Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/11147/7148

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Author: search.filters.author.İnanç Uçar, ÖzlemHas files: Yes

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  • Conference Object
    Citation - WoS: 2
    Citation - Scopus: 1
    Determination of Aluminum Oxide Thickness on the Annealed Surface of 8000 Series Aluminum Foil by Fourier Transform Infrared Spectroscopy
    (Springer, 2017) İnanç Uçar, Özlem; Ekin Meşe, Ayten; Birbaşar, Onur; Dündar, Murat; Özdemir, Durmuş
    Aluminum foil produced with prescribed thermomechanical processing route develop oxide film. Alloy chemistry and annealing practices, particularly its duration and exposed temperature, determine the characteristics of the oxide film. The magnitude and characteristics of the oxide film may impair surface features leading to serious problems in some applications, such as coating, printing and in some severe cases failure in formability. Therefore, it is important for the rolling industry to be able to monitor the oxide formation on the foil products and quantify its thickness. Well known methods to measure an oxide thickness that is in the order of nanometer, require meticulous sample preparation techniques, long duration for measurements and sophisticated equipment. However, in this study, a simple and rapid grazing angle attenuated total reflectance infrared (GA-ATR-FTIR) spectroscopic method combined with chemometrics multivariate calibration has been developed for the oxide thickness determination which is validated with x-ray photoelectron spectroscopy (XPS). 3000 and 8000 series aluminum foil materials which were produced by twin roll casting technique were used in this study. Foil samples were annealed at various different temperatures and annealing times in a laboratory scale furnace. Immediately after collecting GA-ATR-FTIR spectra, the 3000 series alloy samples were sent to a laboratory where XPS reference oxide thickness measurements had been performed. Partial Least Squares (PLS) method was used to develop a multivariate calibration model based on FTIR spectra and XPS reference oxide thickness values in order to predict the aluminum oxide thickness. The correlation coefficient of XPS reference oxide thickness values versus grazing angle ATR-FTIR based PLS predicted values was found as 0.9903 the standard error of cross validation (SECV) was found to be 0.29 nm in range of 4.9–14.0 nm for Al2O3. In addition, the standard error of prediction (SEP) for the validation set was 0.24 nm with the model generated with three principal components (PCs). © The Minerals, Metals & Materials Society 2017.
  • Conference Object
    Determination of Aluminum Rolling Oil and Machinery Oil Residues on Finished Aluminum Sheet and Foil Using Elemental Analysis and Fourier Transform Infrared Spectroscopy Coupled With Multivariate Calibration
    (John Wiley and Sons Inc., 2014) İnanç Uçar, Özlem; Mollaoğlu Altuner, Hatice; Günyüz, Mert; Dündar, Mustafa Murat; Özdemir, Durmuş
    The surface characteristics of rolled aluminum products such as sheets and foils are strongly affected by the particular rolling process and the type of aluminum rolling oil compositions. After the rolling process, coiled aluminum sheets and foils undergoes annealing to form desired crystal structure and remove the rolling oil residues. Depending on the time and the temperature that rolled aluminum exposed for annealing, rolling oil residues are mostly removed from the coiled aluminum products but if there is any contamination in rolling oil due to hydraulic and gearing parts of the rolling systems these heavier oils are not easily evaporates from the aluminum surfaces especially inner parts of the coiled aluminum sheets and foils. These rolling oil contaminants create serious problems for the some specific applications of these aluminum products in certain industries such as automotive and coating as remaining thin oil layer prevents proper painting and coating. Therefore, it is very crucial for the rolling industry to be able to monitor the heavy oil contamination on the rolled products and determine the source of these contaminants .In this study, it was aimed to develop a nondestructive infrared spectroscopic method combined with chemometric multivariate calibration techniques for the quantitative determination of rolling oil residues and contaminants on the rolled aluminum products. To be able to generate multivariate calibration methods, an industrial elemental analysis system was adopted for the quantitative determination of heavy oil contaminants on the rolled aluminum products and these were used as reference values for infrared analysis of the same samples. In addition, apart from conventional use of elemental analysis systems for the total organic analysis, the raw data (raw chromatogram) obtained from elemental analysis was used to directly generate multivariate calibration models for each contaminant by using synthetically contaminated surfaces as the calibration samples. The results promised that elemental analysis can be used not just for the total organic content but also specifically to determine amount of each contaminant on the aluminum surfaces, it is also, expected that infrared spectroscopy with grazing angle spectra collection accessories can be used for nondestructive analysis of these contaminants.s.
  • Article
    Citation - WoS: 4
    Citation - Scopus: 7
    Determination of Aluminum Rolling Oil Additives and Contaminants Using Infrared Spectroscopy Coupled With Genetic Algorithm Based Multivariate Calibration
    (Elsevier Ltd., 2010) Yalçın, Ayşegül; Ergün, Didem; İnanç Uçar, Özlem; Özdemir, Durmuş
    Genetic algorithm based multivariate calibration models were generated for infrared spectroscopic determination of aluminum rolling oil additives and contaminants such as gear and hydraulic oils. Two different additives and six different suspected contaminants were investigated in the base oil lubricant. Routine analysis samples from 9 different aluminum rolling systems were collected in a period of 2 months in an aluminum rolling plant and gas chromatography (GC) is used as the reference method. Infrared absorbance spectra of the samples were then collected and the reference values obtained with GC were used together with these spectra for model building. Inverse least squares method was optimized with a genetic algorithm by selecting the most contributing regions of the infrared spectra for each component. The R2 values between GC and multivariate spectroscopic determinations were around 0.99 indicating a good correlation between the two methods. Performance of genetic algorithm based multivariate calibration models were also compared with partial least squares (PLS) method. The study showed that infrared spectroscopy coupled with multivariate calibration can be used for continuous monitoring of additives and contaminants in aluminum rolling oil. By this way, analysis time is significantly reduced and simultaneous determination of all the components can be accomplished. © 2010 Elsevier B.V. All rights reserved.