Python for Materials Science Tutorials

This repository contains Jupyter notebooks and Python scripts tailored for applications in Materials Science. The tutorials are designed to guide you through the essential Python tools and libraries used in computational materials research.

Syllabus

The tutorial is divided into the following modules:

1. Basics of Python (Week- 1 and 2)

   • Setting up a virtual environment
   • Understanding variables and data types
   • Using loops and conditionals
   • Writing functions and defining classes

2. Regular Expressions (Week-3)

   • Pattern matching and text processing

3. Data Analysis with Pandas and Numpy (Week-4)

   • Handling and analyzing structured data
   • Performing mathematical operations on arrays

4. Pymatgen (Python Materials Genomics) (Week-5 and 6)

   • Working with crystallographic data
   • Generating and analyzing material structures

5. Advanced Materials Science Libraries (Week-7 and 8)

   • SMACT
   • Atom2Vec, Skipgram, SkipAtom
   • CrabNet

6. Accessing Materials Data (Week-9)

   • Data retrieval using API

7. Matminer (Week-10)

   • Feature engineering for machine learning in materials science
   • Accessing pre-built datasets

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Note:

I will be creating and updating notebooks for each topic weekly, documenting everything I learnt as a beginner. This process will take time as I have to start making notebooks from scratch. I aim to complete all topics within 10 weeks.

Feel free to explore the repository and use the provided tutorials as a guide to enhance your knowledge in computational materials science!

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Contact Details

Suhas Adiga
Theoretical Sciences Unit
JNCASR, Bengaluru, India
📧 [email protected]