GPUMD: A package for constructing accurate machine-learned potentials and performing highly efficient atomistic simulations
We present our latest advancements of machine-learned potentials (MLPs) based on the
neuroevolution potential (NEP) framework introduced in Fan et al.[Phys. Rev. B 104, 104309 …
neuroevolution potential (NEP) framework introduced in Fan et al.[Phys. Rev. B 104, 104309 …
Neuroevolution machine learning potentials: Combining high accuracy and low cost in atomistic simulations and application to heat transport
We develop a neuroevolution-potential (NEP) framework for generating neural network-
based machine-learning potentials. They are trained using an evolutionary strategy for …
based machine-learning potentials. They are trained using an evolutionary strategy for …
On-the-fly machine learning potential accelerated accurate prediction of lattice thermal conductivity of metastable silicon crystals
In this paper, we propose a convenient strategy to accelerate the evaluation of lattice
thermal conductivity through combining phonon Boltzmann transport equation (PBTE) and …
thermal conductivity through combining phonon Boltzmann transport equation (PBTE) and …
Efficient machine-learning based interatomic potentialsfor exploring thermal conductivity in two-dimensional materials
It is well-known that the calculation of thermal conductivity using classical molecular
dynamics (MD) simulations strongly depends on the choice of the appropriate interatomic …
dynamics (MD) simulations strongly depends on the choice of the appropriate interatomic …
Spectral decomposition of thermal conductivity: Comparing velocity decomposition methods in homogeneous molecular dynamics simulations
The design of applications, especially those based on heterogeneous integration, must rely
on detailed knowledge of material properties, such as thermal conductivity (TC). To this end …
on detailed knowledge of material properties, such as thermal conductivity (TC). To this end …
Machine learning interatomic potentials as efficient tools for obtaining reasonable phonon dispersions and accurate thermal conductivity: A case study of typical two …
The accurate description of phonon dispersion of two-dimensional (2D) materials
demonstrates significance in many research fields of condensed matter physics. In this …
demonstrates significance in many research fields of condensed matter physics. In this …
[HTML][HTML] Interatomic potentials for cubic zirconia and yttria-stabilized zirconia optimized by genetic algorithm
S Fujii, A Kuwabara - Computational Materials Science, 2024 - Elsevier
Yttria stabilized zirconia (YSZ) is an important engineering ceramic oxide used for various
applications, including solid electrolytes in solid oxide fuel cells due to its high ionic …
applications, including solid electrolytes in solid oxide fuel cells due to its high ionic …
Effects of transverse geometry on the thermal conductivity of Si and Ge nanowires
We explore the effects of geometry on the thermal conductivity (κ) of silicon and germanium
nanowires, with lengths between 10–120 nm and diameters up to 5–6 nm. To this end we …
nanowires, with lengths between 10–120 nm and diameters up to 5–6 nm. To this end we …
Machine learned interatomic potentials for modeling interfacial heat transport in Ge/GaAs
Molecular dynamics simulations provide a versatile framework to study interfacial heat
transport, but their accuracy remains limited by the accuracy of available interatomic …
transport, but their accuracy remains limited by the accuracy of available interatomic …
[HTML][HTML] Enhanced thermal transport properties of graphene/SiC heterostructures on nuclear reactor cladding material: A molecular dynamics insight
Owing to the excellent thermal properties of graphene, silicon carbide (SiC) combined with
graphene is expected to obtain more outstanding thermal performance and structural …
graphene is expected to obtain more outstanding thermal performance and structural …