New Approach To Assess Stability In Perovskites
Share This:

About The Author

Chris Bartel recently defended his Ph.D. in Chemical Engineering at the University of Colorado under the guidance of Prof. Charles Musgrave and Prof. Al Weimer. His thesis describes the use of machine learning and quantum chemistry to understand and predict the thermodynamic stability of solid-state materials. He will continue working on computational materials science problems as a Postdoctoral Scholar at Lawrence Berkeley National Laboratory, beginning May 2019.

New Approach To Assess Stability In Perovskites

Emergent technologies have been historically predicated on the discovery and development of new materials – silicon computer chips, lithium-ion batteries, gallium nitride LEDs, etc. The space of potential materials that could be made from the more than 80 naturally occurring elements is almost limitless. To meet the challenges of our growing population while dramatically reducing and ultimately eliminating our reliance on fossil fuels for energy, we need a rational approach for accelerating the discovery of next-generation energy materials. A recent...

Read more