Phys Chem Chem Phys
August 2022
The state-of-the-art method generating potential functions used in molecular dynamics is based on machine learning with neural networks, which is critical for molecular dynamics simulation. This method provides an efficient way for fitting multi-variable nonlinear functions, attracting extensive attention in recent years. Generally, the quality of potentials fitted by neural networks is heavily affected by training datasets and the training process and could be ensured by comprehensively verificating the model accuracy.
View Article and Find Full Text PDFTitanium beryllide, BeTi, has been proposed as a prospective neutron multiplier in fusion reactors. First-principles calculations have been performed to investigate the nucleation mechanism of a He bubble in bulk BeTi. Meanwhile, the influence of the presence of H atoms on the nucleation of the He bubble, , the synergistic effect of He and H atoms, has also been investigated.
View Article and Find Full Text PDFFirst-principles calculations have been performed to investigate the interaction between solute impurity O and H/He/vacancy irradiation defects in Ti3AlC2. The formation energy and occupation of O atoms within different defects as well as the trapping progress of O/H clusters are discussed. It is found that the O atom preferentially occupies the hexahedral interstitial site (Ihex-1) in bulk Ti3AlC2, whereas it prefers to occupy the neighbouring tetrahedral interstitial site (Itetr-2) within pre-exisiting Al monovacancy (VAl), Al divacancy (2VAl-Al) and the 2VAl-C divacancy composed of Al and C vacancies.
View Article and Find Full Text PDFFirst-principles calculations have been conducted to investigate the interaction between vacancy defects and H/He impurity in Ti3AlC2. The formation energies of monovacancy and divacancy have been calculated. It is found that Al monovacancy (VAl), Al divacancy (2VAl-Al), and the divacancy composed of Al and C atoms (2VAl-C) are most easily formed in all vacancies.
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