Atomic-scale simulations in multi-component alloys and compounds: a review on advances in interatomic potential
F Wang, HH Wu, L Dong, G Pan, X Zhou… - Journal of Materials …, 2023 - Elsevier
Multi-component alloys have demonstrated excellent performance in various applications,
but the vast range of possible compositions and microstructures makes it challenging to …
but the vast range of possible compositions and microstructures makes it challenging to …
High-accuracy thermodynamic properties to the melting point from ab initio calculations aided by machine-learning potentials
Accurate prediction of thermodynamic properties requires an extremely accurate
representation of the free-energy surface. Requirements are twofold—first, the inclusion of …
representation of the free-energy surface. Requirements are twofold—first, the inclusion of …
[HTML][HTML] Data science and material informatics in physical metallurgy and material science: An overview of milestones and limitations
Data science and material informatics are gaining traction in alloy design. This is due to
increasing infrastructure, computational capabilities and established open-source …
increasing infrastructure, computational capabilities and established open-source …
Performance of two complementary machine-learned potentials in modelling chemically complex systems
Chemically complex multicomponent alloys possess exceptional properties derived from an
inexhaustible compositional space. The complexity however makes interatomic potential …
inexhaustible compositional space. The complexity however makes interatomic potential …
Modeling high-entropy transition metal alloys with alchemical compression
Alloys composed of several elements in roughly equimolar composition, often referred to as
high-entropy alloys, have long been of interest for their thermodynamics and peculiar …
high-entropy alloys, have long been of interest for their thermodynamics and peculiar …
Thermodynamic properties on the homologous temperature scale from direct upsampling: Understanding electron-vibration coupling and thermal vacancies in bcc …
We have calculated thermodynamic properties of four bcc refractory elements—V, Ta, Mo,
and W—up to the melting point with full density-functional-theory accuracy, using the …
and W—up to the melting point with full density-functional-theory accuracy, using the …
Accelerating ab initio melting property calculations with machine learning: application to the high entropy alloy TaVCrW
Melting properties are critical for designing novel materials, especially for discovering high-
performance, high-melting refractory materials. Experimental measurements of these …
performance, high-melting refractory materials. Experimental measurements of these …
Anharmonicity in bcc refractory elements: A detailed ab initio analysis
Explicit anharmonicity, defined as the vibrational contribution beyond the quasiharmonic
approximation, is qualitatively different between the group V and group VI bcc refractory …
approximation, is qualitatively different between the group V and group VI bcc refractory …
Machine-Learning-Based Thermal Conductivity Prediction for Additively Manufactured Alloys
Thermal conductivity (TC) is greatly influenced by the working temperature, microstructures,
thermal processing (heat treatment) history and the composition of alloys. Due to …
thermal processing (heat treatment) history and the composition of alloys. Due to …
Surface segregation in high-entropy alloys from alchemical machine learning
Abstract High-entropy alloys (HEAs), containing several metallic elements in near-equimolar
proportions, have long been of interest for their unique mechanical properties. More …
proportions, have long been of interest for their unique mechanical properties. More …