Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

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

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  • Book Part
    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
    (Wiley Blackwell, 2014) Uçar,Ö.I.; Altuner,H.M.; Günyüz,M.; Dündar,M.M.; Özdemir,D.
    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 infrared spectroscopy with grazing angle spectra collection accessories can be used for nondestructive analysis of these contaminants. © 2014 The Minerals, Metals & Materials Society.
  • 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: 5
    Citation - Scopus: 4
    Uv-Visible Spectrophotometric Quantitative Analysis of Ternary Mixture Using Multivariate Calibration Methods Optimized by a Genetic Algorithm
    (Syscom 18 SRL, 2010) Özdemir, Durmuş; Dinç, Erdal; Baleanu, Dimutru
    Simultaneous determination of ternary mixtures of caffeine, paracetamol and metamizol in commercial tablet formulations using UV-visible spectrophotometry combined with classical least squares (CLS) and genetic algorithm (GA) based multivariate calibration methods were demonstrated. The three genetic multivariate calibration methods are named as Genetic Classical Least Squares (GCLS), Genetic Inverse Least Squares (GILS) and Genetic Regression (GR). The GR method is based on a genetic algorithm based wavelength selection followed by a simple linear regression step whereas the GCLS and GILS are multivariate calibration methods modified by a wavelength selection principle using a genetic algorithm. The sample data set contains the UV-visible spectra of 47 synthetic mixtueres (4 to 48 μg/mL) and 16 tablets containing these components from two different producers. The spectra cover the range from 200 to 330 nm in 0.1 nm intervals. Several calibration models were built with the four methods for the three components. Overall, the standard error of calibration (SEC) and the standard error of prediction (SEP) for the synthetic data were in the range of 0.04 and 2.34 μg/mL for all the four methods. Predictive ability of the calibration models generated with synthetic samples was tested with actual tablet samples and results obtained from four methods were compared. The SEP values for the tablets were in the range of 0.31 and 15.44 mg/tablets.