(48d) Optimizing CO2 Capture through Solid Adsorption: Developing Optimal Strategies | AIChE

(48d) Optimizing CO2 Capture through Solid Adsorption: Developing Optimal Strategies

Authors 

Hernández-Romero, I. M. - Presenter, Universidad Michoacana de San Nicolás de Hidalgo
Flores-Tlacuahuac, A., Tecnologico de Monterrey
Greenhouse gas levels have increased over the last 70 years, mainly CO2, from 300 to 420 ppm. The high concentration of CO2 in the atmosphere is a major cause of climate change. Thus, carbon capture and sequestration are promising solutions to mitigate greenhouse gas emissions. In this sense, Pressure Swing Adsorption technology (PSA) is promising for direct CO2 capture. However, its capture efficiency is highly dependent on the diffusion behavior of CO2 in porous media. Therefore, this paper presents a simulation and optimization approach to incorporate the time-dependent operation aspects of the PSA column packed with 13X zeolite as adsorbent material to maximize the capture of atmospheric CO2. A two-bed, four-step PSA system is considered. The four steps are pressurization, adsorption, depressurization, and regeneration. At the same time, the beds correspond to the adsorber and the regeneration columns.

On the other hand, multiscale modeling analysis has become an important tool to better understand the diffusion process. Therefore, this proposal aims to develop a rigorous mathematical model for CO2 diffusion in porous media, considering three coupled modeling scales: macro, meso, and micro. Furthermore, the CO2 diffusion behavior at each scale will be analyzed, and the results will be compared to investigate if considering such fine details presents significant changes in CO2 capture. It is expected that these considerations will improve the CO2 capture process. In addition, Neumann and Dirichlet boundary conditions define the problem and establish the link between the PSA operation cycles and the three modeling levels. Finally, the numerical formulation, the finite difference method, was used to discretize the spatial domain during an orthogonal fitting for the spatial domain.

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