Prediction of Mechanical Properties of Aerogels using a Multifractal Multidimensional Multiscaling Approach

Aerogels, produced by sol-gel technologies, have several applications in sensors, high energy particle physics, catalysis, heat insulation, supercapacitors, heat storage devices, high efficiency windows, among others. These applications take advantage of the outstanding properties these materials present as a result of their structure. However, the low mechanical properties that these materials present as result of the process, limits their commercial applications. In this dissertation, it is investigated the relationship between the processing conditions and mechanical properties of these materials computationally.;The prediction of the effective properties for these materials is a daunting task because of their complex structure. Aerogels\u27s structure is not homogeneous nor periodic, but rather amorphous, nanostructured, and highly porous, making the traditional techniques used to study other materials inapplicable. This dissertation presents the prediction of mechanical properties of aerogels calculated by a novel Multifractal Multidimensional Multiscaling Approach (MMMA) developed here.;MMMA consists on recursively calculating the effective properties of the material along several scales. Since aerogels and structures produced by sol-gel technologies present a multifractal character, it is shown that MMMA is applicable to predict the effective properties of these materials.;The implementation of MMMA requires a fractal characterization of the structure. For this, computational scattering experiments were performed on structures resembling aerogels. The structures resembling aerogels were produced computationally incorporating the chemistry and the physical phenomena involved in the formation process.;MMMA was used to predict the mechanical properties of silica aerogels for different processing conditions. Thus, mechanical properties, scattering experiments, and processing conditions were investigated and correlated in this work