In this paper, calculations of the (n,t) reaction cross-sections at 14.5 MeV have been presented by utilizing artificial neural network algorithms (ANNs). The systematics are based on the account for the non-equilibrium ...

Copper (Cu), which is produced in cyclotrons or reactors, is a significant tracer in the human body. Bayesian regularized artificial neural networks (ANNs) algorithm, which is one of the ANN approaches, was used in analyzing ...

Photo-nuclear interactions are important for investigating fundamental nuclear physics phenomena. The photo-absorption cross-section energy curve displays a wide resonance called giant dipole resonance (GDR) until 30 MeV. ...

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 ...

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 ...

Since it was reported that several radioisotopes might be advantageous for different medical uses in diagnostics and therapeutics, they have gained significance. Theoretical and experimental researches on such radioisotopes ...

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 ...

This study is concerned with the calculations of double differential neutron cross-sections of the structural fusion materials of 56Fe and 90Zr isotopes that are bombarded with protons. Calculations were performed using ...

The aim of this study is to develop an accurate artificial neural network algorithm for the cross-section of (n,p) reactions at 14.5 ∓0.5 MeV neutron energy which is important to developing materials for fusion reactor ...