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Discrimination and Quantification of Volatile Organic Compounds in the ppb-Range with Gas Sensitive SiC-FETs Using Multivariate Statistics
Linköping University, Department of Physics, Chemistry and Biology, Applied Sensor Science. Linköping University, Faculty of Science & Engineering. Saarland University, Lab for Measurement Technology, Germany. (Applied Sensor Science)
Saarland University, Lab for Measurement Technology, Germany.
Linköping University, Department of Physics, Chemistry and Biology, Applied Sensor Science. Linköping University, Faculty of Science & Engineering. (Applied Sensor Science)
Saarland University, Germany. (Lab for Measurement Technology)
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2015 (English)In: Sensors and actuators. B, Chemical, ISSN 0925-4005, E-ISSN 1873-3077, Vol. 214, 225-233 p.Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Elsevier, 2015. Vol. 214, 225-233 p.
Keyword [en]
Indoor Air Quality, temperature modulation, Linear Discriminant Analysis, Partial Least Squares, trace level detection
National Category
Other Environmental Engineering
Identifiers
URN: urn:nbn:se:liu:diva-115560DOI: 10.1016/j.snb.2015.03.016ISI: 000353131300031OAI: oai:DiVA.org:liu-115560DiVA: diva2:795538
Projects
SENSIndoor
Funder
EU, FP7, Seventh Framework Programme, 604311
Available from: 2015-03-16 Created: 2015-03-16 Last updated: 2017-12-04

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Publisher's full texthttp://dx.doi.org/10.1016/j.snb.2015.03.016

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