Voltage

Engineering

Biology

Materials science

Chromatography

Support vector machine

Modulation (music)

Waveform

Computer science

Acoustics

Physics

Artificial intelligence

Analytical Chemistry (journal)

Chemistry

Sine wave

Topology (electrical circuits)

Biological system

Electrical engineering

IEEE Sensors Journal

Pure SnO 2 is widely used to detect VOC gases due to its high stability. Unfortunately, there is a problem of poor selectivity, especially for gases such as ketones and alcohols, which have a similar high sensitivity. In this paper, dynamic temperature modulation technology was used to solve this problem. Rectangular wave and sine wave, typical voltage jump waveform and voltage smooth waveform, were used as heating voltage waveform. It was introduced in detail that the optimization of dynamic temperature modulation parameters based on response time and power consumption. According to the different heating waveform parameters, we obtained the dynamic response data of six groups of sensors to five concentration gradients of acetone, butanone, n-propyl alcohol and isopropyl alcohol. It was used to evaluate the performance of heating waveform parameters by support vector machine (SVM) and principal component analysis (PCA) combined with K-nearest neighbor (KNN) algorithm. Both data analysis methods showed that the recognition effect was better when the SnO 2 sensor was heated by sine wave. In order to reduce power consumption, the heating waveform was determined as 0-6 V sine wave. Then the mechanism was analyzed in dynamic temperature modulation of the sensor. The voltage smooth waveform reached the stepless response of multiple temperature points by traversing the temperature range. More characteristics can be produced by experiencing more types proportion of adsorbed oxygen species within the cycle. It provided a new research idea for semiconductor gas sensor dynamic temperature modulation technology.

Dynamic Temperature Modulation Measurement of VOC Gases Based on SnO2 Gas Sensor