Enhanced propanol gas sensing performance of p-type NiO gas sensor induced by exceptionally large surface area and crystallinity

Mokoena, Teboho P.; Swart, H.C.; Hillie, K.T.; Tshabalala, Zamaswazi P.; Jozela, Mudalo; Tshilongo, James; Motaung, David E.

doi:10.1016/j.apsusc.2021.151121

Cited by 72 publications

(18 citation statements)

References 31 publications

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“…It is quite essential to fabricate gas sensors that can effectively monitor the concentration of propanol for the early diagnosis of LC, which should meet some requirements like short response (< 10 s), good selectivity, excellent response, and low detection limit [72]. Various nanocomposites based on metal oxide semiconductors have been extensively researched to achieve high sensitivity and fast response, such as Fe-doped ZnO [13,73], 5% Ag-modified hollow sphere In 2 O 3 [42], Cu-doped In 2 O 3 [74], ZnO nanoparticles [75], double-shell Cu 2 O hollow microspheres [76], ZnSnO 3 [77], NiO [78], and ZnO-NiO [79]. relationship between response and n-propanol concentration was 0.9835.…”

Section: Propanolmentioning

confidence: 99%

“…NiO, a p-type semiconductor material that has not been widely concerned, could further reduce the working temperature. According to Mokoena et al [78], NiO, generated from urea and calcined at 400 ℃, has an extremely large SSA (the maximum value = 294 m 2 •g −1 ) and perfect crystallinity. They brought more adsorption sites, and the improved crystallinity could promote the mobility of charge carriers, which were conducive to the gas-sensitive process.…”

Section: Propanolmentioning

confidence: 99%

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Metal oxide semiconductor gas sensing materials for early lung cancer diagnosis

He¹,

Chai²,

Luo³

et al. 2023

Journal of Advanced Ceramics

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The urgency of early lung cancer (LC) diagnosis and treatment has been more and more significant. Exhaled breath analysis using gas sensors is a promising way to find out if someone has LC due to its low-cost, non-invasive, and real-time monitoring compared with traditional invasive diagnostic techniques. Among sensor-based gas detection techniques, metal oxide semiconductor's gas sensors are one of the most important types. This review presents the-state-of-art in metal oxide gas sensors for the diagnosis of early LC. First, the exhaled breath biomarkers are described with emphasis on the concentration of abnormal volatile organic compounds (VOCs) caused by the metabolic process of LC cells. Then, the research status of metal oxide gas sensors in LC diagnosis is summarized. The sensing performance and enhancement strategy of biomarkers provided by metal oxide semiconductor materials are reviewed. Another effective way to improve VOC detection performance is to build a gas sensor array. At the same time, various gas sensors combined with self-powered techniques are mentioned to display a broad development prospect in breath diagnosis.Finally, metal oxide gas sensor-based LC diagnosis is prospected.

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Section: Propanolmentioning

confidence: 99%

Section: Propanolmentioning

confidence: 99%

Metal oxide semiconductor gas sensing materials for early lung cancer diagnosis

He¹,

Chai²,

Luo³

et al. 2023

Journal of Advanced Ceramics

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“…The energy-dispersive spectroscopy (EDS) pattern of SnO 2 film pattern is shown in Additionally, the crystallinity of the semiconductor film as well as the density and particle size of the catalyst have important influences on sensing performance. [29,34,35] The cross-section transmission electron microscope (TEM) images of 30Pd/SnO 2 showed in Figure 3a,b reveal that the film patterns possess a polycrystalline structure, and the interlayer distance is measured to be about 0.34 nm corresponding to the (110) plane of SnO 2 . Moreover, Pd catalysts are distributed on the surface of SnO 2 films in the form of nanoparticles, which are demonstrated by the element mapping patterns (Figure 3c).…”

Section: Preparation and Characterization Of Pd/sno 2 Film Patternsmentioning

confidence: 99%

“…Similarly, Figure2h-k shows that the deposition areas of a component element Sn in the film are the same as that of Pt micro heating electrodes. The result confirms that the SnO 2 film patterns are accurately deposited in the central sensing areas above MEMS micro hotplate arrays.Additionally, the crystallinity of the semiconductor film as well as the density and particle size of the catalyst have important influences on sensing performance [29,34,35]. The cross-section transmission electron microscope (TEM) images of 30Pd/SnO 2 showed in Figure3a,b reveal that the film patterns possess a polycrystalline structure, and the interlayer distance is measured to be about 0.34 nm corresponding to the (110) plane of SnO 2 .…”

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confidence: 99%

Wafer‐Level Manufacturing of MEMS H₂ Sensing Chips Based on Pd Nanoparticles Modified SnO₂ Film Patterns

et al. 2023

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In this manuscript, a simple method combining atomic layer deposition and magnetron sputtering is developed to fabricate high‐performance Pd/SnO2 film patterns applied for micro‐electro‐mechanical systems (MEMS) H2 sensing chips. SnO2 film is first accurately deposited in the central areas of MEMS micro hotplate arrays by a mask‐assistant method, leading the patterns with wafer‐level high consistency in thickness. The grain size and density of Pd nanoparticles modified on the surface of the SnO2 film are further regulated to obtain an optimized sensing performance. The resulting MEMS H2 sensing chips show a wide detection range from 0.5 to 500 ppm, high resolution, and good repeatability. Based on the experiments and density functional theory calculations, a sensing enhancement mechanism is also proposed: a certain amount of Pd nanoparticles modified on the SnO2 surface could bring stronger H2 adsorption followed by dissociation, diffusion, and reaction with surface adsorbed oxygen species. Obviously, the method provided here is quite simple and effective for the manufacturing of MEMS H2 sensing chips with high consistency and optimized performance, which may also find broad applications in other MEMS chip technologies.

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“…It is worth noting that some research studies have proved that several volatile organic compounds (VOCs) could be used as potential noninvasive respiratory biomarkers for lung cancer, − including but not limited to isoprene, n -propanol, and acetone. Meanwhile, the demands for gas sensors efficiently monitoring isoprene, propanol, and acetone have urgently increased for human healthcare field and attracted worldwide attention of researchers. − These efforts mostly focus on the effective detection of a single kind of gas, and the requirement of simultaneous monitoring and identification of multiple gases is still essential. As mentioned above, gas sensors can be selected as a promising new way to realize synchronized detection and identification of multiple lung cancer breath biomarkers.…”

mentioning

confidence: 99%

Pattern Recognition with Temperature Regulation: A Single YSZ-Based Mixed Potential Sensor Classifies Multiple Mixtures of Isoprene, n-Propanol, and Acetone

Lv,

Gu,

Wang

et al. 2023

ACS Sens.

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Gas sensors integrated with machine learning algorithms have aroused keen interest in pattern recognition, which ameliorates the drawback of poor selectivity on a sensor. Among various kinds of gas sensors, the yttria-stabilized zirconia (YSZ)-based mixed potential-type sensor possesses advantages of low cost, simple structure, high sensitivity, and superior stability. However, as the number of sensors increases, the increased power consumption and more complicated integration technology may impede their extensive application. Herein, we focus on the development of a single YSZ-based mixed potential sensor from sensing material to machine learning for effective detection and discrimination of unary, binary, and ternary gas mixtures. The sensor that is sensitive to isoprene, n-propanol, and acetone is manufactured with the MgSb2O6 sensing electrode prepared by a simple sol–gel method. Unique response patterns for specific gas mixtures could be generated with temperature regulation. We chose seven algorithm models to be separately trained for discrimination. In order to realize more accurate discrimination, we further discuss the selection of suitable feature parameters and its reasons. With temperature regulation coefficients which are easily available as feature input to model, a single sensor is verified to achieve elevated accuracy rates of 95 and 99% for the discrimination of seven gases (three unary gases, three binary gas mixtures, and one ternary gas mixture) and redefined six gas mixtures. This article provides a potential new approach via a mixed potential sensor instead of a sensor array that could provide a wide application prospect in the field of electronic nose and artificial olfaction.

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Enhanced propanol gas sensing performance of p-type NiO gas sensor induced by exceptionally large surface area and crystallinity

Cited by 72 publications

References 31 publications

Metal oxide semiconductor gas sensing materials for early lung cancer diagnosis

Metal oxide semiconductor gas sensing materials for early lung cancer diagnosis

Wafer‐Level Manufacturing of MEMS H₂ Sensing Chips Based on Pd Nanoparticles Modified SnO₂ Film Patterns

Pattern Recognition with Temperature Regulation: A Single YSZ-Based Mixed Potential Sensor Classifies Multiple Mixtures of Isoprene, n-Propanol, and Acetone

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Enhanced propanol gas sensing performance of p-type NiO gas sensor induced by exceptionally large surface area and crystallinity

Cited by 72 publications

References 31 publications

Metal oxide semiconductor gas sensing materials for early lung cancer diagnosis

Metal oxide semiconductor gas sensing materials for early lung cancer diagnosis

Wafer‐Level Manufacturing of MEMS H2 Sensing Chips Based on Pd Nanoparticles Modified SnO2 Film Patterns

Pattern Recognition with Temperature Regulation: A Single YSZ-Based Mixed Potential Sensor Classifies Multiple Mixtures of Isoprene, n-Propanol, and Acetone

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Wafer‐Level Manufacturing of MEMS H₂ Sensing Chips Based on Pd Nanoparticles Modified SnO₂ Film Patterns