(390d) Electrode Surface Heating with Organic Films Improves CO2 Electroreduction Kinetics on Copper
AIChE Annual Meeting
2024
2024 AIChE Annual Meeting
Catalysis and Reaction Engineering Division
Electrochemical Engineering and Reactor Design III: Engineering the Reactor for Electrochemical CO2 Conversion - Experimental Demonstrations
Tuesday, October 29, 2024 - 4:24pm to 4:42pm
Management of the electrode surface temperature is an important aspect of (photo)electrochemical reactor design in both fundamental studies and optimized systems for complex reactions such as CO2 reduction. Inadvertent heating from resistive losses in electrochemical systems, as well as radiative heating in photoelectrochemical systems, can result in electrode surface temperatures in excess of 10 °C above ambient. Studies of the effects of electrode temperature have traditionally been limited to thermal management of the entire electrochemical cell, which conflates thermal activation of reactions at the electrode surface with other factors such as the transport of volatile reactants, in particular dissolved CO2. In this talk, we show the impact of local electrode heating on electrochemical CO2 reduction. Using the ferri/ferrocyanide open circuit voltage as a reporter of the effective reaction temperature, we reveal how the interplay of surface heating and convective cooling poses a challenge for co-optimizing mass transport and thermal assistance of electrochemical reactions, where we focus on reduction of CO2 to carbon-coupled (C2+) products. The introduction of an organic coating on the electrode surface facilitates well-behaved electrokinetics with near-ambient bulk electrolyte, enabling the discovery that surface heating to 80 °C decreases the voltage required for peak C2+ performance by ca. 100 mV compared to ambient conditions. This approach to thermal management offers a new dimension to electrochemical systems design as well as the opportunity to further probe thermal effects in electrochemical reactions, as demonstrated through Bayesian inference of Butler-Volmer kinetic parameters from a suite of high throughput experiments.