diff --git a/filtered_feed.xml b/filtered_feed.xml
index f9caad3..6a04353 100644
--- a/filtered_feed.xml
+++ b/filtered_feed.xml
@@ -1,5 +1,5 @@
 <?xml version="1.0" encoding="UTF-8"?>
-<rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/"><channel><title>My Customized Papers</title><link>https://github.com/your_username/your_repo</link><description>Aggregated research papers</description><language>en-US</language><lastBuildDate>Thu, 15 Jan 2026 06:34:05 GMT</lastBuildDate><generator>rfeed v1.1.1</generator><docs>https://github.com/svpino/rfeed/blob/master/README.md</docs><item><title>[cond-mat updates on arXiv.org] Emergent chiral Higgs mode in $\pi$-flux frustrated lattices</title><link>https://arxiv.org/abs/2601.08925</link><description>arXiv:2601.08925v1 Announce Type: new 
+<rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/"><channel><title>My Customized Papers</title><link>https://github.com/your_username/your_repo</link><description>Aggregated research papers</description><language>en-US</language><lastBuildDate>Thu, 15 Jan 2026 12:44:30 GMT</lastBuildDate><generator>rfeed v1.1.1</generator><docs>https://github.com/svpino/rfeed/blob/master/README.md</docs><item><title>[cond-mat updates on arXiv.org] Emergent chiral Higgs mode in $\pi$-flux frustrated lattices</title><link>https://arxiv.org/abs/2601.08925</link><description>arXiv:2601.08925v1 Announce Type: new 
 Abstract: Neutral-atom quantum simulators provide a powerful platform for realizing strongly correlated phases, enabling access to dynamical signatures of quasiparticles and symmetry breaking processes. Motivated by recent observations of quantum phases in flux-frustrated ladders with non-vanishing ground state currents, we investigate interacting bosons on the dimerized BBH lattice in two dimensions-originally introduced in the context of higher-order topology. After mapping out the phase diagram, which includes vortex superfluid (V-SF), vortex Mott insulator (V-MI), and featureless Mott insulator (MI) phases, we focus on the integer filling case. There, the MI/V-SF transition simultaneously breaks the $\mathbb Z_2^{T}$ and U(1) symmetries, where $\mathbb Z_2^{T}$ corresponds to time-reversal symmetry (TRS). Using a slave-boson description, we resolve the excitation spectrum across the transition and uncover a chiral Higgs mode whose mass softens at criticality, providing a dynamical hallmark of emergent chirality that we numerically probe via quench dynamics. Our results establish an experimentally realistic setting for probing unconventional TRS-broken phases and quasiparticles with intrinsic chirality in strongly interacting quantum matter.</description><author>cond-mat updates on arXiv.org</author><pubDate>Thu, 15 Jan 2026 05:00:00 GMT</pubDate><guid isPermaLink="true">oai:arXiv.org:2601.08925v1</guid></item><item><title>[cond-mat updates on arXiv.org] Machine Learning-Driven Creep Law Discovery Across Alloy Compositional Space</title><link>https://arxiv.org/abs/2601.08970</link><description>arXiv:2601.08970v1 Announce Type: new 
 Abstract: Hihg-temperature creep characterization of structural alloys traditionally relies on serial uniaxial tests, which are highly inefficient for exploring the large search space of alloy compositions and for material discovery. Here, we introduce a machine-learning-assisted, high-throughput framework for creep law identification based on a dimple array bulge instrument (DABI) configuration, which enables parallel creep testing of 25 dimples, each fabricated from a different alloy, in a single experiment. Full-field surface displacements of dimples undergoing time-dependent creep-induced bulging under inert gas pressure are measured by 3D digital image correlation. We train a recurrent neural network (RNN) as a surrogate model, mapping creep parameters and loading conditions to the time-dependent deformation response of DABI. Coupling this surrogate with a particle swarm optimization scheme enables rapid and global inverse identification with sparsity regularization of creep parameters from experiment displacement-time histories. In addition, we propose a phenomenological creep law with a time-dependent stress exponent that captures the sigmoidal primary creep observed in wrought INCONEL 625 and extracts its temperature dependence from DABI test at multiple temperatures. Furthermore, we employ a general creep law combining several conventional forms together with regularized inversion to identify the creep laws for 47 additional Fe-, Ni-, and Co-rich alloys and to automatically select the dominant functional form for each alloy. This workflow combined with DABI experiment provides a quantitative, high-throughput creep characterization platform that is compatible with data mining, composition-property modeling, and nonlinear structural optimization with creep behavior across a large alloy design space.</description><author>cond-mat updates on arXiv.org</author><pubDate>Thu, 15 Jan 2026 05:00:00 GMT</pubDate><guid isPermaLink="true">oai:arXiv.org:2601.08970v1</guid></item><item><title>[cond-mat updates on arXiv.org] Agentic AI and Machine Learning for Accelerated Materials Discovery and Applications</title><link>https://arxiv.org/abs/2601.09027</link><description>arXiv:2601.09027v1 Announce Type: new 
 Abstract: Artificial Intelligence (AI), especially AI agents, is increasingly being applied to chemistry, healthcare, and manufacturing to enhance productivity. In this review, we discuss the progress of AI and agentic AI in areas related to, and beyond polymer materials and discovery chemistry. More specifically, the focus is on the need for efficient discovery, core concepts, and large language models. Consequently, applications are showcased in scenarios such as (1) flow chemistry, (2) biosensors, and (3) batteries.</description><author>cond-mat updates on arXiv.org</author><pubDate>Thu, 15 Jan 2026 05:00:00 GMT</pubDate><guid isPermaLink="true">oai:arXiv.org:2601.09027v1</guid></item><item><title>[cond-mat updates on arXiv.org] Data-Driven Exploration and Insights into Temperature-Dependent Phonons in Inorganic Materials</title><link>https://arxiv.org/abs/2601.09123</link><description>arXiv:2601.09123v1 Announce Type: new 
@@ -10,7 +10,7 @@ Abstract: Metal-organic frameworks (MOFs) are porous crystalline materials with
 Abstract: Many factors in perovskite X-ray detectors, such as crystal lattice and carrier dynamics, determine the final device performance (e.g., sensitivity and detection limit). However, the relationship between these factors remains unknown due to the complexity of the material. In this study, we employ machine learning to reveal the relationship between 15 intrinsic properties of halide perovskite materials and their device performance. We construct a database of X-ray detectors for the training of machine learning. The results show that the band gap is mainly influenced by the atomic number of the B-site metal, and the lattice length parameter b has the greatest impact on the carrier mobility-lifetime product ({\mu}{\tau}). An X-ray detector (m-F-PEA)2PbI4 were generated in the experiment and it further verified the accuracy of our ML models. We suggest further study on random forest regression for X-ray detector applications.</description><author>cond-mat updates on arXiv.org</author><pubDate>Thu, 15 Jan 2026 05:00:00 GMT</pubDate><guid isPermaLink="true">oai:arXiv.org:2405.04729v2</guid></item><item><title>[cond-mat updates on arXiv.org] Sharp spectroscopic fingerprints of disorder in an incompressible magnetic state</title><link>https://arxiv.org/abs/2506.08112</link><description>arXiv:2506.08112v2 Announce Type: replace 
 Abstract: Disorder significantly impacts the electronic properties of conducting quantum materials by inducing electron localization and thus altering the local density of states and electric transport. In insulating quantum magnetic materials, the effects of disorder are less understood and can drastically impact fluctuating spin states like quantum spin liquids. In the absence of transport tools, disorder is typically characterized using chemical methods or by semi-classical modeling of spin dynamics. This requires high magnetic fields that may not always be accessible. Here, we show that magnetization plateaus -- incompressible states found in many quantum magnets -- provide an exquisite platform to uncover small amounts of disorder, regardless of the origin of the plateau. Using optical magneto-spectroscopy on the Ising-Heisenberg triangular-lattice antiferromagnet K$_2$Co(SeO$_3$)$_2$ exhibiting a 1/3 magnetization plateau, we identify sharp spectroscopic lines, the fine structure of which serves as a hallmark signature of disorder. Through analytical and numerical modeling, we show that these fingerprints not only enable us to quantify minute amounts of disorder but also reveal its nature -- as dilute vacancies. Remarkably, this model explains all details of the thermomagnetic response of our system, including the existence of multiple plateaus. Our findings provide a new approach to identifying disorder in quantum magnets.</description><author>cond-mat updates on arXiv.org</author><pubDate>Thu, 15 Jan 2026 05:00:00 GMT</pubDate><guid isPermaLink="true">oai:arXiv.org:2506.08112v2</guid></item><item><title>[cond-mat updates on arXiv.org] Data-Driven Review and Machine Learning Prediction of Diamond Vacancy Center Synthesis</title><link>https://arxiv.org/abs/2507.02808</link><description>arXiv:2507.02808v2 Announce Type: replace 
 Abstract: Diamond and diamond color centers have become prime hardware candidates for solid state-based technologies in quantum information and computing, optics, photonics and (bio)sensing. The synthesis of diamond materials with specific characteristics and the precise control of the hosted color centers is thus essential to meet the demands of advanced applications. Yet, challenges remain in improving the concentration, uniform distribution and quality of these centers. Here, we perform a review and meta-analysis of some of the main diamond synthesis methods and their parameters for the synthesis of N-, Si-, Ge- and Sn-vacancy color-centers. We extract quantitative data from over 60 experimental papers and organize it in a large database (170 data sets and 1692 entries). We then use the database to train two machine learning algorithms to make robust predictions about the fabrication of diamond materials with specific properties from careful combinations of synthesis parameters. We use traditional statistical indicators to benchmark the performance of the algorithms and show that they are powerful and resource-efficient tools for researchers and material scientists working with diamond color centers and their applications.</description><author>cond-mat updates on arXiv.org</author><pubDate>Thu, 15 Jan 2026 05:00:00 GMT</pubDate><guid isPermaLink="true">oai:arXiv.org:2507.02808v2</guid></item><item><title>[cond-mat updates on arXiv.org] Investigating Anharmonicities in Polarization-Orientation Raman Spectra of Acene Crystals with Machine Learning</title><link>https://arxiv.org/abs/2510.04843</link><description>arXiv:2510.04843v2 Announce Type: replace 
-Abstract: We present a first-principles machine-learning computational framework to investigate anharmonic effects in polarization-orientation (PO) Raman spectra of molecular crystals, focusing on anthracene and naphthalene. By combining machine learning models for interatomic potentials and polarizability tensors, we enable efficient, large-scale simulations that capture temperature-dependent vibrational dynamics beyond the harmonic approximation. Our approach reproduces key qualitative features observed experimentally. We show, systematically, what are the fingerprints of anharmonic lattice dynamics, thermal expansion, and Raman tensor symmetries on PO-Raman intensities. However, we find that the simulated polarization dependence of Raman intensities shows only subtle deviations from quasi-harmonic predictions, failing to capture the pronounced temperature-dependent changes that have been reported experimentally in anthracene. We propose that part of these inconsistencies stem from the impossibility to deconvolute certain vibrational peaks when only experimental data is available. This work therefore provides a foundation to improve the interpretation of PO-Raman experiments in complex molecular crystals with the aid of theoretical simulations.</description><author>cond-mat updates on arXiv.org</author><pubDate>Thu, 15 Jan 2026 05:00:00 GMT</pubDate><guid isPermaLink="true">oai:arXiv.org:2510.04843v2</guid></item><item><title>[ScienceDirect Publication: Journal of Energy Storage] Design of corrosion resistant Ce-enhanced hybrid solid electrolyte interphase by Ce(TFSI)&lt;sub&gt;3&lt;/sub&gt; additives for lithium metal batteries</title><link>https://www.sciencedirect.com/science/article/pii/S2352152X26001465?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: 10 March 2026&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; Journal of Energy Storage, Volume 150&lt;/p&gt;&lt;p&gt;Author(s): Mingdong Du, Yanxia Liu, Chenxing Wang, Fulai Qi, Mingyu Shi, Wenjing Liu, Shengnan He, Zhijun Wu, Zhenglong Li, Chenchen Li, Hongge Pan&lt;/p&gt;</description><author>ScienceDirect Publication: Journal of Energy Storage</author><pubDate>Thu, 15 Jan 2026 01:41:46 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S2352152X26001465</guid></item><item><title>[ChemRxiv] Assigning the Stereochemistry of Natural Products by Machine Learning</title><link>https://dx.doi.org/10.26434/chemrxiv-2024-zz9pw-v4?rft_dat=source%3Ddrss</link><description>Nature has settled for L-chirality for proteinogenic amino acids and D-chirality for the carbohydrate backbone of nucleotides. Further stereochemical patterns exist among natural products produced by common biosynthetic pathways. Here we asked the question whether these regularities might be sufficiently prevalent among natural products (NPs) such that their stereochemistry could be machine learned and assigned automatically. Indeed, we report that a language model can be trained to assign the stereochemistry of NPs using the open access NP database COCONUT. In detail, our language model, called NPstereo, translates an NP structure written as absolute SMILES into the corresponding isomeric SMILES notation containing stereochemical information, with 80.2% per-stereocenter accuracy for full assignments and 85.9% per-stereocenter accuracy for partial assignments, across various NP classes including secondary metabolites such as alkaloids, polyketides, lipids and terpenes. NPstereo might be useful to assign or correct the stereochemistry of newly discovered NPs. Scientific contribution: Our study reports that a language model, NPstereo, can learn and predict the stereochemistry of natural products (NPs) from their 2D structures with high accuracy. This work demonstrates that NP stereochemical patterns are machine learnable from data and represents a first step for scalable computational methodologies for stereochemical assignment of newly discovered NPs.</description><author>ChemRxiv</author><pubDate>Thu, 15 Jan 2026 00:00:00 GMT</pubDate><guid isPermaLink="true">https://dx.doi.org/10.26434/chemrxiv-2024-zz9pw-v4?rft_dat=source%3Ddrss</guid></item><item><title>[ChemRxiv] Advancing Calcium-Ion Batteries with a Novel Hydrated Eutectic Electrolyte</title><link>https://dx.doi.org/10.26434/chemrxiv-2025-hxjcm-v2?rft_dat=source%3Ddrss</link><description>Ca-ion batteries (CIBs) have garnered significant attention in the past few years by virtue of their economic and physicochemical advantages, positioning them as a promising electrochemical energy storage technology in the post-lithium-ion battery era. However, the current research progress is insufficient, leaving this emerging field far from practical application, most of which focuses on developing high-performance electrode materials. Herein, we design a novel hydrated eutectic electrolyte (HEE) prepared by mixing Ca(ClO4)2·4H2O and acetamide at room temperature. The solvation structure of Ca2+ can be precisely regulated by controlling the molar ratio of the two chemical components. The HEE with optimal formulation features a wide electrochemical stability window, good ionic conductivity, appropriate viscosity, and a low melting point. Employing this novel HEE, a full CIB assembled with a PEDOT/V2O5 cathode and a PTCDI anode demonstrated outstanding electrochemical performance at room temperature (30 mAh·g−1 at 0.5 A·g−1 after 30,000 cycles) and environmental adaptability within a wide operating temperature range (−20 to 60 ℃). This work may not only provide a sustainable, safe, and cost-effective electrolyte for CIBs but also pave the way for the comprehensive development of CIBs.</description><author>ChemRxiv</author><pubDate>Thu, 15 Jan 2026 00:00:00 GMT</pubDate><guid isPermaLink="true">https://dx.doi.org/10.26434/chemrxiv-2025-hxjcm-v2?rft_dat=source%3Ddrss</guid></item><item><title>[ChemRxiv] DFT-guided discovery of bisureido ester of 2-(methylthio)ethanol: A novel lead against triple-negative breast cancer inducing apoptosis via pH-sensitive chloride transport</title><link>https://dx.doi.org/10.26434/chemrxiv-2026-tql3f?rft_dat=source%3Ddrss</link><description>Dysregulation of transmembrane chloride flux has emerged as a promising strategy for inducing cancer-cell death through disruption of intracellular pH gradients and subsequent apoptosis. Herein, we report the design and synthesis of novel ortho-phenylenediamine (o-PDA) bisurea derivatives bearing carboxyl (5a–f) and 2-(methylthio)ethyl ester (6a,b) groups for pH-sensitive anion transport and resultant anticancer activity. Esterification of 5c–f proved synthetically challenging due to an unprecedented CDI-catalyzed intramolecular cyclization that yielded the 4-oxo-benzo[d][1,3,6]oxadiazepines 8a,b, rationalized via a DFT-supported four-step mechanism involving hydrogen-borrowing catalysis. All target compounds demonstrated 1:1 chloride ion-binding as shown by 1H NMR titration results and demonstrated a pH-gradient-induced transmembrane chloride transport (as shown by vesicular transport studies) which was enhanced by electron-withdrawing substituents on the outer phenyl rings. Ester derivatives 6a,b exhibited significantly higher chloride binding and up to ~67-fold increased transport efficiency over their carboxylic acid analogs. Compound 6b emerged as the lead, combining efficient chloride binding (Ka = 163 M⁻¹), potent transport (EC50 = 0.007 mol%), and superior antiproliferative activity (IC50 = 6.34 µM) against MDA-MB-231 cells via apoptosis induction. These findings establish 6b as a promising lead for chloride-transport-mediated cancer therapy, with further optimization recommended via EWG diversification and strategic consideration of the cyclization pathway in retrosynthetic design.</description><author>ChemRxiv</author><pubDate>Thu, 15 Jan 2026 00:00:00 GMT</pubDate><guid isPermaLink="true">https://dx.doi.org/10.26434/chemrxiv-2026-tql3f?rft_dat=source%3Ddrss</guid></item><item><title>[ScienceDirect Publication: eScience] Emerging inorganic amorphous solid-state electrolytes in all-solid-state lithium batteries: From crystallographic order to atomic and lattice disorder</title><link>https://www.sciencedirect.com/science/article/pii/S2667141726000029?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: Available online 13 January 2026&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; eScience&lt;/p&gt;&lt;p&gt;Author(s): Yijie Yan, Shuxian Zhang, Xiaoge Man, Qingyu Li, Haoyuan Xue, Peng Xiao, Yuanchang Shi, Longwei Yin, Rutao Wang&lt;/p&gt;</description><author>ScienceDirect Publication: eScience</author><pubDate>Wed, 14 Jan 2026 18:33:27 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S2667141726000029</guid></item><item><title>[ScienceDirect Publication: Materials Today Physics] Defect formation energy of impurities in 2D materials: How does data engineering shape machine learning model selection?</title><link>https://www.sciencedirect.com/science/article/pii/S2542529325003621?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: Available online 13 January 2026&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; Materials Today Physics&lt;/p&gt;&lt;p&gt;Author(s): A. El Alouani, M. Al Khalfioui, A. Michon, S. Vézian, P. Boucaud, M.T. Dau&lt;/p&gt;</description><author>ScienceDirect Publication: Materials Today Physics</author><pubDate>Wed, 14 Jan 2026 12:44:11 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S2542529325003621</guid></item><item><title>[ACS Nano: Latest Articles (ACS Publications)] [ASAP] Robust LiNi0.6Mn0.4O2 Cathode Achieved from the Dual-Function Strategy of Microstructural Stress Dissipation and Crystalline Phase Ion Transport Improvement</title><link>http://dx.doi.org/10.1021/acsnano.5c19029</link><description>&lt;p&gt;&lt;img alt="TOC Graphic" src="https://pubs.acs.org/cms/10.1021/acsnano.5c19029/asset/images/medium/nn5c19029_0007.gif" /&gt;&lt;/p&gt;&lt;div&gt;&lt;cite&gt;ACS Nano&lt;/cite&gt;&lt;/div&gt;&lt;div&gt;DOI: 10.1021/acsnano.5c19029&lt;/div&gt;</description><author>ACS Nano: Latest Articles (ACS Publications)</author><pubDate>Wed, 14 Jan 2026 11:35:44 GMT</pubDate><guid isPermaLink="true">http://dx.doi.org/10.1021/acsnano.5c19029</guid></item><item><title>[The Journal of Physical Chemistry Letters: Latest Articles (ACS Publications)] [ASAP] Characterizing RNA Tetramer Conformational Landscape Using Explainable Machine Learning</title><link>http://dx.doi.org/10.1021/acs.jpclett.5c03438</link><description>&lt;p&gt;&lt;img alt="TOC Graphic" src="https://pubs.acs.org/cms/10.1021/acs.jpclett.5c03438/asset/images/medium/jz5c03438_0006.gif" /&gt;&lt;/p&gt;&lt;div&gt;&lt;cite&gt;The Journal of Physical Chemistry Letters&lt;/cite&gt;&lt;/div&gt;&lt;div&gt;DOI: 10.1021/acs.jpclett.5c03438&lt;/div&gt;</description><author>The Journal of Physical Chemistry Letters: Latest Articles (ACS Publications)</author><pubDate>Wed, 14 Jan 2026 10:55:20 GMT</pubDate><guid isPermaLink="true">http://dx.doi.org/10.1021/acs.jpclett.5c03438</guid></item><item><title>[Recent Articles in Phys. Rev. B] Quantum many-body scarring from Kramers-Wannier duality</title><link>http://link.aps.org/doi/10.1103/ny73-r1ss</link><description>Author(s): Weslei B. Fontana, Fabrizio G. Oliviero, and Yi-Ping Huang&lt;br /&gt;&lt;p&gt;Kramers-Wannier duality, a hallmark of the Ising model, has recently gained renewed interest through its reinterpretation as a noninvertible symmetry with a state-level action. Using sequential quantum circuits (SQC), we argue that this duality governs the stability of quantum many-body scar (QMBS) …&lt;/p&gt;&lt;br /&gt;[Phys. Rev. B 113, 024307] Published Wed Jan 14, 2026</description><author>Recent Articles in Phys. Rev. B</author><pubDate>Wed, 14 Jan 2026 10:00:00 GMT</pubDate><guid isPermaLink="true">http://link.aps.org/doi/10.1103/ny73-r1ss</guid></item><item><title>[Wiley: Small: Table of Contents] Machine Learning‐Assisted Tailoring of Pore Structures in Coal‐Derived Porous Carbons for Enhanced Performance</title><link>https://onlinelibrary.wiley.com/doi/10.1002/smll.202512280?af=R</link><description>Small, EarlyView.</description><author>Wiley: Small: Table of Contents</author><pubDate>Wed, 14 Jan 2026 09:20:46 GMT</pubDate><guid isPermaLink="true">10.1002/smll.202512280</guid></item><item><title>[Wiley: Advanced Energy Materials: Table of Contents] Machine Learning for Accelerating Energy Materials Discovery: Bridging Quantum Accuracy with Computational Efficiency</title><link>https://advanced.onlinelibrary.wiley.com/doi/10.1002/aenm.202503356?af=R</link><description>Advanced Energy Materials, Volume 16, Issue 2, 14 January 2026.</description><author>Wiley: Advanced Energy Materials: Table of Contents</author><pubDate>Wed, 14 Jan 2026 08:50:01 GMT</pubDate><guid isPermaLink="true">10.1002/aenm.202503356</guid></item><item><title>[cond-mat updates on arXiv.org] Chiral Two-Body Bound States from Berry Curvature and Chiral Superconductivity</title><link>https://arxiv.org/abs/2601.08055</link><description>arXiv:2601.08055v1 Announce Type: new 
+Abstract: We present a first-principles machine-learning computational framework to investigate anharmonic effects in polarization-orientation (PO) Raman spectra of molecular crystals, focusing on anthracene and naphthalene. By combining machine learning models for interatomic potentials and polarizability tensors, we enable efficient, large-scale simulations that capture temperature-dependent vibrational dynamics beyond the harmonic approximation. Our approach reproduces key qualitative features observed experimentally. We show, systematically, what are the fingerprints of anharmonic lattice dynamics, thermal expansion, and Raman tensor symmetries on PO-Raman intensities. However, we find that the simulated polarization dependence of Raman intensities shows only subtle deviations from quasi-harmonic predictions, failing to capture the pronounced temperature-dependent changes that have been reported experimentally in anthracene. We propose that part of these inconsistencies stem from the impossibility to deconvolute certain vibrational peaks when only experimental data is available. This work therefore provides a foundation to improve the interpretation of PO-Raman experiments in complex molecular crystals with the aid of theoretical simulations.</description><author>cond-mat updates on arXiv.org</author><pubDate>Thu, 15 Jan 2026 05:00:00 GMT</pubDate><guid isPermaLink="true">oai:arXiv.org:2510.04843v2</guid></item><item><title>[ScienceDirect Publication: Journal of Energy Storage] Design of corrosion resistant Ce-enhanced hybrid solid electrolyte interphase by Ce(TFSI)&lt;sub&gt;3&lt;/sub&gt; additives for lithium metal batteries</title><link>https://www.sciencedirect.com/science/article/pii/S2352152X26001465?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: 10 March 2026&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; Journal of Energy Storage, Volume 150&lt;/p&gt;&lt;p&gt;Author(s): Mingdong Du, Yanxia Liu, Chenxing Wang, Fulai Qi, Mingyu Shi, Wenjing Liu, Shengnan He, Zhijun Wu, Zhenglong Li, Chenchen Li, Hongge Pan&lt;/p&gt;</description><author>ScienceDirect Publication: Journal of Energy Storage</author><pubDate>Thu, 15 Jan 2026 01:41:46 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S2352152X26001465</guid></item><item><title>[ChemRxiv] Assigning the Stereochemistry of Natural Products by Machine Learning</title><link>https://dx.doi.org/10.26434/chemrxiv-2024-zz9pw-v4?rft_dat=source%3Ddrss</link><description>Nature has settled for L-chirality for proteinogenic amino acids and D-chirality for the carbohydrate backbone of nucleotides. Further stereochemical patterns exist among natural products produced by common biosynthetic pathways. Here we asked the question whether these regularities might be sufficiently prevalent among natural products (NPs) such that their stereochemistry could be machine learned and assigned automatically. Indeed, we report that a language model can be trained to assign the stereochemistry of NPs using the open access NP database COCONUT. In detail, our language model, called NPstereo, translates an NP structure written as absolute SMILES into the corresponding isomeric SMILES notation containing stereochemical information, with 80.2% per-stereocenter accuracy for full assignments and 85.9% per-stereocenter accuracy for partial assignments, across various NP classes including secondary metabolites such as alkaloids, polyketides, lipids and terpenes. NPstereo might be useful to assign or correct the stereochemistry of newly discovered NPs. Scientific contribution: Our study reports that a language model, NPstereo, can learn and predict the stereochemistry of natural products (NPs) from their 2D structures with high accuracy. This work demonstrates that NP stereochemical patterns are machine learnable from data and represents a first step for scalable computational methodologies for stereochemical assignment of newly discovered NPs.</description><author>ChemRxiv</author><pubDate>Thu, 15 Jan 2026 00:00:00 GMT</pubDate><guid isPermaLink="true">https://dx.doi.org/10.26434/chemrxiv-2024-zz9pw-v4?rft_dat=source%3Ddrss</guid></item><item><title>[ChemRxiv] Advancing Calcium-Ion Batteries with a Novel Hydrated Eutectic Electrolyte</title><link>https://dx.doi.org/10.26434/chemrxiv-2025-hxjcm-v2?rft_dat=source%3Ddrss</link><description>Ca-ion batteries (CIBs) have garnered significant attention in the past few years by virtue of their economic and physicochemical advantages, positioning them as a promising electrochemical energy storage technology in the post-lithium-ion battery era. However, the current research progress is insufficient, leaving this emerging field far from practical application, most of which focuses on developing high-performance electrode materials. Herein, we design a novel hydrated eutectic electrolyte (HEE) prepared by mixing Ca(ClO4)2·4H2O and acetamide at room temperature. The solvation structure of Ca2+ can be precisely regulated by controlling the molar ratio of the two chemical components. The HEE with optimal formulation features a wide electrochemical stability window, good ionic conductivity, appropriate viscosity, and a low melting point. Employing this novel HEE, a full CIB assembled with a PEDOT/V2O5 cathode and a PTCDI anode demonstrated outstanding electrochemical performance at room temperature (30 mAh·g−1 at 0.5 A·g−1 after 30,000 cycles) and environmental adaptability within a wide operating temperature range (−20 to 60 ℃). This work may not only provide a sustainable, safe, and cost-effective electrolyte for CIBs but also pave the way for the comprehensive development of CIBs.</description><author>ChemRxiv</author><pubDate>Thu, 15 Jan 2026 00:00:00 GMT</pubDate><guid isPermaLink="true">https://dx.doi.org/10.26434/chemrxiv-2025-hxjcm-v2?rft_dat=source%3Ddrss</guid></item><item><title>[ChemRxiv] DFT-guided discovery of bisureido ester of 2-(methylthio)ethanol: A novel lead against triple-negative breast cancer inducing apoptosis via pH-sensitive chloride transport</title><link>https://dx.doi.org/10.26434/chemrxiv-2026-tql3f?rft_dat=source%3Ddrss</link><description>Dysregulation of transmembrane chloride flux has emerged as a promising strategy for inducing cancer-cell death through disruption of intracellular pH gradients and subsequent apoptosis. Herein, we report the design and synthesis of novel ortho-phenylenediamine (o-PDA) bisurea derivatives bearing carboxyl (5a–f) and 2-(methylthio)ethyl ester (6a,b) groups for pH-sensitive anion transport and resultant anticancer activity. Esterification of 5c–f proved synthetically challenging due to an unprecedented CDI-catalyzed intramolecular cyclization that yielded the 4-oxo-benzo[d][1,3,6]oxadiazepines 8a,b, rationalized via a DFT-supported four-step mechanism involving hydrogen-borrowing catalysis. All target compounds demonstrated 1:1 chloride ion-binding as shown by 1H NMR titration results and demonstrated a pH-gradient-induced transmembrane chloride transport (as shown by vesicular transport studies) which was enhanced by electron-withdrawing substituents on the outer phenyl rings. Ester derivatives 6a,b exhibited significantly higher chloride binding and up to ~67-fold increased transport efficiency over their carboxylic acid analogs. Compound 6b emerged as the lead, combining efficient chloride binding (Ka = 163 M⁻¹), potent transport (EC50 = 0.007 mol%), and superior antiproliferative activity (IC50 = 6.34 µM) against MDA-MB-231 cells via apoptosis induction. These findings establish 6b as a promising lead for chloride-transport-mediated cancer therapy, with further optimization recommended via EWG diversification and strategic consideration of the cyclization pathway in retrosynthetic design.</description><author>ChemRxiv</author><pubDate>Thu, 15 Jan 2026 00:00:00 GMT</pubDate><guid isPermaLink="true">https://dx.doi.org/10.26434/chemrxiv-2026-tql3f?rft_dat=source%3Ddrss</guid></item><item><title>[Nature Nanotechnology] Superionic composite electrolytes with continuously perpendicular-aligned pathways for pressure-less all-solid-state lithium batteries</title><link>https://www.nature.com/articles/s41565-025-02106-9</link><description>&lt;p&gt;Nature Nanotechnology, Published online: 15 January 2026; &lt;a href="https://www.nature.com/articles/s41565-025-02106-9"&gt;doi:10.1038/s41565-025-02106-9&lt;/a&gt;&lt;/p&gt;Highly ionically conductive and flexible solid-state composite battery electrolytes are engineered by alternately stacking inorganic LixMyPS3 (M = Cd or Mn) nanosheets with lithium-containing organic polymers in a perpendicular orientation to the surface of the electrodes.</description><author>Nature Nanotechnology</author><pubDate>Thu, 15 Jan 2026 00:00:00 GMT</pubDate><guid isPermaLink="true">https://www.nature.com/articles/s41565-025-02106-9</guid></item><item><title>[ScienceDirect Publication: eScience] Emerging inorganic amorphous solid-state electrolytes in all-solid-state lithium batteries: From crystallographic order to atomic and lattice disorder</title><link>https://www.sciencedirect.com/science/article/pii/S2667141726000029?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: Available online 13 January 2026&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; eScience&lt;/p&gt;&lt;p&gt;Author(s): Yijie Yan, Shuxian Zhang, Xiaoge Man, Qingyu Li, Haoyuan Xue, Peng Xiao, Yuanchang Shi, Longwei Yin, Rutao Wang&lt;/p&gt;</description><author>ScienceDirect Publication: eScience</author><pubDate>Wed, 14 Jan 2026 18:33:27 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S2667141726000029</guid></item><item><title>[Wiley: Small: Table of Contents] Asymmetric Ion Transport in Tunnel‐Type Cobalt Vanadate for High‐Performance Mn2+/H+ Hybrid Aqueous Batteries</title><link>https://onlinelibrary.wiley.com/doi/10.1002/smll.202511733?af=R</link><description>Small, Volume 22, Issue 3, 13 January 2026.</description><author>Wiley: Small: Table of Contents</author><pubDate>Wed, 14 Jan 2026 14:17:12 GMT</pubDate><guid isPermaLink="true">10.1002/smll.202511733</guid></item><item><title>[Wiley: Small: Table of Contents] Machine Learning Accelerated Screening Advanced Single‐Atom Anchored MXenes Electrocatalyst for Hydrogen Evolution Reaction</title><link>https://onlinelibrary.wiley.com/doi/10.1002/smll.202510707?af=R</link><description>Small, Volume 22, Issue 3, 13 January 2026.</description><author>Wiley: Small: Table of Contents</author><pubDate>Wed, 14 Jan 2026 14:17:12 GMT</pubDate><guid isPermaLink="true">10.1002/smll.202510707</guid></item><item><title>[ScienceDirect Publication: Materials Today Physics] Defect formation energy of impurities in 2D materials: How does data engineering shape machine learning model selection?</title><link>https://www.sciencedirect.com/science/article/pii/S2542529325003621?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: Available online 13 January 2026&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; Materials Today Physics&lt;/p&gt;&lt;p&gt;Author(s): A. El Alouani, M. Al Khalfioui, A. Michon, S. Vézian, P. Boucaud, M.T. Dau&lt;/p&gt;</description><author>ScienceDirect Publication: Materials Today Physics</author><pubDate>Wed, 14 Jan 2026 12:44:11 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S2542529325003621</guid></item><item><title>[Wiley: Advanced Materials: Table of Contents] 2D Chitin Sub‐Nanosheets with Extreme Ion Transport for Nanofluidic Sensing</title><link>https://advanced.onlinelibrary.wiley.com/doi/10.1002/adma.202510095?af=R</link><description>Advanced Materials, Volume 38, Issue 3, 13 January 2026.</description><author>Wiley: Advanced Materials: Table of Contents</author><pubDate>Wed, 14 Jan 2026 11:46:54 GMT</pubDate><guid isPermaLink="true">10.1002/adma.202510095</guid></item><item><title>[Wiley: Advanced Intelligent Discovery: Table of Contents] Machine Learning Driven Inverse Design of Broadband Acoustic Superscattering</title><link>https://advanced.onlinelibrary.wiley.com/doi/10.1002/aidi.202500210?af=R</link><description>Advanced Intelligent Discovery, EarlyView.</description><author>Wiley: Advanced Intelligent Discovery: Table of Contents</author><pubDate>Wed, 14 Jan 2026 11:46:36 GMT</pubDate><guid isPermaLink="true">10.1002/aidi.202500210</guid></item><item><title>[ACS Nano: Latest Articles (ACS Publications)] [ASAP] Robust LiNi0.6Mn0.4O2 Cathode Achieved from the Dual-Function Strategy of Microstructural Stress Dissipation and Crystalline Phase Ion Transport Improvement</title><link>http://dx.doi.org/10.1021/acsnano.5c19029</link><description>&lt;p&gt;&lt;img alt="TOC Graphic" src="https://pubs.acs.org/cms/10.1021/acsnano.5c19029/asset/images/medium/nn5c19029_0007.gif" /&gt;&lt;/p&gt;&lt;div&gt;&lt;cite&gt;ACS Nano&lt;/cite&gt;&lt;/div&gt;&lt;div&gt;DOI: 10.1021/acsnano.5c19029&lt;/div&gt;</description><author>ACS Nano: Latest Articles (ACS Publications)</author><pubDate>Wed, 14 Jan 2026 11:35:44 GMT</pubDate><guid isPermaLink="true">http://dx.doi.org/10.1021/acsnano.5c19029</guid></item><item><title>[The Journal of Physical Chemistry Letters: Latest Articles (ACS Publications)] [ASAP] Characterizing RNA Tetramer Conformational Landscape Using Explainable Machine Learning</title><link>http://dx.doi.org/10.1021/acs.jpclett.5c03438</link><description>&lt;p&gt;&lt;img alt="TOC Graphic" src="https://pubs.acs.org/cms/10.1021/acs.jpclett.5c03438/asset/images/medium/jz5c03438_0006.gif" /&gt;&lt;/p&gt;&lt;div&gt;&lt;cite&gt;The Journal of Physical Chemistry Letters&lt;/cite&gt;&lt;/div&gt;&lt;div&gt;DOI: 10.1021/acs.jpclett.5c03438&lt;/div&gt;</description><author>The Journal of Physical Chemistry Letters: Latest Articles (ACS Publications)</author><pubDate>Wed, 14 Jan 2026 10:55:20 GMT</pubDate><guid isPermaLink="true">http://dx.doi.org/10.1021/acs.jpclett.5c03438</guid></item><item><title>[Recent Articles in Phys. Rev. B] Quantum many-body scarring from Kramers-Wannier duality</title><link>http://link.aps.org/doi/10.1103/ny73-r1ss</link><description>Author(s): Weslei B. Fontana, Fabrizio G. Oliviero, and Yi-Ping Huang&lt;br /&gt;&lt;p&gt;Kramers-Wannier duality, a hallmark of the Ising model, has recently gained renewed interest through its reinterpretation as a noninvertible symmetry with a state-level action. Using sequential quantum circuits (SQC), we argue that this duality governs the stability of quantum many-body scar (QMBS) …&lt;/p&gt;&lt;br /&gt;[Phys. Rev. B 113, 024307] Published Wed Jan 14, 2026</description><author>Recent Articles in Phys. Rev. B</author><pubDate>Wed, 14 Jan 2026 10:00:00 GMT</pubDate><guid isPermaLink="true">http://link.aps.org/doi/10.1103/ny73-r1ss</guid></item><item><title>[Wiley: Small: Table of Contents] Machine Learning‐Assisted Tailoring of Pore Structures in Coal‐Derived Porous Carbons for Enhanced Performance</title><link>https://onlinelibrary.wiley.com/doi/10.1002/smll.202512280?af=R</link><description>Small, EarlyView.</description><author>Wiley: Small: Table of Contents</author><pubDate>Wed, 14 Jan 2026 09:20:46 GMT</pubDate><guid isPermaLink="true">10.1002/smll.202512280</guid></item><item><title>[Wiley: Advanced Energy Materials: Table of Contents] Machine Learning for Accelerating Energy Materials Discovery: Bridging Quantum Accuracy with Computational Efficiency</title><link>https://advanced.onlinelibrary.wiley.com/doi/10.1002/aenm.202503356?af=R</link><description>Advanced Energy Materials, Volume 16, Issue 2, 14 January 2026.</description><author>Wiley: Advanced Energy Materials: Table of Contents</author><pubDate>Wed, 14 Jan 2026 08:50:01 GMT</pubDate><guid isPermaLink="true">10.1002/aenm.202503356</guid></item><item><title>[cond-mat updates on arXiv.org] Chiral Two-Body Bound States from Berry Curvature and Chiral Superconductivity</title><link>https://arxiv.org/abs/2601.08055</link><description>arXiv:2601.08055v1 Announce Type: new 
 Abstract: Motivated by the discovery of exotic superconductivity in rhombohedral graphene, we study the two-body problem in electronic bands endowed with Berry curvature and show that it supports chiral, non-$s$-wave bound states with nonzero angular momentum. In the presence of a Fermi sea, these interactions give rise to a chiral pairing problem featuring multiple superconducting phases that break time-reversal symmetry. These phases form a cascade of chiral topological states with different angular momenta, where the order-parameter phase winds by $2\pi m$ around the Fermi surface, with $m = 1,3,5,\ldots$, and the succession of phases is governed by the Berry-curvature flux through the Fermi surface area, $\Phi = b k_F^2/2$. As $\Phi$ increases, the system undergoes a sequence of first-order phase transitions between distinct chiral phases, occurring whenever $\Phi$ crosses integer values. This realizes a quantum-geometry analog of the Little--Parks effect -- oscillations in $T_c$ that provide a clear and experimentally accessible hallmark of chiral superconducting order.</description><author>cond-mat updates on arXiv.org</author><pubDate>Wed, 14 Jan 2026 05:00:00 GMT</pubDate><guid isPermaLink="true">oai:arXiv.org:2601.08055v1</guid></item><item><title>[cond-mat updates on arXiv.org] Symmetry-aware Conditional Generation of Crystal Structures Using Diffusion Models</title><link>https://arxiv.org/abs/2601.08115</link><description>arXiv:2601.08115v1 Announce Type: new 
 Abstract: The application of generative models in crystal structure prediction (CSP) has gained significant attention. Conditional generation--particularly the generation of crystal structures with specified stability or other physical properties has been actively researched for material discovery purposes. Meanwhile, the generative models capable of symmetry-aware generation are also under active development, because space group symmetry has a strong relationship with the physical properties of materials. In this study, we demonstrate that the symmetry control in the previous conditional crystal generation model may not be sufficiently effective when space group constraints are applied as a condition. To address this problem, we propose the WyckoffDiff-Adaptor, which embeds conditional generation within a WyckoffDiff architecture that effectively diffuses Wyckoff positions to achieve precise symmetry control. We successfully generated formation energy phase diagrams while specifying stable structures of particular combination of elements, such as Li--O and Ti--O systems, while simultaneously preserving the symmetry of the input conditions. The proposed method with symmetry-aware conditional generation demonstrates promising results as an effective approach to achieving the discovery of novel materials with targeted physical properties.</description><author>cond-mat updates on arXiv.org</author><pubDate>Wed, 14 Jan 2026 05:00:00 GMT</pubDate><guid isPermaLink="true">oai:arXiv.org:2601.08115v1</guid></item><item><title>[cond-mat updates on arXiv.org] A microscopic origin for the breakdown of the Stokes Einstein relation in ion transport</title><link>https://arxiv.org/abs/2601.08309</link><description>arXiv:2601.08309v1 Announce Type: new 
 Abstract: Ion transport underlies the operation of biological ion channels and governs the performance of electrochemical energy-storage devices. A long-standing anomaly is that smaller alkali metal ions, such as Li$^+$, migrate more slowly in water than larger ions, in apparent violation of the Stokes-Einstein relation. This breakdown is conventionally attributed to dielectric friction, a collective drag force arising from electrostatic interactions between a drifting ion and its surrounding solvent. Here, combining nanopore transport measurements over electric fields spanning several orders of magnitude with molecular dynamics simulations, we show that the time-averaged electrostatic force on a migrating ion is not a drag force but a net driving force. By contrasting charged ions with neutral particles, we reveal that ionic charge introduces additional Lorentzian peaks in the frequency-dependent friction coefficient. These peaks originate predominantly from short-range Lennard-Jones (LJ) interactions within the first hydration layer and represent additional channels for energy dissipation, strongest for Li$^+$ and progressively weaker for Na$^+$ and K$^+$. Our results demonstrate that electrostatic interactions primarily act to tighten the local hydration structure, thereby amplifying short-range LJ interactions rather than directly opposing ion motion. This microscopic mechanism provides a unified physical explanation for the breakdown of the Stokes-Einstein relation in aqueous ion transport.</description><author>cond-mat updates on arXiv.org</author><pubDate>Wed, 14 Jan 2026 05:00:00 GMT</pubDate><guid isPermaLink="true">oai:arXiv.org:2601.08309v1</guid></item><item><title>[cond-mat updates on arXiv.org] DataScribe: An AI-Native, Policy-Aligned Web Platform for Multi-Objective Materials Design and Discovery</title><link>https://arxiv.org/abs/2601.07966</link><description>arXiv:2601.07966v1 Announce Type: cross