Computational Materials Science

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15 papers in the last four weeks, up 400% on the four weeks before. 0.1% of all new papers.

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  1. Physics-Aligned Electronic Ground-State Learning Improves Generalization

    Oct 7, 2026Eike S. Eberhard, Xaver Kainz, Viktor Kotsev +2Physics-Informed MLOOD Generalization

    Technical University of Munich (TUM) · Munich Data Science Institute (MDSI) · Munich Center for Machine Learning (MCML) +1

  2. OxiGen: Oxidation-State-Aware Crystal Generation

    Oct 6, 2026Dylan John, Kim E. Jelfs, Alex M. Ganose +1Constrained Generative ModelingCrystal Structure Generation

    Department of Chemistry, Imperial College London · Department of Electrical and Electronic Engineering, Imperial College London

  3. BranchIP: Learning Adaptive Equivariant Computation for Interatomic Potentials

    Oct 1, 2026Laura Zichi, Gil Harari, Chuin Wei Tan +6Machine Learning Interatomic PotentialsEquivariant Neural Networks

    Harvard University · Robert Bosch LLC Research and Technology Center

  4. EP-Flow: Disordered Crystal Structure Prediction without Site-Level Annotations

    Oct 1, 2026Qiuliang Liu, Liming Wu, Qi Li +5Constrained Generative ModelingFlow Matching

    Institute of Physics, Chinese Academy of Sciences, Beijing, China · University of Chinese Academy of Sciences, Beijing, China · Gaoling School of Artificial Intelligence, Renmin University of China

  5. CompMat-Bench: Benchmarking AI Agents for Computational Materials Science

    Sep 30, 2026Chenmu Zhang, Levi Felix, Jun-Jie Zhang +6AI Agents for Scientific DiscoveryAI Agent Evaluation

    Department of Materials Science and NanoEngineering Rice University, Houston, TX 77005, USA

  6. A strategic roadmap for an atomistic machine-learning ecosystem

    Sep 30, 2026Jörg Behler, Michele Ceriotti, Cecilia Clementi +46Machine Learning Interatomic PotentialsScientific ML

  7. AtomWorld-Mem: Memory-Restored World States for Long-Horizon Atomistic Evolution

    Sep 25, 2026Tian Luo, Ruge Zhang, Haozhi Han +5Hierarchical MemoryLatent World Models

    Sichuan University, Chengdu, China · Institute for AI Industry Research (AIR), Tsinghua University, Beijing, China · Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China +2

  8. SoLiD26: A First Principles Solid-Liquid Interface Dataset for Machine-learned Interatomic Potentials

    Sep 23, 2026Jonas Busk, Emil J. P. Frost, Yogeshwaran Krishnan +7Machine Learning Interatomic PotentialsMaterials Science

    Department of Energy Conversion and Storage, Technical University of Denmark, Kongens Lyngby, Denmark. · Pioneer Center for Accelerating P2X Materials Discovery (CAPeX), Technical University of Denmark, Kongens Lyngby, Denmark.

  9. Complete Neural Electronic Initialization Accelerates Materials DFT

    Sep 18, 2026Felix Ærtebjerg, Jonas Elsborg, Arghya BhowmikQuantum ChemistryComputational Materials Science

    Department of Energy Conversion and Storage, Technical University of Denmark

  10. CrystalMO-TuRBO: Multi-Objective Trust-Region Bayesian Optimization for High-precision Joint Crystal Structure Refinement

    Sep 17, 2026Joseph Agada, Yishu Wang, Arpan BiswasBayesian OptimizationTrust-Region Optimization

    University of Tennessee - Oak Ridge Innovation Institute University of Tennessee Knoxville, TN 37996 · Department of Materials Science and Engineering University of Tennessee Knoxville, TN 37996

  11. Truncated automatic sparse differentiation for machine learning interatomic potentials

    Sep 17, 2026Marcel F. Langer, Adrian Hill, Michele CeriottiAutomatic DifferentiationMachine Learning Interatomic Potentials

    Laboratory of Computational Science and Modeling (COSMO), EPFL, Lausanne, Switzerland · Machine Learning Group, Technical University of Berlin, Berlin, Germany · BIFOLD – Berlin Institute for the Foundations of Learning and Data, Berlin, Germany

  12. Physics as the label for measuring and correcting materials reasoning in multimodal models

    Sep 14, 2026Hasan Kurban, Rasul Khanbayov, Mustafa KurbanMultimodal ReasoningMultimodal Model Evaluation

    College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar · Ankara University, Ankara, Turkey

  13. Neural-Network Solutions to Real-Space Charge Density and Generalization

    Sep 14, 2026Yuxuan Zeng, Taoyuze Lv, Zhicheng ZhongNeural Surrogate ModelingEquivariant Neural Networks

    School of Artificial Intelligence & Data Science, University of Science and Technology of China · Suzhou Institute for Advanced Research, University of Science and Technology of China

  14. Prescreening Point Defects in Semiconductors With Machine Learning

    Sep 13, 2026Paul Karlsson, Joel Davidsson, Rickard ArmientoMaterials Property PredictionPhysics-Informed ML

    Department of Physics, Chemistry and Biology, Linköping University, Linköping, Sweden

  15. El Agente Potente: High-Throughput Agentic Atomistic Simulations

    Sep 13, 2026Tsz Wai Ko, Jiaru Bai, Thomas Swanick +6AI Agents for Scientific DiscoveryScientific Workflow Automation

    Department of Chemistry, University of Toronto, 80 St. George St., Toronto, ON M5S 3H6, Canada · 2Vector Institute for Artificial Intelligence, W1140-108 College St., Schwartz Reisman Innovation Campus, Toronto, ON M5G 0C6, Canada · Department of Computer Science, University of Toronto, 40 St George St., Toronto, ON M5S 2E4, Canada +7

  16. 4DMulti: automated multicomponent identification at complex material interfaces

    Sep 13, 2026Haoran Zhang, Zian Mao, Shufen Chu +6Image ClassificationComputational Materials Science

    Global Institute of Future Technology, Shanghai Jiao Tong University, 200240, Shanghai, China. · Global College, Shanghai Jiao Tong University, 200240, Shanghai, China. · School of Materials Science and Engineering, Shanghai Jiao Tong University, 200240, Shanghai, China.

  17. uFlowCSP: Crystal Structure Prediction using Mean flow generative models

    Sep 9, 2026Sourin Dey, Dipannoy Das Gupta, Lai Wei +2Crystal Structure PredictionOne-Step Generative Modeling

    Department of Computer Science and Engineering University of South Carolina Columbia, SC 29201 · Department of Computer Science and Cybersecurity University of North Georgia Columbia, SC 29201

  18. Autonomous discovery of new structure-plausibility laws for explainable and rapid crystal diagnosis and screening

    Sep 1, 2026Zhilong Song, Lixue ChengAI Agents for Scientific DiscoveryCrystal Structure Prediction

    Department of Chemistry, Hong Kong University of Science and Technology, Kowloon, Hong Kong 999077, China. · IAS Center for AI for Scientific Discoveries, Hong Kong University of Science and Technology, Kowloon, Hong Kong 999077, China. · Department of Chemical and Biological Engineering, Hong Kong University of Science and Technology, Kowloon, Hong Kong 999077, China.

  19. Agentic programs: an emerging form of scientific software in computational materials science

    Sep 1, 2026Yunsung Lim, Haekwan Jeon, Jaesun Kim +2LLM Agent HarnessesComputational Materials Science

    Research Institute of Advanced Materials, Seoul National University, Seoul, 08826, Republic of Korea. · Department of Materials Science and Engineering, Seoul National University, Seoul, 08826, Republic of Korea. · Center for AI and Natural Sciences, Korea Institute for Advanced Study, Seoul, 02455, Republic of Korea.

  20. Coupled-cluster molecular properties across the main group that extrapolate beyond training size

    Aug 18, 2026Wenhao He, Xu Chen, Noah Song +10Quantum ChemistryEquivariant Neural Networks

    Center for Computational Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA · Department of Chemistry, Emory University, Atlanta, GA 30322, USA · Department of Nuclear Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA +2

  21. DynaCrys: Crystal Generation with Dynamic Space-Group Diffusion

    Aug 7, 2026Zhuotao Jin, Xiaoyun Wang, Nicholas Brawand +5Crystal Structure GenerationDiffusion Models

    NVIDIA · Center for Computational Science and Engineering, Massachusetts Institute of Technology · Department of Materials Science and Engineering, Massachusetts Institute of Technology +4

  22. ED-CSP: Crystal Structure Prediction from Electron Diffraction

    Aug 6, 2026Germain Poloudenny, Yaël Frégier, Arnaud DemortièreCrystal Structure PredictionCrystal Structure Generation

    Laboratoire de Mathématiques de Lens (LML), UR 2462, Université d’Artois, Lens, France · Laboratoire de Réactivité et de Chimie des Solides (LRCS), CNRS UMR 7314, UPJV, Amiens, France · Réseau sur le Stockage Electrochimique de l’Energie (RS2E), CNRS FR 3459, Amiens, France +1

  23. Graph Neural Network Force Fields for Spin Dynamics in Metallic Magnets

    Jul 30, 2026Ali Rayat, Yunhao Fan, Gia-Wei ChernGraph Neural NetworksScientific ML

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

  24. ATLAS: A Foundation Neural Sampler for Amorphous Materials

    Jul 21, 2026Mouyang Cheng, Denis Blessing, Botao Yu +4Diffusion Model SamplingMaterials Science

    Microsoft Research New England, Cambridge, MA 02142, USA · Center for Computational Science and Engineering, MIT, Cambridge, MA 02139, USA · Department of Materials Science and Engineering, MIT, Cambridge, MA 02139, USA +4

  25. Dual-Level Atomic and Coordination Geometry Learning for Crystal Property Prediction Using Graph Neural Networks

    Jul 17, 2026Sanjay ChakrabortyGraph Neural NetworksMaterials Property Prediction

    Department of Computer and Information Science (IDA), REAL, AIICS, Linköping University, Linköping, Sweden

  26. Microstructure-Conditioned Surrogate Models for Graded Multiscale Optimization of Mycelium Composites

    Jul 15, 2026J. Storm, I. B. C. M. Rocha, S. Schyck +2Neural Surrogate ModelingSurrogate Modeling

    SLIMM Lab, Faculty of Civil Engineering and Geosciences, Delft University of Technology, P.O. Box 5048, Delft, 2600GA, Zuid-Holland, The Netherlands · Shaping Matter Lab, Faculty of Aerospace Engineering, Delft University of Technology, Delft, Zuid-Holland, The Netherlands

  27. DeepCormack: Fermi surface tomography using model-based data-driven algorithms

    Jul 14, 2026Georg F. B. Lovric, Bryn Drury, Carola-Bibiane Schönlieb +2Image ReconstructionComputational Materials Science

    Department of Applied Mathematics and Theoretical Physics, University of Cambridge, Cambridge, UK. · H.H. Wills Physics Laboratory, University of Bristol, Tyndall Avenue, Bristol BS8 1TL, UK

  28. CatRetriever: Contrastive Representation Learning for Slab-to-Bulk Retrieval in Generative Catalyst Discovery

    Jul 13, 2026Jungho Oh, Woosung Kim, Dong Hyeon Mok +2Contrastive LearningMaterials Science

    KU-KIST Graduate School of Converging Science and Technology, Korea University, Seoul 02841, Republic of Korea · Department of Materials Science and Engineering, Korea University, Seoul 02841, Republic of Korea · Department of Chemical and Biomolecular Engineering, Sogang University, Seoul 04107, Republic of Korea +5

  29. The evolution of AI from image interpretation toward scientific inference in nanoparticle electron microscopy

    Jul 11, 2026Evropi Toulkeridou, Jiafei Li, Leonardo Lari +1Materials ScienceMicroscopy Image Analysis

    Statistical Analysis and Optimal Design of Experiments Group, Department of Mathematics, University of Castilla-La Mancha, 45071 Toledo, Spain · Materials Science and Engineering, Guangdong Technion – Israel Institute of Technology, Shantou, Guangdong 515063, China · LAME Laboratory, Area Science Park Campus di Basovizza, SS14, KM163.5, 34149, Trieste, Italy +2

  30. Beyond Drug Discovery: The Nanotechnology Molecular Optimization (NMO) Benchmark

    Jun 29, 2026Matthias Blaschke, Daniel Kienzle, Zsuzsanna Koczor-Benda +3Molecular OptimizationBenchmark Design

    University of Augsburg · CAAPS† · Germany +2