Passivating contact-based tunnel junction Si solar cells using machine learning for tandem cell applications
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 rese...
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sg-ntu-dr.10356-1735312024-02-16T15:39:04Z Passivating contact-based tunnel junction Si solar cells using machine learning for tandem cell applications Park, Hyunjung Morisset, Audrey Kim, Munho Lee, Hae-Seok Hessler-Wyser, Aïcha Haug, Franz-Josef Ballif, Christophe School of Electrical and Electronic Engineering Engineering Tunnel Junction Passivating Contact 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. Ministry of Education (MOE) Published version This research was funded by the New & Renewable Energy Core Technology Program of the Korea Institute of Energy Technology Evaluation and Planning (KETEP), and supported by the ministry of Trade, Industry, Energy, of the Republic of Korea (No. 20204010600470). Munho Kim acknowledges the support of Ministry of Education, Singapore, under AcRF Tier 2 (T2EP50120-0001). We acknowledge additional support through the visiting scientist program of the Institute of Electrical and Microengineering (EPFL-IEM). 2024-02-13T02:24:07Z 2024-02-13T02:24:07Z 2023 Journal Article Park, H., Morisset, A., Kim, M., Lee, H., Hessler-Wyser, A., Haug, F. & Ballif, C. (2023). Passivating contact-based tunnel junction Si solar cells using machine learning for tandem cell applications. Energy and AI, 14, 100299-. https://dx.doi.org/10.1016/j.egyai.2023.100299 2666-5468 https://hdl.handle.net/10356/173531 10.1016/j.egyai.2023.100299 2-s2.0-85170420817 14 100299 en T2EP50120-0001 Energy and AI © 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). application/pdf |
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Engineering Tunnel Junction Passivating Contact Park, Hyunjung Morisset, Audrey Kim, Munho Lee, Hae-Seok Hessler-Wyser, Aïcha Haug, Franz-Josef Ballif, Christophe Passivating contact-based tunnel junction Si solar cells using machine learning for tandem cell applications |
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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. |
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School of Electrical and Electronic Engineering |
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School of Electrical and Electronic Engineering Park, Hyunjung Morisset, Audrey Kim, Munho Lee, Hae-Seok Hessler-Wyser, Aïcha Haug, Franz-Josef Ballif, Christophe |
format |
Article |
author |
Park, Hyunjung Morisset, Audrey Kim, Munho Lee, Hae-Seok Hessler-Wyser, Aïcha Haug, Franz-Josef Ballif, Christophe |
author_sort |
Park, Hyunjung |
title |
Passivating contact-based tunnel junction Si solar cells using machine learning for tandem cell applications |
title_short |
Passivating contact-based tunnel junction Si solar cells using machine learning for tandem cell applications |
title_full |
Passivating contact-based tunnel junction Si solar cells using machine learning for tandem cell applications |
title_fullStr |
Passivating contact-based tunnel junction Si solar cells using machine learning for tandem cell applications |
title_full_unstemmed |
Passivating contact-based tunnel junction Si solar cells using machine learning for tandem cell applications |
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passivating contact-based tunnel junction si solar cells using machine learning for tandem cell applications |
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2024 |
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https://hdl.handle.net/10356/173531 |
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