The Department of Energy’s Lawrence Berkeley National Laboratory (Berkeley Lab) and several collaborating institutions have successfully demonstrated a machine-learning technique to accelerate the discovery of materials for film capacitors—crucial components in electrification and renewable energy technologies. The technique was used to screen a library of nearly 50,000 chemical structures to identify a compound with record-breaking performance. The other collaborators from University of Wisconsin–Madison, Scripps Research Institute, University of California, Berkeley, and University of Southern Mississippi contributed expertise in machine learning, chemical synthesis, and material characterization. Their research was reported in the journal Nature Energy. “For cost-effective, reliable renewable energy technologies, we need better performing capacitor materials than what are available today,” said Yi Liu, a senior scientist at Berkeley Lab who led the study. “This breakthrough screening technique will help us find these ‘needle-in-a-haystack’ materials.”

Full research : Researchers inch closer to perfecting a futuristic energy tech with a breakthrough film capacitor.