Master Degree / Yüksek Lisans Tezleri
Permanent URI for this collectionhttps://hdl.handle.net/11147/3008
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Master Thesis In-Depth Investigation of the Effects of Different Preprocessing Strategies on Infrared Spectroscopic Data(01. Izmir Institute of Technology, 2021) Deniz, Elin İlayda; Özdemir, DurmuşWhenever collecting experimental data, they may contain several spurious sources of variability which can hinder the extraction of the desired relevant information so that it is rarely the case that they can be processed as such by chemometrics approaches. In recent years, pre-processing techniques has become an integral part of chemometrics modeling with the purpose of providing better endmodels through fundamental knowledge for Near-Infrared (NIR) users. The aim of pre-processing techniques is to improve success of multivariate regression by reducing undesired physical phenomena in the spectra. This thesis describes the theory of present pre-processing techniques and compares the qualitative and quantitative results of their application. Mean centering, scatter-correction methods and spectral derivatives are the instances of those pre-processing techniques used in this thesis. Those techniques and combinations of them have been applied in order to find the best pre-processing strategy. To be able to observe the results and compare the effects of the applied methods, Partial Least Squares and Genetic Inverse Laast Squares are carried out as multivariate calibration methods. When comparing the calibration results of raw data with pre-processing techniques applied data, decreasement standard eror of prediction (SEP) values observed after appliying those techniques, which is good manner. However, better in comparison, t-Test: Paired Two Sample for Means applied. The results demontrates that there is no significant difference within 95% confidence level.Master Thesis Development of Chemometrics Method Based on Infrared Spectroscopy for the Determination of Cement Composition and Process Optimization [master Thesis](01. Izmir Institute of Technology, 2021) Tepeli, Dilek; Özdemir, DurmuşCalcium, silicon, aluminum, iron oxide-containing raw materials are used in controlled portions to manufacture cement. (How cement Is Made, n.d.) This mixture is first converted to clinker, obtained by heating the mixture to 1500oC; some additives are added and ground to obtain cement. Depending on the purpose, various types are produced, and therefore, the determination of cement composition is an essential task for the quality consideration and the sustainability of the production processes. The quantitative analysis of cement is performed with X-ray fluorescence spectroscopy. However, XRF generally requires tedious and lengthy analysis times. In this study, quantitative determination of the raw materials, intermediate products, and types of cement by using Fourier transform infrared spectroscopy coupled with chemometrics multivariate calibration method is aimed, which could be an alternative for the current XRF technique. Samples were collected from a local cement factory that has been in the sector for several years. Reference analyses of the samples were performed at the quality control laboratory of the same factory. The same samples were analyzed by the FTIR-ATR spectrometer. The resulting FTIR spectra combined with XRF reference composition data were used to construct calibration models using the partial least squares method (PLS). Based on the obtained results, the proposed method could generate quite successful results for the quantitative determination of all types of products used to produce cement. The regression coefficients (R2) of the PLS models vary from 0.95 to 0.99. The standard errors of cross-validations were found as from 0.21 to 1.42 (w/w%).Master Thesis Determination of Crucial Parameters in Gasoline Blends by Using Infrared Spectroscopy Coupled With Multivariate Calibration Methods(01. Izmir Institute of Technology, 2021) Sakallı, Fatma Nur; Özdemir, DurmuşIn petroleum refineries, converting the manual gasoline blending system to an automatic inline blending system provides the most economical blending in gasoline production, increasing efficiency, and reliability. The most important requirement for an automatic inline blending system is the determination of gasoline parameters in a short time with high reliability. For this purpose, fast and simple analytical methods have been developed to determine crucial parameters of gasoline blends by using Fourier Transform Infrared Spectroscopy (FTIR) coupled with multivariate calibration methods which are Partial Least Squares Regression (PLSR) and Genetic Inverse Least Squares Regression (GILS) for this study. Turkey Petroleum Refinery Incorporated Company (TUPRAS) Izmir Refinery collected all gasoline samples and tested them using reference test methods at Quality Control Laboratory. Since commercial product samples were used in this study, the data ranges of the parameters were quite narrow. The Standard Error of Cross-Validation (SECV) and Standard Error of Prediction (SEP) values were acceptable, although the determintion coefficient (R2) value of some parameters was below the expectation. It has been observed that the prediction results of GILS are better in these parameters, whose R2 value is low because the data range is very narrow. In the comparison made with the reproducibility values specified in the reference measurement methods, it was determined that the calibration model results of most parameters were acceptable. Collecting more samples in a longer time interval to expand the data range of the parameters, or preparing a data set with experimental design can improve the prediction performance.Master Thesis Development of Molecular Fluorescence Spectroscopy Based Multivariate Calibration Models for Quantitative Determination of Fatty Acids and Triacylglycerol Compositions of Olive Oils(01. Izmir Institute of Technology, 2020) Hedef, Onur; Özdemir, DurmuşThis study illustrates the quantitative determination of fatty acid and triacylglycerol composition of olive oils by using multivariate calibration methods namely partial least squares (PLS) and genetic inverse least squares (GILS) coupled with molecular fluorescence spectroscopy. The reference analysis of the olive oils was carried out with gas chromatography (GC) and high-performance liquid chromatography (HPLC) for the compositions, respectively. A total of 125 olive oil samples were collected from Marmara and Aegean olive growing regions in western Turkey, right after the olives oils are produced in the 2010 -2011 season. Chromatographic and fluorescence analyses were performed simultaneously on the samples and then collected spectra were combined with reference analysis results for the multivariate calibration step. Among the several components analyzed by both GC and HPLC, 10 components from fatty acids and 10 components from triacylglycerols were chosen for modeling. Multivariate calibration models were constructed by randomly selecting 100 samples as calibration set and assigning the remaining 25 samples to the independent validation set using PLS and GILS with leave one out cross-validation based on the fluorescence spectra of the olive oils. The results have demonstrated that the compositions could be successfully determined by using molecular fluorescence spectroscopy. The standard error of cross-validation (SECV) and standard error of prediction (SEP) values were acceptable for most of the components. The regression coefficients (R2) of reference values vs. predicted values ranged from 0.70 to 0.98, indicating that molecular fluorescence spectroscopy combined with multivariate calibration could potentially be used for quantitative determination.Master Thesis Determination of Hydrocarbon Composition of Naphtha by Using Fourier Transform Infrared Spectroscopy and Multivariate Calibration(01. Izmir Institute of Technology, 2020) Şentürk, Selahattin; Özdemir, DurmuşAccurate monitoring of the charging and output of the refinery unit is required. These direct refineries need to provide a quick response to posts on crude oil compositions or directions to their latest request. Determining the physical properties of the intermediate products of the crude oil unit in the refinery based on conventional analytical methods requires time consuming and expensive processes. At this stage, multivariate calibration techniques, creating models that can replace conventional analysis methods and obtaining results using fast spectroscopic analysis. For this study, multivariate calibration techniques were used to determine the hydrocarbons in the naphtha product from crude oil distillation column. The results were evaluated by comparing with using the reference conventional method results. Parameters are Aromatics, Olefins, Benzene, Naphthenes, Paraffins, C7Plus (the sum of compounds with more than 7 carbons) and C6Minus (the sum of compounds with less than 6 carbons). Samples were analyzed by Fourier transform near infrared region spectroscopy between 10000 cm-1- 4000 cm-1 wavenumbers. Calibration models were obtained by partial least squares and genetic inverse least squares methods. Using these models, the relevant parameters for the validation set samples were estimated and compared statistically with the values of the reference analysis methods. The results has been indicated that parameters has been successfully modelled with R2 range from 0.917 to 0.998 for LSRN samples and R2 range from 0.963 to 0.996 for HSRN samplesMaster Thesis The Development of Chemometric Methods Based on Molecular Spectroscopy for the Standardization of Production Processes and Product Traceability of Personal Care and Cleaning Products(Izmir Institute of Technology, 2019) Çiftçi İlmek, Berfu; Özdemir, DurmuşPersonal care and cleaning products are the main consumer goods. Changes in our heath caused by all of the chemicals that we exposed to everyday if these products are not produced according to the regulations and determined formulations. Because of this reason, quality control of the product formulation quantitatively is very important. There are some analytical methods for the determination of anion active matter, nonionic matter and total active matter in the product mixture. However, these techniques are expensive and do not give accurate results. The purpose of this thesis principally based on development of rapid, accurate and practical infrared spectroscopic technique based on multivariate chemometrics data analysis methods for the standardization of production processes and product traceability of personal care and cleaning products. In this thesis, two different products are studied which are namely liquid soap and shower gel. Fourier Transform Infrared spectroscopy coupled with Attenuated Total Reflectance accessory based chemometrics multivariate calibration models were developed for the quantitative determination of liquid soap and shower gel compounds. Genetic Inverse Least Squares was used as the chemometrics method for the development of multivariate calibration models in the quantitative determination of liquid soap and shower gel compositions. Standard error of cross validation and standard error of prediction values for content of the liquid soap samples were found 0.26% and 0.21 % (w/w %), respectively. Standard error of cross validation and standard error of prediction values for content of the shower gel samples were found 0.27 % and 0.30 % (w/w %), respectively.Master Thesis Determination of Total Acid Number in the Optimization of Oleate Production by Using Fourier Transform Infrared Spectroscopy and Multivariate Calibration(Izmir Institute of Technology, 2019) Toygar Türkün, Nihan; Özdemir, DurmuşPolyethylene glycol oleate (PEG-Oleate) is a non-ionic surfactant, and is an important emulsifier for water-oil systems. It is produced by reacting oleic acid and polyethylene glycol (PEG) under vacuum for around 4 hours and at 160 °C, in the presence of acid catalyst which is para toluene sulfonic acid (PTSA). The quality and process control of this production is determination of total acid number (TAN) by the standard method ASTM D974 which is a color indicator titration. Although titration is a simple method, it is relatively time consuming and prone to human error. Besides, the solvents used in titration method, are significantly unhealthy for humans. The aim of this study is to develop fast and simple procedure for the determination of total acid number based on Fourier Transform Infrared Spectroscopy (FTIR) combined with multivariate calibration methods namely Genetic Inverse Least Squares (GILS) and Partial Least Squares (PLS). The reference total acid number of the samples collected during the esterification reaction, had been carried out by the ASTM D974 standart method and the Fourier Transform Infrared (FTIR) spectra of the same samples were also collected simultaneously with single reflection diamond Attenuated Total Reflectance (ATR) accessory. Univariate calibration was applied on a specific wavenumber corresponding to the ester peak around 1739 cm–1. Although the changes in the ester peak was showing an inrease associated to the esterification of the reactants, the results of the univariate calibration was unsucsesful. The best regression coefficient was found to be 0.997 by GILS method along with SECV and SEP as 2.295 and 2.694 mg KOH/g, respectively. The results of GILS showed that it is possible to monitor esterification process of PEG oleate.Master Thesis Development of Chemometric Calibration Toolbox and Its Application for Determination of Slep Adulteration(Izmir Institute of Technology, 2018) Akkoç, Gün Deniz; Özdemir, DurmuşA chemometric calibration toolbox, which contains Inverse Least Squares (ILS) regression, Principle Components Regression (PCR), Partial Least Squares Regression (PLSR), Genetic Inverse Least Squares (GILS) regression, and Ridge regression, was developed in MATLAB environment. During the development, multiple strategies to improve the calculation speed, namely vectorization and parallelization, were employed. Besides these programmatic strategies, efficient cross-validation (CV) procedures were implemented that are specifically tailored for parameter tuning of PCR and PLSR. For GILS, by constructing CV matrices in advance, the computational cost was further reduced. Additionally, a Graphical User Interface (GUI), which also includes baseline correction and variable range selection capabilities, was developed. For increased convenience, regardless of the chosen model, the toolbox returns a single vector of regression coefficients that accounts for centering and scaling of variables along with variable selection. Using the developed toolbox, quantitative determination of salep adulteration was carried out through chemometric calibration methods on Mid-IR data obtained from FTIRATR which is a fast and easy-to-use spectroscopic instrument. The main motivation was the lack of an established method for determination of adulteration of salep which can be quite common due to very high price of pure salep, despite the strict legal regulations. Using 365 samples covering a wide range of adulteration scenarios with 20 adulterants, calibration models were obtained and evaluated. Ensemble model, obtained by averaging GILS and Ridge, yielded the best RMSEP of 6.82 (w/w %). To cope with the unspecific adulterant problem, SIMCA was employed to provide an qualitative insight about the presence of such compounds.Master Thesis Development of Fast and Simple Analytical Methods for the Determination of Honey Adulteration and Forgery Based on Chemometric Multivariate Data Analysis by Using Molecular Spectroscopy(Izmir Institute of Technology, 2016) Başar, Başak; Özdemir, DurmuşHoney is one of the most valuable and expensive nutrition due to its health effects on human body. In recent years, honey adulteration has become an important problem and is a subject of many publications. There exists various analytical methods for determination of honey adulteration with 13C/12C isotope ratio mass spectrometry (IR-MS) being the most common. However, one of the recent studies indicates that different honey types depending on geographical and botanical origin may have significantly different 13C/12C isotope ratios rendering this method questionable. Thus, development of an analytical method for qualitative and quantitative determination of forgery and adulteration of honey without tedious and complicated sample preparation while being relatively simple and fast new analytical methods became a must. In this study, Fourier Transform Infrared spectroscopy coupled with Attenuated Total Reflectance and Fourier Transform Near Infrared spectroscopy based chemometrics multivariate calibration models were developed for the quantitative determination of honey adulteration. To simulate adulteration scenarios, artificially adulterated honey samples were prepared by adding beet sugar, corn syrup, glucose and sucrose with various concentrations to pure honey samples. Two different multivariate calibration methods namely Genetic Inverse Least Squares and Partial Least Squares were used and the applicability of these methods have been evaluated with an independent validations and test set composed of FTIR spectra of more than 100 pure honey samples along with the adulterated samples. Standard error of cross validation and standard error of prediction values for honey content of the samples were found 2.52% and 2.19% (w/w %), respectively.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, DurmuşSurface 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.