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Journal Articles

Revealing the molecular structures of α-Al₂O₃(0001)–water interface by machine learning based computational vibrational spectroscopy

Xianglong Du, Weizhi Shao, Chenglong Bao, Linfeng Zhang, Jun Cheng, Fujie Tang

J. Chem. Phys. 161, 124702 (2024)

https://doi.org/10.1063/5.0230101

Published: September 2024

View article titled, Revealing the molecular structures of α-Al2O3(0001)–water interface by machine learning based computational vibrational spectroscopy

Journal Articles

Acoustic phonon excitation in gold probed by time-resolved photoemission electron microscopy

Pengzuo Jiang, Linfeng Zhang, Wei Zheng, Yang Wang, Yu Liu, Jingying Xiao, Yaolong Li, Nikita Medvedev, Anatoly Ischenko, Zexin Kang, Yunquan Liu, Zheng Li, Chengyin Wu

J. Chem. Phys. 161, 024704 (2024)

https://doi.org/10.1063/5.0213237

Published: July 2024

View article titled, Acoustic phonon excitation in gold probed by time-resolved photoemission electron microscopy

Journal Articles

DeePMD-kit v2: A software package for deep potential models

J. Chem. Phys. 159, 054801 (2023)

https://doi.org/10.1063/5.0155600

Published: August 2023

View article titled, DeePMD-kit v2: A software package for deep potential models

Journal Articles

Machine learning-assisted multi-scale modeling

Weinan E, Huan Lei, Pinchen Xie, Linfeng Zhang

J. Math. Phys. 64, 071101 (2023)

https://doi.org/10.1063/5.0149861

Published: July 2023

View article titled, Machine learning-assisted multi-scale modeling

Journal Articles

Machine learning assisted coarse-grained molecular dynamics modeling of meso-scale interfacial fluids

Pei Ge, Linfeng Zhang, Huan Lei

J. Chem. Phys. 158, 064104 (2023)

https://doi.org/10.1063/5.0131567

Published: February 2023

View article titled, Machine learning assisted coarse-grained molecular dynamics modeling of meso-scale interfacial fluids

Book Chapter

Learning DeePMD-Kit: A Guide to Building Deep Potential Models

Book: A Practical Guide to Recent Advances in Multiscale Modeling and Simulation of Biomolecules

Series: AIPP Books, Methods

Published: January 2023

10.1063/9780735425279_006

EISBN: 978-0-7354-2527-9

ISBN: 978-0-7354-2524-8

Open the PDF for Learning DeePMD-Kit: A Guide to Building Deep Potential Models in another window

Journal Articles

A deep potential model with long-range electrostatic interactions

Linfeng Zhang, Han Wang, Maria Carolina Muniz, Athanassios Z. Panagiotopoulos, Roberto Car, Weinan E

J. Chem. Phys. 156, 124107 (2022)

https://doi.org/10.1063/5.0083669

Published: March 2022

View article titled, A deep potential model with long-range electrostatic interactions

Magazine Articles

Machine-learning-assisted modeling

Weinan E, Jiequn Han, Linfeng Zhang

Physics Today 74, 36–41 (2021)

https://doi.org/10.1063/PT.3.4793

Published: July 2021

View article titled, Machine-learning-assisted modeling

Journal Articles

Machine learning phase space quantum dynamics approaches

Xinzijian Liu, Linfeng Zhang, Jian Liu

J. Chem. Phys. 154, 184104 (2021)

https://doi.org/10.1063/5.0046689

Published: May 2021

View article titled, Machine learning phase space quantum dynamics approaches

Includes: Supplementary data

Journal Articles

Ultrafast extreme ultraviolet photoemission electron microscope

Wei Zheng, Pengzuo Jiang, Linfeng Zhang, Yang Wang, Quan Sun, Yunquan Liu, Qihuang Gong, Chengyin Wu

Rev. Sci. Instrum. 92, 043709 (2021)

https://doi.org/10.1063/5.0047076

Published: April 2021

View article titled, Ultrafast extreme ultraviolet photoemission electron microscope

Journal Articles

Deep potential generation scheme and simulation protocol for the Li₁₀GeP₂S₁₂-type superionic conductors

Jianxing Huang, Linfeng Zhang, Han Wang, Jinbao Zhao, Jun Cheng, Weinan E

J. Chem. Phys. 154, 094703 (2021)

https://doi.org/10.1063/5.0041849

Published: March 2021

View article titled, Deep potential generation scheme and simulation protocol for the Li10GeP2S12-type superionic conductors

Journal Articles

When do short-range atomistic machine-learning models fall short?

Shuwen Yue, Maria Carolina Muniz, Marcos F. Calegari Andrade, Linfeng Zhang, Roberto Car, Athanassios Z. Panagiotopoulos

J. Chem. Phys. 154, 034111 (2021)

https://doi.org/10.1063/5.0031215

Published: January 2021

View article titled, When do short-range atomistic machine-learning models fall short?

Includes: Supplementary data

Journal Articles

Warm dense matter simulation via electron temperature dependent deep potential molecular dynamics

Yuzhi Zhang, Chang Gao, Qianrui Liu, Linfeng Zhang, Han Wang, Mohan Chen

Phys. Plasmas 27, 122704 (2020)

https://doi.org/10.1063/5.0023265

Published: December 2020

View article titled, Warm dense matter simulation via electron temperature dependent deep potential molecular dynamics

Includes: Supplementary data

Journal Articles

Deep learning inter-atomic potential model for accurate irradiation damage simulations

Hao Wang, Xun Guo, Linfeng Zhang, Han Wang, Jianming Xue

Appl. Phys. Lett. 114, 244101 (2019)

https://doi.org/10.1063/1.5098061

Published: June 2019

View article titled, Deep learning inter-atomic potential model for accurate irradiation damage simulations

Includes: Supplementary data

Journal Articles

Adaptive coupling of a deep neural network potential to a classical force field

Linfeng Zhang, Han Wang, Weinan E

J. Chem. Phys. 149, 154107 (2018)

https://doi.org/10.1063/1.5042714

Published: October 2018

View article titled, Adaptive coupling of a deep neural network potential to a classical force field

Journal Articles

DeePCG: Constructing coarse-grained models via deep neural networks

Linfeng Zhang, Jiequn Han, Han Wang, Roberto Car, Weinan E

J. Chem. Phys. 149, 034101 (2018)

https://doi.org/10.1063/1.5027645

Published: July 2018

View article titled, DeePCG: Constructing coarse-grained models via deep neural networks

Journal Articles

Reinforced dynamics for enhanced sampling in large atomic and molecular systems

Linfeng Zhang, Han Wang, Weinan E

J. Chem. Phys. 148, 124113 (2018)

https://doi.org/10.1063/1.5019675

Published: March 2018

View article titled, Reinforced dynamics for enhanced sampling in large atomic and molecular systems

NARROW

Topics

Revealing the molecular structures of α-Al₂O₃(0001)–water interface by machine learning based computational vibrational spectroscopy

Acoustic phonon excitation in gold probed by time-resolved photoemission electron microscopy

DeePMD-kit v2: A software package for deep potential models

Machine learning-assisted multi-scale modeling

Machine learning assisted coarse-grained molecular dynamics modeling of meso-scale interfacial fluids

Learning DeePMD-Kit: A Guide to Building Deep Potential Models

A deep potential model with long-range electrostatic interactions

Machine-learning-assisted modeling

Machine learning phase space quantum dynamics approaches

Ultrafast extreme ultraviolet photoemission electron microscope

Deep potential generation scheme and simulation protocol for the Li₁₀GeP₂S₁₂-type superionic conductors

When do short-range atomistic machine-learning models fall short?

Warm dense matter simulation via electron temperature dependent deep potential molecular dynamics

Deep learning inter-atomic potential model for accurate irradiation damage simulations

Adaptive coupling of a deep neural network potential to a classical force field

DeePCG: Constructing coarse-grained models via deep neural networks

Reinforced dynamics for enhanced sampling in large atomic and molecular systems

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