New Approach to Solar Material Design and Manufacturing Uses AI
OSAKA, Japan, June 7, 2018 — To speed the search for well-matched solar materials, scientists applied random forest (RF) screening, a machine learning technique, for the design, synthesis, and characterization of a polymer that could facilitate rapid development of optoelectronic materials for organic photovoltaics (OPVs). Scientists from Osaka University gathered data on 1200 OPVs from around 500 studies. Using RF machine learning (artificial intelligence), they built a model combining the bandgap, molecular weight,