Özdemir, Durmuş
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Özdemir, D.
Ozdemir, D.
Ozdemir, D
Özdemir, D
Ozdemir, Durmus S.
Özdemir, Durmuş Ş.
Ozdemir, Durmus
Ozdemir, D.
Ozdemir, D
Özdemir, D
Ozdemir, Durmus S.
Özdemir, Durmuş Ş.
Ozdemir, Durmus
Job Title
Email Address
durmusozdemir@iyte.edu.tr
Main Affiliation
04.01. Department of Chemistry
Status
Current Staff
ORCID ID
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WoS Researcher ID
Sustainable Development Goals
1NO POVERTY
0
Research Products
2ZERO HUNGER
1
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3GOOD HEALTH AND WELL-BEING
1
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4QUALITY EDUCATION
2
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5GENDER EQUALITY
0
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6CLEAN WATER AND SANITATION
2
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7AFFORDABLE AND CLEAN ENERGY
4
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8DECENT WORK AND ECONOMIC GROWTH
1
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9INDUSTRY, INNOVATION AND INFRASTRUCTURE
22
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10REDUCED INEQUALITIES
0
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11SUSTAINABLE CITIES AND COMMUNITIES
0
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12RESPONSIBLE CONSUMPTION AND PRODUCTION
4
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13CLIMATE ACTION
6
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14LIFE BELOW WATER
0
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15LIFE ON LAND
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16PEACE, JUSTICE AND STRONG INSTITUTIONS
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17PARTNERSHIPS FOR THE GOALS
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Documents
37
Citations
672
h-index
16
Documents
29
Citations
550
Scholarly Output
68
Articles
37
Views / Downloads
63153/28380
Supervised MSc Theses
22
Supervised PhD Theses
3
WoS Citation Count
494
Scopus Citation Count
577
Patents
1
Projects
10
WoS Citations per Publication
7.26
Scopus Citations per Publication
8.49
Open Access Source
53
Supervised Theses
25
| Journal | Count |
|---|---|
| GIDA | 3 |
| Mikrobiyoloji Bulteni | 2 |
| Light Metals 2014 | 2 |
| Rivista Italiana Delle Sostanze Grasse | 2 |
| Petroleum Science and Technology | 2 |
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68 results
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Now showing 1 - 10 of 68
Master Thesis Prediction of Extractives and Lignin Contents of Anatolian Black Pine (pinus Nigra Arnold. Var Pallasiana) and Turkish Pine (pnus Brutia Ten.) Trees Using Infrared Spectroscopy and Multivariate Calibration(Izmir Institute of Technology, 2008) Karaman, İbrahim; Özdemir, Durmuş; Özdemir, DurmuşDetermination of quality parameters such as extractives and lignin contents of wood by wet chemistry analyses takes long time. Near-infrared (NIR) and mid-infrared (MIR) spectroscopy coupled with multivariate calibration offer fast and nondestructive alternative to obtain reliable results. However, due to complexity of multi-wavelength spectra, wavelength selection is generally required. Turkish pine and Anatolian black pine are the most growing pine species in Turkey. Forest products industry has widely accepted use of these trees because of their ability to grow on a wide range of sites and their suitability to produce desirable products. Determination of extractives and lignin contents of wood provides information to tree breeders when to cut and on how much chemical is needed in pulping and bleaching process. In this study, 58 samples of Turkish pine and 51 samples of Anatolian black pine were collected to investigate the correlation between NIR and MIR spectra of these samples and their extractives and lignin contents which were determined with reference methods. Genetic inverse least squares (GILS) was used for multivariate calibration. Standard error of calibration (SEC) values were less than 1.86% (w/w) for lignin and 1.19% (w/w) for extractives whereas standard error of prediction (SEP) values were less than 3.81% (w/w) for lignin and 2.04% (w/w) for extractives. Resulting R2 values for calibrations were larger than 0.8. Classification for Turkish pine and Anatolian black pine samples was performed by genetic algorithm based principal component analysis (GAPCA) and these two pine species were classified by using NIR and MIR spectra.Article Citation - WoS: 21Citation - Scopus: 23Determination of Octane Number of Gasoline Using Near Infrared Spectroscopy and Genetic Multivariate Calibration Methods(Taylor and Francis Ltd., 2005) Özdemir, DurmuşThe feasibility of rating the octane number of gasoline using near infrared (NIR) spectroscopy and three different genetic algorithm-based multivariate calibration methods was demonstrated. The three genetic multivariate calibration methods are genetic regression (GR), genetic classical least squares (GCLS), and genetic inverse least squares (GILS). The sample data set was obtained from the ftp address (ftp://ftp.clarkson.edu/pub/hopkepk/Chemdata/) with the permission of Professor. J. H. Kalivas. This data set contains the NIR spectra of 60 gasoline samples collected using diffuse reflectance as log (I / R) with known octane numbers and covers the range from 900 to 1700 nm in 2 nm intervals. Of these 60 spectra, 20 were used as the calibration set, 20 were used as the prediction set, and 20 were reserved for the validation purposes. Several calibration models were built with the three genetic algorithm-based methods, and the results were compared with the partial least squares (PLS) prediction errors reported in the literature. Overall, the standard error of calibration (SEC), standard error of prediction (SEP), and standard error of validation (SEV) values were in the range of 0.15-0.32 (in the units of motor octane number) for the GR and GILS, which are comparable with the literature. However, GCLS produced relatively large results (0.36 for SEC, 0.39 for SEP and 0.52 for SEV) when compared with the other two methods.Article Analytical Methodology for Monitoring and Distribution Pattern Analysis of Polycyclic Aromatic Hydrocarbons in River Basins Based on Chemometrics(Wiley, 2025) Yildirim, Ebru calkan; Pelit, Fusun; Ozdemir, Durmus; Kazan, Aysegul; Tasdelen, Ozge; Baycan, NevalWith the increase in urbanization and industrialization, the environmental quality of river basins, which serve as a crucial source of irrigation for agricultural activities, has been deteriorating progressively. Thus, monitoring persistent toxic substances in urban water resources is crucial for maintaining ecological stability and protecting human health. In recent years, particular attention has been directed toward the prevention of polyaromatic hydrocarbons (PAHs), highlighting the importance of analyzing these compounds in water samples through more environmentally sustainable techniques. In this study, we report a green, rapid, cost-effective and simple dispersive liquid-liquid extraction (DLLME) method to monitor PAHs in river waters taken from 21 stations located within the geographical boundaries of the Gediz River Basin in Izmir Province, T & uuml;rkiye. Methodological parameters were optimized by chemometric techniques including Plackett-Burman (PBD) and Box-Behnken design. The method's accuracy was tested upon spiked river samples, and the recoveries ranged from 80% to 102%. The calibration curves were linear, with correlation coefficients greater than 0.98. The limit of detection values were between 0.01 and 0.05 ng mL-1. The reproducibility (RSD%) varied from 4.0% to 19%. Multivariate classification methods such as principal component analysis (PCA) and hierarchical cluster analysis (HCA), along with the supervised classification method partial least squares discriminant analysis (PLS-DA) were applied to elucidate the general distribution patterns of individual PAHs in the basin water samples. The chemometric evaluation conducted across four seasons revealed that PAH contamination was higher in the fall and winter months, resulting in a clear separation from spring and summer samples by using the first two principal components.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.Article Citation - WoS: 43Citation - Scopus: 48Determination of Honey Adulteration With Beet Sugar and Corn Syrup Using Infrared Spectroscopy and Genetic-Algorithm Multivariate Calibration(Wiley, 2018) Başar, Başak; Özdemir, DurmuşBACKGROUND Fourier transform infrared spectroscopy (FTIR) equipped with attenuated total reflectance accessory was used to determine honey adulteration. Adulterated honey samples were prepared by adding corn syrup, beet sugar and water as adulterants to the pure honey samples in various amounts. The spectra of adulterated and pure honey samples (n = 209) were recorded between 4000 and 600 cm(-1) wavenumber range. RESULTS CONCLUSION Genetic-algorithm-based inverse least squares (GILS) and partial least squares (PLS) methods were used to determine honey content and amount of adulterants. Results indicated that the multivariate calibration generated with GILS could produce successful models with standard error of cross-validation in the range 0.97-2.52%, and standard error of prediction between 0.90 and 2.19% (% w/w) for all the components contained in the adulterated samples. Similar results were obtained with PLS, generating slightly larger standard error of cross-validation and standard error of prediction values. The fact that the models were generated with several honey samples coming from various different botanical and geographical origins, quite successful results were obtained for the detection of adulterated honey samples with a simple Fourier transform infrared spectroscopy technique. Having a genetic algorithm for variable selection helped to build somewhat better models with GILS compared with PLS. (c) 2018 Society of Chemical IndustryArticle Citation - WoS: 63Citation - Scopus: 73Near Infrared Spectroscopic Determination of Olive Oil Adulteration With Sunflower and Corn Oil(Taiwan Food and Drug Administration, 2007) Özdemir, Durmuş; Öztürk, BetülDetermination of authenticity of extra virgin olive oils has become very important in recent years due to the increasing public concerns about possible adulterations with relatively cheap vegetable oils such as sunflower oil. This study was focused on the application of near infrared (NIR) spectroscopy in conjunction with multivariate calibration to identify the adulteration of olive oils. NIR transmittance measurements were made on pure olive oil and olive oil adulterated with varying concentrations (4-96%, v/v) of sunflower and corn oil in two sets of 26 binary and ternary mixtures. Multivariate calibration models were generated using genetic inverse least squares (GILS) method and used to predict the concentration of adulterants along with the concentration of olive oil in the samples. Over all, standard error of predictions ranged between 2.49 and 2.88% (v/v) for the binary mixtures of olive and sunflower oil and between 1.42 and 6.38% (v/v) for the ternary mixtures of olive, sunflower and corn oil.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.Article Fourier Dönüşümlü Kızılötesi (ft-ır) Spektroskopisi ile Malassezia Türlerinin Değerlendirilmesi(Ankara Microbiology Society, 2011) Ergin, Çağrı; Vuran, M. Emre; Gök, Yaşar; Özdemir, Durmuş; Karaarslan, Aydın; Kaleli, İlknur; Çon, Ahmet HilmiMalassezia türleri, normal deri florasının üyesi kabul edilen, cilt enfeksiyonlarına da yol açabilen lipofilik ekzobasidiyomiçet mantarlardır. Rutin mikrobiyoloji laboratuvarlarında uygulanan fenotipik karakterlere dayalı tür tanımlaması her zaman için taksonomik araştırmalarla uyumlu olmayabilmektedir. Lipofilik ve lipide bağımlı Malassezia türleri lipid ile zenginleştirilmiş besiyerlerine gereksinim gösterir. Bu nedenle, lipid bölgesine odaklanmış Fourier dönüşümlü kızılötesi (Fourier transform infrared; FT-IR) spektroskopisi, Malassezia türlerinin tanımlanmasında yardımcı olabilir. Bu çalışmada, insan patojeni olan 10 farklı türe ait standart Malassezia suşu (M.dermatis CBS 9145, M.furfur CBS 7019, M.japonica CBS 9432, M.globosa CBS 7966, M.nana CBS 9561, M.obtusa CBS 7876, M.pachydermatis CBS 1879, M.slooffiae CBS 7956, M.sympodialis CBS 7222 ve M.yamatoensis CBS 9725), modifiye Dixon agar besiyerinde standart kültürü takiben FT-IR spektroskopisi ile incelenmiştir. Çalışmamızda, tüm spektrum analizi ile iki ana grup (M1 grubu; M.globosa, M.obtusa, M.sympodialis, M.dermatis, M.pachydermatis ve M2 grubu; M.furfur, M.japonica, M.nana, M.slooffiae, M.yamatoensis) ayırımı yapılmıştır. M1 grubunda; M.obtusa’nın 1686-1606 $cm^ {-1}$, M2 grubunda M.japonicum’un 2993-2812 $cm^ {-1}$ dalga sayısı penceresinde yapılan ikinci basamak işlemlerinde, düşük düzeyde ayırım gücü ile tanımlandığı görülmüştür. Bununla birlikte, M.sympodialis, M.globosa ve M.pachydermatis ile M.furfur ve M.yamatoensis’in birbirlerinden ayırım gösterdiği bölgeler saptanamamıştır. Sonuç olarak, farklı spektral bölgelerin analiz verilerine göre; FT-IR spektroskopik analizinin, standart kültürü yapılan Malassezia türlerinin ayırımında yeterli olmadığı kanısına varılmıştır.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 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.