Özbayoğlu, Gülhan

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Citation - WoS: 7
Citation - Scopus: 7
Synthesis, Characterizations and Investigation of Thermoluminescence Properties of Strontium Pyrophosphate Doped With Metals
(Pergamon-elsevier Science Ltd, 2014) Ilkay, L. S.; Ozbayoglu, G.; Yilmaz, A.
Strontium pyrophosphate, Sr2P2O7, was synthesized by solid-state synthesis method; the product was co-doped with copper-silver (Cu-Ag), copper-indium (Cu-In) and manganese-praseodymium (Mn-Pr) oxides (CuO, MnO, In2O3, Pr6O11 and AgNO3) by solid-state reaction method. The variation of dopant concentrations was investigated from 0.5 to 15% by weight. In addition to these processes, chemical characterizations of samples and the investigation of thermoluminescence (TLD) properties of strontium pyrophosphate with and without dopants were conducted. For the characterization; powder X-ray Diffraction (XRD) were implemented for phase purity of samples. Fourier Transform Infrared Spectroscopy (FTIR) was used to determine whether the bond structures were affected from the doping or not. Thermoluminescence (TLD) analyses were conducted on strontium pyrophosphate doped with different amounts of dopants for the first time. Glow curves showed that intensities were affected by different amounts of dopants. It can be concluded from that strontium pyrophosphate doped with 7% MnO and 1% Pr6O11 had the most powerful peak intensity around 160 degrees C and dosimetric property for promising application. (C) 2014 Elsevier Ltd. All rights reserved.
Citation - Scopus: 2
Comparison of Gross Calorific Value Estimation of Turkish Coals Using Regression and Neural Networks Techniques
(2012) Ozbayoglu,A.M.; Ozbayoglu,M.E.; Ozbayoglu,G.
Gross calorific value (GCV) of coals was estimated using artificial neural networks, linear and non-linear regression techniques. Proximate and ultimate analysis results were collected for 187 different coal samples. Different input data sets were compared, such as both proximate and ultimate analysis data, and only proximate analysis data and only ultimate analysis data. It was observed that the best results were obtained when both proximate analysis and ultimate analysis results were used for estimating the gross calorific value. When the performance of artificial neural networks and regression analysis techniques were compared, it was observed that both artificial neural networks and regression techniques were promisingly accurate in estimating gross calorific values. In general, most of the models estimated the gross calorific value within ±3% of the expected value.
Maghemite - a Source of Heavy Medium for Coal Washeries
(2010) Arol,A.; Ozbayoglu,G.; Anaç,S.; Bulut,M.
Use of magnetite as heavy medium in coal preparation plants has been increasing steadily in recent years. It might be in short supply in some areas or excessively costly in certain times. In Turkey, the cost of heavy medium magnetite has almost tripled since 2003. As a result, alternative sources of heavy medium material have been evaluated. A maghemite ore from Elbistan-Kahramanmaras was found to be an interesting source. Tests showed that the maghemite ore can be enriched via magnetic separation at 1556 gauss to obtain a heavy medium material with 4.93 g/cm3 density and 97.22 per cent magnetic recovery. Further tests were conducted to determine the optimum fi eld strength for magnetic separation, friability and regeneration recovery.

Journal	Count
Physicochemical Problems of Mineral Processing	3
26th International Mineral Processing Congress, IMPC 2012: Innovative Processing for Sustainable Growth - Conference Proceedings -- 26th International Mineral Processing Congress, IMPC 2012: Innovative Processing for Sustainable Growth -- 24 September 2012 through 28 September 2012 -- New Delhi -- 97654	1
International Journal of Coal Preparation and Utilization	1
Journal of Alloys and Compounds	1
Journal of Rare Earths	1

Özbayoğlu, Gülhan

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