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Reduction of thermal conductivity in carbon nanotubes by fullerene encapsulation from machine-learning molecular dynamics simulations

Journal of applied physics, 2023-12, Vol.134 (24)

2023

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Neuroevolution machine learning potentials: Combining high accuracy and low cost in atomistic simulations and application to heat transport

Physical review. B, 2021-09, Vol.104 (10), p.1, Article 104309

2021

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Correcting force error-induced underestimation of lattice thermal conductivity in machine learning molecular dynamics

The Journal of chemical physics, 2024-07, Vol.161 (1)

2024

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Molecular dynamics simulations of heat transport using machine-learned potentials: A mini-review and tutorial on GPUMD with neuroevolution potentials

Journal of applied physics, 2024-04, Vol.135 (16)

2024

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Ultrahigh Convergent Thermal Conductivity of Carbon Nanotubes from Comprehensive Atomistic Modeling

Physical review letters, 2021-07, Vol.127 (2), p.025902-025902, Article 025902

2021

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Investigation of phase transition, mechanical behavior and lattice thermal conductivity of halogen perovskites using machine learning interatomic potentials

Physical chemistry chemical physics : PCCP, 2023-11, Vol.25 (44), p.3644-3655

2023

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Anisotropic and high thermal conductivity in monolayer quasi-hexagonal fullerene: A comparative study against bulk phase fullerene

International journal of heat and mass transfer, 2023-06, Vol.206, p.123943, Article 123943

2023

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Heat transport in pristine and polycrystalline single-layer hexagonal boron nitride

Physical chemistry chemical physics : PCCP, 2018, Vol.20 (38), p.24602-24612

2018

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Barbalinardo et al. Reply

Physical review letters, 2022-06, Vol.128 (25), p.259602-259602, Article 259602

2022

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Homogeneous nonequilibrium molecular dynamics method for heat transport and spectral decomposition with many-body potentials

Physical review. B, 2019-02, Vol.99 (6), p.064308, Article 064308

2019

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Thermal conductivity of irregularly shaped nanoparticles from equilibrium molecular dynamics

Journal of physics. Condensed matter, 2024-08, Vol.36 (34), p.345703

2024

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Combining linear-scaling quantum transport and machine-learning molecular dynamics to study thermal and electronic transports in complex materials

Journal of physics. Condensed matter, 2024-06, Vol.36 (24), p.245901

2024

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Thermal transports of 2D phosphorous carbides by machine learning molecular dynamics simulations

International journal of heat and mass transfer, 2024-06, Vol.224, p.125359, Article 125359

2024

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Exactly equivalent thermal conductivity in finite systems from equilibrium and nonequilibrium molecular dynamics simulations

Physica. E, Low-dimensional systems & nanostructures, 2022-10, Vol.144, p.115410, Article 115410

2022

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GPUMD: A package for constructing accurate machine-learned potentials and performing highly efficient atomistic simulations

The Journal of chemical physics, 2022-09, Vol.157 (11), p.114801-114801

2022

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Thermal conductivity reduction in carbon nanotube by fullerene encapsulation: A molecular dynamics study

Carbon (New York), 2020-05, Vol.161, p.800-808

2020

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Atomistic insights into the mechanical anisotropy and fragility of monolayer fullerene networks using quantum mechanical calculations and machine-learning molecular dynamics simulations

Extreme Mechanics Letters, 2023-01, Vol.58, p.101929, Article 101929

2023

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Heat transport across graphene/hexagonal-BN tilted grain boundaries from phase-field crystal model and molecular dynamics simulations

Journal of applied physics, 2021-12, Vol.130 (23)

2021

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Equivalence of the equilibrium and the nonequilibrium molecular dynamics methods for thermal conductivity calculations: From bulk to nanowire silicon

Physical review. B, 2018-03, Vol.97 (9), Article 094305

2018

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Heat transport in pristine and polycrystalline single-layer hexagonal boron nitrideElectronic supplementary information (ESI) available: The files here are the bicrystalline samples constructed using the phase field crystal method. See DOI: 10.1039/c8cp05159c

2018-10

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Reliable Resistive Switching and Synaptic Behaviors Based on a TiO x ‐Doped N Memristor for Information Storage and Neuromorphic Computing

Physica status solidi. PSS-RRL. Rapid research letters, 2021-10, Vol.15 (10), p.n/a

2021

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Reliable Resistive Switching and Synaptic Behaviors Based on a TiOx‐Doped N Memristor for Information Storage and Neuromorphic Computing

Physica status solidi. PSS-RRL. Rapid research letters, 2021-10, Vol.15 (10)

2021

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Interpretation of apparent thermal conductivity in finite systems from equilibrium molecular dynamics simulations

Physical review. B, 2021-01, Vol.103 (3), p.035417, Article 035417

2021

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Phase-field crystal model for heterostructures

Physical review. B, 2019-10, Vol.100 (16), Article 165412

2019

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The effect of the structure of functional monomers on the resistance of copolymers to Fe2+ and S2

Journal of petroleum science & engineering, 2022-05, Vol.212, p.110309, Article 110309

2022

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Reduction of thermal conductivity in carbon nanotubes by fullerene encapsulation from machine-learning molecular dynamics simulations

Neuroevolution machine learning potentials: Combining high accuracy and low cost in atomistic simulations and application to heat transport

Correcting force error-induced underestimation of lattice thermal conductivity in machine learning molecular dynamics

Molecular dynamics simulations of heat transport using machine-learned potentials: A mini-review and tutorial on GPUMD with neuroevolution potentials

Ultrahigh Convergent Thermal Conductivity of Carbon Nanotubes from Comprehensive Atomistic Modeling

Investigation of phase transition, mechanical behavior and lattice thermal conductivity of halogen perovskites using machine learning interatomic potentials

Anisotropic and high thermal conductivity in monolayer quasi-hexagonal fullerene: A comparative study against bulk phase fullerene

Heat transport in pristine and polycrystalline single-layer hexagonal boron nitride

Barbalinardo et al. Reply

Homogeneous nonequilibrium molecular dynamics method for heat transport and spectral decomposition with many-body potentials

Thermal conductivity of irregularly shaped nanoparticles from equilibrium molecular dynamics

Combining linear-scaling quantum transport and machine-learning molecular dynamics to study thermal and electronic transports in complex materials

Thermal transports of 2D phosphorous carbides by machine learning molecular dynamics simulations

Exactly equivalent thermal conductivity in finite systems from equilibrium and nonequilibrium molecular dynamics simulations

GPUMD: A package for constructing accurate machine-learned potentials and performing highly efficient atomistic simulations

Thermal conductivity reduction in carbon nanotube by fullerene encapsulation: A molecular dynamics study

Atomistic insights into the mechanical anisotropy and fragility of monolayer fullerene networks using quantum mechanical calculations and machine-learning molecular dynamics simulations

Heat transport across graphene/hexagonal-BN tilted grain boundaries from phase-field crystal model and molecular dynamics simulations

Equivalence of the equilibrium and the nonequilibrium molecular dynamics methods for thermal conductivity calculations: From bulk to nanowire silicon

Heat transport in pristine and polycrystalline single-layer hexagonal boron nitrideElectronic supplementary information (ESI) available: The files here are the bicrystalline samples constructed using the phase field crystal method. See DOI: 10.1039/c8cp05159c

Reliable Resistive Switching and Synaptic Behaviors Based on a TiO x ‐Doped N Memristor for Information Storage and Neuromorphic Computing

Reliable Resistive Switching and Synaptic Behaviors Based on a TiOx‐Doped N Memristor for Information Storage and Neuromorphic Computing

Interpretation of apparent thermal conductivity in finite systems from equilibrium molecular dynamics simulations

Phase-field crystal model for heterostructures

The effect of the structure of functional monomers on the resistance of copolymers to Fe2+ and S2

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