Crystal Structure Generation

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Overview

Crystal structure generation studies how to produce plausible periodic arrangements of atoms, supporting the search for materials with useful properties and the prediction of unknown structures. Common approaches include diffusion and flow-matching models, autoregressive generators, and models that encode crystallographic symmetry through space groups and Wyckoff positions. Researchers add chemical and physical constraints, property guidance, or energy-based screening, then evaluate candidates on benchmarks such as MP-20 and molecular-crystal datasets. A central challenge is balancing structural validity and stability with genuine novelty: models can reproduce known structural prototypes, while reliable validation often requires costly relaxation or first-principles calculations.

Latest papers

CardsList

61 papers11 papers in the last four weeks, up 38% on the four weeks before. 0.1% of all new papers.

  1. Probing the limits of forward screening and inverse design of crystal materials

    Oct 23, 2026Zhilong Song, Zijun Pang, Lixue ChengMaterials DiscoveryInverse Design

    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

  2. Orbitol: Crystal Generation on Wyckoff Orbits

    Oct 21, 2026Ivan Žugec, Joshua Rosenthal, Ivor Lončarić +2Crystal Structure GenerationMaterials Discovery

    Atomic Intelligence, Zagreb, Croatia · University of Amsterdam · Ruđer Bošković Institute

  3. CrystalAR: Autoregressive Modeling for Symmetric Crystal Generation

    Oct 20, 2026Ziqiao Meng, Rongsheng Chen, Zhi Zheng +4Crystal Structure GenerationCrystal Structure Prediction

    Institute for Functional Intelligent Materials (IFIM), National University of Singapore · School of Computing, National University of Singapore · Southern University of Science and Technology

  4. DiffGA: Steering Frozen Diffusion Models for Materials Design via Evolutionary Search

    Oct 10, 2026Shivang Agarwal, Rodrigo Wang, Kevin Ryczko +1Inverse DesignCrystal Structure Generation

    SandboxAQ, Palo Alto, CA 94301, USA.

  5. Zatom-2: Multitask Pretraining on Atomistic Data for Generative Modeling across Domains

    Oct 8, 2026Miruna Cretu, Alex Abrudan, Antonia Panescu +11Generative ModelingMolecular Generation

    University of Cambridge · Yale University · MIT +3

  6. 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

  7. AnchorPose for Geometry-Aware MOF Assembly through Meso-Grained Pose Generation

    Oct 5, 2026Zhonglong Peng, Rui Jiao, Chang Chen +3Crystal Structure Generation

    Institute of Physics, Chinese Academy of Sciences · University of the Chinese Academy of Sciences · Tsinghua University

  8. Reinforcement Learning on the Discrete Composition Channel of a Crystal Generator: Validated Gains and Reward Hacking

    Oct 2, 2026Pawan Prakash, Philipp Höllmer, Addis Fuhr +4Crystal Structure GenerationReward Hacking

    University of Florida · New York University · Oak Ridge National Laboratory

  9. Riemannian Flow Models with Reinforcement Learning for Molecular Crystal Structure Prediction

    Sep 30, 2026Thomas Egg, Harry Winston Sullivan, Maya M. Martirossyan +8Crystal Structure PredictionCrystal Structure Generation

    Center for Soft Matter Research, Department of Physics, New York University, New York 10003, USA · Simons Center for Computational Physical Chemistry, Department of Chemistry, New York University, New York 10003, USA · Department of Chemical Engineering and Materials Science, University of Minnesota, Minneapolis, MN 55455, USA +7

  10. GLASS: Global Latent Aggregation with Slot-based Set Decoding for Scalable All-Atom Crystal Generation

    Sep 29, 2026Hendrik Kraß, Seyed Mohamad Moosavi, Mathias NiepertCrystal Structure GenerationMaterials Science

    Institute for Artificial Intelligence University of Stuttgart · NEC Labs Europe

  11. Where Should Physics Enter a Molecular Crystal Generator?

    Sep 28, 2026Haocheng Tang, Junmei Wang, Wengong JinPhysics-Informed Generative ModelingCrystal Structure Generation

    Khoury College of Computer Science Northeastern University Boston, MA 02115, USA · School of Pharmacy University of Pittsburgh Pittsburgh, PA 15213, USA

  12. Let CSP Be Your ANCHOR: Adaptive Crystal Search over Frozen Structure Priors

    Sep 27, 2026Emma Lei Hovmand, Jonas Elsborg, Melih Kandemir +1Novelty SearchCrystal Structure Prediction

    Department of Energy Conversion and Storage, Technical University of Denmark · Department of Mathematics and Computer Science, University of Southern Denmark

  13. Topology-Stratified Materials Discovery with A Flow-Based Generative Model

    Sep 22, 2026Jingyi Zhou, Oyshee Chowdhury, Noah Oyeniran +1Materials ScienceGenerative Modeling

    Department of Aerospace Engineering and Mechanics, University of Alabama, Tuscaloosa, 35487, Alabama, United States. · Alabama Materials Institute, The University of Alabama, Tuscaloosa, 35487, Alabama, United States.

  14. Deep Generative Crystal Structure Prediction: A Benchmark Study and a Controlled Test of Prototype Dependence

    Sep 22, 2026Lai Wei, Rongzhi Dong, Ying Feng +2Crystal Structure PredictionGenerative Modeling

    Department of Computer Science and Engineering, University of South Carolina, Columbia, SC 29201 · Department of Computer Science and Cybersecurity, University of North Georgia, Dahlonega, GA 30597

  15. OMatG-flash: An All-Atom Flow Map with Reinforce Adjoint Matching for Scalable Materials Discovery

    Sep 22, 2026Thomas Egg, Harry Winston Sullivan, Ellad B. Tadmor +1Flow MatchingCrystal Structure Prediction

    New York University · University of Minnesota

  16. Robust and Efficient AI Frameworks for Scalable Material Design and Property Prediction

    Sep 15, 2026Kishalay DasGraph SSLMaterials Property Prediction

  17. Symmetry- and Property-Aware Crystal Generation with Reinforcement Learning for Inverse Materials Design

    Sep 11, 2026Ting-Wei Hsu, Arun Bansil, Qimin YanCrystal Structure GenerationInverse Design

    Department of Physics, Northeastern University, Boston, 02155, Massachusetts, USA. · Quantum Materials and Sensing Institute, Northeastern University, Burlington, 01803, Massachusetts, USA.

  18. 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

  19. Text-guided flow matching enables sample-efficient crystal structure generation

    Sep 1, 2026Wentao LiConditional Flow MatchingCrystal Structure Prediction

    1Tsinghua University

  20. Packora: Systematic Design for Generative Molecular Crystal Structure Prediction

    Aug 27, 2026Nayoung Kim, Kiyoung Seong, Sungsoo AhnCrystal Structure PredictionCrystal Structure Generation

    Korea Advanced Institute of Science and Technology (KAIST)

  21. Crystal-structure design by agentic AI in a language of motifs

    Aug 16, 2026Dinh-Khiet Le, Minh-Quyet Ha, Hong-Phuc Vu-Dinh +6Crystal Structure GenerationMaterials Discovery

    Japan Advanced Institute of Science and Technology, 1-1 Asahidai, Nomi, Ishikawa 923-1292, Japan · Department of Physics, School of Science, Institute of Science Tokyo, 2-12-1 Ookayama, Meguro-ku, Tokyo 152-8551, Japan · Research Center for Materials Informatics, Department of Advanced Data Science, The Institute of Statistical Mathematics, 10-3 Midori-cho, Tachikawa, Tokyo 190-8562, Japan +1

  22. Symmetry-Breaking De Novo Crystal Generation via Markovian Jump Diffusion

    Aug 13, 2026Van Khoa Nguyen, Alexandros KalousisSymmetry BreakingMaterials Science

    HES-SO Geneva · University of Geneva

  23. 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

  24. 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

  25. Representations from Pretrained Machine-Learning Interatomic Potentials as Coarse Coordinates for Material Generation and Evaluation

    Jul 30, 2026Paul Hagemann, Katharina Ueltzen, Simon Müller +2Crystal Structure Generation

  26. Chemical filters for ultra-high-throughput materials screening and generation

    Jul 20, 2026Kinga O. Mastej, Panyalak Detrattanawichai, Hyunsoo Park +3Constrained Generative ModelingMaterials Science

    Department of Materials, Imperial College London, London SW7 2AZ, United Kingdom

  27. SinAE: A Single-Architecture Flow-Matching Autoencoder for Cross-Domain Atomic Systems

    Jul 14, 2026Yuxuan Ren, Fan Yang, Jianhua Yao +1Autoencoders3D Molecular Generation

    Department of Computer Science National University of Singapore · Tencent AI for Life Science Lab

  28. Surrogate-Gated Generation and Foundation-Model Embeddings for Bayesian Materials Design

    Jun 26, 2026Sk Md Ahnaf Akif Alvi, Jan Janssen, Danny Perez +2Surrogate-Assisted OptimizationBayesian Optimization

    Department of Materials Science and Engineering, Texas A&M University, College Station, TX 77843, USA · Theoretical Division T-1, Los Alamos National Laboratory, Los Alamos, NM 87544, USA · Max-Planck-Institute for Sustainable Materials, Düsseldorf, Germany 40237 +3

  29. Substitution-Based Analysis of Structural Novelty for Generative Models of Materials

    Jun 22, 2026Masahiro Negishi, Aron WalshMemorization in Generative ModelsCrystal Structure Generation

    Department of Materials, Imperial College London, Exhibition Road, South Kensington, SW7 2AZ, London, United Kingdom.

  30. Discovering Crystal Structure Prediction Algorithms with an AI Co-Scientist

    Jun 22, 2026Kiyoung Seong, Nayoung Kim, Sungsoo AhnAutomated Algorithm DiscoveryCrystal Structure Prediction

    Korea Advanced Institute of Science and Technology (KAIST)