F-Doped In2O3 Nanofibers for Enhanced BTX Detection with a Portable Wireless Sensing Module

Benzene, toluene, and xylene (BTX) gases pose severe threats to public health on account of their toxic, carcinogenic properties and environmental recalcitrance. In addition, their similar molecular structures and chemical inertness complicate the practical quantification of BTX, severely hindering their high-selectivity detection. In this work, a chemiresistive sensor based on F-doped In2O3 nanofibers was constructed. This strategy successfully enhanced the sensor response values toward benzene, toluene, and xylene by approximately 4.3, 4.5, and 4.2 times, respectively. Meanwhile, the limits of detection were reduced from 1, 0.5, and 0.25 ppm to 0.5, 0.25 and 0.05 ppm, respectively. The theoretical lower detection limits for benzene, toluene, and xylene are as low as 9.9 ppb, 5.7 ppb, and 2.5 ppb, respectively. Machine learning methods were further employed for the identification of BTX gases and their binary mixtures. By capturing the distinctive and reproducible patterns of feature vectors from various analytes, the optimal algorithm established decision boundaries and achieved a classification accuracy of 92.1%. Meanwhile, the reasons for the improved gas sensing performance are discussed. Furthermore, a portable wireless gas sensing module based on F-doped In2O3 nanofibers was developed, which can be applied for detecting BTX.

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Publication Details

Journal
Nanomaterials
Published
2026-09-06
DOI
https://doi.org/10.3390/nano16171119
Primary Topic
Gas Sensing Nanomaterials and Sensors
Type
article
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article

F-Doped In2O3 Nanofibers for Enhanced BTX Detection with a Portable Wireless Sensing Module

Xiaobin Zhou, Jiaqi Yang, Yi Chen, Xiaojuan Yan et al.
Nanomaterials
Gas Sensing Nanomaterials and Sensors
article

F-Doped In2O3 Nanofibers for Enhanced BTX Detection with a Portable Wireless Sensing Module

Xiaobin Zhou, Jiaqi Yang, Yi Chen, Xiaojuan Yan, Gang Zhao, Lisen Yuan, Weiguang Ma
article en

Abstract

Benzene, toluene, and xylene (BTX) gases pose severe threats to public health on account of their toxic, carcinogenic properties and environmental recalcitrance. In addition, their similar molecular structures and chemical inertness complicate the practical quantification of BTX, severely hindering their high-selectivity detection. In this work, a chemiresistive sensor based on F-doped In2O3 nanofibers was constructed. This strategy successfully enhanced the sensor response values toward benzene, toluene, and xylene by approximately 4.3, 4.5, and 4.2 times, respectively. Meanwhile, the limits of detection were reduced from 1, 0.5, and 0.25 ppm to 0.5, 0.25 and 0.05 ppm, respectively. The theoretical lower detection limits for benzene, toluene, and xylene are as low as 9.9 ppb, 5.7 ppb, and 2.5 ppb, respectively. Machine learning methods were further employed for the identification of BTX gases and their binary mixtures. By capturing the distinctive and reproducible patterns of feature vectors from various analytes, the optimal algorithm established decision boundaries and achieved a classification accuracy of 92.1%. Meanwhile, the reasons for the improved gas sensing performance are discussed. Furthermore, a portable wireless gas sensing module based on F-doped In2O3 nanofibers was developed, which can be applied for detecting BTX.

NanomaterialsVol. 16(17)
Shanxi University (CN)
Openalex Percentile: Top 19%
Gas Sensing Nanomaterials and Sensors
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