Dynamic interaction between dislocations and obstacles in bcc iron based on atomic potentials derived using neural networks
H Mori, T Tsuru, M Okumura, D Matsunaka… - Physical Review …, 2023 - APS
The introduction of obstacles (eg, precipitates) for controlling dislocation motion in molecular
structures is a prevalent method for designing the mechanical strength of metals. Owing to …
structures is a prevalent method for designing the mechanical strength of metals. Owing to …
Machine learning search for stable binary Sn alloys with Na, Ca, Cu, Pd, and Ag
We present our findings of a large-scale screening for new synthesizable materials in five M–
Sn binaries, M= Na, Ca, Cu, Pd, and Ag. The focus on these systems was motivated by the …
Sn binaries, M= Na, Ca, Cu, Pd, and Ag. The focus on these systems was motivated by the …
Efficient moment tensor machine-learning interatomic potential for accurate description of defects in Ni-Al Alloys
J Wang, P Liu, H Zhu, M Liu, H Ma, Y Chen… - arXiv preprint arXiv …, 2024 - arxiv.org
Combining the efficiency of semi-empirical potentials with the accuracy of quantum
mechanical methods, machine-learning interatomic potentials (MLIPs) have significantly …
mechanical methods, machine-learning interatomic potentials (MLIPs) have significantly …
Spline-based neural network interatomic potentials: Blending classical and machine learning models
JA Vita, DR Trinkle - Computational Materials Science, 2024 - Elsevier
While machine learning (ML) interatomic potentials (IPs) are able to achieve accuracies
nearing the level of noise inherent in the first-principles data to which they are trained, it …
nearing the level of noise inherent in the first-principles data to which they are trained, it …
Diffuse scattering from dynamically compressed single-crystal zirconium following the pressure-induced phase transition
The prototypical α→ ω phase transition in zirconium is an ideal test bed for our
understanding of polymorphism under extreme loading conditions. After half a century of …
understanding of polymorphism under extreme loading conditions. After half a century of …
Material deformation mechanism of polycrystalline tin in nanometric cutting
Z Xue, M Lai, F Xu, F Fang - Journal of Manufacturing Processes, 2024 - Elsevier
The surface generation and subsurface deformation mechanisms of polycrystalline tin in
nanometric cutting are investigated using molecular dynamics. Subsurface deformations …
nanometric cutting are investigated using molecular dynamics. Subsurface deformations …
Nanometric cutting of plasma modified polycrystalline tin
Soft and low-melting-point polycrystalline tin holds considerable promise in the field of
advanced lithography. However, its machinability is significantly hindered by the grain size …
advanced lithography. However, its machinability is significantly hindered by the grain size …
Development of a multi-element neural network modified lattice inversion potential and application to the Ta-He system
Under extended radiation exposure and elevated temperatures, helium (He) accumulation
can compromise the integrity of Tantalum (Ta), a material showing substantial promise for …
can compromise the integrity of Tantalum (Ta), a material showing substantial promise for …
Neural network interatomic potential-driven analysis of phase stability in Ti–V alloys at the atomistic scale
The evolution of the ω phase in titanium–vanadium (Ti–V) alloys is critical for their
mechanical properties, particularly in aerospace and biomedical applications. This study …
mechanical properties, particularly in aerospace and biomedical applications. This study …
Strain rate-dependent tensile deformation and failure behavior in single-crystal -Sn
Given that electronic components often undergo intricate thermal and mechanical loads
during operation, comprehensively understanding lead-free solder, particularly solder based …
during operation, comprehensively understanding lead-free solder, particularly solder based …