Creative Commons Attribution 4.0 International

项目介绍

lammpstutorials/lammpstutorials.github.io 是一个托管在 GitHub 上的开源项目,主要使用 Shell 编写,采用 Creative Commons Attribution 4.0 International 许可证,目前获得 150 个 Star、34 次 Fork。

仓库全名
lammpstutorials/lammpstutorials.github.io
开源许可证
Creative Commons Attribution 4.0 International
Star 数
150
Fork 数
34

README 摘要

LAMMPS tutorials This is the repository of the LAMMPS tutorials webpage. All the LAMMPS input scripts and data files can be found in a separate repository named lammpstutorials-inputs. The tutorials are compatible with the 22Jul2025 release of LAMMPS. About LAMMPS tutorials The LAMMPStutorials website is made of seven tutorials that are ordered by increasing difficulty. Lennard-Jones fluid is meant for absolute…

完整内容见 GitHub 原始 README 或本页 。

常见问题

lammpstutorials.github.io 用什么语言开发?

主要使用 Shell 编写,采用 Creative Commons Attribution 4.0 International 许可证,目前有 150 个 Star。

lammpstutorials.github.io 可以免费商用吗?

仓库标注的许可证为 Creative Commons Attribution 4.0 International,商用前请先阅读仓库 LICENSE 文件确认授权范围。

如何获取 lammpstutorials.github.io 的源码?

可以直接克隆仓库:git clone https://github.com/lammpstutorials/lammpstutorials.github.io.git,默认分支为 main;安装与运行步骤见仓库 README。

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仓库最近一次更新为 9月15日,当前没有未关闭的 Issue;Star 数为 150,可作为社区活跃度的参考。

关于

LAMMPS tutorials for both beginners and advanced users

描述取自 GitHub 官方 API,中文内容由 GitRead 中文社区 编辑团队整理。

语言占比

Shell

Release

README

LAMMPS tutorials

This is the repository of the LAMMPS tutorials webpage. All the LAMMPS input scripts and data files can be found in a separate repository named lammpstutorials-inputs.

The tutorials are compatible with the 22Jul2025 release of LAMMPS.

About LAMMPS tutorials

The LAMMPStutorials website is made of seven tutorials that are ordered by increasing difficulty. Lennard-Jones fluid is meant for absolute LAMMPS and molecular dynamics beginners, and the complexity of the simulation is progressively increased for Pulling on a carbon nanotube, Polymer in water, Nanosheared electrolyte, and Reactive silicon dioxide. Finally, Water adsorption in silica and Free energy calculation use some more advanced simulation methods that are commonly used when studying soft matter systems, respectively grand canonical Monte Carlo simulations and a free energy method named umbrella sampling.

Access the files

You can access all the files by cloning this repository with its submodules:

git clone https://github.com/lammpstutorials/lammpstutorials.github.io.git --recurse-submodule

Alternatively, you can download the inputs only:

git clone https://github.com/lammpstutorials/lammpstutorials.github.io.git

The Matplotlib Pyplot functions for the figures are shared here.

Template

The template from the first page has been adapted from HTML5 UP. The other pages use the Sphinx generator with the furo style.

The article

The official article can be found on LiveCoMS, and the source of the article on GitHub. If you use this work, please cite:

A Set of Tutorials for the LAMMPS Simulation Package [Article v1.0] by Simon Gravelle, Cecilia M. S. Alvares, Jacob R. Gissinger, and Axel Kohlmeyer, published in Living Journal of Computational Molecular Science (LiveCoMS), 6(1), 3037 (2025).

@article{gravelle2025tutorials,
  title   = {A Set of Tutorials for the {LAMMPS} Simulation Package [Article v1.0]},
  author  = {Gravelle, Simon and Alvares, Cecilia M. S. and Gissinger, Jacob R. and Kohlmeyer, Axel},
  journal = {Living Journal of Computational Molecular Science (LiveCoMS)},
  volume  = {6},
  number  = {1},
  pages   = {3037},
  year    = {2025},
  doi     = {10.33011/livecoms.6.1.3037}
}

Authors

  • Simon Gravelle (corr. author), Université Grenoble Alpes, CNRS, LIPhy, 38000 Grenoble, France.
  • Cecilia M. S. Alvares, Department of Chemistry, University of Warwick, Coventry CV4 7AL, United Kingdom
  • Jacob R. Gissinger, Stevens Institute of Technology, Hoboken, NJ 07030, USA.
  • Axel Kohlmeyer, Institute for Computational Molecular Science, Temple University, Philadelphia, PA 19122, USA.

Acknowledgements

Simon Gravelle acknowledges funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement N°101065060. Axel Kohlmeyer acknowledges financial support from Sandia National Laboratories under POs 2149742 and 2407526.

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