Abstract

The CO2 concentration in the atmosphere has continued to increase over the past century and now poses an increasing potentially catastrophic effect to human life and the environment via global warming and the concomitant effect of climate change. Anthropogenic carbon dioxide emissions due to fossil fuel combustion for increasing energy demand is the main driver for the increased carbon dioxide in the atmosphere. A multifaceted approach including carbon dioxide capture and utilization is required to mitigate anthropogenic carbon dioxide emissions. Aerosol science and technology, an enabler for clean combustion technologies and nanomaterial synthesis, can contribute significantly to the advancement of carbon dioxide capture and utilization technologies. To deploy clean combustion technologies, such as pressurized oxy-combustion, for carbon dioxide capture, it is important to understand particle formation and growth mechanisms in relevant combustion conditions. Similarly, to seize the advantages of nanomaterial synthesis via aerosol route for carbon dioxide utilization, it is important to establish fundamental relationships between the aerosol synthesis method and the synthesized nanoparticle functionality and to develop accurate computationally efficient models to enable scalability. To advance carbon capture and utilization using aerosol technology, this dissertation therefore focuses on developing a pressurized drop tube furnace experiment system to understand particle formation and growth in pressurized oxy-combustion systems and the synthesis of nanocatalysts using the spray flame aerosol reactor. This dissertation is divided into four sections. The first section focuses on the development of the pressurized combustion experiment system to enable studies to elucidate the particle formation mechanism in pressurized combustion systems. The design of the pressurized drop tube furnace is presented. Likewise, the design of all accessories of the pressurized drop tube furnace experiment system (sampling unit, particle feed unit, exhaust gas treatment unit, gas supply unit) are presented. Finally, experiments to elucidate the impacts of pressure, combustion atmosphere and temperature on the particulate matter size distribution are proposed. The second section focuses on quantifying carbon dioxide conversion potential for reforming processes. Thermodynamic analysis based on equilibrium conditions is used to quantify the CO2 utilization potential for the reforming of oxy-combustion exhaust gas using methane and the reforming of CO2 with hydrocarbons at practical operating regimes for reforming. The reforming process at equilibrium was modeled using Aspen Plus. In this study, the boundaries of the practical operating window for reforming are identified and discussed. The zero-coke equilibrium line is introduced and its relevance to reforming as boundary for the feasible operating window is discussed. Finally, the carbon dioxide conversion potential for reforming is determined for oxy-combustion exhaust gas and then extended to reforming using any hydrocarbon. The third section focuses on the synthesis of catalysts using the spray flame aerosol reactor. Firstly, alumina, a widely used catalyst and catalyst support, was synthesized. The spray flame aerosol reactor was characterized to determine the effect of its control parameters (precursor flow rate, dispersion O2 flow rate and sheath O2 flow rate) on synthesized nanoparticle properties (size distribution, surface area, crystal phase composition). Consequently, more complex supported reforming catalysts Rh/Al2O3 and methanol synthesis catalysts CuO/ZnO/ZrO2 and CuO/ZnO/MgO were designed and synthesized using the spray flame aerosol reactor. The methanol synthesis catalysts were admixed with an acid function catalyst to produce a hybrid catalyst for direct DME synthesis from CO2 rich synthesis gas. The hybrid catalyst showed superior performance in terms of activity and selectivity when compared to similar catalyst whose methanol synthesis component was synthesized by co-precipitation. The fourth section focuses on the development of hybrid physics-based machine learning model for aerosol coagulation. The model which consists of a data driven ANN model used to determine the proxy coagulation coefficients and a reduced order coagulation model enabling an analytical solution was proposed and validated. Comparison of proposed hybrid ANN model results depicting the evolution of particle size distribution in the furnace aerosol reactor with high fidelity sectional model and the computationally efficient moment model indicates the proposed hybrid ANN model is both accurate and computationally efficient. In summary, this dissertation, advances aerosol technology as an enabler for carbon dioxide capture and utilization.

Degree

Doctor of Philosophy (PhD)

Author's Department

Energy, Environmental & Chemical Engineering

Author's School

McKelvey School of Engineering

Document Type

Dissertation

Date of Award

4-11-2025

Language

English (en)

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