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Cited by 352

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Retracted: Highly Sensitive MoS2 Humidity Sensors Array for Noncontact Sensation

Zhao, Jing, Li, Na, Yu, Hua, Wei, Zheng, Liao, Mengzhou, Chen, Peng, Wang, Shuopei, Shi, Dongxia, Sun, Qijun, Zhang, Guangyu·2017·Advanced Materials

Abstract

Recently, 2D materials exhibit great potential for humidity sensing applications due to the fact that almost all atoms are at the surface. Therefore, the quality of the material surface becomes the key point for sensitive perception. This study reports an integrated, highly sensitive humidity sensors array based on large‐area, uniform single‐layer molybdenum disulfide with an ultraclean surface. Device mobilities and on/off ratios decrease linearly with the relative humidity varying from 0% to 35%, leading to a high sensitivity of more than 10 4. The reversible water physisorption process leads to short response and decay times. In addition, the device array on a flexible substrate shows stable performance, suggesting great potential in future noncontact interface localization applications.

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Crossref · 10.1002/adma.201702076This paper is marked retracted.

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Metadata

Authors
Zhao, J., Li, N., Yu, H., Wei, Z., Liao, M., Chen, P., Wang, S., Shi, D., Sun, Q., & Zhang, G.
Venue
Advanced Materials
Publisher
Wiley
Published
2017-07-10
Volume
29
Issue
34
ISSN
  • 0935-9648 (ISSN-L)
  • 1521-4095
OpenAlex
W2735149555
Cited by
352
References
3
FWCI
16.22
Type
journal article
Language
en
Status
Retracted
Open access
closed

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CoChat. (2026). Citation check: Retracted: Highly Sensitive MoS2 Humidity Sensors Array for Noncontact Sensation. https://app.cochat.ai/papers/10.1002/adma.201702076
The paper
Zhao, J., Li, N., Yu, H., Wei, Z., Liao, M., Chen, P., Wang, S., Shi, D., Sun, Q., & Zhang, G. (2017). Retracted: Highly Sensitive MoS2 Humidity Sensors Array for Noncontact Sensation. Advanced Materials. https://doi.org/10.1002/adma.201702076

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.