4.7 Article

Facile control of room temperature nitrogen dioxide gas selectivity induced by copper oxide nanoplatelets

Journal

JOURNAL OF COLLOID AND INTERFACE SCIENCE
Volume 560, Issue -, Pages 755-768

Publisher

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.jcis.2019.10.036

Keywords

CuO; Humidity; Temperature-dependent; NO2 gas sensing

Funding

  1. Department of Science and Innovation (DSI)
  2. Council for Scientific and Industrial Research (CSIR)
  3. National Research Foundation

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Development of room-temperature operating gas sensors, utilizing p-type CuO nanoplatelets for air quality monitoring with excellent response, high sensitivity and good reliability, is highly desirable. Therefore, in this work, we investigated both the influence of synthesis reaction temperature and time on the sensitivity, selectivity, and response of CuO nanoplatelets prepared through the hydrothermal synthetic method, in the presence of NaOH as base, without the support of any surfactant. The gas sensing findings revealed that the CuO nanoplatelets NO2 sensitivity and selectivity can be controlled and tuned by adjusting the synthesis reaction temperature and time, while maintaining the morphology. The CuO-based sensors revealed a remarkable response of 14.5 to 20 ppm NO2, with a sensitivity of 0.47 ppm(-1) at room temperature. A decrease in sensing performance was observed at higher operating temperatures. The findings affirmed that such sensor response/sensitivity is not dependent on the specific surface area and is relatively interrelated to the adsorption sites, the average crystallite size, and low charge carrier concentration, giving rise to a more pronounced change in CuO sensor resistance. The influence of relative humidity (RH) was also investigated to have an understanding of the sensor performance in real testing conditions. Additionally, the stability analyses to four cycles of different humidity percentages and gas concentration-related repeatability conditions were carried out, and the sensor revealed a slight drifting when increasing the number of testing cycles. (C) 2019 Elsevier Inc. All rights reserved.

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