(381ab) Techno-Economic Optimization of CO2 Capture By Vacuum/Pressure Swing Adsorption Using Hierarchically Porous Structured Composites with Ultrahigh MOF Loading

Metal-organic frameworks (MOFs) have emerged as promising candidates for CO₂ adsorption due to their remarkable features, such as an ultra-high specific surface area and highly tunable pore-surface properties [1]. However, their application in large-scale settings under continuous flue gas flow is hindered by processing issues such as dustiness, clustering, and pressure drops in fixed bed columns associated with their micro-crystalline powder nature [2]. Therefore, shaping micron-sized polycrystalline MOF powders into structured forms of millimeter dimensions while preserving porosity and functionality represents an effective yet challenging approach to address these drawbacks [3]. Assessing the potential of structured adsorbents for practical CO₂ capture applications, using performance indicators such as CO₂ uptake capacity, CO₂/N₂ selectivity, and heat of adsorption, is useful. However, the ultimate evaluation must consider monetized and non-monetized key performance indicators of a capture plant, such as cost and energy consumption [4]. Integral to our study was the employment of a dual-methodology framework that intertwines sorbent characterization with techno-economic analysis, thereby ensuring a comprehensive evaluation of novel adsorbent materials.

In this work, a facile and scalable method was employed to structure various micro-crystalline MOFs into millimeter-sized hierarchically porous polymer-based beads with ultra-high MOF loading (~90%) for direct industrial carbon capture applications. These structured adsorbents retained the physicochemical characteristics and CO₂ capture performance of the individual MOF crystals. A dynamic simulation of a cyclic Vacuum/Pressure Swing Adsorption (V/PSA) process, targeted at CO₂ capture and compression from the flue gas emitted by a coal-fired power plant, was executed considering the resulting structured adsorbents. This simulation was grounded in a detailed mathematical model, developed and run within gPROMS software, and its accuracy was validated against experimental data. The design, operating conditions, and scheduling of the V/PSA process were optimized to maximize CO₂ purity, recovery, and productivity while minimizing energy consumption and the cost of CO₂ capture and compression. The resulting cost-optimal operating conditions, module configuration, and train schedule of the V/PSA-based CO₂ capture using the structured MOFs will be presented and discussed. Furthermore, sensitivity analysis was performed to evaluate the impact of uncertainties in estimating certain parameters on the CO₂ capture and compression process performance.

Acknowledgment

Financial support by Khalifa University through the CIRA2020-093 project and Computational resources from the RICH Center (RC2-2019-007) are greatly acknowledged.

References

[1] Varghese, Anish Mathai, K. Suresh Kumar Reddy, Nidhika Bhoria, Swati Singh, Jeewan Pokhrel, and Georgios N. Karanikolos. "Enhancing effect of UV activation of graphene oxide on carbon capture performance of metal-organic framework/graphene oxide hybrid adsorbents." Chemical Engineering Journal 420 (2021): 129677.

[2] Gebremariam, Solomon K., Ludovic F. Dumée, Philip L. Llewellyn, Yasser Fowad AlWahedi, and Georgios N. Karanikolos. "Metal-organic framework hybrid adsorbents for carbon capture–A review." Journal of Environmental Chemical Engineering 11, no. 2 (2023): 109291.

[3] Gebremariam, Solomon K., Anish Mathai Varghese, K. Suresh Kumar Reddy, Yasser Fowad AlWahedi, Ludovic F. Dumée, and Georgios N. Karanikolos. "Polymer-aided microstructuring of moisture-stable GO-hybridized MOFs for carbon dioxide capture." Chemical Engineering Journal 473 (2023): 145286.

[4] Balogun, Hammed A., Daniel Bahamon, Saeed AlMenhali, Lourdes F. Vega, and Ahmed Alhajaj. "Are we missing something when evaluating adsorbents for CO 2 capture at the system level?." Energy & Environmental Science 14, no. 12 (2021): 6360-6380.