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. From Phase Prediction to Phase Design: A ReAct Agent Framework for High-Entropy Alloy Discovery

    Mar 10, 2026Iman Peivaste, Salim BelouettarInverse DesignMaterials Science

    Luxembourg Institute of Science and Technology (LIST), 5, Avenue des Hauts-Fourneaux, Esch-sur-Alzette, 4362, Luxembourg · Department of Physics and Materials Science, University of Luxembourg, L-4365 Esch-sur-Alzette, Luxembourg

  2. Physics-informed neural operator for parametric phase-field modelling of interfacial degradation and microstructural evolution

    Mar 10, 2026Nanxi Chen, Airong Chen, Rujin MaPhysics-Informed Neural OperatorsPDE Surrogate Modeling

    College of Civil Engineering, Tongji University, Shanghai 200092, China

  3. AI-Driven Phase Identification from X-ray Hyperspectral Imaging of cycled Na-ion Cathode Materials

    Mar 8, 2026Fayçal Adrar, Nicolas Folastre, Chloé Pablos +7Materials SciencePhase Transitions

    Laboratoire de Réactivité et de Chimie des Solides (LRCS), CNRS UMR 7314, Université de Picardie Jules Verne, Hub de l’Energie, 15 Rue Baudelocque, Amiens, France · Réseau sur le Stockage Electrochimique de l’Energie (RS2E), CNRS FR 3459, Hub de l’Energie, 15 Rue Baudelocque, Amiens, France · ALISTORE-European Research Institute, CNRS FR 3104, Hub de l’Energie, Rue Baudelocque, Amiens, France +3

  4. Physics-Consistent Neural Networks for Learning Deformation and Director Fields in Microstructured Media with Loss-Based Validation Criteria

    Mar 6, 2026Milad Shirani, Pete H. Gueldner, Murat Khidoyatov +2Structural MechanicsMaterials Science

    Department of Biomedical Engineering, Yale University, New Haven, CT, USA · Department of Mechanical Engineering, Yale University, New Haven, CT, USA

  5. Escaping the Hydrolysis Trap: An Agentic Workflow for Inverse Design of Durable Photocatalytic Covalent Organic Frameworks

    Mar 5, 2026Iman Peivaste, Nicolas D. Boscher, Ahmed Makradi +1Materials ScienceInverse Design

    Luxembourg Institute of Science and Technology (LIST), 5, Avenue des Hauts-Fourneaux, Esch-sur-Alzette, 4362, Luxembourg · Department of Physics and Materials Science, University of Luxembourg, L-4365 Esch-sur-Alzette, Luxembourg

  6. A Soft Robotic Demonstration in the Stratosphere

    Mar 4, 2026Codrin Tugui, Tirth Thakar, Anatol Gogoj +5Soft RoboticsMaterials Science

    University of Connecticut, School of Mechanical, Aerospace, and Manufacturing Engineering, Storrs, Connecticut USA · Institute of Macromolecular Chemistry Petru Poni; Iași, Romania · University of Toronto, Department of Mechanical and Industrial Engineering, Toronto, Ontario, Canada

  7. Field imaging framework for morphological characterization of aggregates with computer vision: Algorithms and applications

    Mar 4, 2026Haohang Huang3D Instance SegmentationInstance Segmentation

    Graduate College of the University of Illinois Urbana-Champaign, Urbana, Illinois

  8. ChemFlow:A Hierarchical Neural Network for Multiscale Representation Learning in Chemical Mixtures

    Mar 3, 2026Jinming Fan, Chao Qian, Wilhelm T. S. Huck +2Molecular Property PredictionMolecular Representation Learning

    College of Chemical and Biological Engineering, Zhejiang Provincial Key Laboratory of Advanced Chemical Engineering Manufacture Technology, Zhejiang University, 310027 Hangzhou (P. R. China) · Institute for Molecules and Materials, Radboud University, Nijmegen, The Netherlands · Institute of Zhejiang University – Quzhou, 324000 Quzhou (P.R. China)

  9. Instant and Reversible Adhesive-free Bonding Between Silicones and Glossy Papers for Soft Robotics

    Mar 3, 2026Takumi Shibuya, Kazuya Murakami, Akitsu Shigetou +1Materials ScienceSoft Robotics

    Department of Mechanical and Intelligent Systems Engineering, The University of Electro-communications, 1-5-1 Chofugaoka, Chofu, Tokyo 182-8585, Japan. · Research Center for Materials Nanoarchitectonics, National Institute for Materials Science, Tsukuba, Ibaraki 305-0044, Japan.

  10. Catalyst-Agent: Autonomous heterogeneous catalyst screening with an LLM Agent

    Mar 1, 2026Achuth Chandrasekhar, Janghoon Ock, Amir Barati FarimaniLLM Agent OrchestrationMaterials Science

    Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA · Department of Chemical and Biomolecular Engineering, University of Nebraska–Lincoln, Lincoln, NE 68588, USA · Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA +3

  11. Printed helicoids with embedded air channels make sensorized segments for soft continuum robots

    Feb 26, 2026Annan Zhang, Hanna Matusik, Miguel Flores-Acton +3Soft RoboticsMaterials Science

    All authors are with the MIT Computer Science & Artificial Intelligence Laboratory, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, MA 02139, USA.

  12. Reasoning-Driven Design of Single Atom Catalysts via a Multi-Agent Large Language Model Framework

    Feb 25, 2026Dong Hyeon Mok, Seoin Back, Victor Fung +1Materials ScienceLarge Language Model-Guided Scientific Discovery

    Department of Chemical and Biomolecular Engineering, Institute of Emergent Materials, Sogang University, Seoul 04107, Republic of Korea · KU-KIST Graduate School of Converging Science and Technology, Korea University, Seoul 02841, Republic of Korea · Department of Integrative Energy Engineering, Korea University, Seoul 02841, Republic of Korea +4

  13. Molecular Representations for AI in Chemistry and Materials Science: An NLP Perspective

    Feb 24, 2026Sanjanasri JP, Pratiti Bhadra, N. Sukumar +1Molecular Representation LearningMaterials Science

    Center for Computational Engineering and Networking (CEN), Amrita Vishwa Vidyapeetham, Coimbatore, India

  14. Fully Convolutional Spatiotemporal Learning for Microstructure Evolution Prediction

    Feb 23, 2026Michael Trimboli, Mohammed Alsubaie, Sirani M. Perera +2Materials ScienceSpatiotemporal Forecasting

    Department of Mathematics and Systems Engineering, Florida Institute of Technology, Melbourne, FL, 32901, USA · Department of Mathematics, Embry-Riddle Aeronautical University, Daytona Beach, FL, 32114, USA · Department of Mechanical and Civil Engineering, Florida Institute of Technology, Melbourne, FL, 32901, USA

  15. AdsorbFlow: energy-conditioned flow matching enables fast and realistic adsorbate placement

    Feb 22, 2026Jiangjie Qiu, Wentao Li, Honghao Chen +2Flow-Based Generative ModelingMaterials Science

    Beijing Key Laboratory of Artificial Intelligence for Advanced Chemical Engineering Materials, Department of Chemical Engineering, Tsinghua University, Beijing, China.

  16. Constrained Diffusion for Accelerated Structure Relaxation of Inorganic Solids with Point Defects

    Feb 22, 2026Jingyi Cui, Jacob K. Christopher, Ankita Biswas +2Computational Materials ScienceMaterials Science

    University of Virginia

  17. Machine-learning force-field models for dynamical simulations of metallic magnets

    Feb 20, 2026Gia-Wei Chern, Yunhao Fan, Sheng Zhang +1Materials Science

    Department of Physics, University of Virginia, Charlottesville, VA 22904, USA

  18. Inelastic Constitutive Kolmogorov-Arnold Networks: A generalized framework for automated discovery of interpretable inelastic material models

    Feb 19, 2026Chenyi Ji, Kian P. Abdolazizi, Hagen Holthusen +2Materials ScienceNeural Network Interpretability

    Computational Mechanics in Medicine, Applied Medical Engineering, RWTH Aachen University Pauwelsstraße 20, 52074 Aachen, Germany · Institute for Continuum and Material Mechanics, Hamburg University of Technology Eißendorfer Straße 42, 21073 Hamburg, Germany · Institute of Applied Mechanics, University of Erlangen-Nuremberg Egerlandstrasse 5, 91058 Erlangen, Germany +1

  19. QuPAINT: Physics-Aware Instruction Tuning Approach to Quantum Material Discovery

    Feb 19, 2026Xuan-Bac Nguyen, Hoang-Quan Nguyen, Sankalp Pandey +4Microscopy Image AnalysisMultimodal Instruction Tuning

    CVIU Lab, University of Arkansas, USA · University of Utah, USA · Department of Physics, University of Arkansas, USA

  20. Retrieval Augmented Generation of Literature-derived Polymer Knowledge: The Example of a Biodegradable Polymer Expert System

    Feb 18, 2026Sonakshi Gupta, Akhlak Mahmood, Wei Xiong +1Retrieval-Augmented GenerationGraph Retrieval-Augmented Generation

    School of Computational Science and Engineering, Georgia Institute of Technology, 771 Ferst Drive NW, Atlanta 30332, GA, USA. · Matmerize, Inc., Atlanta 30308, GA, USA. · School of Materials Science and Engineering, Georgia Institute of Technology, 771 Ferst Drive NW, Atlanta, GA 30332, USA

  21. AI-Driven Structure Refinement of X-ray Diffraction

    Feb 18, 2026Bin Cao, Qian Zhang, Zhenjie Feng +4Materials SciencePhysics-Informed ML

    Guangzhou Municipal Key Laboratory of Materials Informatics, Advanced Materials Thrust, Sustainable Energy and Environment Thrust, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, 511453, China · Materials Genome Institute, Shanghai University, Shanghai 200444, China · Hefei National Research Center for Physical Sciences at the Microscale, and Hefei National Laboratory, University of Science and Technology of China, Hefei, Anhui 230026, China +1

  22. Clever Materials: When Models Identify Good Materials for the Wrong Reasons

    Feb 18, 2026Kevin Maik JablonkaSpurious CorrelationMaterials Property Prediction

    Laboratory of Organic and Macromolecular Chemistry (IOMC), Friedrich Schiller University Jena, Humboldtstrasse 10, 07743 Jena, Germany · Helmholtz Institute for Polymers in Energy Applications Jena (HIPOLE Jena), Lessingstrasse 12-14, 07743 Jena, Germany · Center for Energy and Environmental Chemistry Jena (CEEC Jena), Friedrich Schiller University Jena, Philosophenweg 7a, 07743 Jena, Germany +1

  23. Guided Diffusion by Optimized Loss Functions on Relaxed Parameters for Inverse Material Design

    Feb 17, 2026Jens U. Kreber, Christian Weißenfels, Joerg StuecklerInverse DesignInverse Problems

    Intelligent Perception in Technical Systems Group, University of Augsburg, Germany · Faculty of Mathematics, Natural Science and Engineering, University of Augsburg, Germany · Centre for Advanced Analytics and Predictive Sciences, University of Augsburg, Germany

  24. Adaptive Uncertainty-Guided Surrogates for Efficient phase field Modeling of Dendritic Solidification

    Feb 17, 2026Eider Garate-Perez, Kerman López de Calle-Etxabe, Oihana Garcia +3Surrogate ModelingComputational Materials Science

    Intelligent Information Systems, Tekniker, Iñaki Goenaga 5, Eibar (20600) Spain · Faculty of Informatics UPV-EHU, Paseo Manuel de Lardizabal 1, Donostia (20700) Spain · Department of Computer Sciences and Artificial Intelligence, UPV-EHU, Donostia (20700) Spain +1

  25. A comparative study of transformer models and recurrent neural networks for path-dependent composite materials

    Feb 17, 2026Petter Uvdal, Mohsen MirkhalafNeural Surrogate ModelingRecurrent Neural Networks

    Department of Physics, University of Gothenburg, Origovägen 6B, 41296 Gothenburg, Sweden

  26. PeroMAS: A Multi-agent System of Perovskite Material Discovery

    Feb 10, 2026Yishu Wang, Wei Liu, Yifan Li +8Multi-Agent LLM SystemsAI Agents for Scientific Discovery

    Southeast University Nanjing, China · Sun Yat-Sen University Zhuhai, China · The Hong Kong University of Science and Technology Hong Kong, China +2

  27. Predicting magnetism with first-principles AI

    Feb 9, 2026Max Geier, Liang FuMaterials Property PredictionMaterials Science

    Department of Physics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA

  28. A Generalizable Machine Learning Framework for Half-Heusler Thermoelectrics

    Feb 1, 2026Shoeb Athar, Adrien Mecibah, Philippe JundMaterials Property PredictionMaterials Science

    ICGM, Univ Montpellier, CNRS, ENSCM, 34293 Montpellier, France

  29. Boltzmann generators for amorphous particle systems

    Dec 18, 2025Louis Grenioux, Leonardo Galliano, Ludovic Berthier +2Boltzmann SamplingContinuous Normalizing Flows

    CMAP, CNRS, École polytechnique, Institut Polytechnique de Paris, 91120 Palaiseau, France · Center for Computational Mathematics, Flatiron Institute, New York, NY, USA · Laboratoire de Physique de l’École normale supérieure ENS, Université PSL, CNRS, Sorbonne Université, Université de Paris, 75005 Paris, France +2

  30. Predictive Inorganic Synthesis based on Machine Learning using Small Data sets: a case study of Hydrodynamic Diameter-controlled Cu Nanoparticles

    Dec 18, 2025Brent Motmans, Digvijay Ghogare, Thijs G. I. van Wijk +6Small-Data LearningMaterials Property Prediction

    Hasselt University, Institute for Materials Research (IUMAT), Quantum & Artificial inTelligence design Of Materials (QuATOMs), Martelarenlaan 42, B-3500 Hasselt, Belgium · Hasselt University, Institute for Materials Research (IUMAT), Hybrid Materials Design (HyMaD), Martelarenlaan 42, B-3500 Hasselt, Belgium · imec, IUMAT, Wetenschapspark 1, B-3590 Diepenbeek, Belgium +4