Carbon Dioxide Capture using Binding Organic Liquids: Experimental and Modeling

Abstract

The search for efficient technologies to capture CO2 is critical in addressing climate change while ensuring energy security, a challenge of global significance. Among various approaches, developing novel solvents presents a promising solution to overcome the limitations of traditional aqueous amines for post-combustion CO2 capture by absorption. Carbon Dioxide Binding Organic Liquids (CO2BOLs) and Deep Eutectic Solvents (DES) have emerged as effective and environmentally friendly candidates for CO2 capture. However, optimizing these solvents requires a thorough understanding of how their molecular structures and interactions influence their thermodynamic and transport properties, which is essential for selecting the most suitable solvent for industrial applications. Additionally, the limited availability of experimental data hampers the comprehensive characterization needed to assess these solvents under the required industrial conditions.
The objective of this PhD thesis is to advance the current state of knowledge in two key areas: the development of a robust solvent screening framework for novel solvents and the experimental evaluation of promising solvents complemented with the soft-SAFT (Statistical Associating Fluid Theory) molecular-based equation of state, and by other modeling techniques such as Density Functional Theory (DFT) and quantum-based Conductor-like Screening Model for Real Solvents (COSMO-RS). This framework is applied to various emerging solvents, enabling their ranking based on key performance indicators and providing insights into their behavior at the molecular level. The solvents examined in this study include amine-based DES, CO2BOLs, and chlorophenol-functionalized DES. A wide array of potential hydroxyl compounds and superbases were evaluated, primarily focusing on determining their pKa values, which directly correlate with the solvent’s affinity for CO2 by using COSMO-RS. Other key solvent properties, such as viscosity, toxicity, corrosivity, and flammability were also included in the initial screening. Based on this screening, five alcohols and two superbases were identified as promising candidates for CO2BOLs. The selected CO2BOLs were prepared in the lab and experimentally evaluated for key thermodynamic properties relevant to CO2 capture, including density, viscosity, vapor pressure, and CO2 absorption capacity. The experimental data and micro-level insights obtained from COSMO-RS were used to construct molecular models of the shortlisted CO2BOLs using the soft-SAFT equation of state. Once validated, soft-SAFT was used to calculate a range of property data under various conditions, allowing for a more comprehensive evaluation of thermodynamic properties used to assess the best solvents based on CO2 loading, regeneration energy, and diffusivity. The results reported in this thesis underscore the value of an integrated experimental and modeling approach, combined with advanced modeling tools, in the search for novel solvents for CO2 capture. This approach provides relevant information at process conditions, grounded in a deep understanding of the solvents' fundamental properties, thereby contributing to the practical development of effective CO2 capture technologies.

Date of Award	11 Dec 2024
Original language	American English
Supervisor	Enas Nashef (Supervisor)