Materials Science

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Overview

Materials science studies how a material’s composition, atomic and microstructure, and processing history shape properties such as strength, conductivity, stability, and catalytic activity. Researchers use machine-learning interatomic potentials and equivariant graph networks to approximate first-principles calculations, physics-informed surrogates to model mechanics and microstructure evolution, and generative models to propose crystals, polymers, and metamaterials. Bayesian active learning and autonomous laboratory systems help select experiments and refine candidates, while X-ray diffraction, microscopy, and synthesis benchmarks test predictions against measurements. A central challenge is ensuring that strong results on curated or simulated data generalize to new materials and real experiments while remaining physically valid, synthesizable, and reproducible.

Latest papers

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306 papers43 papers in the last four weeks, up 65% on the four weeks before. 0.2% of all new papers.

  1. LeMat-Synth: a multi-modal toolbox to curate broad synthesis procedure databases from scientific literature

    Oct 28, 2025Magdalena Lederbauer, Siddharth Betala, Valerie Gentzke +22Document Information ExtractionMaterials Science

    Entalpic · ENSA Lyon UMR-MAP Aria · Independent Researcher +8

  2. Synthesizability Prediction of Crystalline Structures with Structure-Aware Feature Learning and Uncertainty Quantification

    Oct 22, 2025Danial Ebrahimzadeh, Sarah Sharif, Yaser Mike BanadMaterials Property PredictionMaterials Science

    School of Electrical and Computer Engineering, University of Oklahoma, 110 W. Boyd St., Norman, 73019, Oklahoma, USA.

  3. AtomBench: A Benchmarking Framework for Generative Crystal Reconstruction Models in Conventional Superconductors

    Oct 17, 2025Charles Rhys Campbell, Aldo H. Romero, Kamal ChoudharyMaterials ScienceGenerative Modeling

    Department of Physics and Astronomy, West Virginia University, Morgantown, WV 26506, USA · Department of Materials Science and Engineering, Whiting School of Engineering, The Johns Hopkins University, Baltimore, MD 21218, USA · Department of Electrical and Computer Engineering, Whiting School of Engineering, The Johns Hopkins University, Baltimore, MD 21218, USA

  4. Interpretable Nanoporous Materials Design with Symmetry-Aware Networks

    Sep 19, 2025Zhenhao Zhou, Salman Bin Kashif, Jin-Hu Dou +4Interpretable MLMaterials Property Prediction

    Center of Hydrogen Science and School of Materials Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China · Innovation Center for Future Materials, Zhangjiang Institute for Advanced Study, Shanghai Jiao Tong University, Shanghai 201203, China · Department of Chemical and Biological Engineering, University at Buffalo, The State University of New York, Buffalo, New York 14260, United States +3

  5. GenShin: Guiding Rational Liposome Design by Ranking Liposomal Protein Corona through a Docking-Pose-Free GNN

    Mar 16, 2025Pingfei Zhu, Hongyi Liu, Xueyan Liu +2Graph Neural NetworksMaterials Science

    Key Laboratory of symbolic Computation and Knowledge Engineering of ministry of education, Jilin University, Qianjin Street 2699, Changchun, Jilin Province, 130012, China · State Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Sciences, Peking University, Xue Yuan Road 38, Beijing 100191, China

  6. Learning Chern Numbers of Topological Insulators with Gauge Equivariant Neural Networks

    Feb 21, 2025Longde Huang, Oleksandr Balabanov, Hampus Linander +3Equivariant Neural NetworksMaterials Science

    Department of Mathematical Sciences, Chalmers University of Technology and University of Gothenburg, SE-412 96 Gothenburg, Sweden. · Department of Physics, Stockholm University, AlbaNova University Center, SE-106 91 Stockholm, Sweden · VERSES AI Research Lab, Los Angeles, USA +1