Predicting Power Conversion Efficiency of Organic Photovoltaics: Models and Data Analysis

[Image: see text] 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...

Descripción completa

Detalles Bibliográficos
Autores principales: Eibeck, Andreas, Nurkowski, Daniel, Menon, Angiras, Bai, Jiaru, Wu, Jinkui, Zhou, Li, Mosbach, Sebastian, Akroyd, Jethro, Kraft, Markus
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2021
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8459373/
https://www.ncbi.nlm.nih.gov/pubmed/34568656
http://dx.doi.org/10.1021/acsomega.1c02156

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8459373/
https://www.ncbi.nlm.nih.gov/pubmed/34568656
http://dx.doi.org/10.1021/acsomega.1c02156

Ejemplares similares