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Assessment of dual-adsorbent beds for CO2 capture by equilibrium-based process design

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DOI: 10.1016/j.seppur.2023.123990

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Adsorption; Process design; Material screening; Carbon capture

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We assessed dual-adsorbent beds for post-combustion CO2 capture using a model-based approach. We developed a process model and evaluated the performance of 2,850 combinations of adsorbents from a database of promising materials. We identified nine categories of process behavior and observed a reduction in energy penalty of the separation by approximately 20%.
We have carried out a model-based assessment of dual-adsorbent beds for post-combustion CO2 capture, whereby we consider systems in which two distinct adsorbent materials are homogeneously mixed to form a fixed bed adsorber. We have employed an equilibrium-based process model (D-BAAM) to simulate and optimize the process performance of a four-step vacuum swing adsorption cycle for CO2 capture with a dual-adsorbent bed. We have used the developed framework to screen the performance of 2,850 binary combinations of adsorbents from a database of 76 promising materials for post-combustion capture, which includes zeolites, activated carbons, metal organic frameworks (MOFs) and zeolitic imidazolate frameworks (ZIFs). Through unconstrained purity/recovery process optimization, we determine that only one pure material in a material pair needs to itself satisfy regulatory constraints on CO2 purity/recovery for post-combustion capture to yield a dual-adsorbent process which satisfies the constraints. For these dual-adsorbent combinations, we have assessed the optimal process performance in the constrained working capacity/energy usage Pareto plane and have identified nine distinct categories of process behavior. Five of these categories have the potential to allow for a reduction in the energy penalty of the separation, as compared to the constituent single-adsorbent processes. We have observed reductions in the energy penalty of the separation of approximately 20%. We contend that such processes may be economically optimal depending on a process specific balance of capital, operating and material costs, and should be investigated in more detail using dynamic process modeling and an associated techno-economic assessment.

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