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

  31. MALOQ: Massively Accelerated Learning of Operators for Quantum Transport

    Jun 27, 2026Manasa Kaniselvan, Alexander Maeder, Denghui Lu +2Quantum ChemistryHigh-Performance Computing

    D-ITET, ETH Zurich, Zurich, Switzerland

  32. A Reduced Order Model for Emergent Mechanics in Woven Systems

    Jun 22, 2026Anvay A. Pradhan, Evgueni T. Filipov, Talia Y. MooreStructural MechanicsMaterials Science

    Department of Mechanical Engineering, University of Michigan, Ann Arbor, Michigan, 48109, USA · Department of Civil and Environmental Engineering, University of Michigan, Ann Arbor, Michigan, 48109, USA · Department of Robotics, University of Michigan, Ann Arbor, Michigan, 48109, USA +1

  33. Deep material network for homogenization of piezoelectric composites

    Jun 21, 2026Ting-Ju Wei, Yen-Ming Lu, Chuin-Shan ChenNeural Surrogate ModelingMaterials Science

    Department of Civil Engineering National Taiwan University Taipei, Taiwan · Department of Civil Engineering Department of Materials Science and Engineering National Taiwan University Taipei, Taiwan

  34. Mat-Pref: Verifiable-Reward Training Improves Compositional Reasoning in Inorganic Materials

    Jun 20, 2026Sarrah R. Mikhail Leung, Taehan Kim, Jeongbin ParkCompositional ReasoningRL for Language Model Reasoning

    University of California, Berkeley · 2Machine Learning at Berkeley · University of Michigan

  35. Computational references are not experiments: pre-registered validation of machine-learned sodium-cathode voltages

    Jun 19, 2026Krishna Teja VepaMaterials Property PredictionVirtual Screening

    Independent Researcher†

  36. Equivariant Graph Neural Networks Improve Optical Spectra Prediction for Materials Screening

    Jun 17, 2026Kasper Helverskov Petersen, François R J Cornet, Martin Ovesen +3Materials Property PredictionEquivariant GNNs

    Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby, Denmark · Department of Physics, Technical University of Denmark, Kongens Lyngby, Denmark

  37. InvDesMobility: a reliability-gated first-principles feedback framework for closed-loop materials discovery

    Jun 15, 2026Wen-Kao Li, Ze-Feng Gao, Peng-Jie Guo +2Materials Property PredictionAutonomous Scientific Discovery

    School of Physics and Key Laboratory of Quantum State Construction (Ministry of Education), Renmin University of China, Beijing 100872, China

  38. Scalar-pathway fidelity improves physical accuracy in short-range equivariant interatomic potentials

    Jun 14, 2026Jia Bi, Alin Marin Elena, Samuel PinillaMachine Learning Interatomic PotentialsEquivariant GNNs

    Science and Technology Facilities Council, Harwell Campus, Didcot, OX11 0QX, Oxfordshire, United Kingdom. · Science and Technology Facilities Council, Keckwick Lane, Daresbury, WA4 4AD, Cheshire, United Kingdom. · Diamond Light Source, Harwell Science and Innovation Campus,2026 Didcot, OX11 0QX, Oxfordshire, United Kingdom.

  39. A Hybrid GNN-FEM Framework for Phase-Field Fracture Simulation. Physics-Preserving Hybridization for Generalizable Surrogate Modeling

    Jun 12, 2026Hyeonbin Moon, Yongjin Choi, Seunghwa RyuStructural MechanicsPDE Surrogate Modeling

    Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea · KAIST InnoCORE PRISM-AI Center, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea · Department of AX, College of AI, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea

  40. XRDiff: Crystal Structure Prediction from Powder X-Ray Diffraction Data Using Diffusion Models

    Jun 12, 2026Nofit Segal, Mingda Li, Benjamin Kurt Miller +1Crystal Structure PredictionDiffusion Models

    Department of Materials Science and Engineering, MIT, Cambridge, MA, USA. · Department of Nuclear Science and Engineering, MIT, Cambridge, MA, USA. · FAIR, Meta, San Francisco, CA, USA.

  41. Magnetic HIP-NN for spin dynamics in disordered itinerant magnets

    Jun 9, 2026Supriyo Ghosh, Yunhao Fan, Sheng Zhang +2Equivariant Neural NetworksMessage Passing Neural Networks

    Department of Physics, University of Virginia, Charlottesville, Virginia 22904, USA · Department of Chemistry, University of Chicago, Chicago, IL 60637, USA · Theoretical Division and CNLS, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA

  42. Agentic multi-fidelity learning of quasiparticle and excitonic properties

    Jun 5, 2026Arnab Neogi, Aaron Forde, Christopher A. Lane +2AI Agents for Scientific DiscoveryMaterials Property Prediction

    Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA · Center for Integrated Nanotechnologies, Materials Physics and Applications Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA

  43. Decision-Aware Evaluation of Physics-Informed Surrogates

    Jun 5, 2026Daniel Cieślak, Andrzej CzyżewskiSurrogate ModelingBenchmark Design

    Gdańsk University of Technology, Gdańsk, Poland

  44. Derivative Informed Learning of Exchange-Correlation Functionals

    Jun 2, 2026Eike S. Eberhard, Luca A. Thiede, Abdul Aldossary +5Quantum ChemistryKnowledge Distillation

    Technical University of Munich, Munich, Germany · Munich Data Science Institute, Munich, Germany · Munich Center for Machine Learning, Munich, Germany +4

  45. Machine Learning Surrogate Modeling for Homogenization of Hyperelastic Materials with Boolean Microstructures

    May 31, 2026Matthias Brändel, Oliver RheinbachNeural Surrogate ModelingHyperelasticity

    Technische Universität Bergakademie Freiberg, Institut für Numerische Mathematik und Optimierung, Fakultät für Mathematik und Informatik, 09596 Freiberg, Germany.

  46. Benchmark Dataset for Catalysis on 2D MXenes

    May 30, 2026Pavlo Melnyk, Anmar Karmush, Mårten Wadenbäck +4Machine Learning Interatomic PotentialsBenchmark Design

    Computer Vision and Learning Systems, Department of Electrical Engineering (ISY) & AI4X, Linköping University (LiU), 58183 Linköping, Sweden. · Materials Design Division, Department of Physics, Chemistry and Biology (IFM), and Wallenberg Initiative Materials Science for Sustainability (WISE); Linköping University (LiU), 58183 Linköping, Sweden. · Wallenberg Initiative Materials Science for Sustainability (WISE); Linköping University (LiU), 58183 Linköping, Sweden.

  47. Discovering Thermodynamically Admissible Dissipation Potentials via Grammar-Based Symbolic Regression

    May 29, 2026Federico Califano, Jacopo CiambellaMaterials ScienceComputational Materials Science

  48. LEIA: Learned Environment for Interactive Architected Materials

    May 27, 2026Haiqian Yang, Yuan Cao, Markus J. BuehlerNeural Surrogate ModelingWorld Model Learning

    Unreasonable Labs · Mountain View, CA 94043, USA

  49. AutoDFT: A Closed-Loop Multi-Agent Framework for Autonomous DFT Calculations

    May 25, 2026Penghui Yang, Zhonghan Zhang, Yue Li +6Multi-Agent LLM SystemsScientific Workflow Automation

    Nanyang Technological University, Singapore · Singapore Management University

  50. SPLIT-PINN: Separable Probability Learning Technique via Physics-Informed Neural Networks for High-Dimensional Probabilistic Modeling

    May 23, 2026Pouria Behnoudfar, Deekshith Naidu Ponnana, Noah J. Schmelzer +6Physics-Informed MLComputational Materials Science

    Department of Mechanical Engineering, University of Wisconsin-Madison, Madison, WI, USA · Department of Civil Engineering, Johns Hopkins University, Baltimore, MD, USA · Materials Physics and Applications Division, Los Alamos National Laboratory, Los Alamos, NM, USA +2

  51. Representability-Aware Neural Networks for Reduced Density Matrices: Application to Fractional Chern Insulators

    May 19, 2026Justin B. Hart, Awwab A. Azam, Thomas Li +4Quantum Machine LearningQuantum Many-Body Physics

    Department of Physics, University of Florida, Gainesville, FL, USA · Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL, USA · Palo Alto High School, Palo Alto, CA, USA +4

  52. Harnessing AtomisticSkills for Agentic Atomistic Research

    May 18, 2026Bowen Deng, Bohan Li, Matthew Cox +20AI Agents for Scientific DiscoveryAI Coding Agents

    Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA · Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA · Department of Chemistry, Kookmin University, Seoul 02707, Republic of Korea +5

  53. Atomistic Modeling of Chemical Disorder in Materials: Bridging Classical Methods and AI-Assisted Approaches

    May 18, 2026Jiayu Peng, Peichen ZhongCrystal Structure GenerationComputational Materials Science

    Department of Materials Design and Innovation, University at Buffalo, Buffalo, NY 14260, USA · Department of Materials Science and Engineering, National University of Singapore, Singapore 117575, Singapore

  54. Reweighting free energy profiles between universal machine learning interatomic potentials for fast consensus building

    May 15, 2026Sauradeep Majumdar, Miguel Steiner, Johannes C. B. Dietschreit +4Free Energy CalculationMachine Learning Interatomic Potentials

    Department of Material Science and Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, 02139, United States. · Institute of Theoretical Chemistry, University of Vienna, Währinger Str. 17, 1090, Vienna, Austria. · Department of Physical and Macromolecular Chemistry, Charles University, Hlavova 8, Praha 2, 12800, Czech Republic.

  55. Crys-JEPA: Accelerating Crystal Discovery via Embedding Screening and Generative Refinement

    May 14, 2026Nian Liu, Nikita Kazeev, Stephen Gregory Dale +8Joint-Embedding Predictive ArchitectureGenerative Modeling

    1National University of Singapore · 2Loyola Marymount University · 3New York University +1

  56. Agentic Design of Compositional Descriptors via Autoresearch for Materials Science Applications

    May 14, 2026Matteo Cobelli, Stefano SanvitoMaterials Property PredictionAutomated Feature Engineering

    School of Physics and CRANN Institute, Trinity College, Dublin 2, Dublin, Ireland.

  57. Generating Symmetric Materials using Latent Flow Matching

    May 11, 2026Anmar Karmush, Cedric Mathieu Brandenburg, Soheil Ershadrad +3Crystal Structure GenerationComputational Materials Science

    Department of Electrical Engineering (ISY) & AI4x, Linköping University · Department of Physics, Chemistry and Biology (IFM), Linköping University · Wallenberg Initiative Materials Science for Sustainability (WISE), Linköping University +1

  58. Enabling Structure-Only Initialization and Out-of-Distribution Generalization in GNN-based Molecular Dynamics Simulators

    May 10, 2026S. A. Shteingolts, Salman N. Salman, Dan MendelsGraph Neural NetworksOOD Generalization

    The Wolfson Department of Chemical Engineering, Technion - Israel Institute of Technology, Haifa, 32000, Israel

  59. Physics-Informed Reduced-Order Operator Learning for Hyperelasticity in Continuum Micromechanics

    May 8, 2026Hamidreza Eivazi, Henning WesselsStructural MechanicsHyperelasticity

    Division Data-Driven Modeling of Mechanical Systems, Institute of Applied Mechanics, Technische Universität Braunschweig, Pockelsstr. 3, 38106 Braunschweig, Germany

  60. SLayerGen: a Crystal Generative Model for all Space and Layer Groups

    May 7, 2026Rees Chang, Andrew Novick, Ryan P Adams +1Crystal Structure GenerationDiffusion Models

    Department of Materials Science & Engineering, University of Illinois at Urbana-Champaign · Department of Computer Science, Princeton University · Materials Research Laboratory, University of Illinois at Urbana-Champaign