Ultra-sensitive room-temperature conductometric sensor for acetone vapor detection using WO3/TiC/g-C3N4 nanocomposite: A breakthrough in environmental and health monitoring
Year: 2025
Type: article
Abstract: The detection of acetone vapor is critical for ensuring environmental safety and safeguarding human health, as prolonged exposure can lead to serious health risks. We report a WO 3 /TiC/g-C 3 N 4 (WTCN)-based conductometric sensor for room-temperature acetone detection. This unique ternary architecture has not yet been explored and demonstrates a remarkable enhancement in sensitivity and selectivity due to strong interfacial synergy. The sensor leverages a novel WTCN ternary nanocomposite to functionalize interdigitated electrodes, which were extensively characterized to ensure optimal performance. The sensor's analytical capabilities were evaluated by exposing it to a variety of volatile organic compounds (VOCs), including ethanol, toluene, chloroform, dichloromethane, methanol, and water vapor, generated from the headspace of aqueous solutions with known concentrations. The WTCN-based sensor outperformed other configurations, showcasing remarkable linearity (R 2 = 0.998) and an impressive sensitivity of 19.808 μS.cm −1 ( v /v%) −1 . The sensor achieved a detection limit of 0.076 v/v% (760 ppm) in the gas phase, highlighting its potential for real-world applications. The response time of the acetone sensor, in the headspace for pure acetone solution ranges from 7 to 28 s and the recovery time from 0.3 to 3 s. Furthermore, the sensor was successfully tested in a practical sample, accurately quantifying acetone in the headspace of a commercial nail varnish remover, with results aligning closely with the manufacturer's specifications. This innovative sensor not only offers a reliable and cost-effective solution for acetone detection but also paves the way for advanced environmental monitoring and health safety applications. Its room-temperature operation, combined with high selectivity and sensitivity, makes it a promising tool for industrial, medical, and environmental diagnostics.
Authors: Amira Nahdi, Salah Kouass, Fathi Touati, Nicole Jaffrezic-Renault, Hamdi Ben Halima
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,230
Funder: University of Carthage
OpenAlex ID: W4416662199