Modelling defects in Ni–Al with EAM and DFT calculations

Abstract

We present detailed comparisons between the results of embedded atom model (EAM) and density functional theory (DFT) calculations on defected Ni alloy systems. We find that the EAM interatomic potentials reproduce low-temperature structural properties in both the γ and γ′ phases, and yield accurate atomic forces in bulk-like configurations even at temperatures as high as ∼1200 K. However, they fail to describe more complex chemical bonding, in configurations including defects such as vacancies or dislocations, for which we observe significant deviations between the EAM and DFT forces, suggesting that derived properties such as (free) energy barriers to vacancy migration and dislocation glide may also be inaccurate. Testing against full DFT calculations further reveals that these deviations have a local character, and are typically severe only up to the first or second neighbours of the defect. This suggests that a QM/MM approach can be used to accurately reproduce QM observables, fully exploiting the EAM potential efficiency in the MM zone. This approach could be easily extended to ternary systems for which developing a reliable and fully transferable EAM parameterisation would be extremely challenging e.g. Ni alloy model systems with a W or Re-containing QM zone.

Machine learning in materials informatics: recent applications and prospects

“…EAM tends to severely under-predict large forces while the machine learning scheme predicts forces with high fidelity (neither EAM nor the machine learning force field were explicitly trained on dislocation data). This general behavior is consistent with recent detailed comparisons of EAM with machine learning force fields [96].…”

Stratified construction of neural network based interatomic models for multicomponent materials

“…Families of bond-order potentials (BOPs), embedded-atom models (EAM), polarizable ion potentials, and Lennard-Jones potentials have been developed to treat systems with dominant covalent, metallic, ionic, and van der Waals types of interaction, respectively [13][14][15][16][17][18]. The main advantage of this approach is a relatively small number of semi-empirical fitting parameters but the rigid functional forms may in some cases fail to capture the full spectrum of many-body effects [19][20][21].…”

Dislocation core structures in Ni-based superalloys computed using a density functional theory based flexible boundary condition approach

“…The screw dislocation in Ni has been relaxed using various empirical potentials which predict a wide range of stacking fault energies and dissociation distances [11][12][13]. The planar fault energies in Ni [14,15] and Ni 3 Al [16][17][18] have been computed from first principles, with Schoeck et al [16] and Mryasov et al [17] using these energies as inputs to a Peierls-Nabarro model to compute dissociation distances in Ni 3 Al, while Yu et al [18] used the planar fault energies and isotropic elasticity theory to estimate these distances. While these computational studies have provided insights into active deformation mechanisms, they are at best approximations of the core structures, with limited utility in predicting the effects of variations in chemistry and kinetics.…”