Computational screening and design of nanoporous membranes for efficient carbon isotope separation

Stable isotopes have been routinely used in chemical sciences, medical treatment and agricultural research. Conventional technologies to produce high-purity isotopes entail lengthy separation processes that often suffer from low selectivity and poor energy efficiency. Recent advances in nanoporous materials open up new opportunities for more efficient isotope enrichment and separation as the pore size and local chemical environment of such materials can be engineered with atomic precision. In this work, we demonstrate the unique capability of nanoporous membranes for the separation of stable carbon isotopes by computational screening a materials database consisting of 12,478 computation-ready, experimental metal-organic frameworks (MOFs). Nanoporous materials with the highest selectivity and membrane performance scores have been identified for separation of 12CH4/13CH4 at the ambient condition (300 K). Analyzing the structural features and metal sites of the promising MOF candidates offers useful insights into membrane design to further improve the performance. An upper limit of the efficiency has been identified for the separation of 12CH4/13CH4 with the existing MOFs and those variations by replacement of the metal sites.