SiC–FET based SO2 sensor for power plant emission applications.
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| Title: | SiC–FET based SO |
|---|---|
| Authors: | Darmastuti, Z.1 zhada@ifm.liu.se, Bur, C.1,2, Möller, P.1, Rahlin, R.3, Lindqvist, N.3, Andersson, M.1, Schütze, A.2, Spetz, A. Lloyd1 |
| Source: | Sensors & Actuators B: Chemical. Apr2014, Vol. 194, p511-520. 10p. |
| Subjects: | Sulfur dioxide, Silicon carbide, Gas detectors, Gas as fuel, Desulfurization, Fourier transform infrared spectroscopy |
| Abstract: | Abstract: Thermal power plants produce SO2 during combustion of fuel containing sulfur. One way to decrease the SO2 emission from power plants is to introduce a sensor as part of the control system of the desulphurization unit. In this study, SiC–FET sensors were studied as one alternative sensor to replace the expensive FTIR (Fourier Transform Infrared) instrument or the inconvenient wet chemical methods. The gas response for the SiC–FET sensors comes from the interaction between the test gas and the catalytic gate metal, which changes the electrical characteristics of the devices. The performance of the sensors depends on the ability of the test gas to be adsorbed, decomposed, and desorbed at the sensor surface. The feature of SO2, that it is difficult to desorb from the catalyst surface, makes it known as catalyst poison. It is difficult to quantify the SO2 with static operation, even at the optimum operation temperature of the sensor due to low response levels and saturation already at low concentration of SO2. The challenge of SO2 desorption can be reduced by introducing dynamic operation in a designed temperature cycle operation (TCO). The intermittent exposure to high temperature can help to desorb SO2. Simultaneously, additional features extracted from the sensor data can be used to reduce the influence of sensor drift. The TCO operation, together with pattern recognition, may also reduce the baseline and response variation due to changing concentration of background gases (4–10% O2 and 0–70% RH), and thus it may improve the overall sensor performance. In addition to the laboratory experiment, testing in the desulphurization pilot unit was performed. Desulphurization pilot unit has less controlled environment compared to the laboratory conditions. Therefore, the risk of influence from the changing concentration of background gas is higher. In this study, linear discriminant analysis (LDA) and partial least square (PLS) were employed as pattern recognition methods. It was demonstrated that using LDA quantification of SO2 into several groups of concentrations up to 2000ppm was possible. Additionally, PLS analysis indicated a good agreement between the predicted value from the model and the SO2 concentration from the reference instrument of the pilot plant. [Copyright &y& Elsevier] |
| Copyright of Sensors & Actuators B: Chemical is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 94407943 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: SiC–FET based SO<subscript>2</subscript> sensor for power plant emission applications. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Darmastuti%2C+Z%2E%22">Darmastuti, Z.</searchLink><relatesTo>1</relatesTo><i> zhada@ifm.liu.se</i><br /><searchLink fieldCode="AR" term="%22Bur%2C+C%2E%22">Bur, C.</searchLink><relatesTo>1,2</relatesTo><br /><searchLink fieldCode="AR" term="%22Möller%2C+P%2E%22">Möller, P.</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Rahlin%2C+R%2E%22">Rahlin, R.</searchLink><relatesTo>3</relatesTo><br /><searchLink fieldCode="AR" term="%22Lindqvist%2C+N%2E%22">Lindqvist, N.</searchLink><relatesTo>3</relatesTo><br /><searchLink fieldCode="AR" term="%22Andersson%2C+M%2E%22">Andersson, M.</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Schütze%2C+A%2E%22">Schütze, A.</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Spetz%2C+A%2E+Lloyd%22">Spetz, A. Lloyd</searchLink><relatesTo>1</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Sensors+%26+Actuators+B%3A+Chemical%22">Sensors & Actuators B: Chemical</searchLink>. Apr2014, Vol. 194, p511-520. 10p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Sulfur+dioxide%22">Sulfur dioxide</searchLink><br /><searchLink fieldCode="DE" term="%22Silicon+carbide%22">Silicon carbide</searchLink><br /><searchLink fieldCode="DE" term="%22Gas+detectors%22">Gas detectors</searchLink><br /><searchLink fieldCode="DE" term="%22Gas+as+fuel%22">Gas as fuel</searchLink><br /><searchLink fieldCode="DE" term="%22Desulfurization%22">Desulfurization</searchLink><br /><searchLink fieldCode="DE" term="%22Fourier+transform+infrared+spectroscopy%22">Fourier transform infrared spectroscopy</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Abstract: Thermal power plants produce SO2 during combustion of fuel containing sulfur. One way to decrease the SO2 emission from power plants is to introduce a sensor as part of the control system of the desulphurization unit. In this study, SiC–FET sensors were studied as one alternative sensor to replace the expensive FTIR (Fourier Transform Infrared) instrument or the inconvenient wet chemical methods. The gas response for the SiC–FET sensors comes from the interaction between the test gas and the catalytic gate metal, which changes the electrical characteristics of the devices. The performance of the sensors depends on the ability of the test gas to be adsorbed, decomposed, and desorbed at the sensor surface. The feature of SO2, that it is difficult to desorb from the catalyst surface, makes it known as catalyst poison. It is difficult to quantify the SO2 with static operation, even at the optimum operation temperature of the sensor due to low response levels and saturation already at low concentration of SO2. The challenge of SO2 desorption can be reduced by introducing dynamic operation in a designed temperature cycle operation (TCO). The intermittent exposure to high temperature can help to desorb SO2. Simultaneously, additional features extracted from the sensor data can be used to reduce the influence of sensor drift. The TCO operation, together with pattern recognition, may also reduce the baseline and response variation due to changing concentration of background gases (4–10% O2 and 0–70% RH), and thus it may improve the overall sensor performance. In addition to the laboratory experiment, testing in the desulphurization pilot unit was performed. Desulphurization pilot unit has less controlled environment compared to the laboratory conditions. Therefore, the risk of influence from the changing concentration of background gas is higher. In this study, linear discriminant analysis (LDA) and partial least square (PLS) were employed as pattern recognition methods. It was demonstrated that using LDA quantification of SO2 into several groups of concentrations up to 2000ppm was possible. Additionally, PLS analysis indicated a good agreement between the predicted value from the model and the SO2 concentration from the reference instrument of the pilot plant. [Copyright &y& Elsevier] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Sensors & Actuators B: Chemical is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1016/j.snb.2013.11.089 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 10 StartPage: 511 Subjects: – SubjectFull: Sulfur dioxide Type: general – SubjectFull: Silicon carbide Type: general – SubjectFull: Gas detectors Type: general – SubjectFull: Gas as fuel Type: general – SubjectFull: Desulfurization Type: general – SubjectFull: Fourier transform infrared spectroscopy Type: general Titles: – TitleFull: SiC–FET based SO2 sensor for power plant emission applications. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Darmastuti, Z. – PersonEntity: Name: NameFull: Bur, C. – PersonEntity: Name: NameFull: Möller, P. – PersonEntity: Name: NameFull: Rahlin, R. – PersonEntity: Name: NameFull: Lindqvist, N. – PersonEntity: Name: NameFull: Andersson, M. – PersonEntity: Name: NameFull: Schütze, A. – PersonEntity: Name: NameFull: Spetz, A. Lloyd IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 04 Text: Apr2014 Type: published Y: 2014 Identifiers: – Type: issn-print Value: 09254005 Numbering: – Type: volume Value: 194 Titles: – TitleFull: Sensors & Actuators B: Chemical Type: main |
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