做材料设计的可以看看，ALKEMIE Agent 能自动跑 LAMMPS。
ALKEMIE Agent 是一个集成了检索增强生成和材料计算知识库的自主平台。该平台在可追踪的控制回路中整合了 AI 辅助结构建模、有界任务执行和工具调用迭代等功能。演示案例涵盖了材料推荐、声子计算、LAMMPS 模拟以及基于主动学习的材料筛选。系统还支持机器学习原子间势训练和 Ab Initio Monte Carlo (AIMC) 采样。
ALKEMIE Agent: an autonomous platform for computational materials design
Despite the powerful multi-scale modeling methods and high-throughput infrastructures established in the materials community, real material computation workflows remain fragmented and heavily manual, requiring researchers to constantly bridge software tools, data analysis, and intermediate decisions. This growing gap between methodological capability and practical execution highlights the need for a new kind of autonomous computational framework, one that can coordinate tools, knowledge, and workflows in a more unified and adaptive way. Here, we introduce ALKEMIE Agent, an agentic platform in which retrieval-augmented generation, a materials-computation knowledge base, registered skills, database-supported provenance, AI-assisted structure modeling, bounded task execution, tool-calling iteration, and error-diagnostic assistance are integrated within a traceable control loop. The capabilities of ALKEMIE Agent are demonstrated through applications including materials recommendation, structure modeling, phonon calculations, machine-learned interatomic potential training, LAMMPS simulations, Ab Initio Monte Carlo (AIMC) sampling, and active-learning-based materials screening. Finally, we outline the future directions and challenges for the development of agentic platforms for computational materials design.