UV-enhanced NO2 sensor using ZnO quantum dots sensitized SnO2 porous nanowires

ZnO quantum dots sensitized SnO2 porous nanowires were fabricated and designed for UV excitation gas sensor. The ZnO/SnO2 composite (SZQ1%) with the molar proportion of 1:100 exhibits excellent sensing properties to NO2 gas under UV irradiation at 40oC. The humidity stability of SZQ1% was also measured and discussed by DC reversed circuit and complex impedance curves. The gas sensing mechanism is well discussed and illustrated to the ZnO quantum dots sensitized and the increased photo-generated carriers under UV irradiation.

Low-Operating-Temperature NO2 Sensor Based on a CeO2/ZnO Heterojunction

CeO2/ZnO-heterojunction-nanorod-array-based chemiresistive sensors were studied for their low-operating-temperature and gas-detecting characteristics. Arrays of CeO2/ZnO heterojunction nanorods were synthesized using anodic electrodeposition coating followed by hydrothermal treatment. The sensor based on this CeO2/ZnO heterojunction demonstrated a much higher sensitivity to NO2 at a low operating temperature (120 °C) than the pure-ZnO-based sensor. Moreover, even at room temperature (RT, 25 °C) the CeO2/ZnO-heterojunction-based sensor responds linearly and rapidly to NO2. This sensor’s reaction to interfering gases was substantially less than that of NO2, suggesting exceptional selectivity. Experimental results revealed that the enhanced gas-sensing performance at the low operating temperature of the CeO2/ZnO heterojunction due to the built-in field formed after the construction of heterojunctions provides additional carriers for ZnO. Thanks to more carriers in the ZnO conduction band, more oxygen and target gases can be adsorbed. This explains the enhanced gas sensitivity of the CeO2/ZnO heterojunction at low operating temperatures.

Seasonal Influence on the Performance of Low-Cost NO2 Sensor Calibrations

Low-cost sensor technology has been available for several years and has the potential to complement official monitoring networks. The current generation of nitrogen dioxide (NO2) sensors suffers from various technical problems. This study explores the added value of calibration models based on (multiple) linear regression including cross terms on the performance of an electrochemical NO2 sensor, the B43F manufactured by Alphasense. Sensor data were collected in duplicate at four reference sites in the Netherlands over a period of one year. It is shown that a calibration, using O3 and temperature in addition to a reference NO2 measurement, improves the prediction in terms of R2 from less than 0.5 to 0.69–0.84. The uncertainty of the calibrated sensors meets the Data Quality Objective for indicative methods specified by the EU directive in some cases and it was verified that the sensor signal itself remains an important predictor in the multilinear regressions. In practice, these sensors are likely to be calibrated over a period (much) shorter than one year. This study shows the dependence of the quality of the calibrated signal on the choice of these short (monthly) calibration and validation periods. This information will be valuable for determining short-period calibration strategies.