(700d) Multi-Scale Dynamic Modeling and Optimization of a Radial Flow Fixed Bed Contactor for Post-Combustion CO2 Capture Using a Metal–Organic Framework

Solid sorbent-based CO₂ capture has high potential for reducing operational costs of post-combustion CO₂ capture. Selection of contactor technology is important for efficient utilization of the solid sorbents. In comparison to the moving and fluidized beds, fixed beds are simple to operate, construct, and require fewer balance of the plant equipment items. In addition, there is little to no particle attrition in fixed beds and therefore fixed beds are highly preferred over moving or fluidized beds for solids such as most metal organic frameworks (MOFs) that exhibit poor attrition resistance. However, the traditional axial flow fixed bed contactor results in high pressure loss and large reactor volume ¹. For post-combustion CO₂ capture where large amount of flue gas needs to be treated, higher pressure loss would require higher blower energy thus increasing the parasitic loss. The radial flow fixed bed (RFFB) contactor is a promising alternative. In an RFFB, the gas flows radially either towards the center or toward the circumference of the bed. The RFBR contactor can lead to reduction in contactor size and the pressure drop, and therefore can improve the process economics. RFFB contactors have been investigated for many applications, including direct air capture^{2, 3}, oxygen generation⁴, and various pressure swing adsorption processes⁵, but a detailed evaluation of RFFB contactors for post-combustion CO₂ capture using first-principles distributed dynamic models is lacking. For rapid heat addition and removal, the model includes an embedded heat exchanger. Furthermore, to capture the local variability in transport variables and model the heat and mass transfer resistances accurately, a particle level model is developed and coupled with the bulk level model leading to a multi-scale model.

In this work, a model of a RFBR is developed for a novel functionalized MOF functionalized with 2,2-dimethyl-1,3-diaminopropane (dmpn) Mg₂(dobpdc) (dobpdc^4– = 4,4′-dioxidobiphenyl-3,3′-dicarboxylate) [dmpn-Mg₂(dobpdc)]⁶ exhibiting unique step-shaped isoterm⁶. A model of the solids particle is developed considering simultaneous mass and heat transfer and adsorption kinetics. Since the laboratory scale contactor from which the data are available for validation is an axial flow packed bed, a model of an axial flow packed bed including the particle level model is developed. Laboratory scale isotherm data, thermogravimetric data and breakthrough data are used for model validation. Then the model of a commercial-scale radial-flow contactor is developed incorporating the particle level model. While the step-shaped isotherm exhibited by these MOFs offers high potential for CO₂ capture, they are associated with high heat of reaction. Thus, for maximizing the economics of these MOFs, efficient removal and addition of heat is very important. Therefore, model of an embedded heat exchanger is developed. During the adsorption process, cooling water is used in the embedded heat exchanger for heat removal while hot water is used during the desorption step. The multi-scale model account for film and internal mass transfer resistances, heat transfer between the solid and the gas, and heat transfer between the gas and the embedded heat exchanger. A temperature swing adsorption cycle is simulated. Optimization of the design and operation of these beds is difficult due to their cyclic characteristics. Incorporating cyclic steady-state constraint, a dynamic optimization problem is solved.

Model results compare well with the laboratory data including the breakthrough data. It is observed that the optimal design of the embedded heat exchanger is critical by considering both cooling and heating needs. An oversized heat exchanger leads to large volume of the beds and this an increase in the capital cost. An undersized heat exchanger leads to faster cycle time and higher energy usage leading to higher operating costs. Optimization leads to much improved economics compared to the base case and leads to efficient utilization of the MOF and reduction in the consumption of utilities.

References:

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