Data-Driven Tunnel Oxide Passivated Contact Solar Cell Performance Analysis Using Machine Learning

© 2024 Wiley‐VCH GmbH.

Bibliographische Detailangaben
Veröffentlicht in:Advanced materials (Deerfield Beach, Fla.). - 1998. - 36(2024), 14 vom: 05. Apr., Seite e2309351
1. Verfasser: Zhou, Jiakai (VerfasserIn)
Weitere Verfasser: Jacobsson, T Jesper, Wang, Zhi, Huang, Qian, Zhang, Xiaodan, Zhao, Ying, Hou, Guofu
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2024
Zugriff auf das übergeordnete Werk:Advanced materials (Deerfield Beach, Fla.)
Schlagworte:Journal Article TOPCon accelerated design machine learning solar cells
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520 |a Tunnel oxide passivated contacts (TOPCon) have gained interest as a way to increase the energy conversion efficiency of silicon solar cells, and the International Technology Roadmap of Photovoltaics forecasts TOPCon to become an important technology despite a few remaining challenges. To review the recent development of TOPCon cells, this work has compiled a dataset of all device data found in current literature, which sums up to 405 devices from 131 papers. This may seem like a surprisingly small number of cells given the recent interest in the TOPCon architecture, but it illustrates a problem of data dissemination in the field. Notwithstanding the limited number of cells, there is a great diversity in cell manufacturing procedures, and this work observes a gradual increase in performance indicating that the field has not yet converged on a set of best practices. By analyzing the data using statistical methods and machine learning (ML) algorithms, this work is able to reinforces some commonly held hypotheses related to the performance differences between different device architectures. This work also identifies a few more unintuitive feature combinations that would be of interest for further experimentally studies. This work also aims to inspire improvements in data management and dissemination within the TOPCon community 
650 4 |a Journal Article 
650 4 |a TOPCon 
650 4 |a accelerated design 
650 4 |a machine learning 
650 4 |a solar cells 
700 1 |a Jacobsson, T Jesper  |e verfasserin  |4 aut 
700 1 |a Wang, Zhi  |e verfasserin  |4 aut 
700 1 |a Huang, Qian  |e verfasserin  |4 aut 
700 1 |a Zhang, Xiaodan  |e verfasserin  |4 aut 
700 1 |a Zhao, Ying  |e verfasserin  |4 aut 
700 1 |a Hou, Guofu  |e verfasserin  |4 aut 
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