(641f) Towards Systematic Assessment of Porous Adsorbents for Post-Combustion CO2 Capture Via Multiscale Simulation Strategies
AIChE Annual Meeting
Thursday, November 1, 2018 - 2:35pm to 3:00pm
So far, these screening methods have been predominantly based on certain adsorbent metrics, such as pore volume and surface area, and equilibrium and dynamic properties, such as adsorption isotherms, selectivity and diffusivity, obtained from molecular simulations. It is now becoming apparent that a more realistic picture of the performance of porous materials in a PSA or VSA process should be obtained from the actual process simulation.
In our study, we reflect on the development of the multiscale strategies that combine molecular simulations and pressure swing adsorption modelling and optimization to predict performance of the materials on the process scale. Several studies that employ these strategies have already emerged, ranking MOFs and other materials for post-combustion carbon capture. Here we focus on the challenges associated with the interface between molecular and process levels of description and demonstrate that the emerging picture is quite complex. In particular, we will discuss (a) the effect of the protocol for fitting experimental adsorption data with analytical adsorption models (e.g. dual-site Langmuir model), (b) influence of the pellet porosity and (c) influence of the pellet size on the process performance and material raking. Another aspect of the multiscale strategies we intend to explore is the accuracy of the molecular force fields, particularly in reproducing nitrogen isotherms, and how this affects predictions for the performance of the material in a process and the resulting ranking.
As a case study, we consider a well-known 4-step vacuum swing adsorption (VSA) cycle with light product pressurization (LPP), and Zeolite 13X as adsorbent in application to carbon dioxide removal from a typical flue gas stream (15% CO2, 85%N2, 1 atm).
In the last part of the presentation we attempt to evaluate performance of four widely studied materials (Zeolite 13X, Silicalite-1, MOF74-Ni and Cu-BTC) and compare process performance predictions based on molecular simulation predictions and experimental data. Our results demonstrate that simulation-based ranking of materials qualitatively agrees with that based on the experimental data, however the actual results can be sensitive to the variation of parameters mentioned above.