi2O3 Nanorods with Asymmetric S−Bi−O Active Sites for Highly Efficient Electrosynthesis of Formic Acid

[The Journal of Physical Chemistry C: Latest Articles (ACS Publications)] [ASAP] Density Effects on the Thermal Decomposition of LLM-105 Explored by Neural Network Potential

[Accounts of Chemical Research: Latest Articles (ACS Publications)] [ASAP] Accelerating Materials Discovery Through Sparse Gaussian Process Machine Learning Potentials

[Wiley: Small: Table of Contents] Revealing Electronic Structure–Chemisorption Relationships for Accelerated Discovery of Aqueous Zinc Battery Additives Through Machine Learning

[Wiley: Small: Table of Contents] Ultra‐High Capacity Density Lithium Metal Battery is Effectuated via Coupling Single Lithium‐Ion Conductor and Lithium‐Ion Sieve Within Yttrium‐Organic Framework

[Wiley: Small: Table of Contents] Boosting Gaseous Mercury Detection via Photooxidation‐Enrichment Fluorescent Membrane with Machine Learning

[Recent Articles in Phys. Rev. Lett.] Gate-Tunable Spectrum and Charge Dispersion Mitigation in a Graphene Superconducting Qubit

[Proceedings of the National Academy of Sciences: Physical Sciences] SR-LLM: An incremental symbolic regression framework driven by LLM-based retrieval-augmented generation

[Wiley: Angewandte Chemie International Edition: Table of Contents] Potential‐Tailored Aryl–Sodium Reagent with Moderate Ionic Binding Strength Enables Precise yet Fast Hard Carbon Presodiation

[npj Computational Materials] Machine learning interatomic potential can infer electrical response

[Applied Physics Letters Open Issues] High-throughput sensing of single-cell properties using parallel multi-stage cell deformation

[Applied Physics Letters Open Issues] Coherent phonon tunneling-driven ultralow and non-monotonic thermal conductivity in quasi-0D Cs 3 Cu 2 I 5

[Applied Physics Letters Open Issues] Machine learning-assisted performance prediction of ZnMSnO-based thin-film transistors

[Applied Physics Reviews Current Issue] Thermal conductivity limits of MoS 2 and MoSe 2 : Revisiting high-order anharmonic lattice dynamics with machine learning potentials

[ChemRxiv] Missense mutations in cancer: in silico predictions, developing treatments, and overcoming cell resistance.

[ChemRxiv] Domain Oriented Universal Machine Learning Potential Enables Fast Exploration of Chemical Space of Battery Electrolytes

[ChemRxiv] Large-scale structure- and sequence-based comparative analysis enables functional annotation of animal venom peptides

[ChemRxiv] Performance of dispersion models in predicting ambient hydrocarbon concentrations at a regional air quality monitor in an oil and gas producing region

[ChemRxiv] Machine Learning-Guided Scope Selection to Balance Performance and Substrate Similarity

[ChemRxiv] Relationship Between Local Disorder and Atomic Motion in an Antiperovskite Solid Electrolyte

[ChemRxiv] Multi-Objective Catalyst Discovery in High-Entropy Alloy Composition Space: The Role of Noble Metals on the Pareto Front for Oxygen Reduction Reaction

[ChemRxiv] Agent-based framework for modeling hyperlocal urban air quality

[iScience] Widely Targeted Metabolomics and Machine Learning Identify Succinate as a Key Metabolite in Sepsis-Associated Encephalopathy

[ACS Nano: Latest Articles (ACS Publications)] [ASAP] Feature-Selective Preprocessing with Electrically Robust Boron Nitride-Based Dynamic Memristors for Reliable Lightweight Neural Networks

[Journal of the American Chemical Society: Latest Articles (ACS Publications)] [ASAP] Interpreting X-ray Diffraction Patterns of Metal–Organic Frameworks via Generative Artificial Intelligence

[npj Computational Materials] Free-energy perturbation in the exchange-correlation space accelerated by machine learning: application to silica polymorphs

[Journal of the American Chemical Society: Latest Articles (ACS Publications)] [ASAP] A Transformative Molecular Muscle Solid Electrolyte

[Wiley: Small Structures: Table of Contents] Li6−xFe1−xAlxCl8 Solid Electrolytes for Cost‐Effective All‐Solid‐State LiFePO4 Batteries

[Wiley: Small: Table of Contents] Unravelling Electronic Structure and Molecular Vibrations of Proteins in Virus Using Novel Correlated Plasmon‐Enhanced Raman Spectroscopy With Machine Learning

[Recent Articles in Phys. Rev. B] Vision transformer neural quantum states for impurity models

[Recent Articles in Phys. Rev. B] Renormalized quantum anharmonicity enhanced electron-phonon coupling in the ambient-pressure compound $\mathrm{Rb}{\mathrm{H}}_{6}$

[Wiley: Angewandte Chemie International Edition: Table of Contents] Dual‐Function Antibacterial and Antibiofilm Agent Based on a Confinement‐Activated Fluorescent System in Water

[Wiley: Advanced Science: Table of Contents] Quantifying Additive Manufacturing Vapor Plumes Using Laser‐Induced Breakdown Spectroscopy, Synchrotron X‐Ray Radiography and Simulations

[npj Computational Materials] Publisher Correction: Machine learning potentials for alloys: a detailed workflow to predict phase diagrams and benchmark accuracy

[npj Computational Materials] Alloy design integrating natural language processing and machine learning: breakthrough development of low-cost, high-performance Ni-based single-crystal superalloys

[Joule] Boosting ionic conductivity of fluoride electrolytes by polyanion coordination chemistry enabling 5 V-Class all-solid-state batteries

[RSC - Digital Discovery latest articles] Adsorb-Agent: Autonomous Identification of Stable Adsorption Configurations via Large Language Model Agent

[The Journal of Physical Chemistry C: Latest Articles (ACS Publications)] [ASAP] Instant Prediction of Moire Superlattice Relaxation in Twisted Bilayers of Transition Metal Dichalcogenides Using Different Neural Network Architectures

[Recent Articles in Phys. Rev. Lett.] Variational Machine Learning Model for Electronic Structure Optimization via the Density Matrix

[Recent Articles in Phys. Rev. B] One-defect one-potential strategy for accurate machine learning prediction of phonons in defect-containing supercells

[Wiley: Advanced Science: Table of Contents] Polymorphism Crystal Structure Prediction with Adaptive Space Group Diversity Control

[Wiley: Advanced Science: Table of Contents] Computationally‐Guided Development of Sulfide Solid Electrolyte Powder Coatings for Enhanced Stability and Performance of Solid‐State Batteries

[Proceedings of the National Academy of Sciences: Physical Sciences] Uncovering inequalities in new knowledge learning by large language models across different languages

[Proceedings of the National Academy of Sciences: Physical Sciences] Heavy-tailed update distributions arise from information-driven self-organization in nonequilibrium learning

[ScienceDirect Publication: Journal of Energy Storage] Machine learning-aided prediction and optimization of specific capacitance in functionalized GO-based Mn/Fe co-doped Bi₂O₃ nanocomposites

[ScienceDirect Publication: Journal of Energy Storage] Machine learning-aided prediction and optimization of specific capacitance in functionalized GO-based Mn/Fe co-doped Bi₂O₃ nanocomposites