Abstract Recent experimental and computational studies increasingly demonstrate that solvent dynamics play a decisive role in nucleation, crystallization, and interfacial kinetics during solution-based thin-film deposition. Across perovskite, sol–gel, and electrodeposited systems, time-dependent solvent reorganization and interfacial structuring have been shown to directly influence film morphology, defect formation, and functional performance. Despite this growing evidence, solvent effects are still predominantly rationalized using static descriptors such as dielectric constant, polarity, or donor number. These macroscopic averages fail to capture the dynamic, time-dependent processes that govern precursor coordination, nucleation, and crystallization under nonequilibrium conditions. This mini-review consolidates experimental and computational evidence showing that solvent reorganization, interfacial structuring, and fluctuating solvation fields critically shape film morphology and functionality. Time-resolved spectroscopies (SFG, 2D-IR, ultrafast X-ray) and in situ scattering (GIWAXS/GISAXS) reveal femtosecond to second-scale solvent dynamics that steer phase transitions and defect formation in perovskite, sol–gel, and electrodeposited systems. Complementary ab initio molecular dynamics (AIMD) and multiscale simulations demonstrate how fluctuating solvation fields modulate reaction barriers and interfacial kinetics. Across materials classes, dynamic solvation—rather than equilibrium solvent parameters—emerges as the controlling factor for structure evolution and performance. The review outlines experimental–computational strategies to quantify solvent fluctuation timescales, proposes dynamic descriptors as new design parameters, and discusses how machine learning can integrate time-resolved solvation data for predictive solvent and process optimization in thin-film science. Graphical Abstract TOC: Beyond static solvent parameters toward dynamic, field-based descriptions of solvation and reactivity in thin-film processes.
Markus Becker (Thu,) studied this question.