Fractionation of Isotopic Methanes with Metal–Organic Frameworks

Abstract

The need of isotopic compounds has been rising in recent years for both medical applications and scientific research. Existing technologies (e.g., cryogenic distillation, Girdler sulfide process, and supersonic beam diffraction) have difficulties to meet the growing global demand for enriching pure isotopic compounds because of low separation capacity, poor selectivity, and large energy consumptions. Metal−organic frameworks (MOFs) have been demonstrated promising for separation of isotopic compounds because of their tunable pore sizes and chemical affinities. In this work, we theoretically investigate 4764 experimentally synthesized MOFs for their potential applications in the separation of three representative isotopic methane pairs selected on the basis of their differences in molecular size, interaction energy, and a combination of both size and energy characteristics. Top MOF candidates have been identified with highest adsorption performance scores, highest adsorption selectivity, and highest membrane selectivity. The theoretical results suggest that MOF adsorption provides the selectivity of isotopic methanes, which is significantly larger than conventional separation methods. While isotopic separation by adsorption alone is compromised by a small working capacity, utilization of MOFs as a porous membrane facilitates efficient separation of isotopic methanes with both high working capacity (permeability) and large selectivity.

Electronic Structure Modeling of Metal–Organic Frameworks

“…Other alternatives exist (e.g., climbing image string, which is analogous to CI-NEB) but are highly uncommon in MOF literature because the cluster modeling alternative generally provides higher fidelity data from smaller model sizes. In fact, string methods have only recently been applied to MOFs and are limited to the diffusion of gas throughout the pores. − …”

Massively Parallel GPU-Accelerated String Method for Fast and Accurate Prediction of Molecular Diffusivity in Nanoporous Materials

“…52 Compared with the LCD distribution of MOFs in the background, which follows approximately a normal distribution with the mean between 4.5 and 5 Å, MOFs with top 0.5% diffusion selectivity has a slightly higher mean, between 5 and 5.5 Å, in the LCD distribution. According to our previous work, 28,29,55 a nanoporous material with the LCD larger than the molecular size would impose more attraction along the MEP, which is beneficial to achieve the diffusivity coefficient at the scale of practical interest.…”

“…While diffusivity is typically calculated from the Einstein equation via mean-square displacement over long equilibrium steps in MD simulation, TST predicts diffusion coefficients based on a minimum energy path (MEP) that is solely determined by the energy landscape of guest–host interactions (shown in Figure ). Mathematical tools such as nudged elastic band (NEB) and string methods have been commonly used to calculate the MEP. − While NEB is mostly used in quantum-mechanical calculations of transport properties such as ion diffusivity, the string method is more suitable to obtain the highly curved MEP dictating gas diffusion in nanoporous materials. − More specifically, the string method is able to identify the diffusion pathways based on the energy gradients such that each path follows an exactly minimum energy route. Besides NEB and string methods, other mathematical tools, such as tunnel and transition-state search, cluster analysis, and grid searching, are also promising. , Computationally, TST is able to predict diffusion coefficients much more efficient than molecular simulation because it entails no thermal fluctuations or atomic motions.…”

Virtual Screening of Nanoporous Materials for Noble Gas Separation

“…The modular nature in both MOFs and COFs enables the design and synthesis of large groups of candidates with tunable aperture sizes, large specific surface areas, and periodic characteristics. 14,15 The structural features and local chemical composition make MOFs and COFs excellent candidates for gas adsorption and separation.…”

“…MOFs are a class of crystalline materials consisting of metallic clusters and organic linkers, where metallic clusters are linked to organic linkers with coordination bonds. , In comparison to MOFs, COFs are also crystalline porous materials but composed of lighter elements (e.g., H, C, N, and O) where different organic linkers are connected by covalent bonds, which makes COFs more lightweight than MOFs. , Different from MOFs, two-dimensional layered structures exist in COFs where interlayer interaction is governed by van der Waals force. The modular nature in both MOFs and COFs enables the design and synthesis of large groups of candidates with tunable aperture sizes, large specific surface areas, and periodic characteristics. , The structural features and local chemical composition make MOFs and COFs excellent candidates for gas adsorption and separation.…”