Aggregation model for the gelation of a sol starting from the processing conditions

A stochastic computational model for the gelation of a sol is explained and tested for the case of neutral silica aerogels. The computational model produces the final structure of the sol after gelation, using two of the several physical phenomena occurring during gelation of sols. Diffusion, represented by Brownian motion, is modeled by a random walk, and chemical reactions are incorporated through a stochastic aggregation model using a probability function; the latter determined in terms of the processing conditions based on the knowledge of the cluster formation energies. The two phenomena are coupled by a Monte Carlo simulation. The analysis of the connected structure and its functionality is demonstrated for neutral silica aerogels. It is shown how the gelation process can be controlled to obtain different structures for different application requirements. The only parameters required by the model are the density and the processing conditions. The results of the model show that those parameters strongly affect the structure of the generated samples. Therefore, processing conditions could be selected to produce aerogels with structures tailored to specific applications, which would constitute a major achievement in aerogel fabrication.

Research highlights
► Sol -gel fractal structures can be modeled with Monte Carlo simulations.
► Monte Carlo simulations allow incorporating Brownian motion and sol-gel chemistry.
► Reactivity parameter incorporates sol -gel chemistry (extra bonding energy in sol).
► Mass distribution and connectivity characterize sol-gel structures.
► Colloid aggregation structures vary with reactivity and concentration.