Who I am ?

Hi 👋 I am Chris, and I am an Alexander von Humboldt postdoctoral fellow in materials informatics at the Georgia Institute of Technology in Atlanta.

What I Did ?

I recieved my PhD (Latin: Dr. rer. nat. [doctor rerum naturalium], German: Doktor der Naturwissenschaften) from the Technical University Munich in collaboration with the Munich University of Applied Sciences in 2018.

My doctoral reasearch focused on investigating the ferroelectric and pyroelectric effects in hafnium dioxide (HfO\(_2\)) and zirconium dioxide (ZrO\(_2\)) thin films (thickness ~\(\text{nm}\) range) using materials informatics tools such as the density functional theory (DFT) or molecular dynamics (MD). HfO\(_2\) and ZrO\(_2\) are inert and CMOS-compatible materials that are commonly used in electronic components (e.g., as gate dielectric of transistors). Their ferroelectricity was found by accident in 2011 when scientists at Qimonda (a German memory company at this time) conducted experiments on silicon doped HfO\(_2\) films. The discovery was a surprise, but also a tremendous opportunity, because ferroelectric HfO\(_2\) thin films can potentially be used in ferroelectric memory devices for information storage. The research question of my PhD was to identify the crystallographic phases that are responsible for the ferroelectricity and their interplay with external and internal physical factors (i.e., dopants, electric field, film thickness, etc.).

What I Do ?

After graduation, I was awarded the Feodor Lynen fellowship for postdoctoral researchers by the Alexander von Humboldt Foundation, which I started in February 2019 in the Ramprasad Group at Georgia Institute of Technology in Atlanta. The Ramprasad group "develops and utilizes computational and data-driven tools to aid materials design" with a strong focus on polymeric materials.

My research focus lies on applying machine learning methods from the computer sciences community in materials sciences. I develop machine learning models (deep neural networks) that predict properties of polymers or design polymers based on property demands for a variety of applications.

People may call me a "materials computer scientist" or "computational materials scientist". Not sure 🤔.