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Isomer Discrimination via Defect Engineering in Monolayer MoS2.
Han, Bin; Gali, Sai Manoj; Dai, Shuting; Beljonne, David; Samorì, Paolo.
Afiliación
  • Han B; Université de Strasbourg, CNRS, ISIS UMR 7006, 8 Allée Gaspard Monge, F-67000 Strasbourg, France.
  • Gali SM; Université de Mons, Laboratory for Chemistry of Novel Materials, Place du Parc 20, Mons 7000, Belgium.
  • Dai S; Université de Strasbourg, CNRS, ISIS UMR 7006, 8 Allée Gaspard Monge, F-67000 Strasbourg, France.
  • Beljonne D; State Key Laboratory of Supramolecular Structure and Materials, College of Chemistry, Jilin University, Changchun 130012, China.
  • Samorì P; Université de Mons, Laboratory for Chemistry of Novel Materials, Place du Parc 20, Mons 7000, Belgium.
ACS Nano ; 17(18): 17956-17965, 2023 Sep 26.
Article en En | MEDLINE | ID: mdl-37704191
The all-surface nature of two-dimensional (2D) materials renders them highly sensitive to environmental changes, enabling the on-demand tailoring of their physical properties. Transition metal dichalcogenides, such as 2H molybdenum disulfide (MoS2), can be used as a sensory material capable of discriminating molecules possessing a similar structure with a high sensitivity. Among them, the identification of isomers represents an unexplored and challenging case. Here, we demonstrate that chemical functionalization of defect-engineered monolayer MoS2 enables isomer discrimination via a field-effect transistor readout. A multiscale characterization comprising X-ray photoelectron spectroscopy, Raman spectroscopy, photoluminescence spectroscopy, and electrical measurement corroborated by theoretical calculations revealed that monolayer MoS2 exhibits exceptional sensitivity to the differences in the dipolar nature of molecules arising from their chemical structure such as the one in difluorobenzenethiol isomers, allowing their precise recognition. Our findings underscore the potential of 2D materials for molecular discrimination purposes, in particular for the identification of complex isomers.
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Texto completo: 1 Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: ACS Nano Año: 2023 Tipo del documento: Article País de afiliación: Francia

Texto completo: 1 Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: ACS Nano Año: 2023 Tipo del documento: Article País de afiliación: Francia