sedaoturak / data-resources-for-materials-science
A list of databases, datasets and books/handbooks where you can find materials properties for machine learning applications.
☆304Updated last month
Alternatives and similar repositories for data-resources-for-materials-science:
Users that are interested in data-resources-for-materials-science are comparing it to the libraries listed below
- Curated list of known efforts in materials informatics, i.e. in modern materials science☆410Updated 5 months ago
- MSE5540/6640 Materials Informatics course at the University of Utah. Learn how data science tools are revolutionizing materials science!☆135Updated this week
- A Highly Opinionated List of Open Source Materials Informatics Resources☆126Updated 3 years ago
- Things that you should (and should not) do in your Materials Informatics research.☆182Updated last year
- Python for Materials Machine Learning, Materials Descriptors, Machine Learning Force Fields, Deep Learning, etc.☆388Updated 2 weeks ago
- Jupyter notebooks demonstrating the utilization of open-source codes for the study of materials science.☆237Updated 7 months ago
- A code to generate atomic structure with symmetry☆294Updated this week
- Data mining for materials science☆504Updated this week
- ☆83Updated 9 years ago
- Pretrained universal neural network potential for charge-informed atomistic modeling https://chgnet.lbl.gov☆273Updated last month
- atomate is a powerful software for computational materials science and contains pre-built workflows.☆250Updated 7 months ago
- A suite of computational materials science tools.☆133Updated 10 months ago
- Graph deep learning library for materials☆308Updated this week
- An automatic engine for predicting materials properties.☆144Updated last year
- The Materials Project Workshop Curriculum☆112Updated last year
- Deep Learning the Chemistry of Materials From Only Elemental Composition for Enhancing Materials Property Prediction☆93Updated last year
- n2p2 - A Neural Network Potential Package☆232Updated this week
- An open-source Python package for creating fast and accurate interatomic potentials.☆309Updated 3 weeks ago
- DScribe is a python package for creating machine learning descriptors for atomistic systems.☆412Updated 2 months ago
- Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals☆515Updated last year
- Materials graph network with 3-body interactions featuring a DFT surrogate crystal relaxer and a state-of-the-art property predictor.☆268Updated 2 weeks ago
- Software for generating machine-learning interatomic potentials for LAMMPS☆161Updated last month
- doped is a Python software for the generation, pre-/post-processing and analysis of defect supercell calculations, implementing the defec…☆160Updated this week
- A Google-Colab Notebook Collection for Materials Design: https://jarvis.nist.gov/☆74Updated 3 weeks ago
- Public repo for Materials API documentation☆140Updated 2 years ago
- Python package to aid materials design and informatics☆103Updated this week
- Repository for links to software packages and databases used in deep-learning applications for materials science☆136Updated 5 months ago
- Tool to quickly create a composition-based feature vector☆27Updated 2 years ago
- pyiron - an integrated development environment (IDE) for computational materials science.☆385Updated last month
- Materials science with Python at the atomic-scale☆201Updated 3 weeks ago