4 papers
AdsMind: A Physics-Grounded Multi-Agent System for Self-Correcting Discovery of Adsorption Configurations on Heterogeneous Catalyst Surfaces
Zongmin Zhang, Yuyang Lou, Bowen Zhang +6
Identifying the lowest-energy surface-adsorbate configuration is critical for modeling heterogeneous catalysis, yet exhaustive exploration with ab initio calculations is computatio…
Accelerating Scientific Discovery with Autonomous Goal-evolving Agents
Yuanqi Du, Botao Yu, Tianyu Liu +25
There has been unprecedented interest in developing agents that expand the boundary of scientific discovery, primarily by optimizing quantitative objective functions specified by s…
CASCADE: Cumulative Agentic Skill Creation through Autonomous Development and Evolution
Xu Huang, Junwu Chen, Yuxing Fei +3
Large language model (LLM) agents currently depend on predefined tools or early-stage tool generation, limiting their adaptability and scalability to complex scientific tasks. We i…
Accelerating inverse materials design using generative diffusion models with reinforcement learning
Junwu Chen, Jeff Guo, Edvin Fako +1
Diffusion models promise to accelerate material design by directly generating novel structures with desired properties, but existing approaches typically require expensive and subs…