Master Degree / Yüksek Lisans Tezleri

Permanent URI for this collectionhttps://hdl.handle.net/11147/3008

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2013 - 20163

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Author: search.filters.author.Özdemir, DurmuşPublisher: search.filters.publisher.İzmir Institute of Technology

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Now showing 1 - 3 of 3
  • Master Thesis
    Development of a New Infrared Spectroscopic Method Based on Multivariate Calibration for the Determination of Aluminum and Magnesium Oxid Thickness on Aluminum Foil and Sheets Surfaces
    (İzmir Institute of Technology, 2016) Meşe, Ayten Ekin; Özdemir, Durmuş
    Surface oxidation is a general problem for certain industrial applications such as coating and painting of the finished rolled products. A detailed understanding for the oxide growth mechanism as well as the development of a simple analytical method to measure this oxide thickness is very important in aluminum rolling industry and this study aims to develop a spectroscopic method to determine the oxide thicknesses on the surface of the aluminum by using multivariate calibration and infrared spectroscopy. Two main series of different aluminum alloys (3005 and 3003BZ) were selected in this study to develop a proposed methodology which is based on the combination of Fourier Transform Infrared Spectroscopy (FTIR) with Grazing Angle ATR accessory and chemometrics multivariate calibration techniques. In order to obtain oxide thickness values, X-ray Photoelectron Spectroscopy (XPS) was used and aluminum oxide (Al2O3) and magnesium oxide (MgO) thicknesses determinations were carried out by two different multivariate calibration models which are Genetic Inverse Least Squares (GILS) and Genetic Partial Least Squares (GPLS). These models were able to predict Al2O3 and MgO thicknesses using FTIR that is faster, easier and cheaper to operate as well as from XPS. The correlation coefficients of XPS reference oxide thickness values versus FTIR-GATR based GILS and GPLS predicted values were better than 0.919 in range of 0 to 25 nanometers for Al2O3 and 0 to 35 nm for MgO. These results suggest that grazing angle FTIR-ATR spectroscopy may offer a simple and nondestructive alternative for quick determination of oxide layer thickness.
  • Master Thesis
    Multivariate Statistical Optimization of Enzyme Immobilization Onto Solid Matrix Using Central Composite Design
    (İzmir Institute of Technology, 2013) Arpakcı, Tuğba; Özdemir, Durmuş
    In recent years, scientist have been used alternative technology in order to increase enzyme stability and also reduce the cost of production of enzyme. Immobilization methods have attracted the attention of scientists due to its advantages in comparison with soluble enzyme or other methods. Immobilization process can be affected by many factors for this reason it is important to optimize the effective factors in order to enhance success of this process. In preliminary studies, Bradford protein assay was used for determination of protein concentration. In order to increase sensitivity and accuracy of this assay, Bradford protein assay was combined with a multivariate calibration methods. Genetic Inverse Least Squares (GILS) and Partial Least Squares (PLS) were used for multivariate calibration. Calibration model was constructed for various concentration of Bovine Serum Albumin (BSA). Standard Error of Calibration (SEC) and Standard Error of Prediction (SEP) were calculated and results of multivariate calibration method were compared with univariate calibration methods and each other. In this study, the bovine serum albumin immobilization studies were carried out. The bovine serum albumin was immobilized on chitosan nanoparticles and effective factors such as chitosan concentration, immobilization time, pH and temperature were optimized by using central composite design (CCD). Central composite design is used to investigate interaction between these parameters and to find the optimum values of effective factors.
  • Master Thesis
    Development of Chromatographic and Moleculer Spetroscopic Multivariate Chemometric Models for the Geographical Classification of Olive Oils
    (İzmir Institute of Technology, 2013) Çelik, Deniz; Özdemir, Durmuş
    Olive oil is a fat obtained from the olive (the fruit of Olea europaea; family Oleaceae), a traditional tree crop of the Mediterranean Basin. The oil is produced by grinding whole olives and extracting the oil by mechanical or chemical means. It is commonly used in cooking, cosmetics, pharmaceuticals, and soaps and as a fuel for traditional oil lamps. The classification of olive based on geographical origin is of great interest since the quality of olive oil depends on its chemical composition and geographical origin. In this study, it is aimed to develop classification models using elemental and molecular composition of olive oil samples via chromatographic method and molecular spectrometry. For this purpose, olive oil samples from diffirent regions of Turkey (Manisa and Bursa) were collected from producers and they were scanned with Fourier Transform Infrared spectrometer equiped with attenuated total reflectance (FTIR-ATR) accesory, and Gas Chromatography (GC), High Performance Liquid Chromatography (HPLC). Afterwards, any clustering of samples based on their regions was investigated using principal component analysis (PCA) and hierarchical cluster analysis (HCA). In conclusion, although molecular spectrometry is more advantageous for the classification of olive oil samples in the case of saving time, saving chemicals and ease of usage, chromatography gave better classification results based on geograpical origin compared to results obtained with molecular spectrometry.