From Sol–Gel Chemistry to Nanofiber Membranes: A Model-Based Approach
Abstract
Sol-gel chemistry offers powerful tools for engineering silica-based materials with tunable properties, including organosilica nanofiber membranes that are essential for applications such as chemical sensing, solvent separation, and electrochemical barriers. Despite their potential, the molecular factors that govern electrospinnability remain insufficiently understood. In particular, the complex relationship between hydrolysis kinetics, crosslinking dynamics, and rheological behavior often forces researchers to rely on empirical trial-and-error methods. To address this challenge, we developed a predictive framework for methyltriethoxysilane (MTES)-based sol-gel systems, establishing correlations between viscosity evolution and key structural parameters, such as hydrolysis degree and the distribution of crosslinking functional groups. A comparative analysis with tetraethoxysilane (TEOS), a more crosslinkable four-arm precursor, was also conducted. Using ²⁹Si NMR spectroscopy and coupled matrix-based Monte Carlo (CMMC) modeling, we extracted Arrhenius parameters for MTES hydrolysis and condensation, which were then applied under non-isothermal conditions simulating electrospinning environments, including solvent evaporation. This allowed us to extract molecular rules defining processing conditions that distinguish between no deposition, electrospraying and electrospinning. To validate the model, we randomly selected three synthesis conditions based on its predictions and tested them experimentally. Scanning electron microscopy (SEM) imaging confirmed that the resulting morphologies matched the predicted electrospinnability outcomes, demonstrating the reliability of the molecular rules derived from the model. By identifying molecular thresholds for successful electrospinning, such as siloxane yields and group fractions, this predictive framework provides a rational alternative to experimental trial-and-error, supporting the design of advanced organosilica membranes for sustainable technologies.