(293i) Mathematical Modeling of Redox-Mediated Processes in Electrochemical Systems

Electrochemical processes are poised to play a pivotal role in the evolving global power system as the efficient interconversion of electrical and chemical energy can enable the deployment of sustainable technologies that support the decarbonization of the electric grid, power the automotive fleet, and offer new opportunities for chemical manufacturing. However, this transition requires new electrochemical technologies with performance, cost, and scalability metrics that align with emerging needs, inspiring innovative approaches that leverage unconventional materials and/or reactor designs. Redox-mediated electrode processes, where a soluble redox couple (the mediator) shuttles electrons to / from an "off-electrode" material, are of emerging interest as they may expand the portfolio of feasible reactants, system configurations, and operating modes. Prior literature has taught how this approach can enhance the charge-storage capacity of redox flow batteries, facilitate difficult-to-perform electrochemical transformations, and unlock spatial and temporal flexibility in electrochemical processes. While promising, the performance of these systems is governed by coupled reactive-transport processes which present complex (and transient) interdependencies that frustrate navigation through the multi-dimensional design space.

Here, we will present a mathematical modeling framework that uses traditional chemical engineering principles to describe redox-mediated electrochemical processes. Simulated electrochemical and fluid dynamic performances will be validated against experimental observations reported in the literature. Subsequently, dimensionless groups will be derived that enable the generalization of model findings (e.g., scaling relationship and property tradeoffs) and the articulation of design criteria for existing and conceptual electrochemical energy systems.

Acknowledgements

This work was funded by the Skoltech – MIT Next Generation Program. N.J.M gratefully acknowledges the NSF Graduate Research Fellowship Program under Grant Number 2141064. Any opinion, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the NSF.