Semester

Spring

Date of Graduation

2025

Document Type

Dissertation

Degree Type

PhD

College

Statler College of Engineering and Mineral Resources

Department

Chemical and Biomedical Engineering

Committee Chair

Debangsu Bhattacharyya

Committee Co-Chair

Fernando Lima

Committee Member

Fernando Lima

Committee Member

Jianli Hu

Committee Member

Yuhe Tian

Committee Member

Grigorios Panagakos

Abstract

One of the key sources of carbon dioxide emissions to the environment is fossil fuel combustion for power generation. Post-combustion CO2 capture using amine-based solvents is currently the most matured process. However, amines are corrosive and lead to degradation products at even moderate temperatures generating environmental pollutants, and require high energy for regeneration. Solid sorbents are a promising alternative. They possess lower regeneration energy, thermal stability, and have highly tunable porous structures with large surface area that can help in achieving high loading and high adsorption rates. This work focuses on mathematical modeling of CO2 adsorption/desorption processes using solid sorbents. First, a multi-scale model of an isothermal axial flow adsorber model is developed with submodels for particle-scale and bulk-scales. The sorbent used is the amine-appended metal-organic framework (MOF) that exhibits a steep step-shaped adsorption isotherm and high loading capacity at post-combustion capture conditions, as well as relatively low temperature of around 100°C that is adequate for desorption. The multi-scale model is validated against lab-scale data. A multi-scale model of a radial flow bed is also developed. Due to the spatial variation of surface area and solid sorbent volume in the radial direction, the inlet position of adsorption and desorption gases affects the performance of the radial-flow adsorbers. Therefore, all possible configurations of the inlet and outlet streams during the adsorption and desorption stages are evaluated. Next, an embedded heat exchanger is proposed to improve the bed capture capacity. The process with heat removal is then scaled up to a commercial capacity, and an economic evaluation of the configurations is done based on process conditions of flue gas from a power plant. A Bayesian uncertainty quantification procedure is developed for quantifying uncertainty in the isotherm model. The uncertainties in the isotherm model are propagated through the adsorption model to quantify the uncertainty in the key performance measures such as breakthrough time, desorption time, and energy consumption.

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