![](https://www.aiche.org/sites/default/files/images/conference/logo/2022_annual_logo_0.png)
![](https://www.aiche.org/sites/default/files/images/conference/logo/2022_annual_logo_0.png)
In this presentation, we will discuss how Bayesian Optimization (BO) approaches can be implemented to efficiently explore the design space of pulsed electrochemical processes and lead to enhancement in performance. Electrooxidation of Cerium(III) to Ce(IV) electrolytes will be discussed as a model electrochemical reaction. This reaction is relevant to redox flow battery and redox-mediated water electrolysis, and due to its high oxidation potential, it competes with parasitic oxygen evolution reaction (OER) which lowers its Faradaic Efficiency (FE). We will show how dynamic potential dosing can help balance Ce(III) transport and electrooxidation rates, allowing finer control over its concentration near the electrode and ultimately enhancing FE. Due to the large number of possible pulse sequences, continuum transport and reaction models were built to identify the appropriate window of operating conditions, and then BO was used to rapidly identify the optimal potential pulses. After 25 experiments, a maximum FE = 0.91 was achieved (active pulse time = 5ms, resting pulse time = 136ms, and active pulse voltage of 2.5 V vs. Ag/AgCl) compared to FE = 0.55 at constant potential operation. Furthermore, we will present a multi-objective BO method to identify the pareto conditions that lead to the optimal trade-off between FE and Ce(III) electrooxidation rate – two relevant performance metrics for practical implementation. Similar BO approaches implemented for dynamic CO2 electroreduction and organic electrosynthesis will also be discussed.