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Theoretical investigation of nonlinear optical properties of Mathieu quantum well
(Springer Berlin Heidelberg, 2023/1/20)
In this study, for the first time, the effect of externally applied static electric, magnetic, and non-resonant THz intense laser fields on nonlinear optical properties such as the total optical absorption coefficients ...
Effects of rare earth element Gd on microstructure, thermodynamic parameters, mechanical, and shape recovery properties of CuAlTa alloys
(Springer International Publishing, 2023/11)
The microstructure, thermodynamic parameters, mechanical properties, and shape recovery properties of alloys consisting of Cu83.5−xAl13.5Ta3Gdx (x=0,0.5,1 mass%) alloy were investigated. Results showed that the addition ...
Effects of the confinement potential parameters and optical intensity on the linear and nonlinear optical properties of spherical quantum dots
(Elsevier, 01.01.2023)
We study the linear and nonlinear optical properties of a spherical GaAs quantum dot with screened modified Kratzer potential (SMKP) by solving the time-independent Schrödinger wave equation using the diagonalization method. ...
Performance of machine learning algorithms on neutron activations for Germanium isotopes
(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 ...
Neutron Single-Particle States in 101Sn by Polynomial Fits and Shell Model Calculations for Light Sn Isotopes
(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, ...
Estimation of fission barrier heights for even–even superheavy nuclei using machine learning approaches
(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 ...
Predicting -decay energy with machine learning
(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 ...
Estimation of the S34 (0) S-factor for 3He (α, γ) 7Be reaction by using distorted wave born approximation and artificial neural network
(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 ...
Applications of different machine learning methods on nuclear charge radius estimations
(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, ...
The second, third harmonic generations and nonlinear optical rectification of the Mathieu quantum dot with the external electric, magnetic and laser field
(16.06.2023)
In this study, the nonlinear optical properties of the In𝑥��Ga1−𝑥��As/GaAs Mathieu quantum dot (MQD) are
investigated for the first time, focusing on the nonlinear optical rectification (NOR), second harmonic
generation ...