Aerosol Spraying of Carbon Nanofiber-Based Films for NO2 Detection: The Role of the Spraying Technique

This study is devoted to the determination of the role of aerosol spraying in the formation of NO2 sensor properties of carbon nanofiber (CNF)-based films. This is the first paper to systematically apply the aerosol spraying technique to CNF-based films and link the spraying parameters directly to sensor performance metrics (response, signal-to-noise ratio, response times, etc.). Chemiresistive gas sensors were created based on CNFs and tested at room temperature (25 ± 1 °C). It has been shown that the increase in the concentration of the CNF/ethanol mixture used for spraying from 3 to 30 mg/mL led to a growth in sensor response from 1.2% to 12.0% at 2 ppm NO2. The increase in the thickness of the CNF film of the sensor induced a growth in ΔR/R0 to NO2 that is attributed to the formation of a porous film. With increased film thickness, the response improves (from 7.0% to 10.6% at 2 ppm NO2) as does the signal-to-noise ratio (from 735:1 to 1892:1). The creation of hybrid all-carbon composites based on CNFs and multi-walled carbon nanotubes (MWCNTs) resulted in a decrease in both sensor response and signal-to-noise ratio; however, the response time and recovery degree improved. Two types of hybrid materials based on CNFs and MWCNTs were created using aerosol spraying to enhance the sensor behavior of CNFs. The obtained data confirm the dominant role of the thickness of CNF-based films and their density (in terms of distance between nearest carbon inclusions within the film) in sensor characteristics. The machine learning data used to describe the sensing behavior of two gases with opposite resistance changes when in contact with CNFs, namely NO2 and NH3, showed final accuracies of 92.13% on training data and 91.98% on validation data.

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Journal
Applied Sciences
Published
2025-11-14
DOI
https://doi.org/10.3390/app152212110
Primary Topic
Gas Sensing Nanomaterials and Sensors
Type
article
Field-Weighted Citation Impact
0.00

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article

Aerosol Spraying of Carbon Nanofiber-Based Films for NO2 Detection: The Role of the Spraying Technique

Valeriy Golovakhin, E. A. Maximovskiy, В. С. Тимофеев, Alexander G. Bannov et al.
Applied Sciences
Gas Sensing Nanomaterials and Sensors
article

Aerosol Spraying of Carbon Nanofiber-Based Films for NO2 Detection: The Role of the Spraying Technique

Valeriy Golovakhin, E. A. Maximovskiy, В. С. Тимофеев, Alexander G. Bannov, A.A. Shishin, Ekaterina Vostretsova
article en

Abstract

This study is devoted to the determination of the role of aerosol spraying in the formation of NO2 sensor properties of carbon nanofiber (CNF)-based films. This is the first paper to systematically apply the aerosol spraying technique to CNF-based films and link the spraying parameters directly to sensor performance metrics (response, signal-to-noise ratio, response times, etc.). Chemiresistive gas sensors were created based on CNFs and tested at room temperature (25 ± 1 °C). It has been shown that the increase in the concentration of the CNF/ethanol mixture used for spraying from 3 to 30 mg/mL led to a growth in sensor response from 1.2% to 12.0% at 2 ppm NO2. The increase in the thickness of the CNF film of the sensor induced a growth in ΔR/R0 to NO2 that is attributed to the formation of a porous film. With increased film thickness, the response improves (from 7.0% to 10.6% at 2 ppm NO2) as does the signal-to-noise ratio (from 735:1 to 1892:1). The creation of hybrid all-carbon composites based on CNFs and multi-walled carbon nanotubes (MWCNTs) resulted in a decrease in both sensor response and signal-to-noise ratio; however, the response time and recovery degree improved. Two types of hybrid materials based on CNFs and MWCNTs were created using aerosol spraying to enhance the sensor behavior of CNFs. The obtained data confirm the dominant role of the thickness of CNF-based films and their density (in terms of distance between nearest carbon inclusions within the film) in sensor characteristics. The machine learning data used to describe the sensing behavior of two gases with opposite resistance changes when in contact with CNFs, namely NO2 and NH3, showed final accuracies of 92.13% on training data and 91.98% on validation data.

Applied SciencesVol. 15(22)
Nikolaev Institute of Inorganic Chemistry (RU), Novosibirsk State Technical University (RU)
Uddannelses- og Forskningsministeriet
Openalex Percentile: Top 66%
Gas Sensing Nanomaterials and Sensors
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