4.7 Article

Synthesis and enhanced NO2 gas sensing properties of ZnO nanorods/TiO2 nanoparticles heterojunction composites

Journal

JOURNAL OF COLLOID AND INTERFACE SCIENCE
Volume 478, Issue -, Pages 22-28

Publisher

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.jcis.2016.05.061

Keywords

ZnO nanorods; TiO2 nanoparticles; NO2 gas sensing; Heterojunction

Funding

  1. outstanding young teacher training program in Guangdong province [Yq2013113]
  2. Natural Science Foundation of Guangdong Province [2014A030307008, 2016A030313670]
  3. Project for training high-level talents of Yangfan Plan in Guangdong Provence
  4. Innovation project of universities in Guangdong Province [2015KTSCX086]
  5. Natural Science Foundation of Lingnan Normal University [LZL1506, QL1512, ZL1503]

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ZnO nanorods/TiO2 nanoparticles composites were synthesized and the effects of TiO2 concentrations on the NO2 sensing properties were studied in detail. The as-prepared composites were characterized by XRD, SEM, TEM, PL, I-V and gas sensing measurements. The gas sensing results demonstrated that all the sensors based on ZnO/TiO2 nanocomposites exhibited much higher response than that of sensors based on pure ZnO nanorods. At the optimum operating temperature of 180 degrees C, the response values of the sensors based on ZnO/TiO2 nanocomposites decorated with TiO2 concentrations of 0, 3, 5, 8 and 10 wt% were 50, 140, 310, 350 and 258, respectively. The PL and I-V results indicated that the increased charge transfer between the ZnO nanorods mediated by TiO2 nanoparticles enhanced the conductivity of the ZnO/TiO2 nanocomposites. The gas sensing mechanism was also carefully analyzed. The attachment of TiO2 nanoparticles onto ZnO nanorods induced more active sites for the adsorption of oxygen molecules (O-2) and O-2 which can be more easily adsorbed on the surface of ZnO nanorods. Furthermore, the conduction channel of ZnO/TiO2 was much narrower as a result of the formation of heterojunction which may further contribute to the enhanced NO2 sensing properties. (C) 2016 Elsevier Inc. All rights reserved.

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