mddatasetbuilder

A script to build reference datasets for training neural network potentials from given LAMMPS trajectories.

https://github.com/tongzhugroup/mddatasetbuilder

Science Score: 57.0%

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CITATION.cff file
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Low similarity (13.5%) to scientific vocabulary

Keywords

chemistry dataset md molecular-dynamics neural-network python

Last synced: 6 months ago · JSON representation ·

Repository

A script to build reference datasets for training neural network potentials from given LAMMPS trajectories.

Basic Info

Host: GitHub
Owner: tongzhugroup
License: lgpl-3.0
Language: Python
Default Branch: master
Homepage: https://mddatasetbuilder.njzjz.win
Size: 319 KB

Statistics

Stars: 40
Watchers: 3
Forks: 12
Open Issues: 5
Releases: 45

Topics

chemistry dataset md molecular-dynamics neural-network python

Created over 7 years ago · Last pushed 6 months ago

Metadata Files

Readme License Citation

MDDatasetBuilder

MDDatasetBuilder is a script to construct reference datasets for the training of neural network potentials from given LAMMPS trajectories.

Complex reaction processes in combustion unraveled by neural network-based molecular dynamics simulation, Nature Communications, 11, 5713 (2020), DOI: 10.1038/s41467-020-19497-z

Installation

MDDatasetBuilder can be installed with pip:

pip install mddatasetbuilder

The installation process should be very quick, taking only a few minutes on a “normal” desktop computer.

Usage

Simple example

A LAMMPS dump file should be prepared. A LAMMPS bond file can be added for the addition information.

bash datasetbuilder -d dump.ch4 -b bonds.reaxc.ch4_new -a C H O -n ch4 -i 25

Here, dump.ch4 is the name of the dump file. bonds.reaxc.ch4_new is the name of the bond file, which is optional. C H O is the element in the trajectory. ch4 is the name of the dataset. 25 means the time step interval and the default value is 1.

Then you can generate Gaussian input files for each structure in the dataset and calculate the potential energy & atomic forces (assume the Gaussian 16 has already been installed.):

bash qmcalc -d dataset_ch4_GJf/000 qmcalc -d dataset_ch4_GJf/001

Next, prepare a DeePMD dataset and use DeePMD-kit to train a NN model.

bash preparedeepmd -p dataset_ch4_GJf cd train && dp train train.json

The runtime of the software depends on the amount of data. It is more suited to running on a server rather than desktop computer.

DP-GEN

In a follow-up work, the MDDatasetBuilder package has been integrated with DP-GEN software as a part of the DP-GEN workflow: bash dpgen init_reaction reaction.json machine.json See DP-GEN documentation for details. Arguments of reaction.json can be found here. machine.json is described here, where reaxff_command is the LAMMPS command (lmp), build_command is the MDDatasetbuilder command (datasetbuilder), and fp_command is the Gaussian 16 command (g16 < input || :).

The genereated data can be used to continue DP-GEN concurrent learning workflow. Read Energy & Fuels, 2021, 35 (1), 762–769 for details.

Owner

Name: Tong Zhu Research Group
Login: tongzhugroup
Kind: organization
Location: Shanghai

Website: https://computchem.cn
Repositories: 6
Profile: https://github.com/tongzhugroup

East China Normal University

Citation (CITATION.cff)

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- family-names: "Zeng"
  given-names: "Jinzhe"
  orcid: "https://orcid.org/0000-0002-1515-8172"
title: "MDDatasetBuilder"
version: 1.3.1
date-released: 2021-03-29
url: "https://github.com/tongzhugroup/mddatasetbuilder"
preferred-citation:
  type: article
  authors:
  - family-names: "Zeng"
    given-names: "Jinzhe"
    orcid: "https://orcid.org/0000-0002-1515-8172"
  - family-names: "Cao"
    given-names: "Liqun"
    orcid: "https://orcid.org/0000-0003-2943-7057"
  - family-names: "Xu"
    given-names: "Mingyuan"
  - family-names: "Zhu"
    given-names: "Tong"
    orcid: "https://orcid.org/0000-0001-7472-3736"
  - family-names: "Zhang"
    given-names: "John Z. H."
    orcid: "https://orcid.org/0000-0003-4612-1863"
  doi: "10.1038/s41467-020-19497-z"
  journal: "Nature Communications"
  month: 11
  start: 5713 # First page number
  end: 5713 # Last page number
  title: "Complex reaction processes in combustion unraveled by neural network-based molecular dynamics simulation"
  issue: 1
  volume: 11
  year: 2020

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Total versions: 29
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pypi.org: mddatasetbuilder

A script to generate molecular dynamics (MD) datasets for machine learning from given LAMMPS trajectories automatically.

Homepage: https://github.com/tongzhugroup/mddatasetbuilder
Documentation: https://mddatasetbuilder.njzjz.win/
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Latest release: 1.3.10
published over 1 year ago

Versions: 29
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