Browsing Fizik Bölümü Makale Koleksiyonu by Author "f11f7037-b475-46b6-8749-d84e30352463"
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Applications of different machine learning methods on nuclear charge radius estimations
Serkan Akkoyun (2023/11/21)Theoretical models come into play when the radius of nuclear charge, one of the most fundamental properties of atomic nuclei, cannot be measured using different experimental techniques. As an alternative to these models, ... -
Artificial-intelligence-supported shell-model calculations for light Sn isotopes
Serkan Akkoyun; Abderrahmane Yakhelef (American Physical Society, 11/04/2022)The region around the doubly magic nuclide 100 Sn is very interesting for nuclear physics studies in terms of structure, reaction, and nuclear astrophysics. The main ingredients in nuclear structure studies using the ... -
Energy transitions and half-life determinations of Sc isotopes from photonuclear reaction on Ti target
Gökhan Koçak; Serkan Akkoyun; İsmail Boztosun; Haris Dopo (World Scientific Publishing Company, 07/03/2022)For the activation of the target nucleus, bremsstrahlung photons generated in a medical linear accelerator can be used. Due to particle separation energy limitations for low photon energies in the giant resonance region ... -
Estimation of fission barrier heights for even–even superheavy nuclei using machine learning approaches
Serkan Akkoyun (2023/3/21)With the fission barrier height information, the survival probabilities of super- heavy nuclei can also be reached. Therefore, it is important to have accurate knowledge of fission barriers, for example, the discovery ... -
Estimation of the S34 (0) S-factor for 3He (α, γ) 7Be reaction by using distorted wave born approximation and artificial neural network
Serkan Akkoyun (2023/9/6)The astrophysical S-factor and total cross-section of radiative capture reaction are analyzed using the first-order distorted wave born approximation and artificial neural network. To make estimations of S 34 (0) at ... -
MODELING OF PATELLA HEIGHT WITH DISTAL FEMUR AND PROXIMAL TIBIA REFERENCE POINTS WITH ARTIFICIAL NEURAL NETWORK
İlhan Otağ; Kaan Çimen; Yunus Torun; Özhan Pazarcı; Serkan Akkoyun; Aynur Otağ; Mehmet Çimen (25/03/2022)The patellofemoral joint is one of the parts of the knee extension mechanism that plays a role in the stability of the knee by enlarging the force arm of the quadriceps muscle and changing the direction of the muscle ... -
Neural network estimations of annealed and non-annealed Schottky diode characteristics at wide temperatures range
Hülya Doğan; Songül Duman; Yunis Torun; Serkan Akkoyun; Seydi Doğan; Uğur Atici (Elsevier, 15/06/2022)In this study, Artificial Neural Network (ANN) model has been proposed to characterize the annealed and the non-annealed Schottky diode from experimental data. The experimental current values of Ni/n-type 6H–SiC Schottky ... -
Neural network predictions of (n, 2n) reaction cross-sections at 14.6 MeV incident neutron energy
Serkan Akkoyun (2023/1/1)In this study, we have estimated the (n,2n) reaction cross-section for 14.6 MeV incident neutron energy by using the artificial neural network (ANN) method. We have also predicted the reaction cross-sections whose experimental ... -
Neutron Single-Particle States in 101Sn by Polynomial Fits and Shell Model Calculations for Light Sn Isotopes
Serkan Akkoyun (2024/2)The neutron single-particle energies (SPEs) in 101Sn are one of the main ingredients needed in nuclear studies in the region around the doubly magic 100Sn nucleus. Due to the lack of experimental data on 101Sn spectrum, ... -
Performance of machine learning algorithms on neutron activations for Germanium isotopes
Serkan Akkoyun (2023/7/1)In the studies of nuclear physics, one of the important parameters for nuclear reactions is the reaction cross-section. It can be obtained from experimental data or by different theoretical models. In this study, we implement ... -
Predicting -decay energy with machine learning
Serkan Akkoyun (2023/3/15)Q β represents one of the most important factors characterizing unstable nuclei, as it can lead to a better understanding of nuclei behavior and the origin of heavy atoms. Recently, machine learning methods have been shown ...