Academic literature on the topic 'Metal-Oxide Based Gas Sensor System'

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Journal articles on the topic "Metal-Oxide Based Gas Sensor System"

1

Moshayedi, Ata, Ensieh Kazemi, Mohammad Tabatabaei, and Liefa Liao. "Brief modeling equation for metal-oxide; TGS type gas sensors." Filomat 34, no. 15 (2020): 4997–5008. http://dx.doi.org/10.2298/fil2015997m.

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The main aim of this research is to propose a mathematical equation in order to reduce the model parameters based on temperature, humidity and gas density variation in metal-oxide semi-conductive sensors. Also the Arduino based Designed E-nose with the capability to change the temperature and humidity is used to obtain the real sensor?s response in various conditions. The sampling procedure consists of three sectors: fixed temperature and fixed humidity, variable temperature and fixed humidity, fixed temperature and variable humidity, which are stored in Excel software and analyzed with MATLAB. The output response is based on combination of First-Order Plus Dead Time (FOPDT) which has the Minimum Parameters system (MPS) to investigate the behavior of the sensors. Finally, after evaluating the models with the real sensor response and bi-sentence exponentials, it is suggested that the MPS model introduces fewer and simpler parameters, which helps to simulate the sensor?s behavior more accurately and consequently in order to draw a better short response.
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2

Kumar, Navjot, and Rahul Prajesh. "Selectivity enhancement for metal oxide (MOX) based gas sensor using thermally modulated datasets coupled with golden section optimization and chemometric techniques." Review of Scientific Instruments 93, no. 6 (2022): 064702. http://dx.doi.org/10.1063/5.0083061.

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The ever-increasing demand for smart sensors for internet of things applications drove the change in outlook toward smart sensor system design. This paper focuses on using low-cost gas sensors [Metal Oxide (MOX)] for detection of more than one gas, which is otherwise complex due to poor selectivity of MOX sensors. In this work, detection of two gases, namely, ammonia (NH3) and carbon monoxide (CO), using a single metal oxide (pristine tin oxide) sensor is demonstrated. Furthermore, chemometric based algorithms have been used to classify and quantify both gases. The present investigation uses the temperature modulated gas sensor response obtained at different concentrations for the mentioned gases. The golden section based optimization technique has been employed to obtain two different ranges of temperatures for both gases. After applying certain pre-processing techniques, the acquired data from the sensors were fed to various classification techniques, such as partial least squares (PLS) discriminant analysis, k-means, and soft independent modeling by class analogy, and 100% classification results were obtained. Furthermore, PLS regression (PLS-R) was used to perform quantitative analysis on the data using the optimized temperature ranges for both gases, and R2 regression coefficients, 0.999 25 for NH3 and 0.9399 for CO, were obtained. The results obtained from both the qualitative and quantitative analyses make our approach low-cost and smart to mitigate the cross-selectivity of metal oxide semiconductor based smart sensor design.
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3

Sauerwald, Tilman, Tobias Baur, Martin Leidinger, et al. "Highly sensitive benzene detection with metal oxide semiconductor gas sensors – an inter-laboratory comparison." Journal of Sensors and Sensor Systems 7, no. 1 (2018): 235–43. http://dx.doi.org/10.5194/jsss-7-235-2018.

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Abstract. For detection of benzene, a gas sensor system with metal oxide semiconductor (MOS) gas sensors using temperature-cycled operation (TCO) is presented. The system has been tested in two different laboratories at the concentration range from 0.5 up to 10 ppb. The system is equipped with three gas sensors and advanced temperature control and read-out electronics for the extraction of features from the TCO signals. A sensor model is used to describe the sensor response in dependence on the gas concentration. It is based on a linear differential surface reduction (DSR) at a low temperature phase, which is linked to an exponential growth of the sensor conductance. To compensate for cross interference to other gases, the DSR is measured at three different temperatures (200, 250, 300 ∘C) and the calculated features are put into a multilinear regression (partial least square regression – PLSR) for the quantification of benzene at both laboratories. In the tests with the first set-up, benzene was supplied in defined gas profiles in a continuous gas flow with variation of humidity and various interferents, e.g. toluene and carbon monoxide (CO). Depending on the gas background and interferents, the quantification accuracy is between ±0.2 and ±2 ppb. The second gas mixing system is based on a circulation of the carrier gas stream in a closed-loop control for the benzene concentration and other test gases based on continuously available reference measurements for benzene and other organic and inorganic compounds. In this system, a similar accuracy was achieved for low background contaminations and constant humidity; the benzene level could be quantified with an error of less than 0.5 ppb. The transfer of regression models for one laboratory to the other has been tested successfully.
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4

Zhu, Xiang Dong, Tao Han, Wei Lu, Lei Xing, and Di Xue. "Design of Portable Gas Detector Based on DSP." Advanced Materials Research 430-432 (January 2012): 1667–70. http://dx.doi.org/10.4028/www.scientific.net/amr.430-432.1667.

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A new design method of gas detection system was given based on the new DSP processor TMS320F28335. The experiment system takes six metal-oxide semiconducter gas sensors as well as temperature and humidity sensors in comprising the sensor array module, followed the excellent detection principle how to choose, and choose CH4 and H2 as the test samples and use dual-BP neural-network with the temperature and humidity compensation function as the method to recognize and measure single gas and mixed gases respectively. The result shows that the measuring instrument has higher measuring accuracy and overcomes the shortcoming of other methods, and has important practical application value.
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5

Chen, Li Wei, Jian Hua Yang, and Zhong Lin Tang. "Experimental Study on Odor Compass System Based on Gas Sensor Array and DSP Technology." Advanced Materials Research 317-319 (August 2011): 1102–6. http://dx.doi.org/10.4028/www.scientific.net/amr.317-319.1102.

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Abstract. Based on metal oxide gas sensors and DSP technology an odor compass is designed in this paper. Odor compass estimates direction of point odor source by analyzing responses of sensors which are placed on different concentration gradient. Main structure consists of distributed metal oxide gas sensors and plexiglas material. Signal sampling and processing are accomplished by DSP system. The directivity of whole system is tested in uniform wind field. Experimental result shows that the responses for the odor sources with 30°disparity have obvious difference. Ratio of resistance response is selected as characteristic quantity. In this way, influence which is generated from individual difference of sensors is effectively eliminated.
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6

Bovhyra, R. V., V. M. Zhyrovetskyy, D. I. Popovych, S. S. Savka, and A. S. Serednytskij. "Development and Creation of Gas-Sensor System Based on Low Dimensional Metal Oxides." Science and innovation 12, no. 6 (2016): 57–62. http://dx.doi.org/10.15407/scine12.06.057.

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7

Jaeschke, Carsten, Oriol Gonzalez, Johannes J. Glöckler, et al. "A Novel Modular eNose System Based on Commercial MOX Sensors to Detect Low Concentrations of VOCs for Breath Gas Analysis." Proceedings 2, no. 13 (2018): 993. http://dx.doi.org/10.3390/proceedings2130993.

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In this work, a new generation of eNose systems particularly suited for exhaled breath gas analysis is presented. The developed analyzer system comprises a compact modular, low volume, temperature controlled sensing chamber explicitly tested for the detection of acetone, isoprene, pentane and isopropanol. The eNose system sensing chamber consists of three compartments, each of which can contain 8 analog Metal Oxide (MOX) sensors or 10 digital MOX sensors. Additional sensors within the digital compartment allow for pressure, humidity and temperature measurements. The presented eNose system contains a sensor array with up to 30 physical sensors and provides the ability to discriminate between low VOC concentrations under dry and humid conditions. The MOX sensor signals were analyzed by pattern recognition methods.
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8

Minska, Natalya, Roman Ponomarenko, Roman Shevchenko, and Olekciy Antoshkin. "Optimization of the Technology of Creating Sensitive Gas Sensors Based on Zinc Oxide." Materials Science Forum 1096 (August 28, 2023): 81–86. http://dx.doi.org/10.4028/p-lm4qpy.

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The main achievements in the development of resistive type gas sensors are analyzed, in particular, the creation of nanostructures based on metal oxides, which make it possible to significantly improve the performance characteristics of the sensors. Experimental samples of the gas sensor based on ZnO were obtained by magnetron sputtering on direct current. The effectiveness of the gas sensor system for recognition and analysis of gases and their mixtures has been established. A study of the sensitivity of experimental samples to the influence of the target gas CO was carried out. The target gas concentration varied from 50 to 150 ppm. It was established that the ZnO-based gas sensor exhibits the highest sensitivity at a target gas concentration of 100 ppm. The sensitivity of the gas sensor increases with increasing exposure time to the target gas.
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Dutta, Taposhree, Tanzila Noushin, Shawana Tabassum, and Satyendra K. Mishra. "Road Map of Semiconductor Metal-Oxide-Based Sensors: A Review." Sensors 23, no. 15 (2023): 6849. http://dx.doi.org/10.3390/s23156849.

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Identifying disease biomarkers and detecting hazardous, explosive, flammable, and polluting gases and chemicals with extremely sensitive and selective sensor devices remains a challenging and time-consuming research challenge. Due to their exceptional characteristics, semiconducting metal oxides (SMOxs) have received a lot of attention in terms of the development of various types of sensors in recent years. The key performance indicators of SMOx-based sensors are their sensitivity, selectivity, recovery time, and steady response over time. SMOx-based sensors are discussed in this review based on their different properties. Surface properties of the functional material, such as its (nano)structure, morphology, and crystallinity, greatly influence sensor performance. A few examples of the complicated and poorly understood processes involved in SMOx sensing systems are adsorption and chemisorption, charge transfers, and oxygen migration. The future prospects of SMOx-based gas sensors, chemical sensors, and biological sensors are also discussed.
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10

Voss, Andreas, Rico Schroeder, Steffen Schulz, et al. "Detection of Liver Dysfunction Using a Wearable Electronic Nose System Based on Semiconductor Metal Oxide Sensors." Biosensors 12, no. 2 (2022): 70. http://dx.doi.org/10.3390/bios12020070.

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The purpose of this exploratory study was to determine whether liver dysfunction can be generally classified using a wearable electronic nose based on semiconductor metal oxide (MOx) gas sensors, and whether the extent of this dysfunction can be quantified. MOx gas sensors are attractive because of their simplicity, high sensitivity, low cost, and stability. A total of 30 participants were enrolled, 10 of them being healthy controls, 10 with compensated cirrhosis, and 10 with decompensated cirrhosis. We used three sensor modules with a total of nine different MOx layers to detect reducible, easily oxidizable, and highly oxidizable gases. The complex data analysis in the time and non-linear dynamics domains is based on the extraction of 10 features from the sensor time series of the extracted breathing gas measurement cycles. The sensitivity, specificity, and accuracy for distinguishing compensated and decompensated cirrhosis patients from healthy controls was 1.00. Patients with compensated and decompensated cirrhosis could be separated with a sensitivity of 0.90 (correctly classified decompensated cirrhosis), a specificity of 1.00 (correctly classified compensated cirrhosis), and an accuracy of 0.95. Our wearable, non-invasive system provides a promising tool to detect liver dysfunctions on a functional basis. Therefore, it could provide valuable support in preoperative examinations or for initial diagnosis by the general practitioner, as it provides non-invasive, rapid, and cost-effective analysis results.
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