Passivating contact-based tunnel junction Si solar cells using machine learning for tandem cell applications

Hyun Jung Park, Audrey Morisset, Munho Kim, Hae Seok Lee, Aïcha Hessler-Wyser, Franz Josef Haug, Christophe Ballif

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Tandem solar cells are a key technology for exceeding the theoretical efficiency limit of single-junction cells. One of the most promising combinations is the silicon–perovskite tandem cells, considering their potential for high efficiency, fabrication on a large scale, and low cost. While most research focuses on improving each subcell, another key challenge lies in the tunnel junction that connects these subcells, significantly impacting the overall cell characteristics. Here, we demonstrate the first use of tunnel junctions using a stack of p+/n+ polysilicon passivating contacts deposited directly on the tunnel oxide to overcome the drawbacks of conventional metal oxide-based tunnel junctions, including low tunneling efficiency and sputter damage. Using Random Forest analysis, we achieved high implied open circuit voltages over 700 mV and low contact resistivities of 500 mΩ cm2, suggesting fill factor losses of less than 1% abs for the operating conditions of a tandem cell.

Original languageEnglish
Article number100299
JournalEnergy and AI
Volume14
DOIs
Publication statusPublished - 2023 Oct

Bibliographical note

Publisher Copyright:
© 2023 The Author(s)

Keywords

  • Machine learning
  • Passivating contact
  • Solar cell
  • Tandem
  • Tunnel junction

ASJC Scopus subject areas

  • Engineering (miscellaneous)
  • General Energy
  • Artificial Intelligence

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