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Gas sensing and capturing based on two‐dimensional layered materials: Overview from theoretical perspective
Toxic gas detection and capture are two important topics, which are highly related with human health and environments. Recently, theoretical simulations based on first‐principles calculations have suggested two‐dimensional (2D) materials to be as ideal candidates for gas sensing and capturing due to...
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Published in: | Wiley interdisciplinary reviews. Computational molecular science 2018-07, Vol.8 (4), p.e1361-n/a |
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Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Toxic gas detection and capture are two important topics, which are highly related with human health and environments. Recently, theoretical simulations based on first‐principles calculations have suggested two‐dimensional (2D) materials to be as ideal candidates for gas sensing and capturing due to the large surface–volume ratio and reactive surface. Starting from graphene, which was firstly proposed for 2D gas sensing, the family currently has been extended to transition metal dichalcogenides, phosphorene, silicene, germanene, MXene, and so on. In this review, we give a comprehensive overview of recent progress in computational investigations of 2D gas sensing/capture materials. We then offer perspectives on possible directions for further fundamental exploration of gas sensor and caption based on 2D materials, which are expected to offer tremendous new opportunities for future research and development.
This article is categorized under:
Structure and Mechanism > Computational Materials Science
Two‐dimensional materials are suitable for gas sensing and capturing due to large surface–volume ratio and active surface, with the mechanism of charge transfer. The designed sensors with high sensitivity and selectivity will be used for gas emission control, military and public safety, and environmental monitoring. |
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ISSN: | 1759-0876 1759-0884 |
DOI: | 10.1002/wcms.1361 |