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Towards exact molecular dynamics simulations with machine-learned force fields

Nature communications, 2018-09, Vol.9 (1), p.3887-10, Article 3887

2018

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SpookyNet: Learning force fields with electronic degrees of freedom and nonlocal effects

Nature communications, 2021-12, Vol.12 (1), p.7273-7273, Article 7273

2021

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Machine learning of accurate energy-conserving molecular force fields

Science advances, 2017-05, Vol.3 (5), p.e1603015-e1603015

2017

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BIGDML—Towards accurate quantum machine learning force fields for materials

Nature communications, 2022-06, Vol.13 (1), p.3733-3733, Article 3733

2022

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Dynamical strengthening of covalent and non-covalent molecular interactions by nuclear quantum effects at finite temperature

Nature communications, 2021-01, Vol.12 (1), p.442-442, Article 442

2021

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Mechanical Vibrations of Atomically Defined Metal Clusters: From Nano- to Molecular-Size Oscillators

Nano letters, 2018-11, Vol.18 (11), p.6842-6849

2018

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Intercavity polariton slows down dynamics in strongly coupled cavities

Nature communications, 2024-04, Vol.15 (1), p.2915-2915

2024

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Machine Learning Force Fields

Chemical reviews, 2021-08, Vol.121 (16), p.10142-10186

2021

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Size and Shape Dependence of the Vibrational Spectrum and Low-Temperature Specific Heat of Au Nanoparticles

Journal of physical chemistry. C, 2013-11, Vol.117 (47), p.25160-25168

2013

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Molecular force fields with gradient-domain machine learning: Construction and application to dynamics of small molecules with coupled cluster forces

The Journal of chemical physics, 2019-03, Vol.150 (11), p.114102-114102

2019

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sGDML: Constructing accurate and data efficient molecular force fields using machine learning

Computer physics communications, 2019-07, Vol.240, p.38-45

2019

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On the forbidden graphene's ZO (out-of-plane optic) phononic band-analog vibrational modes in fullerenes

Communications chemistry, 2021-07, Vol.4 (1), p.103-8, Article 103

2021

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Molecular force fields with gradient-domain machine learning (GDML): Comparison and synergies with classical force fields

The Journal of chemical physics, 2020-09, Vol.153 (12), p.124109-124109

2020

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Structural Determination of Metal Nanoparticles from their Vibrational (Phonon) Density of States

Journal of physical chemistry. C, 2015-05, Vol.119 (20), p.10876-10880

2015

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Vibrational Spectrum, Caloric Curve, Low-Temperature Heat Capacity, and Debye Temperature of Sodium Clusters: The Na139 + Case

Journal of physical chemistry. C, 2013-05, Vol.117 (21), p.11393-11398

2013

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Interpolating Nonadiabatic Molecular Dynamics Hamiltonian with Bidirectional Long Short-Term Memory Networks

The journal of physical chemistry letters, 2023-08, Vol.14 (31), p.7092-7099

2023

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Size evolution of characteristic acoustic oscillations of fullerenes and its connection to continuum elasticity theory

The European physical journal. D, Atomic, molecular, and optical physics, 2022-07, Vol.76 (7), Article 123

2022

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Accurate global machine learning force fields for molecules with hundreds of atoms

Science advances, 2023-01, Vol.9 (2), p.eadf0873-eadf0873

2023

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High-fidelity molecular dynamics trajectory reconstruction with bi-directional neural networks

Machine learning: science and technology, 2022-06, Vol.3 (2), p.25011

2022

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Vibrational properties and specific heat of core-shell Ag-Au icosahedral nanoparticles

Physical chemistry chemical physics : PCCP, 2015-01, Vol.17 (42), p.28054-28059

2015

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Vibrational properties and specific heat of core-shell Ag-Au icosahedral nanoparticlesElectronic supplementary information (ESI) available: Parameters of many-body Gupta potential and VDOSs of Agcore-Aushell and Aucore-Agshell nanoparticles with 147, 309, and 561 atoms. Specific heat of 923-atom nanoalloys with different Ag-Au relative compositions. See DOI: 10.1039/c5cp00232j

2015-10

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Accurate Molecular Dynamics Enabled by Efficient Physically Constrained Machine Learning Approaches

Machine Learning Meets Quantum Physics, p.129-154

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Construction of Machine Learned Force Fields with Quantum Chemical Accuracy: Applications and Chemical Insights

Machine Learning Meets Quantum Physics, p.277-307

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Vibrational Spectrum, Caloric Curve, Low-Temperature Heat Capacity, and Debye Temperature of Sodium Clusters: The Na 139 + Case

Journal of physical chemistry. C, 2013-05, Vol.117 (21), p.11393-11398

2013

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Towards exact molecular dynamics simulations with machine-learned force fields

SpookyNet: Learning force fields with electronic degrees of freedom and nonlocal effects

Machine learning of accurate energy-conserving molecular force fields

BIGDML—Towards accurate quantum machine learning force fields for materials

Dynamical strengthening of covalent and non-covalent molecular interactions by nuclear quantum effects at finite temperature

Mechanical Vibrations of Atomically Defined Metal Clusters: From Nano- to Molecular-Size Oscillators

Intercavity polariton slows down dynamics in strongly coupled cavities

Machine Learning Force Fields

Size and Shape Dependence of the Vibrational Spectrum and Low-Temperature Specific Heat of Au Nanoparticles

Molecular force fields with gradient-domain machine learning: Construction and application to dynamics of small molecules with coupled cluster forces

sGDML: Constructing accurate and data efficient molecular force fields using machine learning

On the forbidden graphene's ZO (out-of-plane optic) phononic band-analog vibrational modes in fullerenes

Molecular force fields with gradient-domain machine learning (GDML): Comparison and synergies with classical force fields

Structural Determination of Metal Nanoparticles from their Vibrational (Phonon) Density of States

Vibrational Spectrum, Caloric Curve, Low-Temperature Heat Capacity, and Debye Temperature of Sodium Clusters: The Na139 + Case

Interpolating Nonadiabatic Molecular Dynamics Hamiltonian with Bidirectional Long Short-Term Memory Networks

Size evolution of characteristic acoustic oscillations of fullerenes and its connection to continuum elasticity theory

Accurate global machine learning force fields for molecules with hundreds of atoms

High-fidelity molecular dynamics trajectory reconstruction with bi-directional neural networks

Vibrational properties and specific heat of core-shell Ag-Au icosahedral nanoparticles

Accurate Molecular Dynamics Enabled by Efficient Physically Constrained Machine Learning Approaches

Construction of Machine Learned Force Fields with Quantum Chemical Accuracy: Applications and Chemical Insights

Vibrational Spectrum, Caloric Curve, Low-Temperature Heat Capacity, and Debye Temperature of Sodium Clusters: The Na 139 + Case

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