DOI
https://doi.org/10.25772/7R83-Y945
Author ORCID Identifier
https://orcid.org/0000-0003-2464-6431
Defense Date
2022
Document Type
Dissertation
Degree Name
Doctor of Philosophy
Department
Chemical and Life Science Engineering
First Advisor
Dr. James K. Ferri
Second Advisor
Dr. B. Frank Gupton
Third Advisor
Dr. Christina Tang
Fourth Advisor
Dr. Massimo F. Bertino
Fifth Advisor
Dr. Jamesa L. Stokes
Abstract
Aerogels are mesoporous materials with unique properties, including high specific surface area, high porosity, low thermal conductivity, and low density, increasing these materials’ effectiveness in applications such as catalyst supports, sorption media, and electrodes in solid oxide fuel cells. Zirconia (ZrO2) aerogels have special interest for high-temperature applications due to the high melting point of ZrO2 (2715°C) and stability between 600°C and 1000°C, where other aerogel systems often begin to sinter and densify. These properties and unique pore structure make zirconia aerogels advantageous as thermal management systems, especially in aeronautics and aerospace applications. However, to be effective in high-temperature applications, the aerogel formulation must be optimized so that pore collapse and subsequent surface area decrease are mitigated following high-temperature exposure. By utilizing surfactant templates, it is anticipated that the mesoporous structure and high surface area of yttria-stabilized zirconia (YSZ) aerogels will be retained following exposure to high temperatures, increasing the thermal stability and efficiency of YSZ aerogels as thermal management systems. To experimentally consider the impact of synthetic variables on aerogels, surfactants are used as templating agents to influence the pore structure and surface area of YSZ aerogels. Additionally, due to the large number of parameters associated with aerogel synthesis and processing, a developed aerogel graph database and a machine learning predictive model are applied to examine the complex relationships between aerogel synthesis, processing, and final properties, specifically BET surface area. Sub-graphs of the developed aerogel graph database are used to visually determine the impact of specific variables on the aerogel surface area, while the predictive model maps from aerogel synthetic and processing conditions to predict the final property, BET surface area, with precision. These digital design tools could reduce experimental dimensionality, time, and resources, enabling the successful synthesis of high surface area aerogels.
Rights
© Rebecca C. Walker
Is Part Of
VCU University Archives
Is Part Of
VCU Theses and Dissertations
Date of Submission
12-15-2022