Summary
This is the initial public release of the Materials Informatics Advanced Practical course - an interactive Jupyter Book designed to teach computational materials discovery techniques. The repository provides a comprehensive educational resource covering everything from basic chemical screening to advanced quantum mechanical simulations.
What's in This Release
Core Educational Content
The course is structured as an interactive web-based textbook built with Jupyter Book, featuring:
- Theoretical foundations (Markdown content) paired with hands-on exercises (Jupyter notebooks)
- Progressive learning path from fundamental concepts to advanced computational methods
- Interactive notebooks that work both locally and on Google Colab
Course Modules
-
Foundational Topics
- Combinatorial Explosion: Understanding the vastness of chemical space
- Chemical Filters: Applying chemical rules to narrow down possibilities
- Compositional & Stoichiometry Screening: Systematic exploration techniques
-
Advanced Computational Methods
- Structure Prediction using SMACT and AI-driven approaches
- Machine Learning Force Fields (MACE) for molecular dynamics
- Density Functional Theory (DFT) with VASP integration
- Chemeleon: Text-guided generative AI for crystal structures
Why This Matters
Materials discovery traditionally relies on time-consuming experimental trial and error. This course equips researchers and students with computational skills allowing them to learn how to:
- Screen millions of potential materials compositions
- Predict crystal structures before synthesis
- Understand thermodynamic stability through quantum calculations
- Accelerate the design of new materials for batteries, semiconductors, and sustainable technologies
Target Audience
- Materials science students
- Researchers entering computational materials science
- Chemists interested in data-driven approaches
- Anyone curious about the intersection of AI and materials design
Acknowledgements
This course builds upon the excellent work of:
- The Materials Design Group and especially the SMACT development team
- Chemeleon and MACE developers
- The Jupyter Book community
- All contributors to the open-source tools featured throughout
Next Steps
Following this initial release, we plan to:
- Gather feedback from early users
- Expand the advanced methods section
- Add more real-world case studies
- Develop additional exercises for self-paced learning
The course is now live and ready for the materials science community. We're excited to see how it helps accelerate materials design research worldwide.
Repository: https://github.com/ryannduma/materialsinformatics
Live Course: [via GitHub Pages]
License: MIT