2023
DOI: 10.1038/s41598-023-34313-6
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In-vehicle wireless driver breath alcohol detection system using a microheater integrated gas sensor based on Sn-doped CuO nanostructures

Abstract: In this paper, we have developed an in-vehicle wireless driver breath alcohol detection (IDBAD) system based on Sn-doped CuO nanostructures. When the proposed system detects the ethanol trace in the driver`s exhaled breath, it can alarm and then prevents the car to be started and also sends the location of the car to the mobile phone. The sensor used in this system is a two-sided micro-heater integrated resistive ethanol gas sensor fabricated based on Sn-doped CuO nanostructures. Pristine and Sn-doped CuO nano… Show more

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Cited by 13 publications
(6 citation statements)
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“…Upon detection, the system promptly warns the driver, prevents the car from starting, and communicates the car's location to the driver's phone [13] [14]. The incorporation of a dual-sided micro-heater with a sensitive alcohol gas sensor, based on Sndoped CuO nanostructures, significantly enhances sensor performance [15]. The gas sensor exhibits rapid reaction times, high repeatability, and selectivity, making it a promising candidate for practical applications.…”
Section: B Advancing Road Safety Through Alcohol Detection Systemsmentioning
confidence: 99%
“…Upon detection, the system promptly warns the driver, prevents the car from starting, and communicates the car's location to the driver's phone [13] [14]. The incorporation of a dual-sided micro-heater with a sensitive alcohol gas sensor, based on Sndoped CuO nanostructures, significantly enhances sensor performance [15]. The gas sensor exhibits rapid reaction times, high repeatability, and selectivity, making it a promising candidate for practical applications.…”
Section: B Advancing Road Safety Through Alcohol Detection Systemsmentioning
confidence: 99%
“…In this context, the development of sensor technology for quick and reliable breath tests, for instance for incorporation into automotive switches is of high interest. According to Ansari et al it is possible to merge a wireless warning system and a gas sensor based on Sn-doped CuO nanostructures onto a vehicle [14], to alert the family or authorities about this event. Thus, there is an active research field on sensitive and fast response sensors that could work at room temperature to allow a sufficiently small device design.…”
Section: Introductionmentioning
confidence: 99%
“…Patil et al [ 8 ] synthesized In 2 O 3 nanoparticle assemblies as nano-cubes via a simple hydrothermal method, achieving a response of 10 for 3 ppm NO 2 at 50 °C with a response time of 21 s, a recovery time of 8.7 min, and a detection limit of 60 ppb. In recent years, p-type CuO gas-sensitive materials have been increasingly utilized in gas sensors due to their excellent chemical stability and catalytic activity [ 9 ] and have been widely applied for detecting reducing gases such as ethanol [ 10 ], hydrogen [ 11 ], and carbon monoxide [ 12 ]. However, research on oxidizing gases such as NO 2 remains scarce.…”
Section: Introductionmentioning
confidence: 99%
“…For example, Lv et al [6] used willow catkins as a biomass template to obtain thin ZnO nanorods via immersion and calcination treatment, achieving a response of 100.4 for 10 ppm NO 2 at 92 • C. Similarly, Gajanan et al [7] prepared WO 3 nanosheets via a hydrothermal 2 of 15 method, achieving a response of 2.25 for 100 ppm NO 2 at 200 • C. Patil et al [8] synthesized In 2 O 3 nanoparticle assemblies as nano-cubes via a simple hydrothermal method, achieving a response of 10 for 3 ppm NO 2 at 50 • C with a response time of 21 s, a recovery time of 8.7 min, and a detection limit of 60 ppb. In recent years, p-type CuO gas-sensitive materials have been increasingly utilized in gas sensors due to their excellent chemical stability and catalytic activity [9] and have been widely applied for detecting reducing gases such as ethanol [10], hydrogen [11], and carbon monoxide [12]. However, research on oxidizing gases such as NO 2 remains scarce.…”
Section: Introductionmentioning
confidence: 99%