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materials-learning-algorithms

Materials Learning Algorithms. A framework for machine learning materials properties from first-principles data.

https://github.com/mala-project/mala

Science Score: 67.0%

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    CITATION.cff file
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    codemeta.json file
    Found codemeta.json file
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    .zenodo.json file
    Found .zenodo.json file
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    DOI references
    Found 7 DOI reference(s) in README
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    Links to: zenodo.org
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    Low similarity (18.1%) to scientific vocabulary

Keywords

density-functional-theory dft electronic-structure machine-learning neural-network
Last synced: 6 months ago · JSON representation ·

Repository

Materials Learning Algorithms. A framework for machine learning materials properties from first-principles data.

Basic Info
Statistics
  • Stars: 94
  • Watchers: 8
  • Forks: 27
  • Open Issues: 31
  • Releases: 11
Topics
density-functional-theory dft electronic-structure machine-learning neural-network
Created almost 5 years ago · Last pushed 6 months ago
Metadata Files
Readme License Citation

README.md

image

MALA

CPU image image DOI

MALA (Materials Learning Algorithms) is a data-driven framework to generate surrogate models of density functional theory calculations based on machine learning. Its purpose is to enable multiscale modeling by bypassing computationally expensive steps in state-of-the-art density functional simulations.

MALA is designed as a modular and open-source python package. It enables users to perform the entire modeling toolchain using only a few lines of code. MALA is jointly developed by the Sandia National Laboratories (SNL) and the Center for Advanced Systems Understanding (CASUS). See Contributing for contributing code to the repository.

This repository is structured as follows: ├── examples : contains useful examples to get you started with the package ├── install : contains scripts for setting up this package on your machine ├── mala : the source code itself ├── test : test scripts used during development, will hold tests for CI in the future └── docs : Sphinx documentation folder

Installation

WARNING: Even if you install MALA via PyPI, please consult the full installation instructions afterwards. External modules (like the QuantumESPRESSO bindings) are not distributed via PyPI!

Please refer to Installation of MALA.

Running

You can familiarize yourself with the usage of this package by running the examples in the example/ folder.

Contributors

MALA is jointly maintained by

A full list of contributors can be found here.

Citing MALA

If you publish work which uses or mentions MALA, please cite this repository and the following papers:

  • A. Cangi, L. Fiedler, B. Brzoza, K. Shah, T. J. Callow, D. Kotik, S. Schmerler, M. C. Barry, J. M. Goff, A. Rohskopf, D. J. Vogel, N. Modine, A. P. Thompson, S. Rajamanickam, Materials Learning Algorithms (MALA): Scalable Machine Learning for Electronic Structure Calculations in Large-Scale Atomistic Simulations, Comp. Phys. Commun. 314, 109654 (2025).

  • J. A. Ellis, L. Fiedler, G. A. Popoola, N. A. Modine, J. A. Stephens, A. P. Thompson, A. Cangi, S. Rajamanickam, Accelerating Finite-Temperature Kohn-Sham Density Functional Theory with Deep Neural Networks, Phys. Rev. B 104, 035120 (2021).

Owner

  • Name: mala-project
  • Login: mala-project
  • Kind: organization

Repositories for the Materials Learning Algorithms (MALA) - source code, data, additional info.

Citation (CITATION.cff) 

# YAML 1.2
cff-version: 1.4.0
message: "If you use this software, please cite it using these metadata."
authors:
  - affiliation: "Center for Advanced Systems Understanding (CASUS), Helmholtz-Zentrum Dresden-Rossendorf e.V. (HZDR)"
    family-names: Cangi
    given-names: Attila
    orcid: https://orcid.org/0000-0001-9162-262X
  - affiliation: "Sandia National Laboratories (SNL)"
    family-names: Rajamanickam
    given-names: Sivasankaran
    orcid: https://orcid.org/0000-0002-5854-409X
  - affiliation: "Center for Advanced Systems Understanding (CASUS), Helmholtz-Zentrum Dresden-Rossendorf e.V. (HZDR)"
    family-names: Brzoza
    given-names: Bartosz
  - affiliation: "Center for Advanced Systems Understanding (CASUS), Helmholtz-Zentrum Dresden-Rossendorf e.V. (HZDR)"
    family-names: Callow
    given-names: Timothy J.
  - affiliation: "Oak Ridge National Laboratory (ORNL)"
    family-names: Ellis
    given-names: J. Austin
    orcid: https://orcid.org/0000-0002-9901-102X
  - affiliation: "Center for Advanced Systems Understanding (CASUS), Helmholtz-Zentrum Dresden-Rossendorf e.V. (HZDR)"
    family-names: Faruk
    given-names: Omar
  - affiliation: "Center for Advanced Systems Understanding (CASUS), Helmholtz-Zentrum Dresden-Rossendorf e.V. (HZDR)"
    family-names: Fiedler
    given-names: Lenz
    orcid: https://orcid.org/0000-0002-8311-0613
  - affiliation: "Sandia National Laboratories (SNL)"
    family-names: Fox
    given-names: James S.
  - affiliation: "Center for Advanced Systems Understanding (CASUS), Helmholtz-Zentrum Dresden-Rossendorf e.V. (HZDR)"
    family-names: Hoffmann
    given-names: Nils
  - affiliation: "Sandia National Laboratories (SNL)"
    family-names: Miller
    given-names: Kyle D.
  - affiliation: "Center for Advanced Systems Understanding (CASUS), Helmholtz-Zentrum Dresden-Rossendorf e.V. (HZDR)"
    family-names: Kotik
    given-names: Daniel
    orcid: https://orcid.org/0000-0001-8735-3199
  - affiliation: "Center for Advanced Systems Understanding (CASUS), Helmholtz-Zentrum Dresden-Rossendorf e.V. (HZDR)"
    family-names: Kulkarni
    given-names: Somashekar
  - affiliation: "Sandia National Laboratories (SNL)"
    family-names: Modine
    given-names: Normand A.
  - affiliation: "Center for Advanced Systems Understanding (CASUS), Helmholtz-Zentrum Dresden-Rossendorf e.V. (HZDR)"
    family-names: Mohammed
    given-names: Parvez
  - affiliation: "Oak Ridge National Laboratory (ORNL)"
    family-names: Oles
    given-names: Vladyslav
  - affiliation: "Sandia National Laboratories (SNL)"
    family-names: Popoola
    given-names: Gabriel A.
  - affiliation: "Center for Advanced Systems Understanding (CASUS), Helmholtz-Zentrum Dresden-Rossendorf e.V. (HZDR)"
    family-names: Pöschel
    given-names: Franz
  - affiliation: "Nvidia Corporation"
    family-names: Romero
    given-names: Josh
  - affiliation: "Helmholtz-Zentrum Dresden-Rossendorf e.V. (HZDR)"
    family-names: Schmerler
    given-names: Steve
    orcid: https://orcid.org/0000-0003-1354-0578
  - affiliation: "Sandia National Laboratories (SNL)"
    family-names: Stephens
    given-names: J. Adam
  - affiliation: "Center for Advanced Systems Understanding (CASUS), Helmholtz-Zentrum Dresden-Rossendorf e.V. (HZDR)"
    family-names: Tahmasbi
    given-names: Hossein
  - affiliation: "Sandia National Laboratories (SNL)"
    family-names: Thompson
    given-names: Aidan P.
    orcid: https://orcid.org/0000-0002-0324-9114
  - affiliation: "Center for Advanced Systems Understanding (CASUS), Helmholtz-Zentrum Dresden-Rossendorf e.V. (HZDR)"
    family-names: Verma
    given-names: Sneha
  - affiliation: "Sandia National Laboratories (SNL)"
    family-names: Vogel
    given-names: D. Jon


date-released: 2025-06-02
keywords:
  - "machine-learning"
  - "dft"
license: "BSD-3-Clause"
repository-code: "https://github.com/mala-project/mala"
title: MALA
doi: 10.5281/zenodo.5557254 # This DOI represents all versions, and will always resolve to the latest one.
version: 1.4.0

GitHub Events

Total
  • Create event: 16
  • Release event: 2
  • Issues event: 66
  • Watch event: 10
  • Delete event: 6
  • Issue comment event: 115
  • Push event: 168
  • Pull request event: 109
  • Pull request review comment event: 38
  • Pull request review event: 50
  • Fork event: 2
Last Year
  • Create event: 16
  • Release event: 2
  • Issues event: 66
  • Watch event: 10
  • Delete event: 6
  • Issue comment event: 115
  • Push event: 168
  • Pull request event: 109
  • Pull request review comment event: 38
  • Pull request review event: 50
  • Fork event: 2

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 132
  • Total pull requests: 231
  • Average time to close issues: 7 months
  • Average time to close pull requests: 19 days
  • Total issue authors: 13
  • Total pull request authors: 14
  • Average comments per issue: 1.58
  • Average comments per pull request: 0.81
  • Merged pull requests: 204
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 34
  • Pull requests: 96
  • Average time to close issues: 2 months
  • Average time to close pull requests: 11 days
  • Issue authors: 4
  • Pull request authors: 10
  • Average comments per issue: 1.15
  • Average comments per pull request: 0.98
  • Merged pull requests: 81
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • RandomDefaultUser (63)
  • elcorto (35)
  • DanielKotik (15)
  • timcallow (7)
  • kyledmiller (4)
  • acangi (3)
  • nerkulec (2)
  • karanprime (1)
  • pcagas (1)
  • elect86 (1)
  • jan-janssen (1)
  • dytnvgl (1)
  • Zevrap-81 (1)
Pull Request Authors
  • RandomDefaultUser (180)
  • DanielKotik (35)
  • elcorto (24)
  • timcallow (15)
  • franzpoeschel (15)
  • nerkulec (10)
  • kyledmiller (5)
  • dytnvgl (3)
  • pcagas (3)
  • brian-kelley (2)
  • acangi (2)
  • jmgoff (2)
  • psteinb (2)
  • karanprime (2)
Top Labels
Issue Labels
enhancement (42) not critical (33) bug (31) important (29) CI/CD (15) documentation (12) needs discussion (7) code quality (7) critical (6) testing (5) install (5) api (4) data (4) external libs (3) question (2) help wanted (2) to do (1)
Pull Request Labels
CI/CD (20) enhancement (9) bug (5) documentation (3) data (2) to do (1) testing (1) not critical (1)

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 38 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 1
  • Total versions: 5
  • Total maintainers: 2
pypi.org: materials-learning-algorithms

Materials Learning Algorithms. A framework for machine learning materials properties from first-principles data.

  • Homepage: https://github.com/mala-project/mala
  • Documentation: https://materials-learning-algorithms.readthedocs.io/
  • License: BSD 3-Clause License Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. 3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
  • Latest release: 1.4.0
    published 9 months ago
  • Versions: 5
  • Dependent Packages: 0
  • Dependent Repositories: 1
  • Downloads: 38 Last month
Rankings
Dependent packages count: 7.4%
Forks count: 8.4%
Stargazers count: 9.3%
Average: 19.6%
Dependent repos count: 22.4%
Downloads: 50.6%
Maintainers (2)
DanielKotik RandomDefaultUser
Last synced: 6 months ago

Dependencies

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