Optimizing the Heck-Matsuda Reaction in Flow with a Constraint-Adapted Direct Search Algorithm

The optimization of a palladium-catalyzed Heck-Matsuda reaction using an optimization algorithm is presented. We modified and implemented the Nelder-Mead method in order to perform constrained optimizations in a multidimensional space. We illustrated the power of our modified algorithm through the optimization of a multivariable reaction involving the arylation of a deactivated olefin with an arenediazonium salt. The great flexibility of our optimization method allows to fine-tune experimental conditions according to three different objective functions: maximum yield, highest throughput, and lowest production cost. The beneficial properties of flow reactors associated with the power of intelligent algorithms for the fine-tuning of experimental parameters allowed the reaction to proceed in astonishingly simple conditions unable to promote the coupling through traditional batch chemistry.