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  5. Drastic Gas Sensing Selectivity in 2-Dimensional MoS<sub>2</sub> Nanoflakes by Noble Metal Decoration

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Article
en
2023

Drastic Gas Sensing Selectivity in 2-Dimensional MoS<sub>2</sub> Nanoflakes by Noble Metal Decoration

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en
2023
Vol 17 (5)
Vol. 17
DOI: 10.1021/acsnano.2c09733

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Ho Won Jang
Ho Won Jang

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Taehoon Kim
Tae Hyung Lee
Seo Yun Park
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Abstract

Noble metal nanoparticle decoration is a representative strategy to enhance selectivity for fabricating chemical sensor arrays based on the 2-dimensional (2D) semiconductor material, represented by molybdenum disulfide (MoS2). However, the mechanism of selectivity tuning by noble metal decoration on 2D materials has not been fully elucidated. Here, we successfully decorated noble metal nanoparticles on MoS2 flakes by the solution process without using reducing agents. The MoS2 flakes showed drastic selectivity changes after surface decoration and distinguished ammonia, hydrogen, and ethanol gases clearly, which were not observed in general 3D metal oxide nanostructures. The role of noble metal nanoparticle decoration on the selectivity change is investigated by first-principles density functional theory (DFT) calculations. While the H2 sensitivity shows a similar tendency with the calculated binding energy, that of NH3 is strongly related to the binding site deactivation due to preferred noble metal particle decoration at the MoS2 edge. This finding is a specific phenomenon which originates from the distinguished structure of the 2D material, with highly active edge sites. We believe that our study will provide the fundamental comprehension for the strategy to devise the highly efficient sensor array based on 2D materials.

How to cite this publication

Taehoon Kim, Tae Hyung Lee, Seo Yun Park, Tae Hoon Eom, Incheol Cho, Yeonhoo Kim, Changyeon Kim, Sol A Lee, Min‐Ju Choi, Jun Min Suh, Insung Hwang, Donghwa Lee, Inkyu Park, Ho Won Jang (2023). Drastic Gas Sensing Selectivity in 2-Dimensional MoS<sub>2</sub> Nanoflakes by Noble Metal Decoration. , 17(5), DOI: https://doi.org/10.1021/acsnano.2c09733.

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Publication Details

Type

Article

Year

2023

Authors

14

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1021/acsnano.2c09733

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