Light-Assisted and Humidity-Tolerant ppb-Level NO <sub>2</sub> Detection at Low Temperature Using a Ternary In <sub>2</sub> O <sub>3</sub> @ZnO@PPy Hybrid
The pervasive issue of nitrogen dioxide (NO<sub>2</sub>) as a hazardous air pollutant requires the development of high-performance gas sensors with high sensitivity, long-term stability, and low-temperature operation. While metal oxide semiconductors (MOS), such as In<sub>2</sub>O<sub>3</sub> and ZnO, have been extensively investigated for this purpose, their practical application is often limited by the requirement for high operating temperatures and insufficient sensitivity to parts-per-billion (ppb) concentrations. Herein, we report a hierarchical ternary hybrid material, In<sub>2</sub>O<sub>3</sub>@ZnO@PPy, specifically designed for near-room temperature and light-assisted NO<sub>2</sub> detection. The collective synergistic effects arising from the hierarchical architecture, inter-semiconductor heterojunctions, and conductive polymer integration enable the In<sub>2</sub>O<sub>3</sub>@ZnO@PPy sensor to exhibit exceptional sensitivity to NO<sub>2</sub> at a low operating temperature of only 70 °C under blue-light excitation. The response value to 10 ppm NO<sub>2</sub> is as high as 221.4. The optimized sensor demonstrates an ultralow limit of detection of 50 ppb. More importantly, the hybrid exhibits remarkable humidity tolerance, maintaining high sensing performance even at 80% relative humidity. Surface wettability analysis suggests that PPy incorporation modulates the interfacial interaction with water molecules, which helps alleviate humidity-induced interference during NO<sub>2</sub> detection. The device further exhibits excellent repeatability, long-term stability, and strong selectivity against common interferents. These findings establish a light-assisted strategy for ppb-level gas sensing and provide a generalizable route for designing multifunctional hybrid materials for environmental monitoring and health diagnostics.
Authors
- Xiangyang Wei
- Rui You
- Ying Li
- Jingyuan Ma
Institutions
- Intelligent Systems Research (United States) (US)
- Opto Eletrônica (Brazil) (BR)
- Academy of Opto-Electronics (CN)
- Shanghai Optical Instrument Research Institute (CN)
- Beijing Information Science & Technology University (CN)
Publication Details
- Journal
- ACS Sensors
- Published
- 2026-02-27
- DOI
- https://doi.org/10.1021/acssensors.5c04256
- Primary Topic
- Gas Sensing Nanomaterials and Sensors
- Type
- article
- Field-Weighted Citation Impact
- 0.00