Machine learning predicts organic solar cell efficiency and stability
A machine-learning framework reads absorption spectra to forecast efficiency and stability of untested organic solar cell blends, accelerating material development.
A machine-learning framework could help researchers predict the efficiency and stability of organic solar cells (OSCs) before a single device is built. The approach, reported in an Energy & Environmen...