NiO/ZnO Nanocomposites for Multimodal Intelligent MEMS Gas Sensors
Shanghai University of Engineering Science · Shanghai Jiao Tong University · +3 more institutions
Abstract
Gas sensor arrays designed for pattern recognition face persistent challenges in achieving high sensitivity and selectivity for multiple volatile organic compounds (VOCs), particularly under varying environmental conditions. To address these limitations, we developed multimodal intelligent MEMS gas sensors by precisely tailoring the nanocomposite ratio of NiO and ZnO components. These sensors demonstrate enhanced responses to ethylene glycol (EG) and limonene (LM) at different operating temperatures, demonstrating material-specific selectivity. Additionally, a multitask deep learning model is employed for real-time, quantitative detection of VOCs, accurately predicting their concentration and type. These…
Citation impact
- FWCI
- 26.26
- Percentile
- 100%
- References
- 47
Authors
9- JZJiaqing Zhu
Shanghai University of Engineering Science
- LCLechen Chen
Shanghai Jiao Tong University, Micro & Nano Research Institute
- WNWangze Ni
Shanghai Jiao Tong University, Micro & Nano Research Institute
- WCWeiwei Cheng
Shanghai University of Engineering Science
- ZYZhi Yang
Shanghai Jiao Tong University, Micro & Nano Research Institute
Topics & keywords
- Materials science
- Selectivity
- Odor
- Non-blocking I/O
- Nanocomposite
- Ethylene glycol
- Process engineering
- Sensor array