We report a computational study to screen 4764 computation-ready experimental metal-organic frameworks (CoRE-MOF) for the membrane separation of a ternary gas mixture (CO₂/N₂/CH₄) at 298 K and 10 bar. Combining Monte Carlo and molecular dynamics simulations, the adsorption, diffusion and permeation of the gas mixture are predicted. The structure-performance relationships are established between the geometrical descriptors of MOFs (pore liming diameter, density, void fraction and volumetric surface area) and the evaluation criteria of membrane performance (permeability and permselectivity). Furthermore, principal component analysis is used to assess the interrelationships among the descriptors, then multiple linear regression is applied to quantitatively determine the respective effects of descriptors on performance. In addition, decision tree modelling is adopted to define a clear effective path for screening. Finally, seven best MOF membranes are identified for single-step separation of both CO₂ and N₂ from CH₄. The microscopic insights and structure-performance relationships from this computational study can facilitate the development of new MOF membranes for the upgrading of natural gas.

我们报告了一项计算研究，以筛选4764计算就绪的实验性金属-有机框架（CoRE-MOF），用于三元混合气（CO ₂ / N ₂ / CH ₄）的膜分离）在298 K和10 bar下。结合蒙特卡罗和分子动力学模拟，可以预测混合气体的吸附，扩散和渗透。在MOF的几何特征（孔石灰直径，密度，空隙率和体积表面积）与膜性能的评估标准（渗透率和渗透选择性）之间建立了结构与性能之间的关系。此外，主成分分析用于评估描述符之间的相互关系，然后应用多元线性回归定量确定描述符对性能的影响。另外，采用决策树建模来定义明确的有效筛选路径。最后，确定了七种最佳的MOF膜，用于两步分离CO ₂和来自CH _4的N ₂。这项计算研究的微观见解和结构-性能关系可以促进开发用于天然气升级的新型MOF膜。