sedaoturak / data-resources-for-materials-science
A list of databases, datasets and books/handbooks where you can find materials properties for machine learning applications.
☆296Updated last week
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☆402Updated 4 months ago
- Things that you should (and should not) do in your Materials Informatics research.☆181Updated last year
- MSE5540/6640 Materials Informatics course at the University of Utah. Learn how data science tools are revolutionizing materials science!☆132Updated this week
- A Highly Opinionated List of Open Source Materials Informatics Resources☆126Updated 2 years ago
- Jupyter notebooks demonstrating the utilization of open-source codes for the study of materials science.☆237Updated 6 months ago
- Python for Materials Machine Learning, Materials Descriptors, Machine Learning Force Fields, Deep Learning, etc.☆383Updated last week
- Graph deep learning library for materials☆303Updated this week
- Data mining for materials science☆495Updated last week
- Deep Learning the Chemistry of Materials From Only Elemental Composition for Enhancing Materials Property Prediction☆92Updated last year
- Pretrained universal neural network potential for charge-informed atomistic modeling https://chgnet.lbl.gov☆267Updated last week
- A code to generate atomic structure with symmetry☆287Updated this week
- A suite of computational materials science tools.☆131Updated 9 months ago
- ☆81Updated 9 years ago
- ChemML is a machine learning and informatics program suite for the chemical and materials sciences.☆163Updated last year
- DScribe is a python package for creating machine learning descriptors for atomistic systems.☆406Updated last month
- atomate is a powerful software for computational materials science and contains pre-built workflows.☆247Updated 6 months ago
- An automatic engine for predicting materials properties.☆142Updated last year
- Repository for links to software packages and databases used in deep-learning applications for materials science☆135Updated 4 months ago
- n2p2 - A Neural Network Potential Package☆228Updated last month
- The Materials Project Workshop Curriculum☆111Updated last year
- A general cross-platform tool for preparing simulations of molecules and complex molecular assemblies☆264Updated last month
- pyiron - an integrated development environment (IDE) for computational materials science.☆380Updated this week
- An open-source Python package for creating fast and accurate interatomic potentials.☆307Updated last week
- Public repo for Materials API documentation☆140Updated 2 years ago
- Materials science with Python at the atomic-scale☆196Updated 3 months ago
- Predict materials properties using only the composition information!☆96Updated last year
- A Google-Colab Notebook Collection for Materials Design: https://jarvis.nist.gov/☆70Updated 5 months ago
- Tool to quickly create a composition-based feature vector☆27Updated 2 years ago
- Materials graph network with 3-body interactions featuring a DFT surrogate crystal relaxer and a state-of-the-art property predictor.☆262Updated last week
- MatDeepLearn, package for graph neural networks in materials chemistry☆179Updated last year