Encoding Enantiomeric Molecular Chiralities on Graphene Basal Planes

Graphene has demonstrated broad applications due to its prominent properties. Its molecular structure makes graphene achiral. Here, we propose a direct way to prepare chiral graphene by transferring chiral structural conformation from chiral conjugated amino acids onto graphene basal plane through π...

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Veröffentlicht in:Angewandte Chemie 2022-04, Vol.134 (15), p.n/a
Hauptverfasser: Meng, Yongqiang, Fan, Jingbiao, Wang, Meihui, Gong, Wenbin, Zhang, Jinping, Ma, Junpeng, Mi, Hongyu, Huang, Yan, Yang, Shu, Ruoff, Rodney S., Geng, Jianxin
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Sprache:eng
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Zusammenfassung:Graphene has demonstrated broad applications due to its prominent properties. Its molecular structure makes graphene achiral. Here, we propose a direct way to prepare chiral graphene by transferring chiral structural conformation from chiral conjugated amino acids onto graphene basal plane through π–π interaction followed by thermal fusion. Using atomic resolution transmission electron microscopy, we estimated an areal coverage of the molecular imprints (chiral regions) up to 64 % on the basal plane of graphene (grown by chemical vapor deposition). The high concentration of molecular imprints in their single layer points to a close packing of the deposited amino acid molecules prior to “thermal fusion”. Such “molecular chirality‐encoded graphene” was tested as an electrode in electrochemical enantioselective recognition. The chirality‐encoded graphene might find use for other chirality‐related studies and the encoding procedure might be extended to other two‐dimensional materials. Chiral graphene is directly prepared by transferring the chiral structural conformation from chiral conjugated amino acids onto the graphene basal plane through π–π interaction followed by thermal fusion. The chiral graphene is characterized using atomic resolution transmission electron microscopy as well as spectroscopic techniques and demonstrated to be useful as electrode in electrochemical enantioselective recognition.
ISSN:0044-8249
1521-3757
DOI:10.1002/ange.202117815