Cloud-Based, High-Throughput, End-To-End Computational Screening of Solid Sorbent Materials for Carbon Capture

Abstract

We demonstrate cloud-based, high-throughput, end-to-end computational screening of solid sorbent materials for carbon capture. This approach combines a molecular screening workflow to simulate adsorption isotherms with quantitative dynamic process modelling to calculate process-based figures of merits. As a reference, we compare three distinctly different porous materials, i.e. Mg-MOF-74, HKUST-1, and ZIF-8 with regards to their capture performance of CO2 from dry flue gas. The calculated figures-of-merit produce the following performance rank order: Mg-MOF-74 > HKUST-1 > ZIF-8. This outcome is in-line with the expected capture performance of these materials based on their experimental CO2 affinity.