http://www.cnr.it/ontology/cnr/individuo/prodotto/ID35792
Investigation of the electric field distribution in x-ray detectors by Pockels effect (Articolo in rivista)
- Type
- Label
- Investigation of the electric field distribution in x-ray detectors by Pockels effect (Articolo in rivista) (literal)
- Anno
- 2006-01-01T00:00:00+01:00 (literal)
- Alternative label
Cola A, Farella I, Auricchio N, Caroli E (2006)
Investigation of the electric field distribution in x-ray detectors by Pockels effect
in IEEE transactions on nuclear science
(literal)
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- Cola A, Farella I, Auricchio N, Caroli E (literal)
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- Rivista
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- ISI Web of Science (WOS) (literal)
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- Univ Lecce, CNR, IMM, CNR,Microelect & Microsyst Inst, I-73100 Lecce, Italy; CNR, IPSL, I-50018 Florence, Italy (literal)
- Titolo
- Investigation of the electric field distribution in x-ray detectors by Pockels effect (literal)
- Abstract
- The detection of aroma volatile compounds emitted by extra virgin olive oils (EVOOs) is of key importance in the quality control of this product. Physical-chemical techniques (GC, GUMS, HPLC) and sensory analysis (panel test) are the classical methods used for this purpose, but they are expensive, time consuming, and do not allow on-line measurements. In this paper a new device, an Electronic Nose, that is a sensor array based on pure and doped SnO2 sol-gel thin films used for the discrimination of different Mediterranean \"single-cultivar\" EVOOs, was presented. To confirm the sensor array responses, analytical technique like headspace-solid phase micro-extraction/gas chromatography/mass spectrometry (HS-SPME/GC/MS) analysis was applied to the analysis of volatiles compounds in EVOOs samples. Moreover sensory analysis on EVOOs was carried out. The obtained GC/MS data were used to identify the particular compounds and characterize the chemical composition of the EVOOs samples. In addition a chemometric pattern recognition technique was used for multivariate data analysis. The variations in the GC/MS fingerprint of the different samples were analysed using principal component analysis (PCA). Statistical analyses were carried out on data obtained from Electronic Nose, GC/MS and sensory analysis. (literal)
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