Physics and Material Science

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Browsing Physics and Material Science by Author "A.A. Saeed"

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    Half-lives of α-decay from nuclei with Z = 92 − 118 using the double folding model with relativistic NN interactions
    (2022-06-21) W.A. Yahya; I.D. Olusola; A.A. Saeed; O.K. Azeez
    The α-decay half-lives of nuclei with Z = 92 − 118 have been calculated using the WKB semi-classical approximation. The α-daughter nuclear interaction potentials are obtained from the double folding model, where the effective nucleon-nucleon (NN) interactions are obtained from relativistic mean field theory La- grangian (R3Y). In addition to using R3Y NN interactions containing only linear σ , ω, and ρ mesons (R3Y-HS), R3Y parametrizations containing non-linear terms (NL2 and NL-SH) are also employed. In fact, they are found to give better descriptions of the α-decay half-lives than R3Y-HS. Moreover, two em- pirical formulas are employed in the study. They have been included to further test the accuracy of the R3Y models.
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    Predictions of \(\alpha \)-decay Half-lives for Neutron-deficient Nuclei with the Aid of Artificial Neural Network
    (2022-03-13) A.A. Saeed; W.A. Yahya; O.K. Azeez
    In recent years, the artificial neural network (ANN) has been success- fully applied in nuclear physics and some other areas of physics. This study begins with the calculations of α-decay half-lives for some neutron- deficient nuclei using the Coulomb and proximity potential model (CPPM), temperature-dependent Coulomb and proximity potential model (CPPMT), Royer empirical formula, new Ren B (NRB) formula, and a trained artificial neural network model (T ANN ). By comparison with experimental values, the ANN model is found to give very good descriptions of the half-lives of the neutron-deficient nuclei. Moreover, CPPMT is found to perform bet- ter than CPPM, indicating the importance of employing the temperature- dependent nuclear potential. Furthermore, to predict the α-decay half-lives of unmeasured neutron-deficient nuclei, another ANN algorithm is trained to predict the Q α values. The results of the Q α predictions are compared with the Weizsäcker–Skyrme-4+RBF (WS4+RBF) formula. The half-lives of unmeasured neutron-deficient nuclei are then predicted using CPPM, CPPMT, Royer, NRB, and T ANN , with Q α values predicted by ANN as in- puts. This study concludes that half-lives of α-decay from neutron-deficient nuclei can successfully be predicted using ANN, and this can contribute to the determination of nuclei at the driplines.