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Pure Magnesium DFT calculations for interatomic potential fitting
This dataset provides DFT (density functional theory as implemented in VASP, Vienna Ab Initio Simulation Package) calculations for pure Magnesium. It was designed by Binglun... -
Machine learning potential for the Cu-W system
Combining the excellent thermal and electrical properties of Cu with the high abrasion resistance and thermal stability of W, Cu-W nanoparticle-reinforced metal matrix... -
Machine learning for metallurgy: a neural network potential for Al-Mg-Si
High-strength metal alloys achieve their performance via careful control of the nucleation, growth, and kinetics of precipitation. Alloy mechanical properties are then... -
Machine learning for metallurgy: a neural network potential for Al-Cu
High-strength metal alloys achieve their performance via careful control of precipitates and solutes. The nucleation, growth, and kinetics of precipitation, and the resulting... -
Machine learning for metallurgy: a neural network potential for Al-Cu
High-strength metal alloys achieve their performance via careful control of precipitates and solutes. The nucleation, growth, and kinetics of precipitation, and the resulting... -
Machine learning for metallurgy: a neural network potential for Al-Cu
High-strength metal alloys achieve their performance via careful control of precipitates and solutes. The nucleation, growth, and kinetics of precipitation, and the resulting... -
Machine learning for metallurgy V: A neural-network potential for zirconium d...
The mechanical performance—including deformation, fracture, and radiation damage—of zirconium is determined at the atomic scale. With Zr and its alloys extensively used in the... -
Stress-dependence of generalized stacking fault energies: a DFT study
Generalized stacking fault energy (GSFE) is a crucial material property for describing nanoscale plasticity in crystalline materials, such as dislocation dissociation,... -
Neural network potential for Zr-H
The introduction of Hydrogen (H) into Zirconium (Zr) influences many mechanical properties, especially due to low H solubility and easy formation of Zirconium hydride phases.... -
Origin of high strength in the CoCrFeNiPd high-entropy alloy
Recent experiments show that the CoCrFeNiPd high-entropy alloy (HEA) is significantly stronger than CoCrFeNi and with nanoscale composition fluctuations beyond those expected... -
Vanadium is an optimal element for strengthening in both fcc and bcc high-ent...
The element Vanadium (V) appears unique among alloying elements for providing high strengthening in both the fcc Co-Cr-Fe-Mn-Ni-V and bcc Cr-Mo-Nb-Ta-V-W-Hf-Ti-Zr high-entropy...
