DOE/Oak Ridge National Laboratory
Researchers at the Department of Energy s Oak Ridge National Laboratory and the University of Tennessee are automating the search for new materials to advance solar energy technologies.
A novel workflow published in
ACS Energy Letters combines robotics and machine learning to study metal halide perovskites, or MHPs thin, lightweight, flexible materials with outstanding properties for harnessing light that can be used to make solar cells, energy-efficient lighting and sensors. Our approach speeds exploration of perovskite materials, making it exponentially faster to synthesize and characterize many material compositions at once and identify areas of interest, said ORNL s Sergei Kalinin.