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To address the global warming problem, many engineers have committed to developing cost and energy saving CO2 separation processes to realize large-scale capture in near future. To achieve this goal, many researchers around the work are proposing novel adsorbents. Selecting the most promising adsorbent among many candidates is a substantial challenge.

There are two major approaches for the selection of adsorbents. The first is the screening approach based on analysis of adsorption isotherms. This approach is computationally less expensive and enables many types of adsorbents to be analyzed at once.[1] However, since the kinetics is ignored, the analysis remains heuristic, and may miss the adsorbent that has the best performance in a separation process. The other approach is model-based analysis, in which the dynamics of the CO2 separation process are represented by a physics-based model.[2] Specifically, adsorption isotherms, adsorption rates, mass balance, heat balance, etc., are all modeled rigorously as a set of partial differential-algebraic equations. This method may identify the most promising adsorbent but is computationally expensive. The computational cost is highly dependent on the shape of the adsorption isotherm; isotherms with a mild change with respect to partial pressure (Figure 1 (a)) make solving partial differential-algebraic equations relatively easy, while an adsorption isotherm with a sharp change at a specific pressure (Figure 1 (b)) or with a discrete change (Figure 1 (c)) poses a computational challenge, which may hinder the model-based process analysis.

In this study, we propose and perform a model-based analysis on adsorbents for various adsorption isotherms,[3] including the one with sharp change, shown in Figure 1(b). Adsorption isotherms with sharp changes are known to exist for some some MOFs, which show excellent process performance.[4] We propose solutions to the computational difficulties, and confirmed that our approach which can deal with many different types of isotherms that provide superior CO2 capture performance over conventional adsorbents. Furthermore, an approach to deal with isotherm hysteresis (Figure 1(c)) is proposed and demonstrated.

Reference
[1] M. Khurana and S. Farooq, Ind. Eng. Chem. Res., 2016, 55, 2447–2460.
[2] R. M. Siqueira et al., Energy Procedia, 2017, 114, 2182–2192.
[3] M. Thommes et al., Pure Appl. Chem., 2015, 87, 1051–1069.
[4] S. Hiraide et al., Nat. Commun., 2020, 11, 3867.

Research Interests
Adsorption, Carbon capture, Process modeling and experimental varidation, Process optimization, Statistical modeling