Abstract

Understanding the polarization dynamics of polar solvents is important in advancing research in soft matter, electrochemistry, and biophysics, where accurate prediction of dielectric response plays a key role. In this context, Stochastic Density Functional Theory (SDFT) has emerged as a powerful theoretical framework capable of capturing the collective dynamic behavior of dipolar molecules by incorporating thermal fluctuations into the time-dependent density field. The present work evaluates the reliability of SDFT in predicting the polarization dynamics of polar solvents and provides key insights into integrating these effects into simulations, enabling more accurate and predictive modeling of the solvent polarization effects in soft-matter systems.  Abstract title: Understanding polar solvents through the lens of Stochastic Density Functional Theory  Abstract: Understanding the microscopic behavior and organization of polar solvents has direct implications for a variety of applications, from advanced battery and fuel cell design to the study of charged soft matter systems. Predicting solvent structure and dynamics from first principles remains a significant challenge due to the complex interplay of thermal fluctuations, electrostatic interactions, and molecular orientation. Among the available theoretical approaches, stochastic density functional theory (SDFT) has emerged as a powerful tool for exploring the collective dynamical properties of polar solvents. In this work, we examine the effectiveness of SDFT in describing a polar solvent by comparing its predictions with Brownian dynamics simulations of the Stockmayer fluid-a widely used theoretical model for polar fluids. Our findings indicate that SDFT offers a promising framework for linking molecular-scale interactions to mesoscopic behavior across a broad range of electrochemical and soft-matter systems.