Identifying Reactive Trends in Glycerol Electro-Oxidation Using an Automated Screening Approach: 28 Ways to Electrodeposit an Au Electrocatalyst

Abstract

Automated, rapid electrocatalyst discovery techniques that comprehensively address the exploration of chemical spaces, characterization of catalyst robustness, reproducibility, and translation of results to (flow) electrolysis operation are needed. Responding to the growing interest in biomass valorization, we studied the glycerol electro-oxidation reaction (GEOR) on gold in alkaline media as a model reaction to demonstrate the efficacy of such methodology introduced here. Our platform combines individually addressable electrode arrays with HardPotato, a Python application programming interface for potentiostat control, to automate electrochemical experiments and data analysis operations. We systematically investigated the effects of reduction potential (E_l) and pulse width (PW) on GEOR activity during the electrodeposition (Edep) of gold, evaluating 28 different conditions in triplicate measurements with great versatility. Our findings reveal a direct correlation between E_l and GEOR activity. Upon CV cycling, we recorded a 52% increase in peak current density and a −0.25 V shift in peak potential as E_l varied from −0.2 to −1.4 V. We also identified an optimal PW of ∼1.0 s, yielding maximum catalytic performance. The swift analysis enabled by our methodology allowed us to correlate performance enhancements with increased electrochemical surface area and preferential deposition of Au(110) and Au(111) sites, even in disparate Edep conditions. We validate our methodology by scaling the Edep process to larger electrodes and correlating intrinsic activity with product speciation via flow electrolysis measurements. Our platform highlights opportunities in automation for electrocatalyst discovery to address pressing needs toward industrial decarbonization, such as biomass valorization.