(610f) Quantitative Insights into the Influence of MOF Defects on Adsorption Properties

Computationally predicting the adsorption properties of Metal-organic Frameworks (MOF) in a high throughput way has become a useful means of identifying promising materials for chemical separations. In almost all cases, high throughput simulations assume that MOFs are defect-free for computational convenience. However, structure defects are unavoidable during synthesis processes or might be introduced during adsorption processes by acid gases or water. Thorough defect studies have been conducted for some well-known MOFs, for example, UiO-66 and ZIF-8. These studies illustrated that defects can have a strong influence on MOF adsorption properties, physical properties, and mechanical properties.

We developed a python package that can generate missing linker defect structures and dangling linker defect structures at user-specified concentrations in arbitrary MOFs. Capping agents are added based on the local chemical environment. At the DFT level of accuracy, a subset of CoRE MOF database was fully optimized to identify the maximum defect concentration without triggering unit cell change. Structures with lower defect concentrations were optimized using DFT only for metal clusters and capping agents. At the force field level of accuracy, all the defect structures are optimized using UFF4MOF, and based on FF relaxed structure mechanical properties are computed.

We systematically studied the adsorption properties of MOFs at different missing linker defect concentrations. Surface areas and accessible volumes increase as the defect concentration increases, although at high defect concentrations this trend can be reversed due to shrinkage of the material. We used ethene and ethane as examples to test the defect influence on adsorption properties. Loadings and selectivity in MOFs with different defect concentrations are computed using GCMC. Most MOFs have lower uptakes with the increase of defect concentrations at 1 bar, but different adsorbates change in different ways, which complicates the trends for adsorption selectivity.