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The nuclear level densities and level-density parameters in fissioning nuclei at their saddle points of fission barriers - $a_{f}$, as well as those for neutron - $a_{n}$, proton - $a_{p}$ , and $\alpha$-particle - $a_{\alpha}$ emission…
Random sequential adsorption algorithm is a popular tool for modelling structure of monolayers built in irreversible adsorption experiments. However, this algorithm becomes very inefficient when the density of molecules in a layer rises.…
Significant progress has been made for assessing the influence of porosity on the performance metrics for cast components through various modeling techniques. However, a computationally efficient framework to account for porosity with…
While traditional trial-and-error methods for designing amorphous alloys are costly and inefficient, machine learning approaches based solely on composition lack critical atomic structural information. Machine learning interatomic…
We analyze the prospect of measuring the neutron form factor of a nucleus through the detection of neutrino-nucleus coherent elastic scattering. We predict numbers of events in a liquid noble nuclear recoil detector at a stopped pion…
Radii of charge and neutron distributions are fundamental nuclear properties. They depend on both nuclear interaction parameters related to the equation of state of infinite nuclear matter and on quantal shell effects, which are strongly…
Symmetry energy for asymmetric nuclear matter at subsaturation densitieswas investigated in the framework of an isospin-dependent quantum molecular dynamics model.Asingle ratio of neutrons and protons is comparedwith the experimental data…
Background: Understanding nuclear shape is a crucial problem in nuclear physics. In particular, determining the sign of quadrupole deformation, i.e., whether prolate or oblate, remains a challenging problem. Purpose: Our aim is to propose a…
We identify a new, flux-dependent correction to the antineutrino spectrum as produced in nuclear reactors. The abundance of certain nuclides, whose decay chains produce antineutrinos above the threshold for inverse beta decay, has a…
Predicting the dramatic changes in material properties caused by irradiation damage is key for the design of future nuclear fission and fusion reactors. Self-ion implantation is an attractive tool for mimicking the effects of neutron…
Any discovery of `new physics' in the neutrino sector first requires a precise prediction of the expected Standard Model cross section. Currently, Coherent Elastic neutrino-Nucleus Scattering (CEvNS) experiments are statistics limited.…
Accurately predicting infrared (IR) spectra in computational chemistry using ab initio methods remains a challenge. Current approaches often rely on an empirical approach or on tedious anharmonic calculations, mainly adapted to semi-rigid…
As photon counting detectors are being explored for medical and industrial imaging applications, there is a critical need to understand spectral characteristics of scattered x-ray photons. Scattered radiation is detrimental to x-ray imaging…
Short range particle repulsion is rather important property of the hadronic and nuclear matter equations of state. We present a novel equation of state which is based on the virial expansion for the multicomponent mixtures with hard-core…
Calculating microscopic optical potentials for elastic nucleon-nucleus scattering has already led to large body of work in the past. For folding first-order calculations the nucleon-nucleon (NN) interaction and the one-body density of the…
We study theoretically how we can determine the neutron density distributions of unstable nuclei from proton elastic scattering. We apply the relativistic impulse model to study the sensitivities of the observables to the density…
A computational method based on a first-principles multiscale simulation has been used for calculating the optical response and the ablation threshold of an optical material irradiated with an ultrashort intense laser pulse. The method…
We propose a mathematical model for estimating biological damage caused by low-dose irradiation. We understand that the Linear Non Threshold (LNT) hypothesis is realized only in the case of no recovery effects. In order to treat the…
Predictions of nuclear properties far from measured data are inherently imprecise because of uncertainties in our knowledge of nuclear forces and in our treatment of quantum many-body effects in strongly-interacting systems. While the model…
Through ensemble learning with multitasking and complex connection neural networks, we aggregated nuclear properties, including ground state charge radii, binding energies, and single-particle state information obtained from the Kohn-Sham…