Molecular Dynamics Simulations of Electrolyte Solutions for Organic Redox Flow Batteries

Organic redox flow batteries (ORFBs) are emerging as promising candidates for sustainable, large-scale energy storage applications [1]. A fundamental understanding of electrolyte behavior at the molecular level is essential for improving the performance, stability, and efficiency of these systems [2]. In this work, we employ classical molecular dynamics (MD) simulations to investigate the structural and dynamical properties of electrolyte solutions and their interactions at the electrode/electrolyte interface. Our study follows a systematic, stepwise approach in which individual components and their mixtures are examined. Initially, pure solvents such as acetonitrile and 3-methoxypropionitrile are simulated to characterize their bulk properties and molecular organization. The study is then extended to the ionic liquid 1-ethyl-3-methylimidazolium bis(trifluoromethanesulfonyl)imide (EMIMTFSI), analyzed both in isolation and in combination with the solvents. These simulations provide insights into solvent structure, ion solvation environments, ion pairing, and the effect of solvent composition on electrolyte organization. Simulations are performed using the LAMMPS package [3], employing the non-polarizable OPLS-AA force field [4] for molecular solvents and the CL&P force field for ionic liquids [5]. To approximate electronic polarization effects, a charge scaling factor is applied [6]. In future work, redox-active species will be incorporated to study solvation dynamics and interfacial processes in ORFB systems. References [1] Leung, P., Shah, A. A., Sanz, L., Flox, C., Morante, J. R., Xu, Q., ... & Walsh, F. C., Recent developments in organic redox flow batteries: A critical review, Journal of Power Sources, 360, 243-283. (2017). [2] Reeves, K. G., Serva, A., Jeanmairet, G., & Salanne, M., A first-principles investigation of the structural and electrochemical properties of biredox ionic species in acetonitrile., Physical Chemistry Chemical Physics, 22 (19), 10561-10568. (2020). [3] A. P. Thompson, H. M. Aktulga, R. Berger, D. S. Bolintineanu, W. M. Brown, P. S. Crozier, P. J. in 't Veld, A. Kohlmeyer, S. G. Moore, T. D. Nguyen, R. Shan, M. J. Stevens, J. Tranchida, C. Trott, S. J. Plimpton., LAMMPS - a flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales., Computer physics communications., 271 , 108171. (2022). [4] Dodda, L. S., Cabeza de Vaca, I., Tirado-Rives, J., & Jorgensen, W. L., LigParGen web server: an automatic OPLS-AA parameter generator for organic ligands., Nucleic acids research, Nucleic acids research. 45(W1), W331-W336. (2017). [5] Canongia Lopes, J. N., & Pádua, A. A., CL&P: A generic and systematic force field for ionic liquids modeling., Theoretical Chemistry Accounts,. 131 , 1-11. (2012). [6] Doherty, B., Zhong, X., Gathiaka, S., Li, B., & Acevedo, O., Revisiting OPLS force field parameters for ionic liquid simulations., Journal of chemical theory and computation,. 13 (12), 6131-6145. (2017).