Science Score: 77.0%
This score indicates how likely this project is to be science-related based on various indicators:
-
✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
✓DOI references
Found 2 DOI reference(s) in README -
✓Academic publication links
Links to: nature.com -
✓Committers with academic emails
2 of 2 committers (100.0%) from academic institutions -
○Institutional organization owner
-
○JOSS paper metadata
-
○Scientific vocabulary similarity
Low similarity (16.3%) to scientific vocabulary
Keywords
Repository
A software for automating materials science computations
Basic Info
- Host: GitHub
- Owner: molmd
- License: mit
- Language: Python
- Default Branch: master
- Homepage: https://molmd.github.io/mispr/
- Size: 11.7 MB
Statistics
- Stars: 31
- Watchers: 4
- Forks: 7
- Open Issues: 0
- Releases: 2
Topics
Metadata Files
README.md
Overview
MISPR is a free, open-source software for executing, managing, and storing computational materials science simulations. It can:
- Predict various materials properties through pre-defined workflows
- Integrate density functional theory (DFT) and molecular dynamics (MD) simulations seamlessly
- Process, analyze, and visualize simulation results with built-in utilities
- Handle errors automatically using recipe-like fixes
- Build and manage computational databases in MongoDB backend for easy querying, analysis, and sharing
- Support multiple queuing systems via FireWorks including SLURM, PBS, SGE, etc.
- Scale architecture to handle computations from individual materials to thousands of compounds
- Modify and chain workflows together flexibly
- Leverage open-source libraries including pymatgen, custodian, and FireWorks
Workflows
MISPR provides several pre-defined workflows:
DFT (Gaussian) Workflows
- ESP: Electrostatic partial charges calculations for charge fitting
- NMR: Nuclear magnetic resonance chemical shift predictions
- BDE: Bond dissociation energy calculations
- BE: Binding energy calculations
- IP_EA: Redox potential calculations; methods supported include HOMO/LUMO, vertical IP/EA, adiabatic IP/EA, and sequential PCET; electron transfer calculations can be performed via single-step or multi-step pathways
MD (LAMMPS) Workflows
A standard workflow for performing classical MD simulations of liquid solutions and subsequently deriving various structural and dynamical properties. The default operations run as follows:
- Run ESP workflow on all species
- Fit RESP charges and extract GAFF parameters (OPLS2005 and user-defined parameters are supported)
- Build initial system configuration
- Create LAMMPS data file containing initial atomic coordinations, molecular topology, and force field parameters
- Run two step energy minimization, NPT equilibration run, melting and quenching, and an NVT production run
- Perform analysis using the generated log and trajectory files (radial distribution function, coordination number, cluster analysis, mean squared displacement and diffusion) using MDPropTools
Hybrid Workflows
- General: A workflow that combines the ESP DFT workflow with the MD workflow described above
- NMR: A workflow that first runs the general hybrid workflow, then analyzes solvation shells from MD trajectories, and finally runs the NMR DFT workflow on representative solvation structures to predict chemical shifts
All these workflows are easily customizable and can be modified to suit specific research needs.
Installation
MISPR requires Python 3.10 or higher. You can install it using pip or download the source from GitHub. Please see the Installation page for detailed instructions.
Useful Links
- MISPR Website: Visit this site to get an overview of MISPR, check the installation instructions, and follow MISPR tutorials
- MISPR API Reference
- Resources
How to cite
Please include the following two citations (paper1 and paper2) if MISPR and/or MDPropTools were used for an academic study:
bib
@article{atwi2022mispr,
title={MISPR: an open-source package for high-throughput multiscale molecular simulations},
author={Atwi, Rasha and Bliss, Matthew and Makeev, Maxim and Rajput, Nav Nidhi},
journal={Scientific Reports},
volume={12},
number={1},
pages={15760},
year={2022},
publisher={Nature Publishing Group UK London}
}
bib
@article{atwi2022automated,
title={An automated framework for high-throughput predictions of NMR chemical shifts within liquid solutions},
author={Atwi, Rasha and Chen, Ying and Han, Kee Sung and Mueller, Karl T and Murugesan, Vijayakumar and Rajput, Nav Nidhi},
journal={Nature Computational Science},
volume={2},
number={2},
pages={112--122},
year={2022},
publisher={Nature Publishing Group US New York}
}
License Information
MISPR is a free, open-source software package (distributed under the MIT license).
Owner
- Name: MolMD Research Group @ SBU
- Login: molmd
- Kind: organization
- Email: navnidhi.rajput@stonybrook.edu
- Location: Stony Brook
- Website: molmd.org
- Repositories: 4
- Profile: https://github.com/molmd
Citation (CITATION.cff)
cff-version: 1.2.0
message: "If you use MISPR in your research, please consider citing the following:"
authors:
- family-names: Atwi
given-names: Rasha
orcid: https://orcid.org/0000-0001-8122-7335
- family-names: Bliss
given-names: Matthew
orcid: https://orcid.org/0000-0003-1354-7649
- family-names: Makeev
given-names: Maxim
orcid: https://orcid.org/0000-0001-7116-1299
- family-names: Rajput
given-names: Nav Nidhi
orcid: https://orcid.org/0000-0003-4740-8217
title: "MDPropTools"
version: 0.0.4
date-released: 2022-09-21
url: https://github.com/molmd/mispr
preferred-citation:
type: article
authors:
- family-names: Atwi
given-names: Rasha
orcid: https://orcid.org/0000-0001-8122-7335
- family-names: Bliss
given-names: Matthew
orcid: https://orcid.org/0000-0003-1354-7649
- family-names: Makeev
given-names: Maxim
orcid: https://orcid.org/0000-0001-7116-1299
- family-names: Rajput
given-names: Nav Nidhi
orcid: https://orcid.org/0000-0003-4740-8217
doi: 10.1038/s41598-022-20009-w
journal: Scientific Reports
month: 9
title: "MISPR: an open-source package for high-throughput multiscale molecular simulations"
issn: 2045-2322
volume: 12
issue: 1
start: 15760
year: 2022
publisher: Nature Publishing Group UK London
GitHub Events
Total
- Watch event: 1
- Push event: 60
- Pull request event: 2
- Fork event: 1
Last Year
- Watch event: 1
- Push event: 60
- Pull request event: 2
- Fork event: 1
Committers
Last synced: almost 3 years ago
All Time
- Total Commits: 525
- Total Committers: 2
- Avg Commits per committer: 262.5
- Development Distribution Score (DDS): 0.006
Top Committers
| Name | Commits | |
|---|---|---|
| Rasha | a****r@h****u | 522 |
| mmbliss | m****s@s****u | 3 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 2
- Total pull requests: 4
- Average time to close issues: over 1 year
- Average time to close pull requests: 9 days
- Total issue authors: 2
- Total pull request authors: 2
- Average comments per issue: 0.5
- Average comments per pull request: 0.25
- Merged pull requests: 2
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 0
- Pull requests: 1
- Average time to close issues: N/A
- Average time to close pull requests: 17 days
- Issue authors: 0
- Pull request authors: 1
- Average comments per issue: 0
- Average comments per pull request: 1.0
- Merged pull requests: 1
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- mmbliss (1)
- ajerschow (1)
Pull Request Authors
- mmbliss (4)
- kuldeepsinhraj (2)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 1
-
Total downloads:
- pypi 17 last-month
- Total dependent packages: 0
- Total dependent repositories: 1
- Total versions: 3
- Total maintainers: 1
pypi.org: mispr
mispr contains FireWorks workflows for Materials Science
- Homepage: https://github.com/molmd/mispr
- Documentation: https://mispr.readthedocs.io/
- License: mit
-
Latest release: 0.0.4
published over 2 years ago
Rankings
Maintainers (1)
Dependencies
- fireworks *
- matplotlib *
- monty *
- networkx *
- numpy *
- pandas *
- pymongo *
- scipy *
- actions/checkout v2 composite
- actions/setup-python v3 composite
- Pygments ==2.16.1
- readthedocs-sphinx-search ==0.3.1
- sphinx ==5.1.1
- sphinx-copybutton ==0.5.2
- sphinx-favicon ==1.0.1
- sphinx-immaterial ==0.11.7
- sphinx-tabs ==3.4.1
- sphinx-togglebutton ==0.3.2
- sphinx_design ==0.4.1
- sphinxcontrib-mermaid ==0.9.2
- dnspython *
- fireworks >=1.9.6
- matplotlib >=3.3.1
- mdproptools *
- monty >=4.0.0
- networkx >=2.5
- numpy >=1.21.1
- pandas >=1.1.2
- parmed *
- pubchempy *
- pymongo >=3.11.0
- pymongo <=3.12.0
- scipy >=1.5.2