(645h) Modelling Hierarchical Carbon-Based Materials for CO2 Capture and Separation
AIChE Annual Meeting
2022
2022 Annual Meeting
Separations Division
Molecular Simulations for Designing Adsorbents and Adsorption Processes
Thursday, November 17, 2022 - 2:15pm to 2:30pm
The work presented in this contribution combines molecular and process modelling for developing efficient, low-cost adsorbent materials for carbon dioxide capture, aiming at using the fundamental understanding of the phenomena happening at the molecular level to optimize their performance under process conditions. Moreover, such molecular simulation methods can be used as a screening method at a very moderate computational expense to fine-tune the process needs, thus making an important contribution to the optimization of the swing adsorption process performance. We present and discuss results concerning two different carbon-based materials: zeolite-templated carbons (ZTCs) and activated carbon samples developed from seeds of date fruits (Phoenix dactylifera, AC-DS) from the United Arab Emirates [4]. Furthermore, the effect of the inclusion of hierarchical features, i.e., a collection of micro and mesopores, is analyzed in detail. We showcase the capabilities and limitations of a developed molecular simulation-based screening tool for the efficient removal of CO2 from industrial gas streams âCO2/N2 and CO2/CH4, with and without including water traces as impurities- by adsorption at relevant gas separation process conditions. The modelling approach for the carbon-based solid sorbents, previously validated and systematically applied for other processes [4], consists of a collection of three-dimensional platelets, packed in random positions and orientations in a periodic simulation cell, with defects and oxygenated groups. Results presented include the adsorption of the pure components, the properties of both binary CO2/N2 and CO2/CH4 mixtures, and the effect of T,P,X conditions on the performance of pressure and temperature swing adsorption processes.
This work is funded by Khalifa University of Science and Technology under projects RC2-2019-007 and CIRA2018-103.
References
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