Autor: |
Lin, Zhipeng, Dhawa, Uttam, Hou, Xiaoyan, Surke, Max, Yuan, Binbin, Li, Shu-Wen, Liou, Yan-Cheng, Johansson, Magnus J., Xu, Li-Cheng, Chao, Chen-Hang, Hong, Xin, Ackermann, Lutz |
Předmět: |
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Zdroj: |
Nature Communications; 7/15/2023, Vol. 14 Issue 1, p1-8, 8p |
Abstrakt: |
Electrooxidation has emerged as an increasingly viable platform in molecular syntheses that can avoid stoichiometric chemical redox agents. Despite major progress in electrochemical C−H activations, these arene functionalizations generally require directing groups to enable the C−H activation. The installation and removal of these directing groups call for additional synthesis steps, which jeopardizes the inherent efficacy of the electrochemical C−H activation approach, leading to undesired waste with reduced step and atom economy. In sharp contrast, herein we present palladium-electrochemical C−H olefinations of simple arenes devoid of exogenous directing groups. The robust electrocatalysis protocol proved amenable to a wide range of both electron-rich and electron-deficient arenes under exceedingly mild reaction conditions, avoiding chemical oxidants. This study points to an interesting approach of two electrochemical transformations for the success of outstanding levels of position-selectivities in direct olefinations of electron-rich anisoles. A physical organic parameter-based machine learning model was developed to predict position-selectivity in electrochemical C−H olefinations. Furthermore, late-stage functionalizations set the stage for the direct C−H olefinations of structurally complex pharmaceutically relevant compounds, thereby avoiding protection and directing group manipulations. Electrochemistry has emerged as an increasingly viable tool in molecular synthesis. Here the authors realize electrocatalyzed C−H activations, with the aid of data science and artificial intelligence, towards selective alkenylations for late-stage drug diversifications. [ABSTRACT FROM AUTHOR] |
Databáze: |
Complementary Index |
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