Modeling and Analysis of Suspension-Based Electrolytes in Redox Flow Cells

Abstract

Electrochemical systems with flowable suspension electrolytes (FSEs) have potential to help address growing demands for large-scale energy storage in order to bridge the gap between energy demand and renewable energy generation. Redox flow batteries with FSEs, for example, have several advantages in addition to long-duration energy storage and independent scaling of power and energy offered by the traditional flow batteries.1 FSEs containing solid energy storage materials enable higher charge storage capacities and hence higher energy densities, as well as new operating modes such as dissolution from and precipitation onto suspended particles.2-3 However, these emerging electrolyte compositions challenge cell design and operation as new performance trade-offs arising from the complex interplay of non-Newtonian rheology, flow-dependent transport properties, and electrochemical phenomena, must be considered.4 In this presentation, we will introduce a one-dimensional model to study the performance of a representative FSE-containing redox flow cell as a function of various material properties and operating conditions. The model integrates porous electrode theory with non-Newtonian suspension rheology and flow-dependent charge and species transport to investigate connections between rheological and electrochemical phenomena. We expound key dimensionless groups that arise from non-dimensionalizing the governing equations and describe the relative magnitudes of interrelated processes. We discuss model predictions of the cell performance in the multivariable space of the dimensionless groups using computed cell overpotentials and power relative to the pumping power, and identify specific operating regimes. Ultimately, the analysis will offer design considerations for electrochemical systems with FSEs, allowing more informed materials selection, cell engineering, and system architectures. Acknowledgments This work was funded by the Skoltech – MIT Next Generation Program. B.J.N gratefully acknowledge the NSF Graduate Research Fellowship Program under Grant Number 1122374. 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. References M. L. Perry and A. Z. Weber, J. Electrochem. Soc., 163, A5064–A5067 (2016).H. Parant et al., Carbon, 119, 10–20 (2017).X. Wang, J. Chai, and J. “Jimmy” Jiang, Nano Materials Science, 3, 17–24 (2021).N. C. Hoyt, R. F. Savinell, and J. S. Wainright, Chemical Engineering Science, 144, 288–297 (2016).