Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/3019
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dc.contributor.advisorÖzdemir, Durmuşen
dc.contributor.authorYalçın, Ayşegül-
dc.date.accessioned2014-07-22T13:50:43Z-
dc.date.available2014-07-22T13:50:43Z-
dc.date.issued2009en
dc.identifier.urihttp://hdl.handle.net/11147/3019-
dc.descriptionThesis (Master)--İzmir Institute of Technology, Chemistry, İzmir, 2009en
dc.descriptionIncludes bibliographical references (leaves: 104-106)en
dc.descriptionText in English; Abstract: Turkish and Englishen
dc.descriptionxv, 106 leavesen
dc.description.abstractThis study focuses on the development of multivariate calibration models for the aluminum rolling oil additives and contaminants using Fourier Transform Infrared (FTIR) spectroscopy and a genetic algorithm based inverse least squares (GILS) method. Multivariate calibration models were generated for both synthetic mixtures and real process samples taken from an industrial aluminum production plant. Two different additives and six different suspected contaminants were investigated in the base oil lubricant. Gas chromatography (GC) was used for the analysis of real process samples in order to establish reference values of additives and contaminants in the base rolling oil. FTIR spectra of real samples together with the reference values established with GC analysis were used to generate multivariate calibration models. GC analysis revealed that most of the contaminants gave overlapped chromatograms and therefore only the total contamination was determined with reference GC analysis. On the other hand, FTIR spectroscopy coupled with multivariate calibration was able to resolve overlapping components with synthetic samples. The reference values for both additives and contaminants obtained by GC were compared with the results of the spectroscopic analysis. The multivariate calibration models based on spectroscopic data validated with the real process samples in a period of twelve months, however only a set of 3-month data is given in this thesis. The R2 values between GC and multivariate spectroscopic determinations were around 0.99 indicating a good correlation between the two methods.en
dc.language.isoenen_US
dc.publisherIzmir Institute of Technologyen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subject.lccTP685 .Y16 2009en
dc.subject.lcshMineral oils--Analysisen
dc.subject.lcshInfrared spektroscopyen
dc.subject.lcshGas chromatographyen
dc.subject.lcshCalibrationen
dc.titleSpectroscopic determination of industrial oil blends using multivariate calibratonen_US
dc.typeMaster Thesisen_US
dc.institutionauthorYalçın, Ayşegül-
dc.departmentThesis (Master)--İzmir Institute of Technology, Chemistryen_US
dc.relation.publicationcategoryTezen_US
item.openairetypeMaster Thesis-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextWith Fulltext-
item.languageiso639-1en-
item.cerifentitytypePublications-
item.grantfulltextopen-
Appears in Collections:Master Degree / Yüksek Lisans Tezleri
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