Materials Property Prediction

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Overview

Materials property prediction studies how composition, atomic structure, microstructure, and processing determine properties such as strength, stability, conductivity, and band gap. Common approaches include descriptor-based regression, graph and equivariant neural networks, pretrained representations, and physics-informed or simulation-based surrogates; multimodal methods also combine structures with images, spectra, or experimental records. These models can speed screening and guide design when direct experiments or first-principles calculations are costly, but performance often depends on having enough relevant, reliable labels. A central challenge is generalizing beyond familiar datasets and computational settings to new materials and experiments, while providing calibrated uncertainty and physically meaningful explanations.

Latest papers

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175 papers21 papers in the last four weeks, up 24% on the four weeks before. 0.1% of all new papers.

  1. Foundation-Model Surrogates Enable Data-Efficient Active Learning for Materials Discovery

    Mar 13, 2026Jeffrey Hu, Rongzhi Dong, Ying Feng +2Active LearningData-Efficient Learning

    Department of Materials Science and Engineering, University of Illinois Urbana Champaign, Champaign,IL, USA · Department of Computer Science & Engineering, University of South Carolina, Columbia, SC, USA · Zuoyue Honors College, Hangzhou Dianzhi University, Hangzhou, China +1

  2. Proof-Carrying Materials: Falsifiable Safety Certificates for Machine-Learned Interatomic Potentials

    Mar 12, 2026Abhinaba Basu, Pavan ChakrabortyMachine Learning Interatomic PotentialsMaterials Property Prediction

    Indian Institute of Information Technology Allahabad (IIITA), Prayagraj, India · National Institute of Electronics and Information Technology (NIELIT), India

  3. Gaussian Process Regression-based Knowledge Distillation Framework for Simultaneous Prediction of Physical and Mechanical Properties of Epoxy Polymers

    Mar 12, 2026Sindu B. S., Jan HamaekersMaterials Property PredictionPolymer Property Prediction

    Special and Multifunctional Structures Laboratory, CSIR-Structural Engineering Research Centre, Taramani, Chennai, Tamil Nadu, India - 600113. · Fraunhofer Institute for Algorithms and Scientific Computing SCAI, Schloss Birlinghoven, 53757 Sankt Augustin, Germany

  4. A recipe for scalable attention-based MLIPs: unlocking long-range accuracy with all-to-all node attention

    Mar 6, 2026Eric Qu, Brandon M. Wood, Aditi S. Krishnapriyan +1Machine Learning Interatomic PotentialsSelf-Attention

    UC Berkeley · FAIR at Meta · LBNL

  5. MOSIV: Multi-Object System Identification from Videos

    Mar 6, 2026Chunjiang Liu, Xiaoyuan Wang, Qingran Lin +9System IdentificationMaterials Property Prediction

    CMU · Georgia Tech · Harvard +4

  6. Neural Electromagnetic Fields for High-Resolution Material Parameter Reconstruction

    Mar 3, 2026Zhe Chen, Peilin Zheng, Wenshuo Chen +3Materials Property PredictionInverse Problems

    Xidian University · The Hong Kong University of Science and Technology

  7. MatRIS: Toward Reliable and Efficient Pretrained Machine Learning Interatomic Potentials

    Mar 2, 2026Yuanchang Zhou, Siyu Hu, Xiangyu Zhang +3Machine Learning Interatomic PotentialsComputational Materials Science

    State Key Lab of Processors, Institute of Computing Technology, Chinese Academy of Sciences · University of Chinese Academy of Sciences · School of Advanced Interdisciplinary Sciences, UCAS

  8. PolyMon: A Unified Framework for Polymer Property Prediction

    Mar 2, 2026Gaopeng Ren, Yijie Yang, Jiajun Zhou +1Polymer Property PredictionMaterials Property Prediction

    Department of Chemistry, Imperial College London

  9. Probing Materials Knowledge in LLMs: From Latent Embeddings to Reliable Predictions

    Mar 2, 2026Vineeth Venugopal, Soroush Mahjoubi, Elsa OlivettiLLM ReliabilityLLM Evaluation

    Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA.

  10. A Stability-Aware Frozen Euler Autoencoder for Physics-Informed Tracking in Continuum Mechanics (SAFE-PIT-CM)

    Feb 27, 2026Emil HovadPhysics-Informed MLPDE Inverse Problems

    Section for Statistics and Data Analysis, DTU Compute, Technical University of Denmark, Kgs. Lyngby, Denmark

  11. Discovery of Interpretable Physical Laws in Materials via Language-Model-Guided Symbolic Regression

    Feb 26, 2026Yifeng Guan, Chuyi Liu, Dongzhan Zhou +4Scientific DiscoverySymbolic Regression

    Shanghai Artificial Intelligence Laboratory, Shanghai, 200232, China. · School of Physics, Zhejiang University, Hangzhou, 310058, China. · Soochow Institute for Energy and Materials Innovations (SIEMIS), Soochow University, Suzhou, 215006, China. +3

  12. MBD-ML: Many-body dispersion from machine learning for molecules and materials

    Feb 25, 2026Evgeny Moerman, Adil Kabylda, Almaz Khabibrakhmanov +1Materials Property PredictionQuantum Chemistry

    Department of Physics and Materials Science, University of Luxembourg, L-1511 Luxembourg City, Luxembourg

  13. Zatom-1: Towards a Multimodal Foundation Model for 3D Molecules and Materials

    Feb 24, 2026Alex Morehead, Miruna Cretu, Antonia Panescu +143D Foundation ModelsMultimodal Foundation Models

    LBNL · ICSI · University of Cambridge +3

  14. Clapeyron Neural Networks for Single-Species Vapor-Liquid Equilibria

    Feb 20, 2026Jan Pavšek, Alexander Mitsos, Elvis J. Sim +1Molecular Property PredictionMaterials Property Prediction

    Process Systems Engineering (AVT.SVT), RWTH Aachen University · JARA Center for Simulation and Data Science (CSD) · Institute of Climate and Energy Systems ICE-1: Energy Systems Engineering, Forschungszentrum Jülich GmbH

  15. 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

  16. 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

  17. 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

  18. Multi-Task Learning for Metal Alloy Property Prediction: An Empirical Study of Negative Transfer and Mitigation Strategies

    Dec 28, 2025Sungwoo KangMulti-Task LearningMaterials Property Prediction

    Department of Electrical and Computer Engineering, Korea University, Seoul 02841, Republic of Korea

  19. 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

  20. AGAPI-Agents: An Open-Access Agentic AI Platform for Accelerated Materials Design on AtomGPT.org

    Dec 12, 2025Jaehyung Lee, Justin Ely, Kent Zhang +3AI Agents for Scientific DiscoveryLLM Agent Evaluation

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

  21. 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.

  22. ADAPT: Lightweight, Long-Range Machine Learning Force Fields Without Graphs

    Sep 28, 2025Evan Dramko, Yihuang Xiong, Yizhi Zhu +4Machine Learning Interatomic PotentialsMaterials Property Prediction

    Department of Computer Science, Rice University, Houston, TX, USA · Thayer School of Engineering, Dartmouth College, Hanover, NH, USA · Department of Materials Science and Nanoengineering, Rice University, Houston, TX, USA +2

  23. 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

  24. Learning Magnetic Order Classification from Large-Scale Materials Databases

    Sep 7, 2025Ahmed E. FahmyMaterials Property PredictionClassification

    Department of Physics, The Ohio State University, Columbus, OH 43210, USA

  25. Surprisingly High Redundancy in Electronic Structure Data Across Materials Explained by Low Intrinsic Dimensionality

    Jul 11, 2025Sazzad Hossain, Ponkrshnan Thiagarajan, Shashank Pathrudkar +4Intrinsic DimensionalityDataset Pruning

    Department of Mechanical and Aerospace Engineering, Michigan Technological University, Houghton, MI, USA. · Hopkins Extreme Materials Institute, Johns Hopkins University, Baltimore, MD, USA. · Department of Materials Science and Engineering, University of California, Los Angeles, CA, USA. +1