Predicting power conversion efficiency of organic photovoltaics: models and data analysis

• Main Authors: Eibeck, Andreas, Nurkowski, Daniel, Menon, Angiras, Bai, Jiaru, Wu, Jinkui, Zhou, Li, Mosbach, Sebastian, Akroyd, Jethro, Kraft, Markus
• Other Authors: School of Chemical and Biomedical Engineering
• Format: Article
• Language: English
• Published: 2022
• Subjects: Engineering::Chemical engineering; Solar-Cells; Clean Energy Project
• Online Access: https://hdl.handle.net/10356/160582
• Institution: Nanyang Technological University

In this paper, the ability of three selected machine learning neural and baseline models in predicting the power conversion efficiency (PCE) of organic photovoltaics (OPVs) using molecular structure information as an input is assessed. The bidirectional long short-term memory (gFSI/BiLSTM), attentiv...