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Sequential closed-loop Bayesian optimization as a guide for organic molecular metallophotocatalyst formulation discovery

Chemistry

Sequential closed-loop Bayesian optimization as a guide for organic molecular metallophotocatalyst formulation discovery

X. Li, Y. Che, et al.

Discover a groundbreaking two-step data-driven approach for synthesizing organic photoredox catalysts (OPCs) and optimizing reactions for metallophotocatalysis, as demonstrated by Xiaobo Li, Yu Che, and their team. They efficiently explored only 2.4% of the catalyst space to identify highly competitive OPC formulations.

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