Rational construction and triethylamine sensing performance of foam shaped α-MoO3@SnS2 nanosheets

Real-Time Monitoring of Air Discharge in a Switchgear by an Intelligent NO2 Sensor Module

An air-insulated power equipment adopts air as the insulating medium and is widely implemented in power systems. When discharge faults occur, the air produces decomposition products represented by NO2. The efficient NO2 sensor enables the identification of electrical equipment faults. However, single-sensor-dependent NO2 detection is vulnerable to interfering gases. Implementing the sensor array could reduce the interference and improve detection efficiency. In the field of NO2 detection, In2O3 sensors have exhibited tremendous advantages. In our work, four composites based on In2O3 are integrated into sensor arrays, which could detect 250 ppb of NO2 and exhibit excellent selectivity when simultaneously exposed to CO. To further reduce the impact of humidity on gas-sensing performance, a convolutional neural network and a long short-term memory model equipped with an attention mechanism are proposed to evaluate NO2 concentration within 1 ppm, and the detection error is 63.69 ppb. In addition, the NO2 concentration estimation platform based on a microgas sensor is established to detect air discharge faults. The average concentration of NO2 generated by 10 consecutive discharge faults at 15 kV is 726.58 ppb, which indicates severe discharge in the switchgear. Our NO2 estimation method has great potential for large-scale deployment in low- and medium-voltage switchgears.

One-Step Hydrothermal Synthesis of 3D Interconnected rGO/In2O3 Heterojunction Structures for Enhanced Acetone Detection

Acetone detection is of great significance for environmental monitoring or diagnosis of diabetes. Nevertheless, fast and sensitive detection of acetone at low temperatures remains challenging. Herein, a series of rGO-functionalized three-dimensional (3D) In2O3 flower-like structures were designed and synthesized via a facile hydrothermal method, and their acetone-sensing properties were systematically investigated. Compared to the pure 3D In2O3 flower-like structures, the rGO-functionalized 3D In2O3 flower-like structures demonstrated greatly improved acetone-sensing performance at relatively low temperatures. In particular, the 5-rGO/In2O3 sensor with an optimized decoration exhibited the highest response value (5.6) to 10 ppm acetone at 150 °C, which was about 2.3 times higher than that of the In2O3 sensor (2.4 at 200 °C). Furthermore, the 5-rGO/In2O3 sensor also showed good reproducibility, a sub-ppm-level detection limit (1.3 to 0.5 ppm), fast response and recovery rates (3 s and 18 s, respectively), and good long-term stability. The extraordinary acetone-sensing performance of rGO/In2O3 composites can be attributed to the synergistic effect of the formation of p-n heterojunctions between rGO and In2O3, the large specific surface area, the unique flower-like structures, and the high conductivity of rGO. This work provides a novel sensing material design strategy for effective detection of acetone.

Dynamic Measurement of VOCs with Multiple Characteristic Peaks Based on Temperature Modulation of ZnO Gas Sensor

Volatile organic compounds (VOC) harm human health seriously in the air. Therefore, it is essential to recognize VOC gases qualitatively and quantitatively. The dynamic measurement method can improve the selectivity of metal oxide semiconductor (MOS) gas sensors to VOC, but there is a problem of the insufficient number of characteristic peaks. From the experimental point of view, the primary judgment basis for the correct qualitative and quantitative recognition of VOC gases by the dynamic measurement method is the characteristic peak of the dynamic response signal. However, the traditional dynamic measurement method generally only has two characteristic peaks. In this experiment, the voltage was changed at the time of the second characteristic peak by controlling the constant dynamic response period. Taking ethyl alcohol as an example, the experimental results show that the characteristic peak of the dynamic response signal does not increase when the voltage is constant. However, a new characteristic peak will appear based on a continuously rising heating voltage. The characteristic peaks of the dynamic response of n-propyl alcohol, isopropyl alcohol, and n-butyl alcohol were also increased based on the rising heating voltage waveform. Based on the K-Nearest-Neighbors algorithm, the qualitative and quantitative recognition rate of the four alcohol homologue gases reached 100%.