The next direction for our platform is incorporating it with machine learning, enabling fully autonomous electrochemical experiments. Electrochemistry is beginning to integrate machine learning to aid in determining reaction mechanisms. Recent work has shown the combination of deep learning and automated experimentation allows for fully closed-loop mechanistic studies of molecular electrochemistry, however this type of workflow has yet to be applied to electrocatalytic systems. We are excited to explore such a closed-loop system for the study of molecular electrocatalysis using our new automated platform. We believe that such a system will enable rapid discovery of new effective electrocatalysts, and accelerate molecular electrocatalysis for energy conversion, fuel valorization, bioelectrochemical sensing, and other practical applications.