Abstract
<h2>Summary</h2> Selective functionalization of the sterically hindered aromatic <i>meta</i>-C–H bond is unprecedented and remains to be a major challenge. Promoted by automation-based high-throughput experimentation (HTE) and deep learning (DL), a novel strategy to functionalize the hindered <i>meta</i>-C–H bond is disclosed. With carbon dioxide as a traceless director, a one-pot three-step protocol was developed to achieve selective arylation of <i>o</i>-alkylaryl ketones at the hindered <i>meta</i> position. This novel strategy involved photo-induced C–H carboxylation, carboxyl group-directed Pd-catalyzed C–H functionalization, and microwave-assisted decarboxylation. With HTE and DL, a broad scope of substrates was explored (1,032 reactions) and a DL-based model (CMPRY) for reaction yield prediction was established. Two independent tests with unseen <i>o</i>-alkylaryl ketones and/or potassium aryltrifluoroborates were used to evaluate the model. The model gave excellent performances in predicting unseen reactions; mean absolute errors in yield were only 6.6% and 8.4%, suggesting its potential in synthetic application.
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