(346c) Strategies for CO2 Capture in Metal-Organic Frameworks in the Presence of Humidity

Alan Myers made contributions to a wide range of topics in the field of adsorption, ranging from theoretical (ideal adsorbed solution theory) to experimental (calorimetry) to molecular simulation (early GCMC studies in zeolites) to what we might now call data science (handbook of adsorption data). The field of adsorption continues to build on his legacy and is as vital as ever today due to the confluence of the recent discovery of new classes of materials, new computational methods that allow for predictive modeling, and emerging applications such as carbon capture and atmospheric water harvesting where adsorption is poised to play a key role. This talk will focus on our recent work on CO₂ capture, illustrating how molecular simulation, machine learning, open-source software, and experiment can be used together to accelerate the discovery of adsorbents for this application.

The main focus will be on the effect of water on carbon capture in metal-organic frameworks. We used a variety of tools from molecular modeling and data science to find top-performing MOFs for CO₂ capture in the presence of humidity and to better understand the structure/performance relationships. In one strategy, we used a multi-scale modeling approach to screen for materials that preferentially adsorb CO₂ over both H₂O and N₂. In another strategy, we created on the computer variations of existing materials such as CALF-20 with good performance to see if we could improve their behavior, especially at high relative humidity. In a third approach, we postulated functional groups that could be incorporated into stable zirconium MOFs to improve their CO₂/N₂ selectivity in the presence of water. Results from these three strategies will be compared, enabling overarching conclusions for future directions.