A scanning flow cell approach for generation of electrocatalyst material libraries via electrodeposition

Multi-element material systems offer great property-tailoring possibilities for electrocatalysis. Experimental exploration of multi-dimensional composition spaces requires high-throughput methods for targeted synthesis and testing. We present a scanning flow cell setup that can synthesize material libraries of multi-component alloys via electrodeposition, test the electrocatalytic activity of the samples immediately after synthesis, and measure the stability under electrocatalytic conditions with online dissolution monitoring. Using this setup, we explored the Au-Pd-Pt ternary space with 45 samples and demonstrated autonomous exploration guided by Bayesian active learning. The oxygen reduction activity of Au-Pd-Pt alloys exhibits a smooth relationship with composition, decreasing with increasing gold fraction. The stability shows an opposite trend, leading to an inverse relationship between stability and activity.