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    Analysis of radiation shielding, physical and optical qualities of various rare earth dopants on barium tellurite glasses: A comparative study
    (Elsevier Ltd, 2023) Boodaghi Malidarre, Roya; Akkurt, İskender; Koçar, Oğuz; Ekmekçi, İsmail
    In the present study, the barium tellurite glasses with the compositions of 60TeO2– 20ZnO– 4BaF2-(16-x) BaCO3- xREEs2O3 (Rare Earth Elements) where x = 0, 1, and 2 of Tm2O3, Er2O3, and Ho2O3 in mol% have been studied via MCNPX simulation code in terms of radiation shielding, physical, and optical qualities. Seven various glasses coded as TeZnBB, TeZnBBTm1.0 (Tm1.0), TeZnBBEr1.0 (Er1.0), TeZnBBHo1.0 (Ho1.0), TeZnBBTm2.0 (Tm2.0), TeZnBBEr2.0 (Er2.0), and TeZnBBHo2.0 (Ho2.0) in this work. The radiation shielding features have been derived using BLL. In addition, N, VM, VS, ri, rp, and F are extracted analytically. The optical properties have been obtained using Tauc’s Plot, Mott and Davis, and Lorentz –Lorentz equations. Findings show that the addition of various REEs to barium tellurite glasses improves the radiation shielding capacity of the base glass. Furthermore, the physical features of preferred glasses are enhanced remarkably and as a result, a tight glass structure is created. Moreover, M has small values near zero, showing a narrow bandgap in relevant optical glasses. Also, RLoss and ? increase which is owing to the increase in the number of Non-Bridging Oxygens and causes the locking up of the free movement of the electrons in preferred glasses.
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    Gamma-neutron shielding parameters of (S3Sb2)x(S2Ge)100_x chalcogenide glasses nanocomposite
    (Pergamon-Elsevier Science Ltd, 2023) Şengül, Aycan; Akhtar, M. Shaheer; Akkurt, İskender; Malidarre, Roya Boodaghi; Er, Zuhal; Ekmekçi, İsmail
    In the purpose of radiation shielding, (S3Sb2)x(S2Ge)100_x (x symbolscript 15, 30, 45 and 60 mol%) chalcogenide glasses were surveyed in the current study. The shielding achievements of the glass samples were investigated by using Phy-X/PSD simulation codes. This is done in terms of (LAC, mu, cm_1) for four different samples. Further, other essential parameters such as HVL, and neutron removal cross section were also calculated. These parameters were also tested with variation of SbS concentration in samples.
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    Prediction of gamma ray spectrum for 22Na source by feed forward back propagation ANN model
    (Pergamon-Elsevier Science Ltd, 2023) Teke, Çağatay; Akkurt, İskender; Arslankaya, Seher; Ekmekçi, Ismail; Günoğlu, Kadir
    The radiation has been used in a variety of different fields since its discovery and thus its measurement becomes vital in these industries. Different type detector may be used to measure gamma rays depends on the purposes of measurements. Gamma ray energy spectrum is an important to determine either elemental analysing of a sample or radiation shielding purposes. On the other hand, Artificial Neural Network (ANN) may be used to predict and analysing of gamma-ray spectrum. In this study, gamma ray spectrum from 22Na source detected in NaI (Tl) detector was estimated by ANN. There have been installed ten different ANN models to find the network structure that produces the best predictive value for the gamma ray spectrum NaI (Tl) Detector. Estimation study has been continued with the ANN model with be possessed of lowest error value. ANN model was created by using energy, distance and gamma-rays energy spectrum (called Io) values. In the ANN model developed using the feed forward back propagation algorithm, were used artificial neurons two in the input layer, ten in the hidden layer and one in the output layer. For the case of present work, the experimental data was used 70% for education, 20% for validation and 10% for testing. The estimated values obtained with the ANN model were compared with the experimental results and a good correlation has been found between them (R2 = 0.99).