From 56a31f1c73503e691ae7eeed3c3ceb2030effae7 Mon Sep 17 00:00:00 2001
From: "github-actions[bot]" <github-actions[bot]@users.noreply.github.com>
Date: Sun, 4 Jan 2026 12:39:06 +0000
Subject: [PATCH] Auto-update RSS feed

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-<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>Sun, 04 Jan 2026 06:31:25 GMT</lastBuildDate><generator>rfeed v1.1.1</generator><docs>https://github.com/svpino/rfeed/blob/master/README.md</docs><item><title>[ScienceDirect Publication: Artificial Intelligence Chemistry] Accelerated green material and solvent discovery with chemistry- and physics-guided generative AI</title><link>https://www.sciencedirect.com/science/article/pii/S2949747725000235?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: Available online 2 January 2026&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; Artificial Intelligence Chemistry&lt;/p&gt;&lt;p&gt;Author(s): Eslam G. Al-Sakkari, Ahmed Ragab, Marzouk Benali, Olumoye Ajao, Daria C Boffito, Hanane Dagdougui&lt;/p&gt;</description><author>ScienceDirect Publication: Artificial Intelligence Chemistry</author><pubDate>Sat, 03 Jan 2026 12:38:39 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S2949747725000235</guid></item><item><title>[Wiley: Angewandte Chemie International Edition: Table of Contents] Minutes‐Scale Ultrafast Synthesis of New Oxyhalides Solid Electrolytes with Interfacial Ionic Conduction for All‐Solid‐State Batteries</title><link>https://onlinelibrary.wiley.com/doi/10.1002/anie.202516259?af=R</link><description>Angewandte Chemie International Edition, Volume 65, Issue 1, 2 January 2026.</description><author>Wiley: Angewandte Chemie International Edition: Table of Contents</author><pubDate>Sat, 03 Jan 2026 06:30:47 GMT</pubDate><guid isPermaLink="true">10.1002/anie.202516259</guid></item><item><title>[Wiley: Advanced Materials: Table of Contents] Potential‐Gated Polymer Integrates Reversible Ion Transport and Storage for solid‐state Batteries</title><link>https://advanced.onlinelibrary.wiley.com/doi/10.1002/adma.202513365?af=R</link><description>Advanced Materials, Volume 38, Issue 1, 2 January 2026.</description><author>Wiley: Advanced Materials: Table of Contents</author><pubDate>Sat, 03 Jan 2026 06:20:51 GMT</pubDate><guid isPermaLink="true">10.1002/adma.202513365</guid></item><item><title>[Wiley: Advanced Materials: Table of Contents] Generative Artificial Intelligence Navigated Development of Solvents for Next Generation High‐Performance Magnesium Batteries</title><link>https://advanced.onlinelibrary.wiley.com/doi/10.1002/adma.202510083?af=R</link><description>Advanced Materials, Volume 38, Issue 1, 2 January 2026.</description><author>Wiley: Advanced Materials: Table of Contents</author><pubDate>Sat, 03 Jan 2026 06:20:51 GMT</pubDate><guid isPermaLink="true">10.1002/adma.202510083</guid></item><item><title>[Wiley: Angewandte Chemie International Edition: Table of Contents] Generality‐Driven Optimization of Enantio‐ and Regioselective Mono‐Reduction of 1,2‐Dicarbonyls by High‐Throughput Experimentation and Machine Learning</title><link>https://onlinelibrary.wiley.com/doi/10.1002/anie.202519425?af=R</link><description>Angewandte Chemie International Edition, Volume 65, Issue 1, 2 January 2026.</description><author>Wiley: Angewandte Chemie International Edition: Table of Contents</author><pubDate>Sat, 03 Jan 2026 06:15:46 GMT</pubDate><guid isPermaLink="true">10.1002/anie.202519425</guid></item><item><title>[Wiley: Angewandte Chemie International Edition: Table of Contents] An All‐Solid‐State Li–Cu Battery via Cuprous/Lithium‐Ion Halide Solid Electrolyte</title><link>https://onlinelibrary.wiley.com/doi/10.1002/anie.202518966?af=R</link><description>Angewandte Chemie International Edition, Volume 65, Issue 1, 2 January 2026.</description><author>Wiley: Angewandte Chemie International Edition: Table of Contents</author><pubDate>Sat, 03 Jan 2026 06:15:46 GMT</pubDate><guid isPermaLink="true">10.1002/anie.202518966</guid></item><item><title>[iScience] AI-Driven Routing and Layered Architectures for Intelligent ICT in Nanosensor Networked Systems</title><link>https://www.cell.com/iscience/fulltext/S2589-0042(26)00001-5?rss=yes</link><description>This review examines the emerging integration of nanosensor networks with modern information and communication technologies to address critical needs in healthcare, environmental monitoring, and smart infrastructure. It evaluates how machine learning and artificial intelligence techniques improve data processing, energy management, real-time communication, and scalable system coordination within nanosensor environments. The analysis compares major learning approaches, including supervised, unsupervised, reinforcement, and deep learning methods, and highlights their effectiveness in data routing, anomaly detection, security, and predictive maintenance.</description><author>iScience</author><pubDate>Sat, 03 Jan 2026 00:00:00 GMT</pubDate><guid isPermaLink="true">https://www.cell.com/iscience/fulltext/S2589-0042(26)00001-5?rss=yes</guid></item><item><title>[ChemRxiv] The growing role of open source software in molecular modeling</title><link>https://dx.doi.org/10.26434/chemrxiv-2026-6n5lz?rft_dat=source%3Ddrss</link><description>The increasing importance and predictive power of modern molecular modeling, driven by physics- and machine learning-based methods, necessitates a new collaborative architecture to replace the isolated, traditional model of software development. The traditional approach often led to redundant engineering effort, high costs, and opaque systems that limit reproducibility, independent scrutiny, and scientific independence.  
+<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>Sun, 04 Jan 2026 12:39:06 GMT</lastBuildDate><generator>rfeed v1.1.1</generator><docs>https://github.com/svpino/rfeed/blob/master/README.md</docs><item><title>[ScienceDirect Publication: Artificial Intelligence Chemistry] Accelerated green material and solvent discovery with chemistry- and physics-guided generative AI</title><link>https://www.sciencedirect.com/science/article/pii/S2949747725000235?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: Available online 2 January 2026&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; Artificial Intelligence Chemistry&lt;/p&gt;&lt;p&gt;Author(s): Eslam G. Al-Sakkari, Ahmed Ragab, Marzouk Benali, Olumoye Ajao, Daria C Boffito, Hanane Dagdougui&lt;/p&gt;</description><author>ScienceDirect Publication: Artificial Intelligence Chemistry</author><pubDate>Sat, 03 Jan 2026 12:38:39 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S2949747725000235</guid></item><item><title>[Wiley: Angewandte Chemie International Edition: Table of Contents] Minutes‐Scale Ultrafast Synthesis of New Oxyhalides Solid Electrolytes with Interfacial Ionic Conduction for All‐Solid‐State Batteries</title><link>https://onlinelibrary.wiley.com/doi/10.1002/anie.202516259?af=R</link><description>Angewandte Chemie International Edition, Volume 65, Issue 1, 2 January 2026.</description><author>Wiley: Angewandte Chemie International Edition: Table of Contents</author><pubDate>Sat, 03 Jan 2026 06:30:47 GMT</pubDate><guid isPermaLink="true">10.1002/anie.202516259</guid></item><item><title>[Wiley: Advanced Materials: Table of Contents] Potential‐Gated Polymer Integrates Reversible Ion Transport and Storage for solid‐state Batteries</title><link>https://advanced.onlinelibrary.wiley.com/doi/10.1002/adma.202513365?af=R</link><description>Advanced Materials, Volume 38, Issue 1, 2 January 2026.</description><author>Wiley: Advanced Materials: Table of Contents</author><pubDate>Sat, 03 Jan 2026 06:20:51 GMT</pubDate><guid isPermaLink="true">10.1002/adma.202513365</guid></item><item><title>[Wiley: Advanced Materials: Table of Contents] Generative Artificial Intelligence Navigated Development of Solvents for Next Generation High‐Performance Magnesium Batteries</title><link>https://advanced.onlinelibrary.wiley.com/doi/10.1002/adma.202510083?af=R</link><description>Advanced Materials, Volume 38, Issue 1, 2 January 2026.</description><author>Wiley: Advanced Materials: Table of Contents</author><pubDate>Sat, 03 Jan 2026 06:20:51 GMT</pubDate><guid isPermaLink="true">10.1002/adma.202510083</guid></item><item><title>[Wiley: Angewandte Chemie International Edition: Table of Contents] Generality‐Driven Optimization of Enantio‐ and Regioselective Mono‐Reduction of 1,2‐Dicarbonyls by High‐Throughput Experimentation and Machine Learning</title><link>https://onlinelibrary.wiley.com/doi/10.1002/anie.202519425?af=R</link><description>Angewandte Chemie International Edition, Volume 65, Issue 1, 2 January 2026.</description><author>Wiley: Angewandte Chemie International Edition: Table of Contents</author><pubDate>Sat, 03 Jan 2026 06:15:46 GMT</pubDate><guid isPermaLink="true">10.1002/anie.202519425</guid></item><item><title>[Wiley: Angewandte Chemie International Edition: Table of Contents] An All‐Solid‐State Li–Cu Battery via Cuprous/Lithium‐Ion Halide Solid Electrolyte</title><link>https://onlinelibrary.wiley.com/doi/10.1002/anie.202518966?af=R</link><description>Angewandte Chemie International Edition, Volume 65, Issue 1, 2 January 2026.</description><author>Wiley: Angewandte Chemie International Edition: Table of Contents</author><pubDate>Sat, 03 Jan 2026 06:15:46 GMT</pubDate><guid isPermaLink="true">10.1002/anie.202518966</guid></item><item><title>[iScience] AI-Driven Routing and Layered Architectures for Intelligent ICT in Nanosensor Networked Systems</title><link>https://www.cell.com/iscience/fulltext/S2589-0042(26)00001-5?rss=yes</link><description>This review examines the emerging integration of nanosensor networks with modern information and communication technologies to address critical needs in healthcare, environmental monitoring, and smart infrastructure. It evaluates how machine learning and artificial intelligence techniques improve data processing, energy management, real-time communication, and scalable system coordination within nanosensor environments. The analysis compares major learning approaches, including supervised, unsupervised, reinforcement, and deep learning methods, and highlights their effectiveness in data routing, anomaly detection, security, and predictive maintenance.</description><author>iScience</author><pubDate>Sat, 03 Jan 2026 00:00:00 GMT</pubDate><guid isPermaLink="true">https://www.cell.com/iscience/fulltext/S2589-0042(26)00001-5?rss=yes</guid></item><item><title>[ChemRxiv] The growing role of open source software in molecular modeling</title><link>https://dx.doi.org/10.26434/chemrxiv-2026-6n5lz?rft_dat=source%3Ddrss</link><description>The increasing importance and predictive power of modern molecular modeling, driven by physics- and machine learning-based methods, necessitates a new collaborative architecture to replace the isolated, traditional model of software development. The traditional approach often led to redundant engineering effort, high costs, and opaque systems that limit reproducibility, independent scrutiny, and scientific independence.  
 
 This perspective advocates for permissively licensed open source software as a scientific and economic multiplier by reducing the duplication of effort, enabling scientific validation of modeling tools, and frictionless experimentation with new ideas. Coordinated, multi-project consortia, such as Open Force Field, Open Free Energy, OpenFold, and OpenADMET have formed to collaboratively build shared computational infrastructure and release all methods under permissive licenses. The success of these large-scale efforts requires organizational structures that extend beyond code. The Open Molecular Software Foundation (OMSF), a US nonprofit, serves as a domain-specific institutional home and fiscal sponsor. By providing governance, administrative infrastructure, and dedicated research software engineers, OMSF aligns incentives across academic and industrial stakeholders. This framework enables a synergistic ecosystem where projects interoperate to accelerate innovation, eliminate duplication, and ensure long-term software sustainability, thereby creating durable foundations that elevate the entire molecular modeling community.</description><author>ChemRxiv</author><pubDate>Sat, 03 Jan 2026 00:00:00 GMT</pubDate><guid isPermaLink="true">https://dx.doi.org/10.26434/chemrxiv-2026-6n5lz?rft_dat=source%3Ddrss</guid></item><item><title>[Journal of the American Chemical Society: Latest Articles (ACS Publications)] [ASAP] Tracing Lithophilic Sites: In Situ Nanovisualization of Their Migration and Degradation in All-Solid-State Lithium Batteries</title><link>http://dx.doi.org/10.1021/jacs.5c19144</link><description>&lt;p&gt;&lt;img alt="TOC Graphic" src="https://pubs.acs.org/cms/10.1021/jacs.5c19144/asset/images/medium/ja5c19144_0006.gif" /&gt;&lt;/p&gt;&lt;div&gt;&lt;cite&gt;Journal of the American Chemical Society&lt;/cite&gt;&lt;/div&gt;&lt;div&gt;DOI: 10.1021/jacs.5c19144&lt;/div&gt;</description><author>Journal of the American Chemical Society: Latest Articles (ACS Publications)</author><pubDate>Fri, 02 Jan 2026 13:23:31 GMT</pubDate><guid isPermaLink="true">http://dx.doi.org/10.1021/jacs.5c19144</guid></item><item><title>[Wiley: Advanced Functional Materials: Table of Contents] Metal−Organic Framework Ion Conductor‐Based Polymer Solid Electrolytes for Long‐Cycle Lithium Batteries</title><link>https://advanced.onlinelibrary.wiley.com/doi/10.1002/adfm.202511014?af=R</link><description>Advanced Functional Materials, Volume 36, Issue 1, 2 January 2026.</description><author>Wiley: Advanced Functional Materials: Table of Contents</author><pubDate>Fri, 02 Jan 2026 11:53:16 GMT</pubDate><guid isPermaLink="true">10.1002/adfm.202511014</guid></item><item><title>[Wiley: Small: Table of Contents] Regulating Interface Chemistry to Construct a Stable Solid Electrolyte Interphase for Long‐Life Zinc Metal Anodes</title><link>https://onlinelibrary.wiley.com/doi/10.1002/smll.202511310?af=R</link><description>Small, Volume 22, Issue 1, 2 January 2026.</description><author>Wiley: Small: Table of Contents</author><pubDate>Fri, 02 Jan 2026 11:26:58 GMT</pubDate><guid isPermaLink="true">10.1002/smll.202511310</guid></item><item><title>[Recent Articles in Phys. Rev. Lett.] Common Sublattice-Pure Van Hove Singularities in the Kagome Superconductors $A{\mathrm{V}}_{3}{\mathrm{Sb}}_{5}$ ($A=\mathrm{K}$, Rb, Cs)</title><link>http://link.aps.org/doi/10.1103/njg9-jpkh</link><description>Author(s): Yujie Lan, Yuhao Lei, Congcong Le, Brenden R. Ortiz, Nicholas C. Plumb, Milan Radovic, Xianxin Wu, Ming Shi, Stephen D. Wilson, and Yong Hu&lt;br /&gt;&lt;p&gt;Kagome materials offer a versatile platform for exploring correlated and topological quantum states, where Van Hove singularities (VHSs) play a pivotal role in driving electronic instabilities, exhibiting distinct behaviors depending on electron filling and interaction settings. In the recently disc…&lt;/p&gt;&lt;br /&gt;[Phys. Rev. Lett. 136, 016401] Published Fri Jan 02, 2026</description><author>Recent Articles in Phys. Rev. Lett.</author><pubDate>Fri, 02 Jan 2026 10:00:00 GMT</pubDate><guid isPermaLink="true">http://link.aps.org/doi/10.1103/njg9-jpkh</guid></item><item><title>[Recent Articles in Phys. Rev. Lett.] Half-Quantized Chiral Edge Current in a $C=1/2$ Parity Anomaly State</title><link>http://link.aps.org/doi/10.1103/vxcb-rwbl</link><description>Author(s): Deyi Zhuo, Bomin Zhang, Humian Zhou, Han Tay, Xiaoda Liu, Zhiyuan Xi, Chui-Zhen Chen, and Cui-Zu Chang&lt;br /&gt;&lt;p&gt;A single massive Dirac surface band is predicted to exhibit a half-quantized Hall conductance, a hallmark of the $C=1/2$ parity anomaly state in quantum field theory. Experimental signatures of the $C=1/2$ parity anomaly state have been observed in semimagnetic topological insulator (TI) bilayers, y…&lt;/p&gt;&lt;br /&gt;[Phys. Rev. Lett. 136, 016601] Published Fri Jan 02, 2026</description><author>Recent Articles in Phys. Rev. Lett.</author><pubDate>Fri, 02 Jan 2026 10:00:00 GMT</pubDate><guid isPermaLink="true">http://link.aps.org/doi/10.1103/vxcb-rwbl</guid></item><item><title>[Wiley: ENERGY &amp; ENVIRONMENTAL MATERIALS: Table of Contents] Synergistic Enhancement of Modified‐PVDF Humidity Sensitivity via Chemical Adsorption‐Ionic Conductivity and its Application in Intelligent Powered Air‐Purifying Respirator</title><link>https://onlinelibrary.wiley.com/doi/10.1002/eem2.70119?af=R</link><description>ENERGY &amp;amp;ENVIRONMENTAL MATERIALS, EarlyView.</description><author>Wiley: ENERGY &amp; ENVIRONMENTAL MATERIALS: Table of Contents</author><pubDate>Fri, 02 Jan 2026 09:41:25 GMT</pubDate><guid isPermaLink="true">10.1002/eem2.70119</guid></item><item><title>[The Journal of Physical Chemistry Letters: Latest Articles (ACS Publications)] [ASAP] In Situ Electric-Field Guided Assembly of Ordered Bilayer Solid Electrolyte Interphase (SEI) Enables High-Current Zinc Metal Anodes</title><link>http://dx.doi.org/10.1021/acs.jpclett.5c03386</link><description>&lt;p&gt;&lt;img alt="TOC Graphic" src="https://pubs.acs.org/cms/10.1021/acs.jpclett.5c03386/asset/images/medium/jz5c03386_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.5c03386&lt;/div&gt;</description><author>The Journal of Physical Chemistry Letters: Latest Articles (ACS Publications)</author><pubDate>Fri, 02 Jan 2026 09:07:52 GMT</pubDate><guid isPermaLink="true">http://dx.doi.org/10.1021/acs.jpclett.5c03386</guid></item><item><title>[Wiley: ENERGY &amp; ENVIRONMENTAL MATERIALS: Table of Contents] Correlating the Interfacial Chemistries With Ion Conduction and Lithium Deactivation in Hybrid Solid Electrolytes</title><link>https://onlinelibrary.wiley.com/doi/10.1002/eem2.70196?af=R</link><description>ENERGY &amp;amp;ENVIRONMENTAL MATERIALS, EarlyView.</description><author>Wiley: ENERGY &amp; ENVIRONMENTAL MATERIALS: Table of Contents</author><pubDate>Fri, 02 Jan 2026 06:03:30 GMT</pubDate><guid isPermaLink="true">10.1002/eem2.70196</guid></item><item><title>[ChemRxiv] Complete Computational Exploration of Eight-Carbon Hydrocarbon Chemical Space</title><link>https://dx.doi.org/10.26434/chemrxiv-2026-qjr5r?rft_dat=source%3Ddrss</link><description>Hydrocarbons are the most fundamental class of chemical species, but even the chemical space of those with eight carbon atoms or less has not been explored exhaustively. Here we report a full enumeration and computational exploration of this space. Density functional theory-based geometry optimisation and energy calculations have identified all stable molecules within this space, forming a new database called CHX8. A universal strain value has been proposed and assigned to each of these molecules, acting as a proxy for synthesisability and providing a clear guideline of how synthetically plausible these molecules could be. This paper explores the limits of chemical space with CHX8, with a focus on trans-fused, unsaturated and anti-Bredt ring systems. We show that, contrary to prevailing wisdom, most of these unconventional structures should be synthetically accessible, with relative strain energies less than that of cubane. It is expected that this dataset will inspire the synthesis of many new molecules with applications in various areas of chemistry, biology and materials science. The resulting dataset also provides a valuable resource for the development of general and robust machine learning models.</description><author>ChemRxiv</author><pubDate>Fri, 02 Jan 2026 00:00:00 GMT</pubDate><guid isPermaLink="true">https://dx.doi.org/10.26434/chemrxiv-2026-qjr5r?rft_dat=source%3Ddrss</guid></item><item><title>[ChemRxiv] A round-robin exercise for the precise prediction of aqueous solubility of organic chemicals using chemometric, machine learning, and stacking ensemble of deep learning models</title><link>https://dx.doi.org/10.26434/chemrxiv-2026-6xb6k?rft_dat=source%3Ddrss</link><description>Aqueous solubility is an important property for assessing the druggability and ecotoxicological effects of molecules. Successful drug candidates should have optimal aqueous solubility to improve bioavailability to target tissues. To effectively screen molecules in a short period of time, reliable predictive models are highly useful. In the present study, we conducted a round-robin exercise using a large, curated dataset of over 6000 compounds to predict aqueous solubility quantitatively. The six participating groups used an array of Machine Learning and Deep Learning algorithms to develop models with strong robustness and external predictive performance. All the models underwent rigorous Leave-One-Out and 10-fold cross-validation. The diversity of training sets and descriptor types used by different groups paved the way for exploring the mechanistic basis for the efficient identification of contributing features. The best-performing model was selected using the statistical Sum of Ranking Differences (SRD) approach, considering the performances on training, cross-validation, and test, as well as the performance difference between the training and test sets. Additionally, a curated, true external set was screened by the six different models. Here, the best-performing model was selected using a consensus ranking strategy based on Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and R_Ext^2. In both approaches, i.e., the inherent model performance in terms of training, test, and cross-validation statistics, and the ability of the model to efficiently predict true external data, the Stacking Ensemble of Deep q-RASPR model emerged as the winner. This model showed comparable predictive performance to the previously reported model, which apparently lacked a proper data curation workflow and contained a significant number of duplicates and mixtures in its dataset, which can inflate model statistics. The insights from the different feature contributions from the different groups identified the useful structural and physicochemical aspects, which can help synthetic chemists to optimize molecules.</description><author>ChemRxiv</author><pubDate>Fri, 02 Jan 2026 00:00:00 GMT</pubDate><guid isPermaLink="true">https://dx.doi.org/10.26434/chemrxiv-2026-6xb6k?rft_dat=source%3Ddrss</guid></item><item><title>[Joule] Seeing the unseen: Real-time tracking of battery cycling-to-failure via surface strain</title><link>https://www.cell.com/joule/fulltext/S2542-4351(25)00453-2?rss=yes</link><description>This study proposes a strain-based approach to address passive failures in lithium-ion batteries, which present spontaneous safety risks often indistinguishable from routine degradation using conventional diagnostics. By establishing a strain-failure correlation, we introduce a slope-based threshold and a failure-proximity index to characterize degradation-to-failure transitions. Incorporating strain-informed machine learning, it effectively detects early failure onset and estimates proximity. This scalable approach is suitable for real-time, onboard monitoring, supporting safer and more reliable battery operation.</description><author>Joule</author><pubDate>Fri, 02 Jan 2026 00:00:00 GMT</pubDate><guid isPermaLink="true">https://www.cell.com/joule/fulltext/S2542-4351(25)00453-2?rss=yes</guid></item><item><title>[ACS Energy Letters: Latest Articles (ACS Publications)] [ASAP] Understanding and Mitigating Lithium Metal Anode Failure in All-Solid-State Batteries with Inorganic Solid Electrolytes</title><link>http://dx.doi.org/10.1021/acsenergylett.5c03333</link><description>&lt;p&gt;&lt;img alt="TOC Graphic" src="https://pubs.acs.org/cms/10.1021/acsenergylett.5c03333/asset/images/medium/nz5c03333_0006.gif" /&gt;&lt;/p&gt;&lt;div&gt;&lt;cite&gt;ACS Energy Letters&lt;/cite&gt;&lt;/div&gt;&lt;div&gt;DOI: 10.1021/acsenergylett.5c03333&lt;/div&gt;</description><author>ACS Energy Letters: Latest Articles (ACS Publications)</author><pubDate>Thu, 01 Jan 2026 18:39:05 GMT</pubDate><guid isPermaLink="true">http://dx.doi.org/10.1021/acsenergylett.5c03333</guid></item><item><title>[ScienceDirect Publication: Computational Materials Science] Accelerating the search for superconductors using machine learning</title><link>https://www.sciencedirect.com/science/article/pii/S0927025625007967?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: February 2026&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; Computational Materials Science, Volume 263&lt;/p&gt;&lt;p&gt;Author(s): Suhas Adiga, Umesh V. Waghmare&lt;/p&gt;</description><author>ScienceDirect Publication: Computational Materials Science</author><pubDate>Thu, 01 Jan 2026 18:29:38 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S0927025625007967</guid></item><item><title>[ScienceDirect Publication: Journal of Catalysis] Machine learning–assisted discovery of chromium bis(2-pyridyl)amine catalysts for ethylene tri-/tetramerization</title><link>https://www.sciencedirect.com/science/article/pii/S0021951725006797?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: February 2026&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; Journal of Catalysis, Volume 454&lt;/p&gt;&lt;p&gt;Author(s): Youcai Zhu, Yue Mu, Xiaoke Shi, Shu Yang, Li Sun, Zhen Liu&lt;/p&gt;</description><author>ScienceDirect Publication: Journal of Catalysis</author><pubDate>Thu, 01 Jan 2026 12:22:12 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S0021951725006797</guid></item><item><title>[ScienceDirect Publication: Journal of Catalysis] The influence of the organic residue and the solvent in the Schlenk equilibrium for Grignard reagents in THF. A molecular dynamics study with machine learning potentials</title><link>https://www.sciencedirect.com/science/article/pii/S0021951725006852?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: February 2026&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; Journal of Catalysis, Volume 454&lt;/p&gt;&lt;p&gt;Author(s): Marco Bortoli, Sigbjørn Løland Bore, Odile Eisenstein, Michele Cascella&lt;/p&gt;</description><author>ScienceDirect Publication: Journal of Catalysis</author><pubDate>Thu, 01 Jan 2026 12:22:12 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S0021951725006852</guid></item><item><title>[ScienceDirect Publication: Journal of Catalysis] Protonation dynamics of confined ethanol–water mixtures in H-ZSM-5 from machine learning-driven metadynamics</title><link>https://www.sciencedirect.com/science/article/pii/S0021951725007249?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: February 2026&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; Journal of Catalysis, Volume 454&lt;/p&gt;&lt;p&gt;Author(s): Princy Jarngal, Benjamin A. Jackson, Simuck F. Yuk, Difan Zhang, Mal-Soon Lee, Maria Cristina Menziani, Vassiliki-Alexandra Glezakou, Roger Rousseau, GiovanniMaria Piccini&lt;/p&gt;</description><author>ScienceDirect Publication: Journal of Catalysis</author><pubDate>Thu, 01 Jan 2026 12:22:12 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S0021951725007249</guid></item><item><title>[ScienceDirect Publication: Acta Materialia] Inverse Design of High-Performance Glasses Through an Encoder-Decoder Machine Learning Approach Toward Materials Discovery: Application to Oxynitride Glasses</title><link>https://www.sciencedirect.com/science/article/pii/S1359645425011693?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: Available online 29 December 2025&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; Acta Materialia&lt;/p&gt;&lt;p&gt;Author(s): Alexis Duval, Eric Robin, Patrick Houizot, Tanguy Rouxel&lt;/p&gt;</description><author>ScienceDirect Publication: Acta Materialia</author><pubDate>Thu, 01 Jan 2026 12:22:12 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S1359645425011693</guid></item><item><title>[ScienceDirect Publication: Acta Materialia] DuctGPT: A Generative Transformer for Forward Screening of Ductile Refractory Multi-Principal Element Alloys</title><link>https://www.sciencedirect.com/science/article/pii/S135964542501050X?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: 1 January 2026&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; Acta Materialia, Volume 304&lt;/p&gt;&lt;p&gt;Author(s): Sai Pranav Reddy Guduru, Mkpe O. Kekung, Ryan T. Ott, Sougata Roy, Prashant Singh&lt;/p&gt;</description><author>ScienceDirect Publication: Acta Materialia</author><pubDate>Thu, 01 Jan 2026 12:22:12 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S135964542501050X</guid></item><item><title>[ScienceDirect Publication: Acta Materialia] On-the-fly machine learning of interatomic potentials for elastic property modeling in Al–Mg–Zr solid solutions</title><link>https://www.sciencedirect.com/science/article/pii/S1359645425011310?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: 15 February 2026&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; Acta Materialia, Volume 305&lt;/p&gt;&lt;p&gt;Author(s): Lukas Volkmer, Leonardo Medrano Sandonas, Philip Grimm, Julia Kristin Hufenbach, Gianaurelio Cuniberti&lt;/p&gt;</description><author>ScienceDirect Publication: Acta Materialia</author><pubDate>Thu, 01 Jan 2026 12:22:12 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S1359645425011310</guid></item><item><title>[ScienceDirect Publication: Journal of Materiomics] Data-augmented machine learning models for oxynitride glasses &lt;em&gt;via&lt;/em&gt; 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Journal of Materiomics&lt;/p&gt;&lt;p&gt;Author(s): Mingyue Yang, Liangyu Mo, Jincheng Qin, Faqiang Zhang, Mingsheng Ma, Yongxiang Li, Zhifu Liu&lt;/p&gt;</description><author>ScienceDirect Publication: Journal of Materiomics</author><pubDate>Thu, 01 Jan 2026 12:21:56 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S2352847825001078</guid></item><item><title>[ScienceDirect Publication: Journal of Materiomics] Domain knowledge-assisted materials data anomaly detection towards constructing high-performance machine learning models</title><link>https://www.sciencedirect.com/science/article/pii/S2352847825000565?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: November 2025&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; Journal of Materiomics, Volume 11, Issue 6&lt;/p&gt;&lt;p&gt;Author(s): Yue Liu, Shuchang Ma, Zhengwei Yang, Duo Wu, Yali Zhao, Maxim Avdeev, Siqi Shi&lt;/p&gt;</description><author>ScienceDirect Publication: Journal of Materiomics</author><pubDate>Thu, 01 Jan 2026 12:21:56 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S2352847825000565</guid></item><item><title>[ScienceDirect Publication: Journal of Materiomics] PTCDA/CuS cathode enabling stable sulfide-based all-solid-state batteries</title><link>https://www.sciencedirect.com/science/article/pii/S2352847825000814?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: January 2026&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; Journal of Materiomics, Volume 12, Issue 1&lt;/p&gt;&lt;p&gt;Author(s): Zhixing Wan, Shuo Wang, Yahao Mu, Ruihua Zhou, Hang Liu, Tingwu Jin, Di Wu, Jianlong Xia, Ce-Wen Nan&lt;/p&gt;</description><author>ScienceDirect Publication: Journal of Materiomics</author><pubDate>Thu, 01 Jan 2026 12:21:56 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S2352847825000814</guid></item><item><title>[ScienceDirect Publication: Current Opinion in Solid State and Materials Science] Solid electrolyte-driven suppression of H2–H3 phase transition in Ni-rich cathodes for stable high-voltage cycling</title><link>https://www.sciencedirect.com/science/article/pii/S1359028625000324?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: December 2025&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; Current Opinion in Solid State and Materials Science, Volume 39&lt;/p&gt;&lt;p&gt;Author(s): Hao Chen, Hsiao-Hsuan Wu, Chia-Chen Li&lt;/p&gt;</description><author>ScienceDirect Publication: Current Opinion in Solid State and Materials Science</author><pubDate>Thu, 01 Jan 2026 12:21:56 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S1359028625000324</guid></item><item><title>[ScienceDirect Publication: Current Opinion in Solid State and Materials Science] State-of-the-art review of additive friction stir deposition: microstructural evolution, machine learning applications, and future directions</title><link>https://www.sciencedirect.com/science/article/pii/S1359028625000300?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: January 2026&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; Current Opinion in Solid State and Materials Science, Volume 40&lt;/p&gt;&lt;p&gt;Author(s): Ashish Kumar, Lei Shi, Virendra Pratap Singh, Sudipta Mohapatra, Long Li, Chuansong Wu, Sergey Mironov, Amitava De&lt;/p&gt;</description><author>ScienceDirect Publication: Current Opinion in Solid State and Materials Science</author><pubDate>Thu, 01 Jan 2026 12:21:56 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S1359028625000300</guid></item><item><title>[ScienceDirect Publication: Journal of Energy Storage] Machine learning-aided prediction and optimization of specific capacitance in functionalized GO-based Mn/Fe co-doped Bi&lt;sub&gt;2&lt;/sub&gt;O&lt;sub&gt;3&lt;/sub&gt; nanocomposites</title><link>https://www.sciencedirect.com/science/article/pii/S2352152X25048285?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: 10 February 2026&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; Journal of Energy Storage, Volume 146&lt;/p&gt;&lt;p&gt;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&lt;/p&gt;</description><author>ScienceDirect Publication: Journal of Energy Storage</author><pubDate>Thu, 01 Jan 2026 12:21:56 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S2352152X25048285</guid></item><item><title>[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</title><link>https://www.sciencedirect.com/science/article/pii/S2352152X25049035?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: 10 February 2026&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; Journal of Energy Storage, Volume 146&lt;/p&gt;&lt;p&gt;Author(s): Jiguo Tu, Yan Li, Libo Chen, Dongbai Sun&lt;/p&gt;</description><author>ScienceDirect Publication: Journal of Energy Storage</author><pubDate>Thu, 01 Jan 2026 12:21:56 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S2352152X25049035</guid></item><item><title>[ScienceDirect Publication: Journal of Energy Storage] Hollow nanofiber ion conductor protective layer on Zn metal anode for long-term stable zinc battery</title><link>https://www.sciencedirect.com/science/article/pii/S2352152X25049953?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: 10 February 2026&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; Journal of Energy Storage, Volume 146&lt;/p&gt;&lt;p&gt;Author(s): Mengfei Sun, Zumin Zhang, Yang Su, Wensheng Yu, Xiangting Dong, Dongtao Liu, Xinlu Wang, Gaopeng Li, Jinxian Wang&lt;/p&gt;</description><author>ScienceDirect Publication: Journal of Energy Storage</author><pubDate>Thu, 01 Jan 2026 12:21:56 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S2352152X25049953</guid></item><item><title>[ScienceDirect Publication: Journal of Energy Storage] Alkaline-compatible polyaniline/graphene negative electrode for ultrahigh-energy all-solid-state asymmetric supercapacitors</title><link>https://www.sciencedirect.com/science/article/pii/S2352152X25048844?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: 10 February 2026&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; Journal of Energy Storage, Volume 146&lt;/p&gt;&lt;p&gt;Author(s): Aizhen Xu, Li Yin, Shaoqing Zhang, Zhiyi Zhao, Wenna Lv, Yuanyu Zhu, Yujun Qin&lt;/p&gt;</description><author>ScienceDirect Publication: Journal of Energy Storage</author><pubDate>Thu, 01 Jan 2026 12:21:56 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S2352152X25048844</guid></item><item><title>[ScienceDirect Publication: Solid State Ionics] Crossover from insulating into solid electrolyte behavior in bulk CaSO&lt;sub&gt;4&lt;/sub&gt;⋅0.5H&lt;sub&gt;2&lt;/sub&gt;O material due to ion exchange processes induced by high-temperature treatment with orthophosphoric acid</title><link>https://www.sciencedirect.com/science/article/pii/S0167273825003170?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: 1 February 2026&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; Solid State Ionics, Volume 434&lt;/p&gt;&lt;p&gt;Author(s): Ivan Nikulin, Tatiana Nikulicheva, Vitaly Vyazmin, Oleg Ivanov, Nikita Anosov, Olga Telpova&lt;/p&gt;</description><author>ScienceDirect Publication: Solid State Ionics</author><pubDate>Thu, 01 Jan 2026 12:21:54 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S0167273825003170</guid></item><item><title>[ScienceDirect Publication: Solid State Ionics] First-principles elucidation of the effects of Al-doping on Li-ion diffusion in LiCoO&lt;sub&gt;2&lt;/sub&gt;</title><link>https://www.sciencedirect.com/science/article/pii/S0167273825003224?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: 1 February 2026&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; Solid State Ionics, Volume 434&lt;/p&gt;&lt;p&gt;Author(s): Jordan A. Barr, Scott P. Beckman, Brandon C. Wood, Liwen F. Wan&lt;/p&gt;</description><author>ScienceDirect Publication: Solid State Ionics</author><pubDate>Thu, 01 Jan 2026 12:21:54 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S0167273825003224</guid></item><item><title>[ScienceDirect Publication: Solid State Ionics] Anion engineering enhances the electrochemical performance of Li&lt;sub&gt;7&lt;/sub&gt;P&lt;sub&gt;3&lt;/sub&gt;S&lt;sub&gt;11&lt;/sub&gt; solid electrolyte</title><link>https://www.sciencedirect.com/science/article/pii/S0167273825003236?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: 15 February 2026&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; Solid State Ionics, Volume 435&lt;/p&gt;&lt;p&gt;Author(s): D. 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Crone&lt;/p&gt;</description><author>ScienceDirect Publication: Computational Materials Science</author><pubDate>Thu, 01 Jan 2026 12:21:54 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S0927025625007207</guid></item><item><title>[ScienceDirect Publication: Computational Materials Science] Predicting hydrogen storage capacity of metal hydrides using novel imputation techniques and tree-based machine learning models</title><link>https://www.sciencedirect.com/science/article/pii/S0927025625007335?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: 30 January 2026&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; Computational Materials Science, Volume 262&lt;/p&gt;&lt;p&gt;Author(s): Zaid Allal, Hassan N. Noura, Flavien Vernier, Ola Salman, Khaled Chahine&lt;/p&gt;</description><author>ScienceDirect Publication: Computational Materials Science</author><pubDate>Thu, 01 Jan 2026 12:21:54 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S0927025625007335</guid></item><item><title>[ScienceDirect Publication: Computational Materials Science] Accelerating magnetic materials discovery using interaction matrix-based machine learning descriptors</title><link>https://www.sciencedirect.com/science/article/pii/S0927025625007384?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: 30 January 2026&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; Computational Materials Science, Volume 262&lt;/p&gt;&lt;p&gt;Author(s): Apoorv Verma, Junaid Jami, Amrita Bhattacharya&lt;/p&gt;</description><author>ScienceDirect Publication: Computational Materials Science</author><pubDate>Thu, 01 Jan 2026 12:21:54 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S0927025625007384</guid></item><item><title>[ScienceDirect Publication: Computational Materials Science] Effects of training machine-learning potentials for radiation damage simulations using different pseudopotentials</title><link>https://www.sciencedirect.com/science/article/pii/S0927025625007414?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: 30 January 2026&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; Computational Materials Science, Volume 262&lt;/p&gt;&lt;p&gt;Author(s): A. Fellman, J. Byggmästar, F. Granberg, F. Djurabekova, K. Nordlund&lt;/p&gt;</description><author>ScienceDirect Publication: Computational Materials Science</author><pubDate>Thu, 01 Jan 2026 12:21:54 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S0927025625007414</guid></item><item><title>[ScienceDirect Publication: Computational Materials Science] Structure-driven prediction and mechanism insights into piezoelectric performance of potassium sodium niobate via interpretable machine learning</title><link>https://www.sciencedirect.com/science/article/pii/S0927025625007530?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: February 2026&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; Computational Materials Science, Volume 263&lt;/p&gt;&lt;p&gt;Author(s): Hui Li, WenKe Lu, Chunlei Li, Jinyi Liu, Zihui Feng, Jiaming Liu, Lan Yang&lt;/p&gt;</description><author>ScienceDirect Publication: Computational Materials Science</author><pubDate>Thu, 01 Jan 2026 12:21:54 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S0927025625007530</guid></item><item><title>[ScienceDirect Publication: Computational Materials Science] Band structure modulation of germanium under arbitrary strain directions: A combined approach of strain matrix theory, first-principles calculation and machine learning</title><link>https://www.sciencedirect.com/science/article/pii/S0927025625007694?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: February 2026&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; Computational Materials Science, Volume 263&lt;/p&gt;&lt;p&gt;Author(s): Hai Wang, Wenqi Huang, Mengjiang Jia&lt;/p&gt;</description><author>ScienceDirect Publication: Computational Materials Science</author><pubDate>Thu, 01 Jan 2026 12:21:54 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S0927025625007694</guid></item><item><title>[ScienceDirect Publication: Computational Materials Science] Machine learning-driven prognostication of multifunctional properties of (K,Na)NbO&lt;sub&gt;3&lt;/sub&gt;-based lead-free ceramics for optimized materials design</title><link>https://www.sciencedirect.com/science/article/pii/S0927025625007803?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: February 2026&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; Computational Materials Science, Volume 263&lt;/p&gt;&lt;p&gt;Author(s): Manisha Kumari, Alok Shukla&lt;/p&gt;</description><author>ScienceDirect Publication: Computational Materials Science</author><pubDate>Thu, 01 Jan 2026 12:21:54 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S0927025625007803</guid></item><item><title>[ScienceDirect Publication: Computational Materials Science] Machine learning for domain transfer between simulated and experimental 2D X-ray diffraction patterns using generative adversarial networks</title><link>https://www.sciencedirect.com/science/article/pii/S0927025625007724?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: February 2026&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; Computational Materials Science, Volume 263&lt;/p&gt;&lt;p&gt;Author(s): Samantha J. Brozak, David Montes de Oca Zapiain, Brendan Donohoe, Tommy Ao, Nathan P. Brown, Marcus D. Knudson, Carianne Martinez, J. Matthew D. 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Computational Materials Science, Volume 263&lt;/p&gt;&lt;p&gt;Author(s): Mahalaxmi Chandramohan, Hridhya Vinod, Meenal Deo&lt;/p&gt;</description><author>ScienceDirect Publication: Computational Materials Science</author><pubDate>Thu, 01 Jan 2026 12:21:54 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S0927025625008110</guid></item><item><title>[ScienceDirect Publication: Artificial Intelligence Chemistry] Machine Learning (ML)-driven quantitative structure-pharmacokinetic relationship (QSPKR) modeling of the tissue-to-plasma partition coefficient (K&lt;sub&gt;p&lt;/sub&gt;) of drugs across different tissues</title><link>https://www.sciencedirect.com/science/article/pii/S2949747725000107?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: December 2025&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; Artificial Intelligence Chemistry, Volume 3, Issue 2&lt;/p&gt;&lt;p&gt;Author(s): Souvik Pore, Kunal Roy&lt;/p&gt;</description><author>ScienceDirect Publication: Artificial Intelligence Chemistry</author><pubDate>Thu, 01 Jan 2026 12:21:54 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S2949747725000107</guid></item><item><title>[ScienceDirect Publication: Artificial Intelligence Chemistry] Machine learning prediction of pKa of organic acids</title><link>https://www.sciencedirect.com/science/article/pii/S2949747725000090?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: December 2025&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; 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Science Bulletin, Volume 70, Issue 24&lt;/p&gt;&lt;p&gt;Author(s): Xinpeng Hu, Mingxiang Liu, Xuemei Fu, Guangming Tao, Xiang Lu, Jinping Qu&lt;/p&gt;</description><author>ScienceDirect Publication: Science Bulletin</author><pubDate>Thu, 01 Jan 2026 12:21:54 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S2095927325011235</guid></item><item><title>[ScienceDirect Publication: Progress in Materials Science] The role of protein content in body fluids in magnesium alloy bioimplant degradation: A machine learning approach</title><link>https://www.sciencedirect.com/science/article/pii/S0079642525002166?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: April 2026&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; Progress in Materials Science, Volume 158&lt;/p&gt;&lt;p&gt;Author(s): M.N. 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Singh Raman, Alankar Alankar&lt;/p&gt;</description><author>ScienceDirect Publication: Progress in Materials Science</author><pubDate>Thu, 01 Jan 2026 12:21:51 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S0079642525002166</guid></item><item><title>[ScienceDirect Publication: Materials Today Physics] Machine-learning potentials for quantum and anharmonic effects in superconducting &lt;math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si1.svg" class="math"&gt;&lt;mrow&gt;&lt;mi mathvariant="bold-italic"&gt;F&lt;/mi&gt;&lt;mi mathvariant="bold-italic"&gt;m&lt;/mi&gt;&lt;mover accent="true"&gt;&lt;mn mathvariant="bold"&gt;3&lt;/mn&gt;&lt;mo&gt;‾&lt;/mo&gt;&lt;/mover&gt;&lt;mi mathvariant="bold-italic"&gt;m&lt;/mi&gt;&lt;/mrow&gt;&lt;/math&gt; LaBeH&lt;sub&gt;8&lt;/sub&gt;</title><link>https://www.sciencedirect.com/science/article/pii/S2542529325002950?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: December 2025&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; Materials Today Physics, Volume 59&lt;/p&gt;&lt;p&gt;Author(s): Guiyan Dong, Tian Cui, Zihao Huo, Zhengtao Liu, Wenxuan Chen, Pugeng Hou, Yue-Wen Fang, Defang Duan&lt;/p&gt;</description><author>ScienceDirect Publication: Materials Today Physics</author><pubDate>Thu, 01 Jan 2026 12:21:49 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S2542529325002950</guid></item><item><title>[ScienceDirect Publication: Materials Today Physics] A computational framework for interface design using lattice matching, machine learning potentials, and active learning: A case study on LaCoO&lt;sub&gt;3&lt;/sub&gt;/La&lt;sub&gt;2&lt;/sub&gt;NiO&lt;sub&gt;4&lt;/sub&gt;</title><link>https://www.sciencedirect.com/science/article/pii/S2542529325002962?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: December 2025&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; Materials Today Physics, Volume 59&lt;/p&gt;&lt;p&gt;Author(s): Guangchen Liu, Songge Yang, Yu Zhong&lt;/p&gt;</description><author>ScienceDirect Publication: Materials Today Physics</author><pubDate>Thu, 01 Jan 2026 12:21:49 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S2542529325002962</guid></item><item><title>[ScienceDirect Publication: Materials Today Physics] Tackling dataset curation challenges towards reliable machine learning: a case study on thermoelectric materials</title><link>https://www.sciencedirect.com/science/article/pii/S2542529325003049?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: December 2025&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; Materials Today Physics, Volume 59&lt;/p&gt;&lt;p&gt;Author(s): Shoeb Athar, Adrien Mecibah, Philippe Jund&lt;/p&gt;</description><author>ScienceDirect Publication: Materials Today Physics</author><pubDate>Thu, 01 Jan 2026 12:21:49 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S2542529325003049</guid></item><item><title>[ScienceDirect Publication: Materials Today Physics] Research progress of machine learning in flexible strain sensors in the context of material intelligence</title><link>https://www.sciencedirect.com/science/article/pii/S2542529325002883?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: December 2025&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; Materials Today Physics, Volume 59&lt;/p&gt;&lt;p&gt;Author(s): Jie Li, Zhe Li, Yan Lu, Gang Ye, Yan Hong, Li Niu, Jian Fang&lt;/p&gt;</description><author>ScienceDirect Publication: Materials Today Physics</author><pubDate>Thu, 01 Jan 2026 12:21:49 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S2542529325002883</guid></item><item><title>[ScienceDirect Publication: Materials Today Physics] A physics-informed machine learning framework for unified prediction of superconducting transition temperatures</title><link>https://www.sciencedirect.com/science/article/pii/S254252932500327X?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: January 2026&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; Materials Today Physics, Volume 60&lt;/p&gt;&lt;p&gt;Author(s): Ehsan Alibagheri, Mohammad Sandoghchi, Alireza Seyfi, Mohammad Khazaei, S. 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Materials Today&lt;/p&gt;&lt;p&gt;Author(s): Hwa-Jung Kim, Jong Hoon Kim, Minseo Choi, Jung Hyun Kim, Hosun Shin, Ki Chang Kwon, Sun Hwa Park, Hyun Min Park, Seokhee Lee, Young Heon Kim, Hyeokjun Park, Seung-Wook Baek&lt;/p&gt;</description><author>ScienceDirect Publication: Materials Today</author><pubDate>Thu, 01 Jan 2026 12:21:49 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S1369702125005139</guid></item><item><title>[ScienceDirect Publication: Nano Energy] Monoclinic Li&lt;sub&gt;2&lt;/sub&gt;ZrO&lt;sub&gt;3&lt;/sub&gt; with cationic vacancy–based ion transport channels enhanced composite polymer electrolytes for high-rate solid-state lithium metal batteries</title><link>https://www.sciencedirect.com/science/article/pii/S2211285525009309?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: January 2026&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; Nano Energy, Volume 147&lt;/p&gt;&lt;p&gt;Author(s): Qianyi Xu, Yanru Wang, Xiang Feng, Timing Fang, Xueyan Li, Longzhou Zhang, Lijie Zhang, Daohao Li, Dongjiang Yang&lt;/p&gt;</description><author>ScienceDirect Publication: Nano Energy</author><pubDate>Thu, 01 Jan 2026 12:21:46 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S2211285525009309</guid></item><item><title>[ScienceDirect Publication: Nano Energy] Sulfonated ether-free polybenzimidazole membrane with fast and selective ion transport enabling ultrahigh cycle stability in vanadium redox flow batteries</title><link>https://www.sciencedirect.com/science/article/pii/S2211285525009292?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: January 2026&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; Nano Energy, Volume 147&lt;/p&gt;&lt;p&gt;Author(s): Hui Yan, Wei Wei, Xin Li, Qi-an Zhang, Ying Li, Ao Tang&lt;/p&gt;</description><author>ScienceDirect Publication: Nano Energy</author><pubDate>Thu, 01 Jan 2026 12:21:46 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S2211285525009292</guid></item><item><title>[ScienceDirect Publication: Nano Energy] Calendar aging of sulfide all-solid-state batteries</title><link>https://www.sciencedirect.com/science/article/pii/S2211285525009358?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: January 2026&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; Nano Energy, Volume 147&lt;/p&gt;&lt;p&gt;Author(s): Yujing Wu, Ziqi Zhang, Dengxu Wu, Fuqiang Xu, Mu Zhou, Hong Li, Liquan Chen, Fan Wu&lt;/p&gt;</description><author>ScienceDirect Publication: Nano Energy</author><pubDate>Thu, 01 Jan 2026 12:21:46 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S2211285525009358</guid></item><item><title>[ScienceDirect Publication: Nano Energy] Energy-efficient, high-accuracy sensing in loose-fitting textile sensor matrix for LLM-enabled human-robot collaboration</title><link>https://www.sciencedirect.com/science/article/pii/S2211285525009425?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: January 2026&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; Nano Energy, Volume 147&lt;/p&gt;&lt;p&gt;Author(s): Pengfei Deng, Yang Meng, Qilong Cheng, Yuanqiu Tan, Zhihong Chen, Tian Li&lt;/p&gt;</description><author>ScienceDirect Publication: Nano Energy</author><pubDate>Thu, 01 Jan 2026 12:21:46 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S2211285525009425</guid></item><item><title>[ScienceDirect Publication: Nano Energy] Lithium superionic solid electrolyte: Phosphorus-free sulfide glass of LiSbGe&lt;sub&gt;(4-x)/4&lt;/sub&gt;S&lt;sub&gt;4-x&lt;/sub&gt;Cl&lt;sub&gt;x&lt;/sub&gt;</title><link>https://www.sciencedirect.com/science/article/pii/S2211285525009620?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: January 2026&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; Nano Energy, Volume 147&lt;/p&gt;&lt;p&gt;Author(s): Yuna Kim, Woojung Lee, Jiyun Han, Yeong Mu Seo, Dokyung Kim, Young Joo Lee, Byung Gon Kim, Munseok S. Chae, Sung Jin Kim, In Young Kim&lt;/p&gt;</description><author>ScienceDirect Publication: Nano Energy</author><pubDate>Thu, 01 Jan 2026 12:21:46 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S2211285525009620</guid></item><item><title>[ScienceDirect Publication: Nano Energy] Advancing high-safety and low-cost all-solid-state batteries with polyanion cathodes: Challenges and recent progress</title><link>https://www.sciencedirect.com/science/article/pii/S2211285525009978?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: February 2026&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; Nano Energy, Volume 148&lt;/p&gt;&lt;p&gt;Author(s): Ali Yaghtin, Atiyeh Nekahi, Jeremy I.G. Dawkins, Xia Li, Karim Zaghib, Sixu Deng&lt;/p&gt;</description><author>ScienceDirect Publication: Nano Energy</author><pubDate>Thu, 01 Jan 2026 12:21:46 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S2211285525009978</guid></item><item><title>[ScienceDirect Publication: Nano Energy] Enabling high-accuracy lithium-ion battery status prediction via machine learning-integrated perovskite sensors</title><link>https://www.sciencedirect.com/science/article/pii/S2211285525009851?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: February 2026&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; Nano Energy, Volume 148&lt;/p&gt;&lt;p&gt;Author(s): Jiaxin Sun, Xianjie Xu, Zhefu Mu, Zijun Huang, Guo Chen, Xinkai Qi, Hongwei Liu, Lei Zhu, Xiuquan Gu, Xinjian He, Sheng Huang&lt;/p&gt;</description><author>ScienceDirect Publication: Nano Energy</author><pubDate>Thu, 01 Jan 2026 12:21:46 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S2211285525009851</guid></item><item><title>[ScienceDirect Publication: Nano Energy] Phase boundary engineering in micro-sized Sn/SnSb anode enabling superior sodium storage: Synergistic stress relief and fast ion transport</title><link>https://www.sciencedirect.com/science/article/pii/S2211285525010249?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: February 2026&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; Nano Energy, Volume 148&lt;/p&gt;&lt;p&gt;Author(s): Yuhong Liang, Chengcheng He, Zhengyang Zhao, Longqing Zhang, Rui Sun, Qian Ning, Huibing He, Yang Ren, Jing Xu, Qiang Zhang, Yajie Song, Xucai Yin&lt;/p&gt;</description><author>ScienceDirect Publication: Nano Energy</author><pubDate>Thu, 01 Jan 2026 12:21:46 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S2211285525010249</guid></item><item><title>[ScienceDirect Publication: Matter] Machine learning-driven ligand engineering decodes and controls structural distortions in 2D perovskites</title><link>https://www.sciencedirect.com/science/article/pii/S2590238525005259?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: Available online 10 October 2025&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; Matter&lt;/p&gt;&lt;p&gt;Author(s): Zhipeng Miao, Yahui Han, Qi Pan, Yipei Wang, Haibin Wang, Yunhang Xie, Jie Yu, Yapeng Shi, Rui Zhang, Yanlin Song, Pengwei Li&lt;/p&gt;</description><author>ScienceDirect Publication: Matter</author><pubDate>Thu, 01 Jan 2026 12:21:46 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S2590238525005259</guid></item><item><title>[ScienceDirect Publication: Matter] SpectroGen: A physically informed generative artificial intelligence for accelerated cross-modality spectroscopic materials characterization</title><link>https://www.sciencedirect.com/science/article/pii/S2590238525004771?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: Available online 14 October 2025&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; Matter&lt;/p&gt;&lt;p&gt;Author(s): Yanmin Zhu, Loza F. Tadesse&lt;/p&gt;</description><author>ScienceDirect Publication: Matter</author><pubDate>Thu, 01 Jan 2026 12:21:46 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S2590238525004771</guid></item><item><title>[ScienceDirect Publication: Matter] Precisely deciphering solid electrolyte interphase</title><link>https://www.sciencedirect.com/science/article/pii/S2590238525004114?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: 5 November 2025&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; Matter, Volume 8, Issue 11&lt;/p&gt;&lt;p&gt;Author(s): Enhui Wang, Shaohua Ge, Wenbin Li, Beibei Fu, Fangyi Zhou, Weihua Chen&lt;/p&gt;</description><author>ScienceDirect Publication: Matter</author><pubDate>Thu, 01 Jan 2026 12:21:46 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S2590238525004114</guid></item><item><title>[ScienceDirect Publication: Matter] Rapid scalable plasma processing of thin-film Li–La–Zr–O solid-state electrolytes</title><link>https://www.sciencedirect.com/science/article/pii/S2590238525005119?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: 5 November 2025&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; Matter, Volume 8, Issue 11&lt;/p&gt;&lt;p&gt;Author(s): Gabriel Badillo Crane, Thomas W. Colburn, Sarah E. Holmes, Justus Just, Yi Cui, Reinhold H. Dauskardt&lt;/p&gt;</description><author>ScienceDirect Publication: Matter</author><pubDate>Thu, 01 Jan 2026 12:21:46 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S2590238525005119</guid></item><item><title>[ScienceDirect Publication: Joule] Impact of metallic interlayers at the lithium-Li&lt;sub&gt;6&lt;/sub&gt;PS&lt;sub&gt;5&lt;/sub&gt;Cl solid electrolyte interface</title><link>https://www.sciencedirect.com/science/article/pii/S2542435125003563?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: 19 November 2025&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; Joule, Volume 9, Issue 11&lt;/p&gt;&lt;p&gt;Author(s): Souhardh Kotakadi, Jack Aspinall, Matthew Burton, Yi Liang, Yuichi Aihara, Mauro Pasta&lt;/p&gt;</description><author>ScienceDirect Publication: Joule</author><pubDate>Thu, 01 Jan 2026 12:21:46 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S2542435125003563</guid></item><item><title>[ScienceDirect Publication: Joule] Li–Si compound anodes enabling high-performance all-solid-state Li-ion batteries</title><link>https://www.sciencedirect.com/science/article/pii/S2542435125003769?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: 17 December 2025&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; Joule, Volume 9, Issue 12&lt;/p&gt;&lt;p&gt;Author(s): Do-Hyeon Kim, Young-Han Lee, Jeong-Myeong Yoon, Pugalenthiyar Thondaiman, Byung Chul Kim, In-Chul Choi, Jeong-Hee Choi, Ki-Joon Jeon, Cheol-Min Park&lt;/p&gt;</description><author>ScienceDirect Publication: Joule</author><pubDate>Thu, 01 Jan 2026 12:21:46 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S2542435125003769</guid></item><item><title>[ScienceDirect Publication: Joule] Boosting ionic conductivity of fluoride electrolytes by polyanion coordination chemistry enabling 5 V-Class all-solid-state batteries</title><link>https://www.sciencedirect.com/science/article/pii/S2542435125004143?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: Available online 19 December 2025&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; Joule&lt;/p&gt;&lt;p&gt;Author(s): Huaimin Jin, Xingyu Wang, Simeng Zhang, Xiangzhen Zhu, Chong Liu, Junyi Yue, Jie Qu, Bei Wu, Xu Han, Yueyue Wang, Yang Xu, Han Wu, Liyu Zhou, Mingying Zhang, Hao Lai, Shuo Wang, Jiangwen Liang, Xueliang Sun, Xiaona Li&lt;/p&gt;</description><author>ScienceDirect Publication: Joule</author><pubDate>Thu, 01 Jan 2026 12:21:46 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S2542435125004143</guid></item><item><title>[ScienceDirect Publication: Joule] Machine learning-driven interface material design for high-performance perovskite solar cells with scalability and band-gap universality</title><link>https://www.sciencedirect.com/science/article/pii/S2542435125004453?dgcid=rss_sd_all</link><description>&lt;p&gt;Publication date: Available online 23 December 2025&lt;/p&gt;&lt;p&gt;&lt;b&gt;Source:&lt;/b&gt; Joule&lt;/p&gt;&lt;p&gt;Author(s): Chenyang Zhang, Yuteng Jia, Bingqian Zhang, Qiangqiang Zhao, Ruida Xu, Shuping Pang, Han Wang, Stefaan De Wolf, Kai Wang&lt;/p&gt;</description><author>ScienceDirect Publication: Joule</author><pubDate>Thu, 01 Jan 2026 12:21:46 GMT</pubDate><guid isPermaLink="true">https://www.sciencedirect.com/science/article/pii/S2542435125004453</guid></item><item><title>[cond-mat updates on arXiv.org] Atomic-scale visualization of d-wave altermagnetism</title><link>https://arxiv.org/abs/2512.24114</link><description>arXiv:2512.24114v1 Announce Type: new 
 Abstract: Altermagnetism is a newly discovered fundamental form of magnetic order, distinct from conventional ferromagnetism and antiferromagnetism. It uniquely exhibits no net magnetization while simultaneously breaking time-reversal symmetry, a combination previously thought to be mutually exclusive. Although its existence and signatures in momentum space have been established, the direct real-space visualization of its defining rotational symmetry breaking has remained a missing cornerstone. Here, using scanning tunnelling microscopy, we present atomic-scale imaging of electronic states in the candidate material CsV2Se2O. We directly visualize the hallmark symmetry breaking in the form of unidirectional electronic patterns tied to magnetic domain walls and spin defects, as well as elliptical charging rings surrounding those defects. These observed electronic states are all linked to the underlying alternating spin texture. Our work provides the foundational real-space evidence for altermagnetism, moving the field from theoretical and momentum-space probes to direct visual confirmation; thereby opening a path to explore how this unconventional magnetic order couples to and controls other quantum electronic states.</description><author>cond-mat updates on arXiv.org</author><pubDate>Thu, 01 Jan 2026 05:00:00 GMT</pubDate><guid isPermaLink="true">oai:arXiv.org:2512.24114v1</guid></item><item><title>[cond-mat updates on arXiv.org] Insights Into Radiation Damage in YBa$_2$Cu$_3$O$_{7-\delta}$ From Machine-Learned Interatomic Potentials</title><link>https://arxiv.org/abs/2512.24430</link><description>arXiv:2512.24430v1 Announce Type: new