LEAP uses a domain-specialized LLM and Bayesian optimization to prioritize perovskite additives, achieving average PCEs of 20.13% and 20.87% in later screening rounds versus 19.25% control, with a champion of 21.32%.
Organometal halide perovskites as visible-light sensitizers for photovoltaic cells.Journal of the american chemical society, 131(17):6050–6051, 2009
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A fine-tuned LLM called Perovskite-R1, built from curated perovskite literature and material libraries, proposes precursor additives and designs with some experimental validation showing improved stability and performance.
citing papers explorer
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LEAP: A closed-loop framework for perovskite precursor additive discovery
LEAP uses a domain-specialized LLM and Bayesian optimization to prioritize perovskite additives, achieving average PCEs of 20.13% and 20.87% in later screening rounds versus 19.25% control, with a champion of 21.32%.
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Perovskite-R1: a domain-specialized large language model for intelligent discovery of precursor additives and experimental design
A fine-tuned LLM called Perovskite-R1, built from curated perovskite literature and material libraries, proposes precursor additives and designs with some experimental validation showing improved stability and performance.