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Deep learning-assisted focused ion beam nanofabrication

Deep learning-assisted focused ion beam nanofabrication
Deep learning-assisted focused ion beam nanofabrication
Deep learning can be used to predict the post-fabrication appearance of structures manufactured by focused ion beam (FIB) milling, accounting for variations in beam focusing/scanning parameters and target medium characteristics with nanoscale accuracy. With predictions generated in milliseconds, the approach can expedite process optimization and enhance precision/reproducibility in FIB nanofabrication.
Buchnev, Oleksandr
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Grant-Jacob, James
c5d144d8-3c43-4195-8e80-edd96bfda91b
Eason, R.W.
e38684c3-d18c-41b9-a4aa-def67283b020
Zheludev, Nikolai
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Mills, Benjamin
05f1886e-96ef-420f-b856-4115f4ab36d0
MacDonald, Kevin F.
76c84116-aad1-4973-b917-7ca63935dba5
Buchnev, Oleksandr
60cdb0d2-3388-47be-a066-61b3b396f69d
Grant-Jacob, James
c5d144d8-3c43-4195-8e80-edd96bfda91b
Eason, R.W.
e38684c3-d18c-41b9-a4aa-def67283b020
Zheludev, Nikolai
32fb6af7-97e4-4d11-bca6-805745e40cc6
Mills, Benjamin
05f1886e-96ef-420f-b856-4115f4ab36d0
MacDonald, Kevin F.
76c84116-aad1-4973-b917-7ca63935dba5

Buchnev, Oleksandr, Grant-Jacob, James, Eason, R.W., Zheludev, Nikolai, Mills, Benjamin and MacDonald, Kevin F. (2022) Deep learning-assisted focused ion beam nanofabrication. 8th International Topical Meeting on Nanophotonics and Metamaterials, , Seefeld-in-Tirol, Austria. 28 - 31 Mar 2022.

Record type: Conference or Workshop Item (Paper)

Abstract

Deep learning can be used to predict the post-fabrication appearance of structures manufactured by focused ion beam (FIB) milling, accounting for variations in beam focusing/scanning parameters and target medium characteristics with nanoscale accuracy. With predictions generated in milliseconds, the approach can expedite process optimization and enhance precision/reproducibility in FIB nanofabrication.

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AI-FIB nanofab - Accepted Manuscript
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Published date: 28 March 2022
Venue - Dates: 8th International Topical Meeting on Nanophotonics and Metamaterials, , Seefeld-in-Tirol, Austria, 2022-03-28 - 2022-03-31

Identifiers

Local EPrints ID: 454137
URI: http://eprints.soton.ac.uk/id/eprint/454137
PURE UUID: f3f96b85-edbb-40f2-8286-a7a1f663f5cc
ORCID for James Grant-Jacob: ORCID iD orcid.org/0000-0002-4270-4247
ORCID for R.W. Eason: ORCID iD orcid.org/0000-0001-9704-2204
ORCID for Nikolai Zheludev: ORCID iD orcid.org/0000-0002-1013-6636
ORCID for Benjamin Mills: ORCID iD orcid.org/0000-0002-1784-1012
ORCID for Kevin F. MacDonald: ORCID iD orcid.org/0000-0002-3877-2976

Catalogue record

Date deposited: 01 Feb 2022 17:39
Last modified: 17 Mar 2024 06:57

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Contributors

Author: Oleksandr Buchnev
Author: James Grant-Jacob ORCID iD
Author: R.W. Eason ORCID iD
Author: Nikolai Zheludev ORCID iD
Author: Benjamin Mills ORCID iD
Author: Kevin F. MacDonald ORCID iD

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