Revealing the origin of the solubility and stability of organic/inorganic electrolytes in aqueous redox flow batteries

Abstract

Computational chemistry has proven to be a powerful tool for gaining a fundamental understanding of chemical phenomena and facilitating their applications. Herein, I introduce novel methods for evaluating the solubility and stability of organic/inorganic charge carriers in redox flow batteries based on a combination of density functional theory and molecular dynamics. I also explore machine-learning approaches to develop a solubility prediction model from an ab initio perspective. Furthermore, I will delve into the mechanistic studies focused on the formation and utilization of metal-ligand multiple bonds, providing valuable insights into inorganic synthesis. In summary, this dissertation will apply various computational techniques to provide in-depth insights across multiple domains, including electrochemistry, organic chemistry, and inorganic chemistry.