2025 AIChE Annual Meeting

(700d) Enhanced Selectivity of Trace SF6 over N2 Via Functionalization of Ni-Based Metal-Organic Framework

Authors

Nickolas Gantzler - Presenter, Oregon State University
Eric Sikma, Sandia National Laboratories
Raphael Reyes, Sandia National Laboratories
Caith McKeown, Sandia National Laboratories
Jack Geary, Sandia National Laboratories
Jacob A. Harvey, Sandia National Laboratories
Jason Sammon, Sandia National Laboratories
N. Scott Bobbitt, Northwestern University
Dorina F. Sava Gallis, Sandia National Laboratories
Sulfur hexafluoride (SF6) is a heavy, inert gas which has garnered significant attention in the last few decades due to its increasing atmospheric concentration and industrial applications. SF6 is predominantly used in industrial processes such as microchip manufacturing or in high-voltage power equipment. To reduce demand, SF6 is commonly diluted with nitrogen gas (N2) to ratios of 1:9 or 1:99 SF6:N2. The recovery of SF6 at trace concentrations (ppmv) from leaks, exhaust, accidental release, or end-of-life equipment is a concern from both an economic and safety perspective. Due to its inertness, SF6 is difficult and costly to produce with the standard separation method relying on cryogenic distillation. From a safety perspective, SF6 can pose an asphyxiation hazard in settings where it can accumulate, and the depletion of SF6 from high-voltage power equipment increases the risk of part failure. An alternative to liquification-based separation is physisorption-based separation via porous materials. Metal-organic frameworks (MOFs) are a class of porous solids composed of inorganic nodes coordinated by organic linkers. MOFs have high internal surface areas and, given the variety of linker and node combinations, encompass a vast chemical space. Due to their highly tunable structure and surface properties, MOFs have shown great promise in applications such as dilute gas separations. In this work, we demonstrate enhanced SF6/N2 selectivity at dilute concentrations in MOFs via linker functionalization of Ni(ina)2. First, using Grand Canonical Monte Carlo simulations, evaluate several SF6 molecular models to determine which accurately recover experimental adsorption trends. We then performed high-throughput computational screening of the ARCMOF database and several MOFs from the literature. Of the top performing MOFs, we chose Ni(ina)2 to pursue for further investigation. We then simulated the impact of various functional groups on SF6 adsorption. The most promising material, Ni(ina-NH2)2, has been synthesized via a novel synthetic method and validated with experimental adsorption isotherms. Finally, we use density functional theory (DFT) to investigate the mechanism driving the enhanced selectivity.

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