Lead-optimized design of metal–organic frameworks for trace SF6 capture

Abstract

The recovery of sulfur hexafluoride (SF₆) at trace concentrations (ppm_v) from leaks, exhaust emissions, accidental release, or decommissioned equipment is critically important due to its potential to displace oxygen in confined spaces, posing significant safety risks. However, the inert nature of SF₆ presents a persistent challenge for its capture at low concentrations. Metal–organic frameworks (MOFs) have shown promise as adsorbents; yet, rational selection of optimal candidates is not trivial, given the complexities involved in controlling the confined chemical environments that dictate SF₆ affinity. Here, a powerful lead-optimized selection process is used to identify a promising amine functionalized MOF for dilute SF₆ capture. First, through an optimized grand canonical Monte Carlo approach, the impact of varied pore functional groups on SF₆ adsorption was probed. The most promising candidate, Ni(ina-NH₂)₂, was then synthesized via a novel synthetic method and its enhanced SF₆ affinity was validated experimentally. Notably, with an experimental uptake of 2 mmol g⁻¹ at 1 kPa, it was found to be amongst the best performing materials for dilute SF₆ capture across all materials reported in the ARCMOF database, which curates over 280 000 of both known and theoretical MOFs. Finally, the mechanism of SF₆ adsorption was probed using density functional theory, revealing that inclusion of an amino group on the linker dramatically lowers the average pore binding site energy, thus promoting SF₆ capture. This work illustrates that lead-optimized materials selection can serve as a transformative strategy for the rapid and rational identification of materials tailored for specific applications.