Materials Informatics is the application of data science tools and techniques to materials research. In this episode, we examine how the uses of machine learning are applied to materials science. We try to give an honest appraisal of the pros and cons of this emerging field to separate the hype from reality and even provide some tips on how to get started in the field.

Articles Discussed:

• Excellent YouTube tutorial for Materials Informatics from Dr. Sparks [LINK]
• 2020 Wang and coworkers Best Practices article in Chemistry of Materials [LINK]
• GitHub repository for best practices jupyter notebooks [LINK]

This episode is sponsored by Matmatch. Check out how they can help you find the perfect material for your next engineering project!

Thanks to Kolobyte and Alphabot for letting us use their music in the show!

If you have questions or feedback please send us emails at materialism.podcast@gmail.com or connect with us on social media: Instagram, Twitter.

Materialism Team: Taylor Sparks (co-creator, co-host, production), Andrew Falkowski (co-creator, co-host, production), Jared Duffy (production, marketing, and editing)

Keywords: machine learning materials informatics data science materials discovery new materials

Support Materialism: A Materials Science Podcast by contributing to their tip jar: https://tips.pinecast.com/jar/materialism