Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (3/3 displayed)

  • 2023Bayesian optimization of hydrogen plasma treatment in silicon quantum dot multilayer and application to solar cells6citations
  • 2023A Novel Self-Separating Silicon Nanowire Thin Film and Application in Lithium-ion Batteries1citations
  • 2014Solid-phase crystallization of amorphous silicon nanowire array and optical properties9citations

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Chart of shared publication
Kutsukake, Kentaro
1 / 2 shared
Usami, Noritaka
1 / 4 shared
Gotoh, Kazuhiro
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Kumagai, Fuga
1 / 1 shared
Kato, Shinya
3 / 10 shared
Li, Haibin
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Soga, Tetsuo
1 / 5 shared
Konagai, Makoto
1 / 5 shared
Yamazaki, Tatsuya
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Ishikawa, Ryousuke
1 / 2 shared
Chart of publication period
2023
2014

Co-Authors (by relevance)

  • Kutsukake, Kentaro
  • Usami, Noritaka
  • Gotoh, Kazuhiro
  • Kumagai, Fuga
  • Kato, Shinya
  • Li, Haibin
  • Soga, Tetsuo
  • Konagai, Makoto
  • Yamazaki, Tatsuya
  • Ishikawa, Ryousuke
OrganizationsLocationPeople

article

Bayesian optimization of hydrogen plasma treatment in silicon quantum dot multilayer and application to solar cells

  • Kutsukake, Kentaro
  • Usami, Noritaka
  • Gotoh, Kazuhiro
  • Kurokawa, Yasuyoshi
  • Kumagai, Fuga
  • Kato, Shinya
Abstract

<jats:title>Abstract</jats:title><jats:p>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 (<jats:italic>σ</jats:italic><jats:sub>p</jats:sub>/<jats:italic>σ</jats:italic><jats:sub>d</jats:sub>) was calculated as the ratio of photoconductivity (<jats:italic>σ</jats:italic><jats:sub>p</jats:sub>) and dark conductivity (<jats:italic>σ</jats:italic><jats:sub>d</jats:sub>) 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 (<jats:italic>V</jats:italic><jats:sub>OC</jats:sub>) 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.</jats:p>

Topics
  • impedance spectroscopy
  • experiment
  • Hydrogen
  • Silicon
  • annealing
  • random
  • quantum dot
  • chemical vapor deposition
  • photoconductivity