Carnegie Mellon University
A Multi-Scale Approach to Understanding CO<sub>2<sub>-Solvent Sy.pdf (11.77 MB)

A Multi-Scale Approach to Understanding CO2-Solvent Systems for the Development of CO2 Capture Technologies

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posted on 2013-05-01, 00:00 authored by Anita S. Lee

CO2 capture from a coal-fired power plant is a difficult problem that is costly due to the high energy demands of the process. Given the existing and well-understood processes for pre-combustion CO2 removal through physical absorption and post-combustion ue gas acid gas treating, developing new solvents with lower energy demands has potential to reduce CO2 capture costs of these processes. In this work, we use analytical and computational techniques to understanding of CO2-solvent systems at a molecular and process scale. This multi-scale understanding of solvent-CO2 systems will guide the design of new solvents for low cost CO2 capture.

At the molecular level, CO2-solvent interactions were studied to understand the role of the solvent and identify solvent molecular properties that could be used as descriptors and/or tuning parameters of the interactions. A Density Functional Theory study of CO2-amine solvents for post-combustion capture showed the reaction energy to form bicarbonate and carbamate products were stabilized for amines functionalized with electron donating groups and destabilized with electron withdrawing groups. Additionally, amine electronegativity was determined to be a good descriptor of the amine-bicarbonate reaction energy, which could be tuned with the choice of functional group and degree of amine functionalization. CO2 interactions with pre-combustion capture physical solvents, hydrophobic CO2-philic oligomers and 1-alkyl-3-methylimidazolium based ionic liquids, were characterized using Raman spectroscopy. Additionally, a technique to quantify solubility of CO2 in physical solvents using the Raman spectra was developed and showed CO2 solubility to correlate with molecular weight of the solvent.

Aspen Plus simulations coupled with a genetic algorithm were used to understand the potential impact of solvent selection on the post-combustion CO2 capture process by modeling a 90% CO2 capture process using MEA, DEA, and AMP. This analysis evaluated and equitably compared the process performance of post-combustion capture solvents and showed the trade-o s between lower energy demands and capital cost of the process and by comparison DEA could achieve 90% capture from a coal-fired power plant with lowest capital cost and highest net power output from the plant. A similar analysis could be performed with the pre-combustion capture process to assess and compare the performance those solvents.




Degree Type

  • Dissertation


  • Chemical Engineering

Degree Name

  • Doctor of Philosophy (PhD)


John Kitchin

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