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

被引:0
|
作者
Tan, Shih Wei [1 ]
Chang, Chia Wei [2 ]
Jiang, Zheng Han [3 ]
Lin, Kun Wei [3 ]
机构
[1] Natl Taiwan Ocean Univ, Dept Elect Engn, Keelung 202301, Taiwan
[2] Natl Cheng Kung Univ, Inst Microelect, Dept Elect Engn, Tainan, Taiwan
[3] Chaoyang Univ Technol, Dept Comp Sci & Informat Engn, Taichung 41349, Taiwan
关键词
Sensors; Gas detectors; Surface roughness; Rough surfaces; Mathematical models; Ammonia; Surface treatment; Indium; Gallium oxide; Transmission electron microscopy; Indium gallium oxide (IGO); Pt nanoparticle (NP); reduce redundant data; sensing response; FILM; NH3; PERFORMANCE; NANOFIBERS; IN2O3;
D O I
10.1109/TED.2024.3513938
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
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 degrees C, its sensing response (SR) 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.
引用
收藏
页码:813 / 821
页数:9
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