Bayesian optimization of dynamic Ce( III ) electrooxidation

Frey, Daniel; Shin, Ju Hee; Akin, Adeola; Zhang, Xinshu; Modestino, Miguel A.

doi:10.1002/aic.17930

Bayesian optimization of dynamic Ce( III ) electrooxidation

Journal Article · 27 October 2022 · AIChE Journal

DOI:https://doi.org/10.1002/aic.17930· OSTI ID:2425596

Frey, Daniel ^[1]; Shin, Ju Hee ^[1]; Akin, Adeola ^[1]; Zhang, Xinshu ^[1]; ^[1]

Department of Chemical and Biomolecular Engineering New York University Brooklyn New York USA

Abstract

Cerium(III/IV) is a redox couple with promising applications in redox flow batteries and redox‐mediated water electrolyzers, but due to its high oxidation potential, parasitic oxygen evolution can occur and decrease the Faradaic efficiency (FE) of the oxidation reaction. Dynamic potential dosing can help balance the transport limitations and the electrooxidation rates, allowing for control over the cerium(III) concentration near the electrode, enhancing FE. Due to the large number of possible pulsing operating conditions, Bayesian optimization (BO) was used to rapidly identify the optimal potential pulses. With an active pulse voltage of 2.5 V vs. Ag/AgCl, the maximum FE achieved was 0.91 (active pulse time = 5 ms, resting pulse time = 136 ms), underscoring the need for long inactive times for cerium(III) diffusion to the electrode. Furthermore, a multiobjective BO was performed to identify optimal trade‐offs between FE and the partial current density to achieve improvements over constant current operation.

Research Organization:: Oak Ridge Institute for Science and Education (ORISE), Oak Ridge, TN (United States)

Sponsoring Organization:: USDOE Office of Science (SC)

DOE Contract Number:: SC0014664

OSTI ID:: 2425596

Journal Information:: AIChE Journal, Journal Name: AIChE Journal Journal Issue: 12 Vol. 68; ISSN 0001-1541

Publisher:: American Institute of Chemical Engineers

Country of Publication:: United States

Language:: English

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