journal article·2025-12-17

Nitrogen-Doped NiO Nanorods Derived from Hydrogen-Bonded Organic Frameworks for Enhanced Triethylamine Gas Sensing: Preparation and Mechanism

Kuan Tian, Wei Zhao, Yi-Xi Jiang, Zhuo-Lin Li, Zhen-Xing Li, Ming-Xing Su, Wan-Ru Wang, Ze-Xing Cai, Hua-Yao Li

ACS Applied Materials & Interfaces· Volume 17· Issue 50
Publisher page

Abstract

Nickel oxide (NiO) is a promising gas-sensing material; however, its gas-sensing performance is often inadequate, such as low response and poor selectivity. Here, we report the successful synthesis of nitrogen-doped NiO (N-doped NiO) nanorods using a novel hydrogen-bonded organic framework (HOF) templating strategy. Compared to undoped NiO nanosheets, the N-doped NiO nanorods exhibit significantly enhanced gas-sensing performance for triethylamine (TEA). Specifically, they demonstrate a 4-fold increase in response to 10 ppm TEA ( R g / R a = 6.51 and LOD = 10 ppb), good selectivity, remarkably faster response/recovery times (14/11 s), and a lower optimal working temperature of 200 °C. To elucidate the underlying enhancement mechanism, we employ gas chromatography–mass spectrometry (GC-MS) to characterize the gas-sensing reaction in situ. Our findings reveal that NiO facilitates the degradation of TEA into acetaldehyde and ethylenediamine. Crucially, the degradation rate on the surface of the N-doped NiO nanorods is substantially faster than that on the pristine NiO nanosheets. This accelerated degradation is primarily attributed to N-doping-induced modifications of the surface structure of NiO, which consequently promotes the adsorption and catalytic degradation efficiency of TEA. This study introduces a mild and rapid method for preparing uniformly doped, nanostructured N-doped NiO. Furthermore, our in situ quantitative GC-MS analysis provides a robust theoretical basis for understanding the enhanced gas-sensing mechanism of N-doped NiO, offering a valuable foundation for the future development of high-performance N-doped metal-oxide gas sensors.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Gas Sensing Nanomaterials and Sensors · Advanced Chemical Sensor Technologies · Solar-Powered Water Purification Methods

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Material and Chemical Engineering

Zhengzhou University of Light Industry

Research Institute of Industrial Technology

School of Physics and Electronic Engineering

Xinyang Normal University

School of Integrated Circuits

Huazhong University of Science and Technology

Funding

Natural Science Foundation of Henan Province · Henan University of Science and Technology · Science, Technology and Innovation Commission of Shenzhen Municipality · National Natural Science Foundation of China

References (34)

Show source-provided references
1. 10.1021/acssensors.4c0117810.1021/acssensors.4c01178 ↗
2. 10.1039/C8MH01365A10.1039/C8MH01365A ↗
3. 10.1016/j.pmatsci.2023.10122210.1016/j.pmatsci.2023.101222 ↗
4. 10.1021/acssensors.9b0097510.1021/acssensors.9b00975 ↗
5. 10.1002/admi.20210162910.1002/admi.202101629 ↗
6. 10.1016/j.snb.2022.13256510.1016/j.snb.2022.132565 ↗
7. 10.1016/j.snb.2023.13380110.1016/j.snb.2023.133801 ↗
8. 10.1021/acssensors.4c0294610.1021/acssensors.4c02946 ↗
9. 10.1007/s10854-024-13976-510.1007/s10854-024-13976-5 ↗
10. 10.3390/s2423745010.3390/s24237450 ↗
11. 10.1016/j.snb.2024.13591610.1016/j.snb.2024.135916 ↗
12. 10.1016/j.snb.2018.04.16110.1016/j.snb.2018.04.161 ↗
13. 10.1016/j.snb.2021.12997110.1016/j.snb.2021.129971 ↗
14. 10.1021/acsami.4c0942810.1021/acsami.4c09428 ↗
15. 10.1016/j.jallcom.2024.17711010.1016/j.jallcom.2024.177110 ↗
16. 10.1039/D4TC01561D10.1039/D4TC01561D ↗
17. 10.1016/j.apsusc.2024.15980510.1016/j.apsusc.2024.159805 ↗
18. 10.1016/j.snb.2020.12796510.1016/j.snb.2020.127965 ↗
19. 10.1016/j.snb.2023.13488810.1016/j.snb.2023.134888 ↗
20. 10.1021/acsami.4c1249510.1021/acsami.4c12495 ↗
21. 10.1016/j.microc.2025.11285310.1016/j.microc.2025.112853 ↗
22. 10.1016/j.cattod.2013.10.08810.1016/j.cattod.2013.10.088 ↗
23. 10.1016/j.solidstatesciences.2018.10.00910.1016/j.solidstatesciences.2018.10.009 ↗
24. 10.1179/1743294414Y.000000038010.1179/1743294414Y.0000000380 ↗
25. 10.3390/nano1506042710.3390/nano15060427 ↗
26. 10.1007/s10854-020-04581-310.1007/s10854-020-04581-3 ↗
27. 10.1016/j.mseb.2024.11750710.1016/j.mseb.2024.117507 ↗
28. 10.1021/acsami.9b0864710.1021/acsami.9b08647 ↗
29. 10.3390/coatings910063410.3390/coatings9100634 ↗
30. 10.1007/s11664-021-09053-w10.1007/s11664-021-09053-w ↗
31. 10.1016/j.foodchem.2022.13331810.1016/j.foodchem.2022.133318 ↗
32. 10.1016/j.snb.2004.05.00610.1016/j.snb.2004.05.006 ↗
33. 10.1021/acssensors.1c0137410.1021/acssensors.1c01374 ↗
34. 10.1021/acssensors.2c0063910.1021/acssensors.2c00639 ↗