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Electrochemical research often requires stringent combinations of experimental parameters that are demanding to manually locate. Recent advances in automated instrumentation and machine-learning algorithms unlock the possibility for accelerated studies of electrochemical fundamentals via high-throughput, online decision-making. Here we report an autonomous electrochemical platform that implements an adaptive, closed-loop workflow for mechanistic investigation of molecular electrochemistry. As a proof-of-concept, this platform autonomously identifies and investigates anECmechanism, an interfacial electron transfer (Estep) followed by a solution reaction (Cstep), for cobalt tetraphenylporphyrin exposed to a library of organohalide electrophiles. The generally applicable workflow accurately discerns theECmechanism’s presence amid negative controls and outliers, adaptively designs desired experimental conditions, and quantitatively extracts kinetic information of theCstep spanning over 7 orders of magnitude, from which mechanistic insights into oxidative addition pathways are gained. This work opens opportunities for autonomous mechanistic discoveries in self-driving electrochemistry laboratories without manual intervention.

 

Redox catalysis has been broadly utilized in electrochemical synthesis due to its kinetic advantages over direct electrolysis. The appropriate choice of redox mediator can avoid electrode passivation and overpotential, which strongly inhibit the efficient activation of substrates in electrolysis. Despite the benefits brought by redox catalysis, establishing the precise nature of substrate activation remains challenging. Herein, we determine that a Co( i ) complex bearing two N , N , N -tridentate ligands acts as a competent redox catalyst for the reduction of benzyl bromide substrates. Kinetic studies combining electroanalytical techniques with multivariable linear-regression analysis were conducted, disclosing an outer-sphere electron-transfer mechanism, which occurs in concert with C–Br bond cleavage. Furthermore, we apply a pattern recognition platform to distinguish between mechanisms in the activation of benzyl bromides, found to be dependent on the ligation state of the cobalt( i ) center and ligand used.