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| 2. |
- Bastuk, Manuel, et al.
(författare)
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Gas identification based on bias induced hysteresis of a gas-sensitive SiC field effect transistor
- 2014
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Ingår i: Journal of Sensors and Sensor Systems. - : Copernicus GmbH. - 2194-8771 .- 2194-878X. ; 3, s. 9-19
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Tidskriftsartikel (refereegranskat)abstract
- In this work dynamic variation of gate bias is used on a gas-sensitive SiC field effect transistor ("GasFET") to optimize its sensitivity and increase its selectivity. Gate bias ramps introduce strong hysteresis in the sensor signal. The shape of this hysteresis is shown to be an appropriate feature both for the discrimination of various gases (ammonia, carbon monoxide, nitrogen monoxide and methane) as well as for different gas concentrations (250 and 500 ppm). The shape is very sensitive to ambient conditions as well as to the bias sweep rate. Thus, the influences of oxygen concentration, relative humidity, sensor temperature and cycle duration, i.e., sweep rate, are investigated and reasons for the observed signal changes, most importantly the existence of at least two different and competing processes taking place simultaneously, are discussed. Furthermore, it is shown that even for very fast cycles, in the range of seconds, the gas-induced shape change in the signal is strong enough to achieve a reliable separation of gases using gate bias cycled operation and linear discriminant analysis (LDA) making this approach suitable for practical application.
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| 3. |
- Bur, Christian, et al.
(författare)
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Characterization of ash particles with a microheater andgas-sensitive SiC field-effect transistors
- 2014
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Ingår i: Journal of Sensors and Sensor Systems. - : Copernicus GmbH. - 2194-8771 .- 2194-878X. ; 3, s. 305-313
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Tidskriftsartikel (refereegranskat)abstract
- Particle emission from traffic, power plants or, increasingly, stoves and fireplaces poses a serious risk for human health. The harmfulness of the particles depends not only on their size and shape but also on adsorbates. Particle detectors for size and concentration are available on the market; however, determining content and adsorbents is still a challenge. In this work, a measurement setup for the characterization of dust and ash particle content with regard to their adsorbates is presented. For the proof of concept, ammonia-contaminated fly ash samples from a coal-fired power plant equipped with a selective non-catalytic reduction (SNCR) system were used. The fly ash sample was placed on top of a heater substrate situated in a test chamber and heated up to several hundred degrees. A silicon carbide field-effect transistor (SiC-FET) gas sensor was used to detect desorbing species by transporting the headspace above the heater to the gas sensor with a small gas flow. Accumulation of desorbing species in the heater chamber followed by transfer to the gas sensor is also possible. A mass spectrometer was placed downstream of the sensor as a reference. A clear correlation between the SiC-FET response and the ammonia spectra of the mass spectrometer was observed. In addition, different levels of contamination can be distinguished. Thus, with the presented setup, chemical characterization of particles, especially of adsorbates which contribute significantly to the harmfulness of the particles, is possible.
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| 4. |
- Bur, Christian, et al.
(författare)
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Discrimination and Quantification of Volatile Organic Compounds in the ppb-Range with Gas Sensitive SiC-FETs Using Multivariate Statistics
- 2015
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Ingår i: Sensors and actuators. B, Chemical. - : Elsevier. - 0925-4005 .- 1873-3077. ; 214, s. 225-233
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Tidskriftsartikel (refereegranskat)abstract
- Gas sensitive field effect transistors based on silicon carbide, SiC-FETs, have been studied for indoor air quality applications. The selectivity of the sensors was increased by temperature cycled operation, TCO, and data evaluation based on multivariate statistics. Discrimination of benzene, naphthalene, and formaldehyde independent of the level of background humidity is possible by using shape describing features as input for Linear Discriminant Analysis, LDA, or Partial Least Squares – Discriminant Analysis, PLS-DA. Leave-one-out cross-validation leads to a correct classification rate of 90 % for LDA, and for PLS-DA a classification rate of 83 % is achieved. Quantification of naphthalene in the relevant concentration range, i.e. 0 ppb to 40 ppb, was performed by Partial Least Squares Regression and a combination of LDA with a second order polynomial fit function. The resolution of the model based on a calibration with three concentrations was approximately 8 ppb at 40 ppb naphthalene for both algorithms.Hence, the suggested strategy is suitable for on demand ventilation control in indoor air quality application systems.
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| 5. |
- Bur, Christian, et al.
(författare)
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Discrimination and Quantification of Volatile Organic Compounds in the ppb-Range with Gas Sensitive SiC-Field Effect Transistors
- 2014
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Ingår i: Procedia Engineering. - : Elsevier. - 1877-7058.
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Konferensbidrag (refereegranskat)abstract
- Gas sensitive FETs based on SiC have been studied for the discrimination and quantification of hazardous volatile organiccompounds (VOCs) in the low ppb range. The sensor performance was increased by temperature cycled operation (TCO) anddata evaluation based on multivariate statistics, here Linear Discriminant Analysis (LDA). Discrimination of formaldehyde,naphthalene and benzene with varying concentrations in the ppb range is demonstrated. In addition, it is shown that naphthalenecan be quantified in the relevant concentration range independent of the relative humidity and against a high ethanol background.Hence, gas sensitive SiC-FETs are suitable sensors for determining indoor air quality.
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