Development Of Pd-immobilized Porous Polymer Catalysts Via Bayesian Optimization

This article discusses the use of machine learning for the optimization of polymer-immobilized catalysts, specifically for Suzuki-Miyaura coupling reactions. The study utilizes a Bayesian optimization method to improve the efficiency of the catalyst and provides a new perspective on using machine learning for complex materials.