Search

This work reports the impact of deviations in heater current caused by an imprecise 5V power source on the parameters utilized in gas sensing modules in MQ series towards 62 ppm of Ethanol vapor. The gas sensing experiments involved three MQ series gas sensors under lab-made chamber for continuous Ethanol vapor measurement. To investigate how heaters' current irregularities, affect the gas sensing performance parameters, the sensor's response/recovery time, pattern recognition techniques of principal component analysis (PCA) and hierarchical cluster analysis (HCA) were employed. While minor voltage drops (±100 mV) may not significantly affect sensing resistance (RS) due to real-time input voltage (Vin) adjustment, a constant current source is essential for heating resistance (RH). The study revealed that a slight increase (±3 mA) in heater supply, particularly from 154 mA (94 °C) to 157 mA (96 °C), can significantly accelerate the recovery time (Trec) of the MQ-7 sensor from 484 s to 316 s, resulting in a difference of over 150 s. This improvement can be attributed to the desorption of gas molecules at higher temperatures, aiding in sensor cleaning. However, this small change does not significantly affect the response time (Tres), which remains between 245 and 295 s at worst. Our gas sensor exhibits enhanced sensitivity and operational stability thanks to a calibrated circuit and stable 5V power supply. Strong correlations between normalized response and sensing films' temperatures, with a correlation coefficient of 0.985, provide insights into the relationship between heater currents, temperature effects, and gas sensitivity. These findings offer insights for optimizing sensing performance under gas exposure conditions.

Here we present a proof-of-concept study showing the potential of a chemical gas sensors system to identify the patients with alveolar echinococcosis disease through exhaled breath analysis. The sensors system employed comprised an array of three commercial gas sensors and a custom gas sensor based on WO3 nanowires doped with gold nanoparticles, optimized for the measurement of common breath volatile organic compounds. The measurement setup was designed for the concomitant measurement of both sensors DC resistance and AC fluctuations during breath samples exposure. Discriminant Function Analysis classification models were built with features extracted from sensors responses, and the discrimination of alveolar echinococcosis was estimated through bootstrap validation. The commercial sensor that detects gases such as alkane derivatives and ethanol, associated with lipid peroxidation and intestinal gut flora, provided the best classification (63.4% success rate, 66.3% sensitivity and 54.6% specificity) when sensors’ responses were individually analyzed, while the model built with the AC features extracted from the responses of the cross-reactive sensors array yielded 90.2% classification success rate, 93.6% sensitivity and 79.4% specificity. This result paves the way for the development of a noninvasive, easy to use, fast and inexpensive diagnostic test for alveolar echinococcosis diagnosis at an early stage, when curative treatment can be applied to the patients.

The development of advanced metal-oxide-semiconductor sensing technologies for the detection of Volatile Organic Compounds (VOCs) present in exhaled breath is of great importance for non-invasive, cheap and fast medical diagnostics. Our experimental studies investigate the effects of operating temperature selection and UV-light irradiation on improving the response of WO3 nanowire sensors towards exhaled breath exposure. Herein, six WO3 nanowire sensors (both pristine and doped with a range of metal nanoparticles such as Pt, Au, Au/Pt, Ni and Fe) were synthesised via Aerosol-Assisted Chemical Vapour Deposition (AACVD) and characterized by means of Atomic Force Microscopy (AFM), Scanning Electron Microscopy (SEM), Transmission Electron Microscopy (TEM) and Energy Dispersive X-ray (EDX-ray). Breath measurements were performed in the dark and under UV-light irradiation at various sensor operating temperatures. The results demonstrate that UV-light irradiation combined with the optimisation of the sensors' operating temperature can greatly enhance the sensors' responses towards breath exposure.