摘要
In this work, we develop LEAP (LLM-driven Exploration via Active Learning for Perovskites), an expert-in-the-loop closed-loop framework that couples a domain-specialized large language model with active learning for iterative additive prioritization, achieving improved device performance in proof-of-concept perovskite solar cell experiments.