Chen-Yan Zheng, Hai-Long Qian, Cheng Yang, Xiu-Ping Yan
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引用次数: 0
Abstract
Nanochannel membranes are promising materials for enantioselective sensing. However, it is difficult to make a compromise between the selectivity and permeability in traditional nanochannel membranes. Therefore, new types of nanochannel membranes with high enantioselectivity and excellent permeability should be explored for chiral analysis. Here, asymmetric catalysis strategy is reported for interfacial polymerization synthesis of chiral covalent-organic framework (cCOF) nanochannel membrane for enantioselective sensing. Chiral phenylethylamine (S/R-PEA) and 2,4,6-triformylphloroglucinol (TP) are used to prepare chiral TP monomer. 4,4',4″-triaminotriphenylamine (TAPA) is then condensed with chiral TP to obtain cCOF nanochannel membrane via a C═N Schiff-base reaction. The molar ratio of TP to S/R-PEA is adjusted so that S/R-PEA is bound to the aldehyde only or both the aldehyde and hydroxyl groups on TP to obtain chiral-induced COF (cCOF-1) or both chiral-induced and modified COF (cCOF-2) nanochannel membrane, respectively. The prepared cCOF-2 nanochannel membrane showed two times more selectivity for limonene enantiomers than cCOF-1 nanochannel membrane. Furthermore, cCOF-2 nanochannel platform exhibited excellent sensing performance for other chiral molecules such as limonene, propanediol, methylbutyric acid, ibuprofen, and naproxen (limits of detection of 19-42 ng L-1, enantiomer excess of 63.6-86.3%). This work provides a promising way to develop cCOF-based nanochannel enantioselective sensor.
Small MethodsMaterials Science-General Materials Science
CiteScore
17.40
自引率
1.60%
发文量
347
期刊介绍:
Small Methods is a multidisciplinary journal that publishes groundbreaking research on methods relevant to nano- and microscale research. It welcomes contributions from the fields of materials science, biomedical science, chemistry, and physics, showcasing the latest advancements in experimental techniques.
With a notable 2022 Impact Factor of 12.4 (Journal Citation Reports, Clarivate Analytics, 2023), Small Methods is recognized for its significant impact on the scientific community.
The online ISSN for Small Methods is 2366-9608.