AI agents are emerging as a practical way to run multi-step scientific workflows that interleave reasoning, tool use, and verification. Scaling such agentic science remains difficult because workflows are hard to observe and reproduce, many scientific tools and laboratory systems are not agent-ready, and execution trac...
Lin-Feng Zhang, Si-Heng Chen, Yu-Zhu Cai et al.· AI Plus· 0 citations
General-purpose machine-learning interatomic potentials (MLIPs) for organic reactions need to be accurate on both the minimum energy path (MEP) for static evaluation of basic properties and the broader configurational space for simulating reaction dynamics. Existing general datasets for gas-phase organic reactions rely...
Wan-Run Jiang, Jin-Zhe Zeng, Man-Yi Yang et al.· 0 citations
dpti, an open-source Python package that automates TI workflows for phase diagram calculations with MLIPs, and provides a useful tool for automated phase diagram calculations of materials modeled by MLIPs.
Fengbo Yuan, Xin Zhong, Donghao Zheng et al.· 0 citations
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