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Fully Self-Powered Gas Sensor through Fe-Ion Doping Engineering in Ni2P for Ultrasensitive and Visualized NO2 Sensing
Zhaokun Sun1, Ningning Zhang1, Xiao Wang1
1Laboratory of Functional Micro-nano Materials and Devices, School of Physics and Technology, University of Jinan, 336 Nanxin Zhuang West Road, Jinan, Shandong Province 250022, P.R. China.
This study introduces a self-powered nitrogen dioxide (NO2) gas sensor using iron-doped nickel phosphide and deep learning. The novel sensor achieves high sensitivity, rapid detection, and accurate quantification for advanced environmental monitoring.
Area of Science:
- Materials Science
- Electrochemistry
- Artificial Intelligence
Background:
- Self-powered gas sensors based on zinc-air batteries (ZABs) offer integrated sensing and power, but face challenges in sensitivity, selectivity, and drift.
- Existing ZAB gas sensors require improvements for reliable detection in complex environments.
Purpose of the Study:
- To develop an ultrasensitive and selective nitrogen dioxide (NO2) gas sensor using a ZAB.
- To enhance NO2 sensing performance through material modification and deep learning algorithms.
- To create a smart sensing device for visualized and remote gas detection.
Main Methods:
- Fabrication of a ZAB-based NO2 sensor utilizing iron-doped nickel phosphide (FNP) as the gas-sensitive cathode material.
- Investigation of FNP material properties, including enhanced charge carrier mobility and d-band center shift due to Fe doping.
- Application of InceptionTime model and wavelet transformation for signal processing and data analysis.
- Construction of a smart sensing device integrating sensors, microcontrollers, and electrochromic displays.
Main Results:
- The FNP-based sensor demonstrated a high response (0.22 V @ 20 ppm) and a low limit of detection (LOD) of 61.8 ppb with a fast response time of 14 s.
- Deep learning algorithms significantly reduced the LOD to 36.9 ppb, enabling remarkable gas recognition and concentration quantification.
- The enhanced adsorbate-substrate interaction and facilitated electron transfer in FNP contribute to improved NO2 reduction reaction kinetics.
Conclusions:
- Fe-doped nickel phosphide is a promising material for enhancing the performance of ZAB-based NO2 sensors.
- Deep learning algorithms effectively improve the sensitivity, selectivity, and quantification capabilities of self-powered gas sensors.
- The developed smart sensing device offers a practical solution for remote and visualized environmental gas monitoring.
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