Gas Sensor Selectivity Assessment Indicator of Fill Factor from Response Curve: A Case Study on WS <sub>2</sub> -Based Ammonia Gas Sensors
With the advancement of smart detection technologies, gas sensors have gained increasingly widespread applications in environmental monitoring, industrial safety, medical diagnostics, and intelligent agriculture. The response curve of a single gas sensor is conventionally used to calculate sensor performance evaluation parameters of response/recovery time and response value. The selectivity of a single sensor is currently evaluated by a selectivity coefficient based on the response value, which faces difficulty in distinguishing gases with different concentrations. In this study, a new metric of fill factor (FF) derived from response curve morphology features was introduced to offer a novel solution for single-sensor selectivity analysis. Three variants of the novel metrics, FF<sub>res</sub> (response phase fill factor), FF<sub>rec</sub> (recovery phase fill factor), and FF (total fill factor), can be calculated from the response curve. As a proof-of-concept, the FFs of WS<sub>2</sub>, WS<sub>2</sub>@PANI, and Au/PANI/WS<sub>2</sub> sensors at different concentrations of ammonia, acetone, methanol, ethanol, and water vapor were calculated and used for gas selectivity analysis. Results demonstrated distinct FF ranges for ammonia and other gases, validating FF as a potential selectivity indicator. This approach provides a multidimensional analysis framework for enhanced single-sensor discrimination by constructing a parameter space incorporating curve morphology features.
Authors
- Chengli Tang (ORCID: https://orcid.org/0000-0002-8361-3878)
- Ming Li (ORCID: https://orcid.org/0000-0001-8655-3869)
- Peng Wang (ORCID: https://orcid.org/0000-0002-3093-4280)
- Zhiyuan Zhu
Institutions
- Zhejiang Sci-Tech University (CN)
- Jiaxing University (CN)
Publication Details
- Journal
- ACS Sensors
- Published
- 2025-09-23
- DOI
- https://doi.org/10.1021/acssensors.5c01453
- Citations
- 1
- Primary Topic
- Gas Sensing Nanomaterials and Sensors
- Type
- article
- Field-Weighted Citation Impact
- 0.73