Tuning Pore Size in Square-Lattice Coordination Networks for Size-Selective Sieving of CO2
Porous materials capable of selectively capturing CO2 from flue‐gases or natural gas are of interest in terms of rising atmospheric CO2 levels and methane purification. Size‐exclusive sieving of CO2 over CH4 and N2 has rarely been achieved. Herein we show that a crystal engineering approach to tunin...
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Published in | Angewandte Chemie International Edition Vol. 55; no. 35; pp. 10268 - 10272 |
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Main Authors | , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Germany
Blackwell Publishing Ltd
22.08.2016
Wiley Subscription Services, Inc |
Edition | International ed. in English |
Subjects | |
Online Access | Get full text |
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Summary: | Porous materials capable of selectively capturing CO2 from flue‐gases or natural gas are of interest in terms of rising atmospheric CO2 levels and methane purification. Size‐exclusive sieving of CO2 over CH4 and N2 has rarely been achieved. Herein we show that a crystal engineering approach to tuning of pore‐size in a coordination network, [Cu(quinoline‐5‐carboxyate)2]n (Qc‐5‐Cu) ena+bles ultra‐high selectivity for CO2 over N2 (SCN≈40 000) and CH4 (SCM≈3300). Qc‐5‐Cu‐sql‐β, a narrow pore polymorph of the square lattice (sql) coordination network Qc‐5‐Cu‐sql‐α, adsorbs CO2 while excluding both CH4 and N2. Experimental measurements and molecular modeling validate and explain the performance. Qc‐5‐Cu‐sql‐β is stable to moisture and its separation performance is unaffected by humidity.
Sieves you right: Crystal engineering of supramolecular isomers of [Cu(quinoline‐5‐carboxyate)2]n metal–organic materials enables the right pore‐chemistry for ultra‐high CO2/N2 and CO2/CH4 selectivity even in the presence of water vapor. |
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Bibliography: | NSFC - No. 21225105; No. 21290173 ArticleID:ANIE201603934 SFI - No. 13/RP/B2549 istex:3C743DF55C459200F4DB08210F24E7A38D11442C ark:/67375/WNG-MW8LS30B-H National Science Foundation - No. CHE-1152362 ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
ISSN: | 1433-7851 1521-3773 |
DOI: | 10.1002/anie.201603934 |