Atomistic simulations are essential tools in chemistry and materials science, accelerating the discovery of novel catalysts, energy storage materials, and pharmaceuticals. However, running these simulations remains challenging due to the wide range of computational methods, diverse software ecosystems, and the need for expert knowledge and manual effort for the setup, execution, and validation stages. In this work, we present ChemGraph, an agentic framework powered by artificial intelligence and state-of-the-art simulation tools to streamline and automate computational chemistry and materials science workflows. ChemGraph leverages graph neural network-based foundation models for accurate yet computationally efficient calculations and large language models (LLMs) for natural language understanding, task planning, and scientific reasoning to provide an intuitive and interactive interface. Users can perform tasks such as molecular structure generation, single-point energy, geometry optimization, vibrational analysis, and thermochemistry calculations with methods ranging from tight-binding and machine learning interatomic potentials to density functional theory or wave function theory-based methods. We evaluate ChemGraph across 13 benchmark tasks and demonstrate that smaller LLMs (GPT-4o-mini, Claude-3.5-haiku, Qwen2.5-14B) perform well on simple workflows, while more complex tasks benefit from using larger models like GPT-4o. Importantly, we show that decomposing complex tasks into smaller subtasks through a multi-agent framework enables smaller LLM models to match or exceed GPT-4o's performance in specific scenarios.
ChemGraph-XANES: An Agentic Framework for XANES Simulation and Curation
Chemical Sciences and Engineering Division Argonne National Laboratory（阿贡国家实验室化学科学与工程部）；Computational Science Division Argonne National Laboratory（阿贡国家实验室计算科学部）
Agentic generation of verifiable rules for deterministic, self-expanding reaction classification
École Polytechnique Fédérale de Lausanne (EPFL)（洛桑联邦理工学院）；Laboratory for Chemical Technology, Ghent University（根特大学化学技术实验室）；NCCR Catalysis（瑞士国家研究能力中心催化项目）
Harnessing AtomisticSkills for Agentic Atomistic Research
Department of Materials Science；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；Harvard University, Department of Chemistry；Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA 02139, USA；Department of Nuclear Science；Shell Information Technology International Inc., Texas 77082, United States；Shell International Exploration \& Production Inc., Texas 77079, United States
Science Done on a Machine by a Machine: AI Agents in Computational Chemistry
State Key Laboratory of Physical Chemistry of Solid Surfaces（固体表面物理化学国家重点实验室）；College of Chemistry（化学学院）；Xiamen University（厦门大学）；School of Physics, Anhui University（安徽大学物理学院）
Autonomous Chemical Mechanistic Discovery through Agentic Reasoning and Validation
Shanghai Artificial Intelligence Laboratory（上海人工智能实验室）；Institute for Advanced Study in Mathematics, Harbin Institute of Technology（哈尔滨工业大学数学研究院）；School of Mathematics, Harbin Institute of Technology（哈尔滨工业大学数学学院）；School of Chemistry and Molecular Engineering, East China Normal University（华东师范大学化学与分子工程学院）；Department of Chemistry, Fudan University（复旦大学化学系）；Department of Electronic Engineering, Tsinghua University（清华大学电子工程系）；School of Chemical Science and Engineering, Tongji University（同济大学化学科学与工程学院）
CASCADE: Cumulative Agentic Skill Creation through Autonomous Development and Evolution
Department of Materials Science and Engineering, University of California, Berkeley, California, United States（加州大学伯克利分校材料科学与工程系）；Materials Sciences Division, Lawrence Berkeley National Laboratory, California, United States（劳伦斯伯克利国家实验室材料科学部）；Laboratory of Artificial Chemical Intelligence (LIAC), Institute of Chemical Sciences and Engineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland（日内瓦联邦理工学院化学科学与工程研究所人工化学智能实验室）；National Centre of Competence in Research (NCCR) Catalysis, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland（日内瓦联邦理工学院催化研究国家中心）
The convergent laboratory: when AI reasoning, autonomous experiments, high performance and quantum computing reshape chemistry
Argonne National Laboratory（阿贡国家实验室）；The University of Chicago（芝加哥大学）；NVIDIA Corporation（英伟达公司）；Northwestern University（西北大学）；Lila Sciences, Inc.（Lila Sciences公司）；PsiQuantum（PsiQuantum公司）；University of Toronto（多伦多大学）；Vector Institute for Artificial Intelligence（向量人工智能研究所）
LARC: Towards Human-level Constrained Retrosynthesis Planning through an Agentic Framework
Department of Computer Science and Engineering, 2 Division of Medicinal Chemistry & Pharmacognosy, 3 Department of Biomedical Informatics, 4 Translational Data Analytics Institute（1 计算机科学与工程系，2 药物化学与药理学系，3 生物医学信息学系，4 转化数据分析研究所）
Agentic reinforcement learning empowers next-generation chemical language models for molecular design and synthesis
School of Electronic and Computer Engineering, Peking University（电子与计算机工程学院，北京大学）；Shenzhen Graduate School, Shenzhen, 518055, China（深圳研究生院，深圳，518055，中国）；International Digital Economy Academy (IDEA)（国际数字经济学院（IDEA））；Peng Cheng Laboratory, Shenzhen, 518000, China（鹏城实验室，深圳，518000，中国）
FRAGMENTA: Efficient End-to-end Fragmentation-based Generative Model with Agentic Tuning for Drug Lead Optimization in Small Data Regime
Department of Computer Science and Engineering（计算机科学与工程系）；University of Colorado Denver（科罗拉多大学丹佛分校）；Skaggs School of Pharmacy（斯卡格斯药学院）；University of Colorado Anschutz Medical Campus（科罗拉多大学安舒茨医疗分校）
ARMOR: An Agentic Framework for Reaction Feasibility Prediction via Adaptive Utility-aware Multi-tool Reasoning
Department of Biomedical Informatics（生物医学信息学系）；Department of Computer Science and Engineering（计算机科学与工程系）；Division of Medicinal Chemistry and Pharmacognosy（药物化学与药理学系）；Translational Data Analytics Institute（转化数据分析研究所）
La Agente Óptima: Towards Agentic Self-Driving Laboratories
University of Toronto（多伦多大学）；Acceleration Consortium（加速联盟）；Vector Institute for Artificial Intelligence（向量人工智能研究所）；Canadian Institute for Advanced Research (CIFAR)（加拿大高级研究院）；NVIDIA（英伟达）；University of Amsterdam（阿姆斯特丹大学）；Instituto de Micro y Nanotecnología, IMN-CNM, CSIC（西班牙国家研究委员会微纳米技术研究所）；Sungkyunkwan University（成均馆大学）；Merck KGaA（默克集团）
Evidence-Grounded Frontier Mapping and Agentic Hypothesis Generation in Nanomedicine
ARIA Lab, Signal Processing Systems, Department of Electrical Engineering, Eindhoven University of Technology（ARIA实验室，信号处理系统，电气工程系，埃因霍温理工大学）；Laboratory of Chemical Biology, Department of Biomedical Engineering, Eindhoven University of Technology（化学生物学实验室，生物医学工程系，埃因霍温理工大学）；The Louis Family Laboratory for Targeted Drug Delivery and Personalized Medicine Technologies, Department of Chemical Engineering, Technion - Israel Institute of Technology（定向药物输送与个性化医学技术实验室，化学工程系，技术离子-以色列理工学院）；Department of Nanomedicine and Theranostics, Institute for Experimental Molecular Imaging (ExMI), RWTH Aachen University Hospital（纳米医学与诊疗学系，实验分子成像研究所（ExMI），亚琛工业大学医院）；Department of Internal Medicine and Radboud Center for Infectious Diseases (RCI), Radboud University Medical Center（内科学系和Radboud感染疾病中心（RCI），Radboud大学医学中心）
Can Agents Price a Reaction? Evaluating LLMs on Chemical Cost Reasoning
Carnegie Mellon University（卡内基梅隆大学）；University of Notre Dame（Notre Dame 大学）；University of North Carolina, Chapel Hill（北卡罗来纳大学教堂山分校）；University of Pittsburgh（匹兹堡大学）
From Prompts to Protocols: An AI Agent for Laboratory Automation
Department of Computer Science, University of North Carolina at Chapel Hill（北卡罗来纳大学教堂山分校计算机科学系）；Department of Chemistry, University of North Carolina at Chapel Hill（北卡罗来纳大学教堂山分校化学系）
El Agente Quntur: A research collaborator agent for quantum chemistry
University of Toronto（多伦多大学）；Vector Institute for Artificial Intelligence（向量人工智能研究所）；Canadian Institute for Advanced Research (CIFAR)（加拿大高级研究 institute）；NVIDIA；Institute of Medical Science（医学科学研究所）
LLM-Guided Test-Time Discovery of Quantum-Chemical Approximation Algorithms
Lattice Lab, Toyota Motor Corporation（丰田汽车公司格子实验室）；Department of Chemistry, Graduate School of Science, Nagoya University（名古屋大学理学部化学科）；National Institute of Informatics（国家信息研究所）
El Agente Sólido: A New Age(nt) for Solid State Simulations
University of Toronto（多伦多大学）；Acceleration Consortium（加速联盟）；Vector Institute for Artificial Intelligence（矢量人工智能研究所）；Canadian Institute for Advanced Research (CIFAR)（加拿大高等研究院）；NVIDIA（英伟达）；Institute of Medical Science（医学科学研究所）
El Agente Sólido是一种基于多代理框架的自动化固态量子化学模拟工具，结合密度泛函理论与机器学习势能，提升材料发现的效率和可重复性。
