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

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

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...

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Bibliographic Details
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: Journal Article
Language:English
Published: 2022
Subjects:
Engineering::Chemical engineering
Solar-Cells
Clean Energy Project
Online Access:https://hdl.handle.net/10356/160582

Internet

https://hdl.handle.net/10356/160582

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