Welcome to the Consortium for the Advancement of Materials Science with AI (CAMSAI) GitHub organization. This organization, part of The Alliance for AI, hosts repositories focused on utilizing artificial intelligence (AI) to advance research and innovation in materials science, chemistry, and related fields.

The Consortium for the Advancement of Materials Science with AI (CAMSAI) operates as an interdisciplinary initiative under the guidance of The Alliance for AI. It combines expertise in materials science, chemistry, data science, and computer science to accelerate progress in materials research through the application of AI.

• Develop and share AI tools for materials discovery, property prediction, and optimization.
• Facilitate the integration of computational and experimental methodologies in materials science.
• Promote sustainable and efficient materials design using AI-driven innovations.
• Support interdisciplinary collaboration by providing accessible, open-source tools, models, and resources.

The CAMSAI GitHub organization includes repositories in the following categories:

1. AI Tools and Frameworks
   Libraries and utilities designed to support materials modeling, property prediction, and structure optimization.

2. Datasets
   Open datasets curated for training and validating machine learning models in materials and chemical research.

3. Pre-trained Models
   AI models built for specific applications, such as property prediction and generative design.

4. Example Workflows
   Jupyter notebooks and scripts demonstrating practical applications of CAMSAI tools and models.

5. Documentation and Resources
   Comprehensive references, guides, and best practices for using and contributing to CAMSAI resources.

• Browse repositories to locate tools, datasets, and models applicable to your research or development needs.
• Clone repositories for local use or extend their functionalities for custom applications.
• Review example workflows to learn how CAMSAI tools can address specific materials science problems.
• Access documentation for detailed instructions, API references, and troubleshooting tips.

Contributions to CAMSAI repositories are encouraged. To contribute:

1. Fork the relevant repository.
2. Create a new branch for your proposed changes.
3. Commit your updates and push them to your branch.
4. Open a pull request to the repository for review and potential inclusion.

For inquiries, support, or collaboration opportunities, contact us at:
📧 Website: camsai.org
📧 Email: [email protected]
🌐 Parent Organization: The Alliance for AI

Unless otherwise stated, repositories in this organization are licensed under the Apache License 2.0. Refer to the LICENSE file in each repository for detailed licensing terms. For more information about the license, visit Apache License 2.0.