Discrimination and quantification of volatile organic compounds in the ppb-range with gas sensitive SiC-FETs using multivariate statistics.
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| Title: | Discrimination and quantification of volatile organic compounds in the ppb-range with gas sensitive SiC-FETs using multivariate statistics. |
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| Authors: | Bur, Christian1,2 c.bur@lmt.uni-saarland.de, Bastuck, Manuel2 m.bastuck@lmt.uni-saarland.de, Puglisi, Donatella1 donpu@ifm.liu.se, Schütze, Andreas2 schuetze@lmt.uni-saarland.de, Lloyd Spetz, Anita1 spetz@ifm.liu.se, Andersson, Mike1 mikan@ifm.liu.se |
| Source: | Sensors & Actuators B: Chemical. Jul2015, Vol. 214, p225-233. 9p. |
| Subjects: | Volatile organic compounds, Silicon carbide, Field-effect transistors, Multivariate analysis, Regression analysis |
| 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., 0–40 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. [ABSTRACT FROM AUTHOR] |
| 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: 102189163 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Discrimination and quantification of volatile organic compounds in the ppb-range with gas sensitive SiC-FETs using multivariate statistics. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Bur%2C+Christian%22">Bur, Christian</searchLink><relatesTo>1,2</relatesTo><i> c.bur@lmt.uni-saarland.de</i><br /><searchLink fieldCode="AR" term="%22Bastuck%2C+Manuel%22">Bastuck, Manuel</searchLink><relatesTo>2</relatesTo><i> m.bastuck@lmt.uni-saarland.de</i><br /><searchLink fieldCode="AR" term="%22Puglisi%2C+Donatella%22">Puglisi, Donatella</searchLink><relatesTo>1</relatesTo><i> donpu@ifm.liu.se</i><br /><searchLink fieldCode="AR" term="%22Schütze%2C+Andreas%22">Schütze, Andreas</searchLink><relatesTo>2</relatesTo><i> schuetze@lmt.uni-saarland.de</i><br /><searchLink fieldCode="AR" term="%22Lloyd+Spetz%2C+Anita%22">Lloyd Spetz, Anita</searchLink><relatesTo>1</relatesTo><i> spetz@ifm.liu.se</i><br /><searchLink fieldCode="AR" term="%22Andersson%2C+Mike%22">Andersson, Mike</searchLink><relatesTo>1</relatesTo><i> mikan@ifm.liu.se</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Sensors+%26+Actuators+B%3A+Chemical%22">Sensors & Actuators B: Chemical</searchLink>. Jul2015, Vol. 214, p225-233. 9p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Volatile+organic+compounds%22">Volatile organic compounds</searchLink><br /><searchLink fieldCode="DE" term="%22Silicon+carbide%22">Silicon carbide</searchLink><br /><searchLink fieldCode="DE" term="%22Field-effect+transistors%22">Field-effect transistors</searchLink><br /><searchLink fieldCode="DE" term="%22Multivariate+analysis%22">Multivariate analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Regression+analysis%22">Regression analysis</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: 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., 0–40 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. [ABSTRACT FROM AUTHOR] – 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.2015.03.016 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 9 StartPage: 225 Subjects: – SubjectFull: Volatile organic compounds Type: general – SubjectFull: Silicon carbide Type: general – SubjectFull: Field-effect transistors Type: general – SubjectFull: Multivariate analysis Type: general – SubjectFull: Regression analysis Type: general Titles: – TitleFull: Discrimination and quantification of volatile organic compounds in the ppb-range with gas sensitive SiC-FETs using multivariate statistics. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Bur, Christian – PersonEntity: Name: NameFull: Bastuck, Manuel – PersonEntity: Name: NameFull: Puglisi, Donatella – PersonEntity: Name: NameFull: Schütze, Andreas – PersonEntity: Name: NameFull: Lloyd Spetz, Anita – PersonEntity: Name: NameFull: Andersson, Mike IsPartOfRelationships: – BibEntity: Dates: – D: 31 M: 07 Text: Jul2015 Type: published Y: 2015 Identifiers: – Type: issn-print Value: 09254005 Numbering: – Type: volume Value: 214 Titles: – TitleFull: Sensors & Actuators B: Chemical Type: main |
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