Synthesis of Mesoporous CuOx Using Inverse Micelle Sol–gel Process for NO2 Gas Sensing

• Published in: Korean Journal of Metals and Materials Vol. 62; no. 8; pp. 631 - 638
• Main Authors: Heo, Sung Gue, Kim, Sangwoo, Seo, Seok-Jun, Sim, Jae Jin, Shin, Jiyeon, Mirzaei, Ali, Choi, Myung Sik
• Format: Journal Article
• Language: English
• Published: 대한금속·재료학회 01.08.2024
• Subjects: 재료공학
• ISSN: 1738-8228; 2288-8241
• DOI: 10.3365/KJMM.2024.62.8.631

Nitrogen dioxide (NO2) is a highly dangerous gas, mostly emitting emitted from fossil fuels, and a major contributor to air pollution. It has negatively effects affects on the human health as well asand contributes to environmental issues like acid rain. In this study, mesoporous CuOx nanoparticles (NPs) were successfully synthesized using a low-temperature inverse micelle sol–gel method. Subsequently, the synthesized NPs were annealed at temperatures of 250, 350, and 450 °C. Advanced characterization of the synthesized samples revealed that upon with increasing the annealing temperature, the sizes of the NPs increased, whileereas their surface areas decreased. The sample annealed at 250°C showed a remarkably higher surface area (161.85 m2/g) compared with the samples annealed at 350 °C (39.88 m2/g) and 450 °C (22.52 m2/g) thanks to finer particle sizes and a mesoporous nature. Resistive gas sensors incorporating these samples were successfully fabricated and tested for sensitivity towards both NO2 (oxidizing gas) and H2S (reducing gas) at 200 °C. The sensor with the mesoporous CuOx NPs annealed at the lowest temperature (250 °C) exhibited an enhanced response to NO2 gas but no response to H2S. The strong response to NO2 gas is considered to be due to the high surface area of the sensing layer which provides plenty of adsorption sites for gas molecules and the oxidizing nature of NO2 gas with high affinity to electrons. These findings highlight the effectiveness of the inverse micelle sol–gel method forin synthesizing mesoporous CuOx NPs for gas sensing, as well as the need for to optimizing optimize the annealing temperature to maximize the sensor response.