Machine learning assisted identification of the matched energy level of materials for high open circuit voltage in binary organic solar cells

Abstract

The effects of the materials' energy levels on the Voc in binary OSCs are analyzed and the energy level matching strategy of materials for high Voc is delivered by machine learning. Experimental results verify the reliability of this machine learning approach.