New algorithm can more quickly predict LED materials: Researchers report machine learning speeds discovery of new materials

They then synthesized and tested one of the compounds predicted computationally -- sodium-barium-borate -- and determined it offers 95 percent efficiency and outstanding thermal stability. Jakoah Brgoch, assistant professor of chemistry, and members of his lab describe the work a paper published Oct. 22 in Nature Communications. The researchers used machine learning to quickly scan huge numbers of compounds for key attributes, including Debye temperature and chemical compatibility. Brgoch previously demonstrated that Debye temperature is correlated with efficiency. LED, or light-emitting diode, based bulbs work by using small amounts of rare earth elements, usually europium or cerium, substituted within a ceramic or oxide host -- the interaction between the two materials determines the performance.