LEAP: A closed-loop framework for perovskite precursor additive discovery
Researchers have developed LEAP, a closed-loop framework that uses a domain-specific large language model combined with active learning to discover additives for perovskite solar cells. This LLM is trained to extract knowledge from scientific literature and represent molecules, which then informs a Bayesian optimization process for prioritizing additives. Experimental validation showed improved additive prioritization, leading to higher power conversion efficiencies in perovskite devices. AI
IMPACT Introduces a novel LLM-driven framework for accelerating materials discovery in photovoltaics.