The large design space of the sorbents' structure and the associated capability of tailoring properties to match process requirements make adsorption-based technologies suitable candidates for improved CO2 capture processes. This is particularly of interest in novel, diluted, and ultradiluted separations as direct CO2 removal from the atmosphere. Here, we present an equilibrium model of vacuum temperature swing adsorption cycles that is suitable for large throughput sorbent screening, e.g., for direct air capture applications. The accuracy and prediction capabilities of the equilibrium model are improved by incorporating feed-forward neural networks, which are trained with data from rate-based models. This allows one, for example, to include the process productivity, a key performance indicator typically obtained in rate-based models. We show that the equilibrium model reproduces well the results of a sophisticated rate-based model in terms of both temperature and composition profiles for a fixed cycle as well as in terms of process optimization and sorbent comparison. Moreover, we apply the proposed equilibrium model to screen and identify promising sorbents from the large NIST/ARPA-E database; we do this for three different (ultra)diluted separation processes: direct air capture, y CO2 = 0.1%, and y CO2 = 1.0%. In all cases, the tool allows for a quick identification of the most promising sorbents and the computation of the associated performance indicators. Also, in this case, outcomes are very well in line with the 1D model results. The equilibrium model is available in the GitHub repository https://github.com/UU-ER/SorbentsScreening0D.
A new ammonia-based process for CO2 capture from flue gas has been developed, which utilizes the formation of solid ammonium bicarbonate to increase the CO2 concentration in the regeneration section of the process. Precipitation, separation, and dissolution of the solid phase are realized in a dedicated process section, while the packed absorption and desorption columns remain free of solids. Additionally, the CO2 wash section applies solid formation to enable a reduction of the wash water consumption. A rigorous performance assessment employing the SPECCA index (Specific Primary Energy Consumption for CO2 Avoided) has been implemented to allow for a comparison of the overall energy penalty between the new process and a standard ammonia-based capture process without solid formation. A thorough understanding of the relevant solid-solid-liquid-vapor phase equilibria and an accurate modeling of them have enabled the synthesis of the process, and have inspired the development of the optimization algorithm used to screen a wide range of operating conditions in equilibrium-based process simulations. Under the assumptions on which the analysis is based, the new process with controlled solid formation achieved a SPECCA of 2.43 MJ kgCO2-1, corresponding to a reduction of 17% compared to the process without solid formation (with a SPECCA of 2.93 MJ kgCO2-1). Ways forward to confirm this significant improvement, and to increase the accuracy of the optimization are also discussed.
