Identifying Reactive\nTrends in Glycerol Electro-Oxidation\nUsing an Automated Screening Approach: 28 Ways to Electrodeposit an\nAu Electrocatalyst

Automated, rapid electrocatalyst discovery techniques\nthat comprehensively\naddress the exploration of chemical spaces, characterization of catalyst\nrobustness, reproducibility, and translation of results to (flow)\nelectrolysis operation are needed. Responding to the growing interest\nin biomass valorization, we studied the glycerol electro-oxidation\nreaction (GEOR) on gold in alkaline media as a model reaction to demonstrate\nthe efficacy of such methodology introduced here. Our platform combines\nindividually addressable electrode arrays with HardPotato, a Python\napplication programming interface for potentiostat control, to automate\nelectrochemical experiments and data analysis operations. We systematically\ninvestigated the effects of reduction potential (<i>E</i><sub>l</sub>) and pulse width (PW) on GEOR activity during the electrodeposition\n(Edep) of gold, evaluating 28 different conditions in triplicate measurements\nwith great versatility. Our findings reveal a direct correlation between <i>E</i><sub>l</sub> and GEOR activity. Upon CV cycling, we recorded\na 52% increase in peak current density and a −0.25 V shift\nin peak potential as <i>E</i><sub>l</sub> varied from −0.2\nto −1.4 V. We also identified an optimal PW of ∼1.0\ns, yielding maximum catalytic performance. The swift analysis enabled\nby our methodology allowed us to correlate performance enhancements\nwith increased electrochemical surface area and preferential deposition\nof Au(110) and Au(111) sites, even in disparate Edep conditions. We\nvalidate our methodology by scaling the Edep process to larger electrodes\nand correlating intrinsic activity with product speciation via flow\nelectrolysis measurements. Our platform highlights opportunities in\nautomation for electrocatalyst discovery to address pressing needs\ntoward industrial decarbonization, such as biomass valorization.