Characterization of CO2 separation from post-combustion flue gas mixtures using nanocomposite membrane: Molecular dynamics analysis
| dc.contributor.advisor | Muthu, SD Jacob | |
| dc.contributor.author | Quader, Niaz | |
| dc.contributor.committeemember | Shirif, Ezeddin | |
| dc.contributor.committeemember | Henni, Amr | |
| dc.date.accessioned | 2024-11-08T20:37:50Z | |
| dc.date.available | 2024-11-08T20:37:50Z | |
| dc.date.issued | 2024-03 | |
| dc.description | A Thesis Submitted to the Faculty of Graduate Studies and Research In Partial Fulfillment of the Requirements for the Degree of Master of Applied Science in Industrial Systems Engineering, University of Regina. xvii, 138 p. | |
| dc.description.abstract | Dependency on fossil fuels to fulfill the global energy requirement has led to an increase in the concentration of greenhouse gases in the atmosphere particularly carbon dioxide (CO2) from industrial pollution. This has resulted in environmental impact, climate changes, etc. Hence, carbon capture became the focus of industries and academics to reduce the effects of greenhouse gases. However, capturing those free-flowing CO2, especially from the post-combustion flue gas has been a challenge. On the contrary, membrane-based carbon capture and storage (CCS) became a great option due to its retrofitting capability, sustainability, and reusability. Still, considerable research is required to properly investigate and identify the combination of the composite material which comprises both the characteristics of high diffusion rate, high permeability, and high selectivity. In this research, three different nanocomposite membranes composed of a Polyether-block-amide (PEBAX) matrix reinforced with carbon nanotube (CNT), armchair graphene, and zigzag graphene were modelled using a molecular dynamics (MD) simulation tool. Three different flue gas mixtures were modelled using the combination of CO2/N2, CO2/O2, and CO2/N2/O2 with an equal ratio (1:1) composition of the flue gas mixture and an actual post-combustion (APC) flue gas mixture ratio. Two different flue gas mixture were considered to understand the influence of the flue gas for variable concentration and density when permeating through the nanocomposite membrane. The nanocomposite membranes were characterized to determine the diffusion coefficient, selectivity, and permeability of the flue gas mixtures. The Molecular Dynamic Simulation results were obtained using LAMMPS MD modelling code and the visualization software, OVITO. The results confirmed that the CNT-based nano-reinforcement performed substantially better compared to graphene reinforcement for high CO2 selectivity and flue gas permeability for both the (1:1) and APC ratio due to high CO2 separation and capturing take place within the CNT, creating a steady flow for the flue gases with lower molecular weight. Whereas zigzag graphene-based nanocomposite with higher free volume was better suitable for the diffusion of CO2/N2 and CO2/N2/O2 flue gas composition for all ratios and CO2/O2 at equal (1:1) ratios. For CO2/O2 at the actual ratio, CNT-reinforced nanocomposite was found to be the better-performing nanocomposite membrane for flue gas diffusion. Keywords: Nano Composite Membrane, Molecular Dynamics, LAMMPS, Polyether-block-amide (PEBAX), Carbon Nanotube, Graphene, Gas Selectivity, Gas Diffusion | |
| dc.description.authorstatus | Student | en |
| dc.description.peerreview | yes | en |
| dc.identifier.uri | https://hdl.handle.net/10294/16519 | |
| dc.language.iso | en | en |
| dc.publisher | Faculty of Graduate Studies and Research, University of Regina | en |
| dc.title | Characterization of CO2 separation from post-combustion flue gas mixtures using nanocomposite membrane: Molecular dynamics analysis | |
| dc.type | Thesis | en |
| thesis.degree.department | Faculty of Engineering and Applied Science | |
| thesis.degree.discipline | Engineering - Industrial Systems | |
| thesis.degree.grantor | University of Regina | en |
| thesis.degree.level | Master's | en |
| thesis.degree.name | Master of Applied Science (MASc) |