Teaching

In this course, our focus as teaching assistants revolves primarily around EDS (Energy Dispersive X-ray Spectroscopy) and XRD (X-ray Diffraction) techniques. Throughout the semester, lab sessions are designed to guide students on how to process, evaluate and interpret raw characterization data. To put theory into practice, we design hands-on projects where students work with datasets: they are given raw XRD and EDS data for an unidentified sample. Their challenge is to act like materials detective identifying the unknown material, resolving its phase and composition and deducing its core properties through data analysis. It is fun but challenging course. Especially there is a lot to learn.

Each week, we show students how they can handle their data by combining theoretical knowledge from the lectures. For this reason, we cover certain topics. I try to put the overloaded information into a structured format, such as slides, to cover the topics more clearly. You can find the slides here :)

Also, I try to build some interactive learning tools for the students to better grasp the logic behind the theoretical concepts and see their effects on experimental data. You can find some of them below:

This course covers topics ranging from atomistic scale simulations to discrete dislocation dynamics. For students to implement the theoretical knowledge gained in lectures, we, as teaching assistants, give some lab sessions. We mostly follow the book Introduction to Computational Materials Science: Fundamentals to Applications by Richard LeSar in this course and use its codes in our labs for implementations. You can find my lab sessions for this course in the YouTube playlist below: