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高性能甲烷吸附剂的计算识别与实验验证

Computational Identification and Experimental Demonstration of High-Performance Methane Sorbents.

作者信息

Nath Karabi, Ahmed Alauddin, Siegel Donald J, Matzger Adam J

机构信息

Department of Chemistry and Macromolecular Science and Engineering Program, University of Michigan, 930 North University Avenue, Ann Arbor, MI 48109, USA.

Mechanical Engineering Department, University of Michigan, Ann Arbor, MI 48109, USA.

出版信息

Angew Chem Int Ed Engl. 2022 Jun 20;61(25):e202203575. doi: 10.1002/anie.202203575. Epub 2022 Apr 27.

Abstract

Remarkable methane uptake is demonstrated experimentally in three metal-organic frameworks (MOFs) identified by computational screening: UTSA-76, UMCM-152 and DUT-23-Cu. These MOFs outperform the benchmark sorbent, HKUST-1, both volumetrically and gravimetrically, under a pressure swing of 80 to 5 bar at 298 K. Although high uptake at elevated pressure is critical for achieving this performance, a low density of high-affinity sites (coordinatively unsaturated metal centers) also contributes to a more complete release of stored gas at low pressure. The identification of these MOFs facilitates the efficient storage of natural gas via adsorption and provides further evidence of the utility of computational screening in identifying overlooked sorbents.

摘要

通过计算筛选确定的三种金属有机框架(MOF)——UTSA - 76、UMCM - 152和DUT - 23 - Cu,实验证明了它们对甲烷具有显著的吸附能力。在298K、80至5巴的变压条件下,这些MOF在体积和重量吸附方面均优于基准吸附剂HKUST - 1。尽管在高压下的高吸附量对于实现这种性能至关重要,但高亲和力位点(配位不饱和金属中心)的低密度也有助于在低压下更完全地释放储存的气体。这些MOF的识别有助于通过吸附高效储存天然气,并进一步证明了计算筛选在识别被忽视的吸附剂方面的实用性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/031f/9322563/197dd0b2872a/ANIE-61-0-g003.jpg

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