Artificial Intelligence-Driven Development of Nickel-Catalyzed Enantioselective Cross-Coupling Reactions

ACS Catalysis, Год журнала: 2024, Номер unknown, С. 18457 - 18468

Опубликована: Дек. 3, 2024

The conventional approach to developing asymmetric synthetic methods relies heavily on empirical optimization. However, the integration of artificial intelligence (AI) and high-throughput experimentation (HTE) technology presents a paradigm shift with immense potential revolutionize discovery optimization reactions. In this study, we present an efficient workflow for development series nickel-catalyzed cross-coupling reactions, leveraging AI HTE technology. Many enantioselective reactions share common Ni(III) intermediate, which dictates enantioselectivity. To harness mechanistic insight, embarked predictive model coupling elucidating general rules governing Through application data science tools technology, curated set construct AI-based model. This was subsequently utilized facilitate nickel hydride-catalyzed regioselective Employing AI-assisted virtual ligand screening HTE-enabled condition optimization, successfully identified optimal ligands eight Consequently, chiral sp3 C–C bonds were synthesized high yield

Язык: Английский

Photocatalyzed cascade hydrogen atom transfer for the construction of α-CF₃-1,4-diketones

Organic Chemistry Frontiers, Год журнала: 2024, Номер unknown

Опубликована: Дек. 5, 2024

A TBADT-photocatalyzed cascade hydrogen atom transfer procedure was established for the synthesis of α-CF 3 -1,4-diketones from aldehydes and 2-bromo-3,3,3-trifluoro-1-propenes.

Язык: Английский