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您的检索式：作者名="Musen Zhou"
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| 1 | Computational screening and design of nanoporous membranes for efficient carbon isotope separation显示文摘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^(12)CH_4/^(13)CH_4 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^(12)CH_4/^(13)CH_4 with the existing MOFs and those variations by replacement of the metal sites. | Jingqi Wang Musen Zhou Diannan Lu Weiyang Fei Jianzhong Wu | 2020 | Green Energy & Environment2020，5，3： | 1 |
| 2 | Inverse design of metal-organic frameworks for C_(2)H_(4)/C_(2)H_(6)separation显示文摘Efficient separation of C_(2)H_(4)/C_(2)H_(6)mixtures is of paramount importance in the petrochemical industry.Nanoporous materials,especially metal-organic frameworks(MOFs),may serve the purpose owing to their tailorable structures and pore geometries.In this work,we propose a computational framework for high-throughput screening and inverse design of high-performance MOFs for adsorption and membrane processes.High-throughput screening of the computational-ready,experimental(CoRE 2019)MOF database leads to materials with exceptionally high ethane-selective adsorption selectivity(LUDLAZ:7.68)and ethene-selective membrane selectivity(EBINUA02:2167.3).Moreover,the inverse design enables the exploration of broader chemical space and identification of MOF structures with even higher membrane selectivity and permeability.In addition,a relative membrane performance score(rMPS)has been formulated to evaluate the overall membrane performance relative to the Robeson boundary.The computational framework offers guidelines for the design of MOFs and is generically applicable to materials discovery for gas storage and separation. | Musen Zhou Jianzhong Wu | 2022 | npj Computational Materials2022，，1： | 0 |
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