4.7 Article

Rational synthesis of molybdenum disulfide nanoparticles decorated reduced graphene oxide hybrids and their application for high-performance NO2 sensing

期刊

SENSORS AND ACTUATORS B-CHEMICAL
卷 260, 期 -, 页码 508-518

出版社

ELSEVIER SCIENCE SA
DOI: 10.1016/j.snb.2017.12.181

关键词

Reduced graphene oxide; Molybdenum disulfide nanoparticles; Nitrogen dioxide sensor; High-performance

资金

  1. National Natural Science Foundation of China [61671218, 61674066, 61673191]
  2. Jilin Provincial Science & Technology Department [20160520090JH]
  3. High Tech Project of Jilin Province [20150204029GX]

向作者/读者索取更多资源

In this work, we have reported a novel NO2 sensor using molybdenum disulfide nanoparticles (MoS2 NPs) decorated RGO (MoS2-RGO) hybrids as sensing materials, where MoS2-RGO hybrids were prepared by a two-step wet-chemical method. Firstly, MoS2 NPs prepared by modified liquid exfoliation method from bulky MoS2 powder. Then, MoS2-RGO hybrids were obtained by self-assembly of MoS2 NPs and GO nanosheets, followed by a facile hydrothermal treatment progress. The combined characterizations indicate that MoS2 NPs with the size of 3-5 nm are uniformly dispersed on RGO nanosheets. Most importantly, the sensor based on MoS2-RGO hybrids could detect NO2 at room temperature. To further improve sensing performances, especially response and recovery rate, sensing properties are further examined by increasing the operation temperature to 160 degrees C. It is notably seen that MoS2-RGO-based NO2 sensor not only shows improved sensitivity to NO2 compared to pure RGO-based sensor, but also exhibits fast response and recovery characteristics (response time and recovery time are 8 s and 20 s toward 3 ppm NO2). This work paves a new way for application of MoS2 and RGO in chemical sensors, providing an effective method for fabrication of NO2 sensors with high sensitivity and fast response/recovery rate. (C) 2017 Elsevier B.V. All rights reserved.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据