Master Degree / Yüksek Lisans Tezleri
Permanent URI for this collectionhttps://hdl.handle.net/11147/3008
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Master Thesis Development of Chemometric Multivariate Calibration Models for Spectroscopic Quality Analysis of Biodiesel Blends(Izmir Institute of Technology, 2011) Bağcıoğlu, Murat; Özdemir, Durmuş; Özdemir, DurmuşThe fact that the biodiesel is produced from renewable resources and environmentally friendly when compared to the fossil-based petroleum diesel, biodiesel has gained an increasing interest. It is mainly produced from a variety of different animal fat and vegetable oil combined with an alcohol in the presence of a homogeneous catalyst and the determination of the quality of the produced biodiesel is as important as its production. Industrial scale biodiesel production plants have been adopted the chromatographic analysis protocols some of which are standard reference methods proposed by official bodies of the governments and international organizations. However, analysis of multi component mixtures by chromatographic procedures can become time consuming and may require a lot of chemical consumption. For this reason, as an alternative, spectroscopic methods combined with chemometrics offer several advantages over classical chromatographic procedures in terms of time and chemical consumption. With the immense development of computer technology and reliable fast spectrometers, new chemometric methods have been developed and opened up a new era for processing of complex spectral data. In this study, laboratory scale produced biodiesel was mixed with methanol, commercial diesel and several different vegetable oils that are used to prepare biodiesels and then several different ternary mixture systems such as diesel-vegetable oil-biodiesel and methanol-vegetable oil-biodiesel were prepared and gas chromatographic analysis of these samples were performed. Then, near infrared (NIR) and mid infrared (FTIR) spectra of the same samples were collected and multivariate calibration models were constructed for each component for all the infrared spectroscopic techniques. Chemometric multivariate calibration models were proposed as genetic inverse least square (GILS) and artificial neural networks (ANN). The results indicate that determination of biodiesel blends quality with respect to chemometric modeling gives reasonable consequences when combined with infrared spectroscopic techniques.Master Thesis Spectroscopic Determination of Industrial Oil Blends Using Multivariate Calibraton(Izmir Institute of Technology, 2009) Yalçın, Ayşegül; Özdemir, DurmuşThis 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.