(381x) Self-Diffusion of Volatile Organic Compounds in Zr-MOFs: A Joint Computational and Experimental Study

The association of specific volatile organic compounds (VOCs) in exhaled human breath (EHB), often called a chemical “fingerprint”, to a particular disease is a growing field of study. The ability of trained scent dogs to identify COVID-positive respiratory secretion samples lends itself to the possibility of developing a non-invasive, breath-based diagnostic tool to provide insight into a person’s state of health. However, detecting the target constituents --- often existing at dilute concentrations in a complex mixture of water, CO2, and other VOC interferents --- poses a significant challenge.

Metal-organic frameworks (MOFs) have demonstrated tremendous aptitude for applications in gas sensing and separation technologies. MOFs are porous, crystalline solids composed of metal nodes coordinated by organic linkers which form an extended network. Zirconium (Zr) MOFs exhibit exceptional thermal and hydrolytic stability which makes them attractive candidates for studying VOC detection in EHB. If MOFs are to be used in a beath-based diagnostic tool, understanding the interactions between the VOCs and the MOF is vital.

In this work, we use molecular dynamics simulations and experimental NMR to study the self-diffusion properties of several polar and non-polar VOCs in a topologically diverse set of Zr-MOFs. We compute self-diffusion coefficients at multiple loadings over a range of temperatures and compare against experimental values. We will discuss trends between self-diffusion and heat of adsorption, molecular properties (e.g. chain length, polar or non-polar, and isomers), and framework topology. Finally, we consider the challenges of comparing simulation to NMR experiments.

SNL is managed and operated by NTESS under DOE NNSA contract DE-NA0003525.