Revealing atomic-scale distributions of energy and stress in defective or complex systems, based on the behavior of electrons, should contribute much to materials science and engineering, while only few practical ab initio methods were developed for this purpose. Thus, we developed computational techniques of local-energy and local-stress calculations within the plane-wave PAW (projector augmented wave)-GGA (generalized gradient approximation) framework. This is natural extension of ab initio energy-density and stress-density schemes, while the inherent gauge dependency is removed by integrating these densities in each local region where the contained gauge-dependent terms are integrated to be zero. In this overview, we explain our scheme with some details and discuss the concepts or physical meanings of local energy and local stress via the comparison with related schemes using similar densities, LCAO (linear combination of atomic orbitals) methods, Green's function formulation implemented by multiple scattering or TB (tight-binding) methods, or EAM (embedded-atom method) potentials. We present recent applications to metallic surfaces, grain boundaries (GBs) with and without solute segregation, tensile tests of metallic GBs, local elastic constants of microstructures in alloys, and machine-learning based GB-energy prediction, where the local-energy and local-stress analyses provide novel aspects of phenomena, deep insights into the mechanism, and effective data for novel machine-learning based modelling. We discuss unsettled issues and future applications, especially for large-scale metallic systems.
We use ab initio local stress calculations to investigate layer-by-layer ab initio stress inside late transition metal (111) surfaces, focusing on the origin of stress on the surface top layer. It is found that the band shift on each surface layer is strongly correlated with the in-plane stress. For the top layer, this correlation can be explained by the Friedel model. The reduction of the local d-band width due to the coordination reduction is the main origin of both the d-band center shift and in-plane tensile stress. The changes in the directional d-d bonding character analyzed by the in-plane and out-of-plane projected densities of states should be an additional origin of the excess tensile stress, except for Ag explained mainly by the Friedel model.
Surface nanostructured S45C, Si+B added S45C (S45C(Si+B)) and SCM440H steels were prepared by surface nanostructured wearing (SNW) and subsequent induction heating and quenching (IHQ). The Vickers hardness values at the top surface of these steels were around Hv 8.5 GPa, and also the thicknesses of quenched surface layer (Hv 7 GPa) were around 800 μm. The rolling contact fatigue lives of these steels in a roller pitting test were longer than those of the S45C, S45C(Si+B) and SCM440H steels without the surface nanostructure prepared by only IHQ. This is because the degree of the softening during the roller pitting test was smaller in the SNW&IHQed steels comparison with the only IHQed steels.
High-entropy alloys (HEAs) have received attention because of their excellent mechanical and thermodynamic properties. A recent study revealed that Co-free face-centered cubic HEAs could improve strength and ductility, which is crucial for nuclear materials. Here we implemented first-principles calculations to explore the fundamental mechanism for enhancing the mechanical properties in Co-free Cr25Fe25Ni25Mn25 alloy. We found that the local lattice distortion of Co-free HEA was more significant than that of the well-known Cantor alloy. Furthermore, the short-range order formation in Co-free HEA caused the highly fluctuated stacking fault energy. Thus, the significant local lattice distortion and the non-uniform solid solution states comprising low- and high-stacking fault regions improve strength and ductility.
A dynamic behavior analysis on CFRP-made jet-engine fan blade has been performed by using K-computer. The simulation aimed to model a bird strike event by using an SPH-FEM weak-coupling analysis, where a single finite element is assigned to each unidirectional CFRP prepreg layer in the thickness direction of the fan blade. As a fundamental study, we performed an impact analysis with about 3.5 million elements using 8192 cores. The massively parallel simulation realized a dynamic behavior analysis of the full-scale fan blade model under impact loading.
We present new algorithm for density functional theory to avoid charge sloshing problems. In metallic electron structure calculation of large scale, such as Si-Al or Ga-As interface, the numerical instability called charge sloshing occurs during the self-consistent iterations due to its strong coupling between Poisson and Kohn-Sham equations. In traditional algorithm two equations are solved succesively, and potentials or electron densities obtained from present and previous iterations were mixed in some procedure using appropriate parameters for each system. This procedure, however, is not so efficient for the large electron structure calculations which require computational time of 2-3 monthes until the calculation is done. So we proposed a strong coupled formalism of two equation based on the mixed variational principle. In our algorithm Poisson equation and Kohn-Sham equation are solved simultaneously without any parameters.
This study integrates machine-learning potentials (MLP) into crack propagation simulations, comparing the obtained atomic structural changes and stress distribution in four crack systems with the ones by embedded-atom-method (EAM) and modified-EAM (MEAM) potentials. The MLP predicts stress concentration at crack tips, with increased load leading to bond breakage and cleavage, implying brittle fracture. In contrast, EAM and MEAM suggest ductile failure, with observed dislocation ejection and gradual crack opening due to structural changes. Overall, MLP exhibits a distinct fracture tendency compared to conventional potentials.
