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
• 其他作者: School of Chemical and Biomedical Engineering
• 格式: Article
• 語言: English
• 出版: 2022
• 主題: Engineering::Chemical engineering; Solar-Cells; Clean Energy Project
• 在線閱讀: https://hdl.handle.net/10356/160582

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...