Master Degree / Yüksek Lisans Tezleri

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Access Right: Open AccessSubject: search.filters.subject.Fourier transform spectroscopy

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  • Master Thesis
    Structural Investigation of Isopropanol and Alkaline Ph-Induced Trypsin Gel and Thin Flim and Its Biotechnological Applications
    (Izmir Institute of Technology, 2011) Karaçiçek, Bilge; Ceylan, Çağatay
    Trypsin is a biologically and industrially important member of serine protease family. Gelation forms a three dimensional network structure through the interaction of protein molecules among themselves and also with the environment. The aim of the study was the investigation of structural and the functional properties of bovine pancreatic trypsin after gelation and aggregation processes. The phase behaviour of trypsin was determined for different protein concentration, NaOH concentration and CaCl2 concentrations. In addition, the effect of sucrose addition to gelation time was observed. Increasing protein concentrations caused a decrease in gelation time. Increasing NaOH concentrations resulted in a decrease in gelation time. In low CaCl2 concentrations gelation was observed but in high CaCl2 concentrations aggregation was observed. The gels were resolubilized in water. Trypsin stability studies showed that there was a nearly 50% specific activity loss after the gelation process. According to FTIR studies β–sheet structure in 1637 cm-1 band disappeared in trypsin gel and trypsin aggregates. Increases in α–helix structure in 1651 cm-1 in trypsin gel with sucrose and aggregate with and without sucrose were observed. Iodoacetamide was shown to delay in gelation indicating the importance of intermolecular disulfides in the gelation process. The QCM studies showed that the film formed after gelation had absorbtion ability to different gases (benzene, carbon monoxide, carbon dioxide, dichloromethane, hydrogen peroxide and propanol) and can be used for gas sensing purposes. GI-XRD studies showed that trypsin thin film did not contain any crystalline structures.
  • 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, Durmuş
    The 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.