Quantum Monte Carlo and Density Functional Theory Analysis of Methane Partial Oxidation to Methanol in Mn-Based Metal-Organic Frameworks

Achieving efficient activation and selectivity in methane partial oxidation to methanol remains a significant challenge, making the exploration of catalysts crucial for understanding the reaction mechanism. Metal-organic frameworks (MOFs) offer substantial potential due to their tunable structures and large surface areas. The MOFs [Mn₂(BDC)₂(DMF)₂]_n, [Mn-(HTPA)(DMF)₂]_n●H₂O, and [Mn₃(ABTC)₂(H₂O)₄●9.5H₂O]_n were studied for their high-temperature resilience, stable active sites, and reactivity towards methane-to-methanol conversion, making them promising candidates. In this study, we combine density functional theory (DFT) with quantum Monte Carlo (QMC) to enhance the accuracy of electronic and energetic predictions for these MOF systems. By simplifying the MOF structure to its secondary building unit, focusing on the active sites and replacing the complex linkers with simpler acetates, we achieve a reduction in computational cost for QMC calculation. Our results provide a framework for comparing QMC and DFT results, increasing energetic accuracy and serving as a benchmark for selecting the most appropriate DFT theory level for the studied MOFs, guiding future research in optimizing MOF catalysts for methane conversion.