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Bayesian optimization of hydrogen plasma treatment in silicon quantum dot multilayer and application to solar cells
Silicon quantum dot multilayer (Si-QDML) is a promising material for a light absorber of all silicon tandem solar cells due to tunable bandgap energy in a wide range depending on the silicon quantum dot (Si-QD) size, which is possible to overcome the Shockley–Queisser limit. Since solar cell perform...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10214912/ https://www.ncbi.nlm.nih.gov/pubmed/37382685 http://dx.doi.org/10.1186/s11671-023-03821-9 |
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author | Kumagai, Fuga Gotoh, Kazuhiro Miyamoto, Satoru Kato, Shinya Kutsukake, Kentaro Usami, Noritaka Kurokawa, Yasuyoshi |
author_facet | Kumagai, Fuga Gotoh, Kazuhiro Miyamoto, Satoru Kato, Shinya Kutsukake, Kentaro Usami, Noritaka Kurokawa, Yasuyoshi |
author_sort | Kumagai, Fuga |
collection | PubMed |
description | Silicon quantum dot multilayer (Si-QDML) is a promising material for a light absorber of all silicon tandem solar cells due to tunable bandgap energy in a wide range depending on the silicon quantum dot (Si-QD) size, which is possible to overcome the Shockley–Queisser limit. Since solar cell performance is degenerated by carrier recombination through dangling bonds (DBs) in Si-QDML, hydrogen termination of DBs is crucial. Hydrogen plasma treatment (HPT) is one of the methods to introduce hydrogen into Si-QDML. However, HPT has a large number of process parameters. In this study, we employed Bayesian optimization (BO) for the efficient survey of HPT process parameters. Photosensitivity (PS) was adopted as the indicator to be maximized in BO. PS (σ(p)/σ(d)) was calculated as the ratio of photoconductivity (σ(p)) and dark conductivity (σ(d)) of Si-QDML, which allowed the evaluation of important electrical characteristics in solar cells easily without fabricating process-intensive devices. 40-period layers for Si-QDML were prepared by plasma-enhanced chemical vapor deposition method and post-annealing onto quartz substrates. Ten samples were prepared by HPT under random conditions as initial data for BO. By repeating calculations and experiments, the PS was successfully improved from 22.7 to 347.2 with a small number of experiments. In addition, Si-QD solar cells were fabricated with optimized HPT process parameters; open-circuit voltage (V(OC)) and fill factor (FF) values of 689 mV and 0.67, respectively, were achieved. These values are the highest for this type of device, which were achieved through an unprecedented attempt to combine HPT and BO. These results prove that BO is effective in accelerating the optimization of practical process parameters in a multidimensional parameter space, even for novel indicators such as PS. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s11671-023-03821-9. |
format | Online Article Text |
id | pubmed-10214912 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-102149122023-05-27 Bayesian optimization of hydrogen plasma treatment in silicon quantum dot multilayer and application to solar cells Kumagai, Fuga Gotoh, Kazuhiro Miyamoto, Satoru Kato, Shinya Kutsukake, Kentaro Usami, Noritaka Kurokawa, Yasuyoshi Discov Nano Research Silicon quantum dot multilayer (Si-QDML) is a promising material for a light absorber of all silicon tandem solar cells due to tunable bandgap energy in a wide range depending on the silicon quantum dot (Si-QD) size, which is possible to overcome the Shockley–Queisser limit. Since solar cell performance is degenerated by carrier recombination through dangling bonds (DBs) in Si-QDML, hydrogen termination of DBs is crucial. Hydrogen plasma treatment (HPT) is one of the methods to introduce hydrogen into Si-QDML. However, HPT has a large number of process parameters. In this study, we employed Bayesian optimization (BO) for the efficient survey of HPT process parameters. Photosensitivity (PS) was adopted as the indicator to be maximized in BO. PS (σ(p)/σ(d)) was calculated as the ratio of photoconductivity (σ(p)) and dark conductivity (σ(d)) of Si-QDML, which allowed the evaluation of important electrical characteristics in solar cells easily without fabricating process-intensive devices. 40-period layers for Si-QDML were prepared by plasma-enhanced chemical vapor deposition method and post-annealing onto quartz substrates. Ten samples were prepared by HPT under random conditions as initial data for BO. By repeating calculations and experiments, the PS was successfully improved from 22.7 to 347.2 with a small number of experiments. In addition, Si-QD solar cells were fabricated with optimized HPT process parameters; open-circuit voltage (V(OC)) and fill factor (FF) values of 689 mV and 0.67, respectively, were achieved. These values are the highest for this type of device, which were achieved through an unprecedented attempt to combine HPT and BO. These results prove that BO is effective in accelerating the optimization of practical process parameters in a multidimensional parameter space, even for novel indicators such as PS. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s11671-023-03821-9. Springer US 2023-03-13 /pmc/articles/PMC10214912/ /pubmed/37382685 http://dx.doi.org/10.1186/s11671-023-03821-9 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Research Kumagai, Fuga Gotoh, Kazuhiro Miyamoto, Satoru Kato, Shinya Kutsukake, Kentaro Usami, Noritaka Kurokawa, Yasuyoshi Bayesian optimization of hydrogen plasma treatment in silicon quantum dot multilayer and application to solar cells |
title | Bayesian optimization of hydrogen plasma treatment in silicon quantum dot multilayer and application to solar cells |
title_full | Bayesian optimization of hydrogen plasma treatment in silicon quantum dot multilayer and application to solar cells |
title_fullStr | Bayesian optimization of hydrogen plasma treatment in silicon quantum dot multilayer and application to solar cells |
title_full_unstemmed | Bayesian optimization of hydrogen plasma treatment in silicon quantum dot multilayer and application to solar cells |
title_short | Bayesian optimization of hydrogen plasma treatment in silicon quantum dot multilayer and application to solar cells |
title_sort | bayesian optimization of hydrogen plasma treatment in silicon quantum dot multilayer and application to solar cells |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10214912/ https://www.ncbi.nlm.nih.gov/pubmed/37382685 http://dx.doi.org/10.1186/s11671-023-03821-9 |
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