NSDF-materialscience is part of the National Science Data Fabric (NSDF) initiative. This material is based upon work supported by the National Science Fundation (NSF) under Grant No. 2138811.
Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. Copyright © 2021 National Science Data Fabric.
The content in this folder supplement the following publication:
- Naweiluo Zhou1, Giorgio Scorzelli, Jakob Luettgau, Rahul Reddy Kancharla, Joshua Kane, Robert Wheeler, Brendan P. Croom, Pania Newell, Valerio Pascucci, and Michela Taufer. Orchestration of Materials Science Workflows for Heterogeneous Resources at Large Scale. [submitted]
On GitHub, you can copy this citation in APA or BibTeX format via the "Cite this repository" button.
NSDF-materialscience e is an open source project. Questions, discussion, and contributions are welcome. Contributions can be anything from new packages to bugfixes, documentation, or even new core features. Resources:
- Slack workspace: nsdf-workspace.
- Github Discussions: issues: not just for discussions, also Q&A.
- Mailing list: https://groups.google.com/g/nsdf - [email protected]
- Twitter: @FabricNsdf.
Contributing to NSDF-materialscience is easy. Just send us a pull request. When you send your request, make develop the destination branch on the NSDF-materialscience repository.
NSDF-materialscience'sdevelop branch has the latest contributions. Pull requests
should target develop, and users who want the latest package versions,
features, etc. can use develop.
NSDF-materialscience was created by the NSDF team . To reach out email us at [email protected]
NSDF-materialscience is distributed under the terms of BSD 3-Clause License. See LICENCE.txt file
Ensure a Python environment with the dependencies listed in the requirements.txt file and follow the steps in the Jupyter notebooks:
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt
jupyter lab