We present Crystalyse, an open, provenance-enforced scientific agent for computational materials design of inorganic crystals that orchestrates tools for compositional screening, crystal structure generation, and machine-learning force-field evaluation. Crystalyse offers three operating modes to trade exploration speed against validation depth: creative (rapid query), adaptive (context-aware routing) and rigorous (comprehensive checks). We release the underlying source code and evaluation scripts to enable plug-and-play use and development. In demonstrations on quaternary oxide exploration, sodium-ion cathode design, and lead-free indoor photovoltaic candidate generation, the agent integrates chemical compound generation with fast stability and property filters. Under adversarial testing, provenance enforcement eliminated material-property hallucinations (a broad adversarial suite pass rate reached 86% from a 57% baseline). Crystalyse provides an agentic artificial intelligence system that can complement existing materials design pipelines, assisting in hypothesis generation while preserving transparency and reproducibility.
Accelerated Inorganic Materials Design with Generative AI Agents
The University of Tokyo, Institute of Industrial Science（东京大学工业科学研究所）；University of Montreal, Department of Computer Science and Operations Research（蒙特利尔大学计算机科学与运筹学系）；Mila - Quebec AI Institute（米拉-魁北克人工智能研究所）
Agentic workflow enables the recovery of critical materials from complex feedstocks via selective precipitation
Physical and Computational Sciences Directorate, Pacific Northwest National Laboratory（太平洋西北国家实验室物理与计算科学部门）；Department of Chemical Engineering, University of Washington（华盛顿大学化学工程系）
MASON: Materials Atomistic Structure builder Operated in Natural language
College of Electronic Information and Optical Engineering, Nankai University（南开大学电子信息与光学工程学院）；School of Physics, Nankai University（南开大学物理学院）；Tianjin Key Laboratory of Optoelectronic Sensor and Sensing Network Technology, Nankai University（南开大学天津市光电传感器与传感网络技术重点实验室）；Shenzhen Research Institute of Nankai University（南开大学深圳研究院）；CIC nanoGUNE BRTA（巴斯克研究中心纳米科学联合中心）；College of Energy and Environment Science, Yunnan Normal University（云南师范大学能源与环境科学学院）
From Natural Language to Materials Discovery:The Materials Knowledge Navigation Agent
Department of Materials Science and Engineering, Carnegie Mellon University（材料科学与工程系，卡内基梅隆大学）；Department of Mechanical Engineering, Carnegie Mellon University（机械工程系，卡内基梅隆大学）
An LLM agent for end-to-end computational materials discovery
Northwestern Polytechnical University（西北工业大学）；National University of Singapore（新加坡国立大学）；University of Toronto（多伦多大学）；Chinese Academy of Sciences（中国科学院）；Huazhong University of Science and Technology（华中科技大学）；The University of Tokyo（东京大学）
Towards Agentic Intelligence for Materials Science
DIRO & Institut Courtois, Université de Montréal（蒙特利尔大学DIRO与Courtois研究所）；Mila – Quebec AI Institute（魁北克AI研究所）；University of Waterloo（滑铁卢大学）；Université de Sherbrooke（Sherbrooke大学）；University of California, San Diego（加州大学圣地亚哥分校）；The University of Tokyo, Institute of Industrial Science（东京大学工业科学研究所）；The Chinese University of Hong Kong, Shenzhen（香港中文大学（深圳））；Singapore Management University（新加坡管理学院）；The Hong Kong University of Science and Technology, Guangzhou（香港科学与技术大学（广州））；Alibaba DAMO Academy（阿里巴巴达摩院）；University of Illinois Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校）；CIFAR AI Chair（CIFAR人工智能主席）
Operationalizing Serendipity: Multi-Agent AI Workflows for Enhanced Materials Characterization with Theory-in-the-Loop
Physical Sciences Division, Pacific Northwest National Laboratory（太平洋西北国家实验室物理科学部）；Computational Sciences and Engineering Division, Oak Ridge National Laboratory（橡树岭国家实验室计算科学与工程部）；AtomQ
Toward Greater Autonomy in Materials Discovery Agents: Unifying Planning, Physics, and Scientists
Department of Computer Science and Engineering, Texas A&M University（计算机科学与工程系，德克萨斯A&M大学）；Department of Materials Science and Engineering, Texas A&M University（材料科学与工程系，德克萨斯A&M大学）；Department of Electrical and Computer Engineering, Texas A&M University（电气与计算机工程系，德克萨斯A&M大学）；Computing and Data Sciences, Brookhaven National Laboratory（布鲁赫斯国家实验室计算与数据科学部）；Department of Physics and Astronomy, Texas A&M University（物理与天文学系，德克萨斯A&M大学）
Enabling large language model agents for high-fidelity many-body perturbation theory calculations
University of Southern California（南加州大学）；Sogang University（西江大学）；Center for Nano Materials, Sogang University（西江大学纳米材料中心）；Tamkang University（淡江大学）；Lawrence Berkeley National Laboratory（劳伦斯伯克利国家实验室）
OptiMat Alloys: a FAIR, living database of multi-principal element alloys enabled by a conversational agent
Empa - Swiss Federal Laboratories for Materials Science and Technology（瑞士联邦材料科技研究所）；National Centre for Computational Design and Discovery of Novel Materials MARVEL, Empa（MARVEL新型材料计算设计与发现国家中心）
Harnessing agent memory to build lifelong AI partners for materials scientists
The University of Hong Kong（香港大学）；Materials Innovation Institute for Life Sciences and Energy (MILES), HKU-SIRI（香港大学-深圳国际研究院生命科学与能源材料创新研究院）；International Digital Economy Academy (IDEA)（国际数字经济学院）
DREAMS: Density Functional Theory Based Research Engine for Agentic Materials Simulation
Department of Mechanical Engineering, University of Michigan, Ann Arbor, Michigan, USA（机械工程系，密歇根大学，安阿伯，密歇根州，美国）；Max-Planck-Institute for Sustainable Materials, Materials Informatics, Düsseldorf, Germany（可持续材料研究所，材料信息学，杜塞尔多夫，德国）；Mechanical Engineering, University of Michigan, Ann Arbor, Michigan, USA（机械工程，密歇根大学，安阿伯，密歇根州，美国）
Autonomous Inorganic Materials Discovery via Multi-Agent Physics-Aware Scientific Reasoning
Laboratory for Atomistic and Molecular Mechanics (LAMM) Massachusetts Institute of Technology（原子与分子力学实验室（LAMM）麻省理工学院）；Center for Computational Science and Engineering Schwarzman College of Computing Massachusetts Institute of Technology（计算科学与工程中心施瓦茨曼计算学院麻省理工学院）
GraphAgents: Knowledge Graph-Guided Agentic AI for Cross-Domain Materials Design
Department of Civil and Environmental Engineering Massachusetts Institute of Technology（土木与环境工程系 马萨诸塞理工学院）；Department of Mechanical Engineering Massachusetts Institute of Technology（机械工程系 马萨诸塞理工学院）；Department of Civil and Environmental Engineering Department of Mechanical Engineering Schwarzman College of Computing Massachusetts Institute of Technology（土木与环境工程系 机械工程系 斯沃茨曼计算学院 马萨诸塞理工学院）
Hypothesis-Driven Autonomous Materials Synthesis with Multimodal LLM Agents
Institute of Industrial Science, The University of Tokyo（东京大学工业科学研究所）；The University of Tokyo（东京大学）；Rigaku Corporation（理学公司）；MITSUI KNOWLEDGE INDUSTRY CO., LTD.（三井知识产业株式会社）
Crystal-structure design by agentic AI in a language of motifs
Japan Advanced Institute of Science and Technology（日本先进科学技术学院）；Institute of Science Tokyo（东京科学大学）；The Institute of Statistical Mathematics（统计数理研究所）；Tohoku University（东北大学）
SciAgents: Automating scientific discovery through multi-agent intelligent graph reasoning
Massachusetts Institute of Technology（麻省理工学院）；Schwarzman College of Computing（计算学院）；Center for Computational Science and Engineering（计算科学与工程中心）；Laboratory for Atomistic and Molecular Mechanics (LAMM)（原子与分子力学实验室）
Automated Extraction of Material Properties using LLM-based AI Agents
Mehta Family School of Data Science and Artificial Intelligence（梅塔家族数据科学与人工智能学院）；Indian Institute of Technology Roorkee（印度理工学院罗尔基分校）；Department of Metallurgical and Materials Engineering（冶金与材料工程系）
AtomAgents: Alloy design and discovery through physics-aware multi-modal multi-agent artificial intelligence
Massachusetts Institute of Technology（麻省理工学院）；Center for Computational Science and Engineering（计算科学与工程中心）；Schwarzman College of Computing（计算学院（施瓦曼计算学院））
System of Agentic AI for the Discovery of Metal-Organic Frameworks
University of California, Berkeley（加州大学伯克利分校）；Lawrence Berkeley National Laboratory（伯克利国家实验室）；Google DeepMind（谷歌DeepMind）；Kavli Energy NanoScience Institute（Kavli能源纳米科学研究所）
Hierarchical Deep Research with Local-Web RAG: Toward Automated System-Level Materials Discovery
Pritzker School of Molecular Engineering, University of Chicago（芝加哥大学普利兹克分子工程学院）；Chemical Sciences and Engineering Division, Argonne National Laboratory（阿贡国家实验室化学科学与工程 division）；Department of Computer Science, University of Chicago（芝加哥大学计算机科学系）
Rapid and Automated Alloy Design with Graph Neural Network-Powered LLM-Driven Multi-Agent Systems
Massachusetts Institute of Technology（麻省理工学院）；Schwarzman College of Computing（计算学院）；Center for Computational Science and Engineering（计算科学与工程中心）；Laboratory for Atomistic and Molecular Mechanics (LAMM)（原子与分子力学实验室）
34 Examples of LLM Applications in Materials Science and Chemistry: Towards Automation, Assistants, Agents, and Accelerated Scientific Discovery
ETH Zurich（苏黎世联邦理工学院）；University of Missouri-Columbia（密苏里大学哥伦比亚分校）；McGill University（麦吉尔大学）；University of Houston（休斯顿大学）；Duke University（杜克大学）；University of California at Berkeley（加州大学伯克利分校）；Lawrence Berkeley National Laboratory（伯克利国家实验室）；University of Southern California（南加州大学）；Humboldt University of Berlin（柏林洪堡大学）；Université catholique de Louvain（列日天主大学）；Matgenix SRL（Matgenix公司）；University of California, Los Angeles（加州大学洛杉矶分校）；Friedrich-Schiller-Universität Jena（耶拿弗里德里希-施莱尔大学）；Federal Institute of Materials Research and Testing (BAM)（材料研究与测试联邦机构）；Argonne National Laboratory（阿贡国家实验室）；University of Toronto（多伦多大学）；EPFL（洛桑联邦理工学院）；Massachusetts Institute of Technology（麻省理工学院）；University of Amsterdam（阿姆斯特丹大学）；Acceleration（加速机构）
