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Dataset for Deep learning enabled strategies for modelling of complex aperiodic plasmonic metasurfaces of arbitrary size

Dataset for Deep learning enabled strategies for modelling of complex aperiodic plasmonic metasurfaces of arbitrary size
Dataset for Deep learning enabled strategies for modelling of complex aperiodic plasmonic metasurfaces of arbitrary size
Raw data for numerical simulation results that support the paper "Deep learning enabled strategies for modelling of complex aperiodic plasmonic metasurfaces of arbitrary size" published in ACS Photonics. "dataset.zip" containing folders "figX" with X from 1 to 8 Each figure's dataset is bundled in an according subfolder. The data is labelled in an understandable form, if applicable headers have been added to raw-data textfiles.
https://doi.org/10.5258/SOTON/D2063
University of Southampton
Majorel, Clément
9675de01-802c-46c0-a148-120ebc8eb08f
Girard, Christian
208998d8-df24-4aca-bf5b-8eb67e16ab5a
Arbouet, Arnaud
1015aa0b-ecff-4ec3-9fe0-c1558e9127fb
Muskens, Otto
2284101a-f9ef-4d79-8951-a6cda5bfc7f9
Wiecha, Peter R.
f297f06e-c298-4f3b-8cb9-98ccd21cd124
Majorel, Clément
9675de01-802c-46c0-a148-120ebc8eb08f
Girard, Christian
208998d8-df24-4aca-bf5b-8eb67e16ab5a
Arbouet, Arnaud
1015aa0b-ecff-4ec3-9fe0-c1558e9127fb
Muskens, Otto
2284101a-f9ef-4d79-8951-a6cda5bfc7f9
Wiecha, Peter R.
f297f06e-c298-4f3b-8cb9-98ccd21cd124

Majorel, Clément, Girard, Christian, Arbouet, Arnaud, Muskens, Otto and Wiecha, Peter R. (2022) Dataset for Deep learning enabled strategies for modelling of complex aperiodic plasmonic metasurfaces of arbitrary size. University of Southampton https://doi.org/10.5258/SOTON/D2063 [Dataset]

Record type: Dataset

Abstract

Raw data for numerical simulation results that support the paper "Deep learning enabled strategies for modelling of complex aperiodic plasmonic metasurfaces of arbitrary size" published in ACS Photonics. "dataset.zip" containing folders "figX" with X from 1 to 8 Each figure's dataset is bundled in an according subfolder. The data is labelled in an understandable form, if applicable headers have been added to raw-data textfiles.

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readme.txt - Dataset
Available under License Creative Commons Attribution.
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dataset.zip - Dataset
Available under License Creative Commons Attribution.
Download (8MB)

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Published date: 11 January 2022
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Identifiers

Local EPrints ID: 456187
URI: http://eprints.soton.ac.uk/id/eprint/456187
DOI: https://doi.org/10.5258/SOTON/D2063
PURE UUID: 232d2cab-f70a-40e5-b697-3454ee07a0f2
ORCID for Otto Muskens: ORCID iD orcid.org/0000-0003-0693-5504

Catalogue record

Date deposited: 26 Apr 2022 16:35
Last modified: 23 Feb 2024 02:45

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Contributors

Creator: Clément Majorel
Creator: Christian Girard
Creator: Arnaud Arbouet
Creator: Otto Muskens ORCID iD
Creator: Peter R. Wiecha

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