Study of a Platinum Nanoparticles/Indium Gallium Oxide Based Ammonia Gas Sensor and a Gas Sensing Model for Internet of Things (IoT) Application

An ammonia (NH3) gas sensor has been developed using a combination of indium gallium oxide (IGO) thin film and platinum (Pt) nanoparticles (NPs). The IGO film was created through radio frequency (RF) magnetron sputtering, while the Pt NPs were applied via vacuum thermal evaporation (VTE). The addition of Pt NPs significantly enhances the responsiveness of the sensor to NH3. A comprehensive analysis of the sensor of the structure, elemental composition, and material properties was conducted. Tests show that when the Pt NP/IGO sensor is exposed to 1000-ppm NH3/air at 300 °C, its sensing response (<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${S} _{R}$ </tex-math></inline-formula>) reaches 209.4, and even at 1-ppm NH3, its sensing response is 1.29. Furthermore, the sensor exhibits excellent selectivity and maintains stable performance over a 90-day period. The study proposes a composite first-order differential gas sensing model to reduce redundant data and improve data transmission efficiency in transient sensing applications for the Internet of Things (IoT). The algorithm developed in this study uses environmental thresholds for data preprocessing and is compared with the GM(1, 1) sensing simulation. Experimentally, the algorithm effectively enhances transmission efficiency without increasing computational complexity. Compared to the original transmission data, the proposed method demonstrates a significant reduction in data percentage by 87.8%. As mentioned above, the studied ammonia sensor has potential applications in the IoT and biomedical fields.