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dc.contributor.authorMirmohseni, A
dc.contributor.authorRostamizadeh, K
dc.date.accessioned2018-08-26T08:30:13Z
dc.date.available2018-08-26T08:30:13Z
dc.date.issued2006
dc.identifier.urihttp://dspace.tbzmed.ac.ir:8080/xmlui/handle/123456789/51937
dc.description.abstractQuartz crystal nanobalance (QCN) sensors are considered as powerful mass-sensitive sensors to determine materials in the sub-nanogram level. In this study, a single piezoelectric quartz crystal nanobalance modified with polystyrene was employed to detect benzene, toluene, ethylbenzene and xylene (BTEX compounds). The frequency shift of the QCN sensor was found to be linear against the BTEX compound concentrations in the range about 1- 45 mg l(-1). The correlation coefficients for benzene, toluene, ethylbenzene, and xylene were 0.991, 0.9977, 0.9946 and 0.9971, respectively. The principal component analysis was also utilized to process the frequency response data of the single piezoelectric crystal at different times, considering to the different adsorption-desorption dynamics of BTEX compounds. Using principal component analysis, it was found that over 90% of the data variance could still be explained by use of two principal components (PC1 and PC2). Subsequently, the successful identification of benzene and toluene was possible through the principal component analysis of the transient responses of the polystyrene modified QCN sensor. The results showed that the polystyrene-modified QCN had favorable identification and quantification performances for the BTEX compounds.
dc.language.isoEnglish
dc.relation.ispartofSENSORS
dc.relation.ispartof3rd International Symposium on Sensor Science
dc.subjectquartz crystal nanobalance (QCN)
dc.subjectBTEX compounds
dc.subjectprincipal component analysis
dc.titleQuartz crystal nanobalance in conjunction with principal component analysis for identification of volatile organic compounds
dc.typeArticle; Proceedings Paper
dc.citation.volume6
dc.citation.issue4
dc.citation.spage324
dc.citation.epage334
dc.citation.indexWeb of science
dc.identifier.DOIhttps://doi.org/10.3390/s6040324


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