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Toplam kayıt 31, listelenen: 1-10
Assessment of neutron and gamma-ray shielding characteristics in ternary composites: experimental analysis and Monte Carlo simulations
(Elsevier, 2024-06)
The research aims to exploring the gamma-ray shielding capacities of polyacrylonitrile/chrome-filled polymer composites through a combination of experimental, theoretical and simulation methods. Additionally, employing ...
A pilot study of ion current estimation by ANN from action potential waveforms
(Journal of Biological Physics, 2022)
Experiments using conventional experimental approaches to capture the dynamics of ion
channels are not always feasible, and even when possible and feasible, some can be timeconsuming. In this work, the ionic current–time ...
Estimations of level density parameters by using artificial neural network for phenomenological level density models
(Applied Radiation and Isotopes, 2021)
The main aim of this study is to develop accurate artificial neural network (ANN) algorithms to estimate level density parameters. An efficient Bayesian-based algorithm is presented for classification algorithms. Unknown ...
Photo-neutron cross-section calculations of 54,56Fe, 90,91,92,94Zr, 93Nb and 107Ag isotopes with newly obtained giant dipole resonance parameters
(Applied Radiation and Isotopes, 2020)
The knowledge of the interaction of photons with matter is of vital importance to investigate fundamental nu- clear physics problems. Giant dipole resonance (GDR) mechanism is dominant up to 30 MeV at photo-absorption ...
Influence of Nd2O3 on radiation shielding and elastic properties of TeO2–MgO–Na2O glasses: a simulation study by PHITS and MCNP
(2023)
This study investigates the elastic properties and the photon and neutron shielding properties of TeO2–MgO–Na2O–Nd2O3 glasses, as well as the mass stopping power and projected range of alpha and proton charged particles ...
Estimations of giant dipole resonance parameters using artificial neural network
(Applied Radiation and Isotopes, 2021)
In this study; Giant Dipole Resonance (GDR) parameters of the spherical nucleus have been estimated by using artificial neural network (ANN) algorithms. The ANN training has been carried out with the Levenberg–Marquardt ...
Mass excess estimations using artificial neural networks
(Applied Radiation and Isotopes, 2022)
Mass excess knowledge is important to investigate the fundamental properties of atomic nuclei. It is a meaningful and important parameter for the determinations of nucleon binding energy, nuclear reaction Q value, energy ...
Estimations for (n,a) reaction cross sections at around 14.5MeV using Levenberg-Marquardt algorithm-based artificial neural network
(Elsevier, 2023)
Prediction of neutron-induced reaction cross-sections at around the 14.5 MeV neutron energy is crucial to calculate nuclear transmutation rates, nuclear heating, and radiation damage from gas formation in fusion reactor ...
Production cross-section and reaction yield calculations for 123-126I isotopes on 123Sb(α,xn) reactions
(Kuwait Journal of Science, 2021)
Most of the radioisotopes used in the medical fields, like examination and treatment studies, were produced by employing nuclear reactions. Within the process of a nuclear reaction, one of the most important parameters is ...
Investigation of the effects of different composite materials on neutron contamination caused by medical LINAC
(Kerntechnik, 2020)
In a medical linear accelerator, the primary and secondary collimators are generally made of high atomic weight metals. The energy of the x-rays generated by accelerated electrons exceeds the bonding energies of high atomic ...