A Perspective on Methods to Computationally Design the Morphology of Aerogels

Abstract

Reconstructing aerogel morphology presents significant challenges, in particular, if 3D visualizations of their mesoporous network are desired. Available microscopic and tomographic tools find it difficult to probe into all types of aerogels for the purposes of reconstructing their 3D nanoporous morphology. This is where computational approaches have shown promising efforts. Herein, diverse models that can be applied to describing different aerogels are explored. To begin with, cluster–cluster aggregation models are examined for simulating the sol–gel process and the resulting morphologies in fractal aerogels, e.g., silica‐based. Gaussian random field models and polymerization‐induced phase separation models are explored for modeling organic non‐fractal aerogels, e.g., resorcinol‐formaldehyde (RF) ones. This is followed by Langevin‐dynamics‐based discrete element models that are explored for simulating gelation in fibrillar aerogels, e.g., those from biopolymer sources. Lastly, modified Voronoi approaches are investigated for describing the 3D fibrillar morphology, also of fibrillar aerogels, like those from biopolymers. A perspective is presented highlighting the strengths as well as shortcomings in each of the model approaches. Possibilities to either extend available approaches or explore new ones are briefly discussed at every interval.