No Cover Image

Journal article 335 views 1 download

High optical storage density using three-dimensional hybrid nanostructures based on machine learning

Dekun Yang, Zhidan Lei, Lijie Li Orcid Logo, Wei Shen, Hui Li, Chengqun Gui, Yi Song Orcid Logo

Optics and Lasers in Engineering, Volume: 161, Start page: 107347

Swansea University Author: Lijie Li Orcid Logo

  • manuscript-revised_accepted.pdf

    PDF | Accepted Manuscript

    ©2022 All rights reserved. All article content, except where otherwise noted, is licensed under a Creative Commons Attribution Non-Commercial No Derivatives License (CC-BY-NC-ND)

    Download (1.46MB)

Check full text

DOI (Published version): 10.1016/j.optlaseng.2022.107347

Published in: Optics and Lasers in Engineering
ISSN: 0143-8166
Published: Elsevier BV 2023
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa61679
Tags: Add Tag
No Tags, Be the first to tag this record!
first_indexed 2022-10-31T23:45:53Z
last_indexed 2023-01-13T19:22:35Z
id cronfa61679
recordtype SURis
fullrecord <?xml version="1.0" encoding="utf-8"?><rfc1807 xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema"><bib-version>v2</bib-version><id>61679</id><entry>2022-10-31</entry><title>High optical storage density using three-dimensional hybrid nanostructures based on machine learning</title><swanseaauthors><author><sid>ed2c658b77679a28e4c1dcf95af06bd6</sid><ORCID>0000-0003-4630-7692</ORCID><firstname>Lijie</firstname><surname>Li</surname><name>Lijie Li</name><active>true</active><ethesisStudent>false</ethesisStudent></author></swanseaauthors><date>2022-10-31</date><deptcode>ACEM</deptcode><abstract/><type>Journal Article</type><journal>Optics and Lasers in Engineering</journal><volume>161</volume><journalNumber/><paginationStart>107347</paginationStart><paginationEnd/><publisher>Elsevier BV</publisher><placeOfPublication/><isbnPrint/><isbnElectronic/><issnPrint>0143-8166</issnPrint><issnElectronic/><keywords>High density optical storage; Nanostructures; Deep learning; 3D lithography</keywords><publishedDay>1</publishedDay><publishedMonth>2</publishedMonth><publishedYear>2023</publishedYear><publishedDate>2023-02-01</publishedDate><doi>10.1016/j.optlaseng.2022.107347</doi><url/><notes/><college>COLLEGE NANME</college><department>Aerospace, Civil, Electrical, and Mechanical Engineering</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>ACEM</DepartmentCode><institution>Swansea University</institution><apcterm/><funders>This work was supported by the National Key Research and Development Program of China, under Grant No. 2019YFB1704600; the Hubei Provincial Natural Science Foundation of China, under Grant No. 2020CFA032.</funders><projectreference/><lastEdited>2024-07-17T15:30:35.1445163</lastEdited><Created>2022-10-31T10:46:55.4216951</Created><path><level id="1">Faculty of Science and Engineering</level><level id="2">School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Electronic and Electrical Engineering</level></path><authors><author><firstname>Dekun</firstname><surname>Yang</surname><order>1</order></author><author><firstname>Zhidan</firstname><surname>Lei</surname><order>2</order></author><author><firstname>Lijie</firstname><surname>Li</surname><orcid>0000-0003-4630-7692</orcid><order>3</order></author><author><firstname>Wei</firstname><surname>Shen</surname><order>4</order></author><author><firstname>Hui</firstname><surname>Li</surname><order>5</order></author><author><firstname>Chengqun</firstname><surname>Gui</surname><order>6</order></author><author><firstname>Yi</firstname><surname>Song</surname><orcid>0000-0001-9632-404x</orcid><order>7</order></author></authors><documents><document><filename>61679__25618__9fcfe6c0aee544c48b20b187d2037571.pdf</filename><originalFilename>manuscript-revised_accepted.pdf</originalFilename><uploaded>2022-10-31T23:45:38.9514995</uploaded><type>Output</type><contentLength>1535474</contentLength><contentType>application/pdf</contentType><version>Accepted Manuscript</version><cronfaStatus>true</cronfaStatus><embargoDate>2023-10-28T00:00:00.0000000</embargoDate><documentNotes>©2022 All rights reserved. All article content, except where otherwise noted, is licensed under a Creative Commons Attribution Non-Commercial No Derivatives License (CC-BY-NC-ND)</documentNotes><copyrightCorrect>true</copyrightCorrect><language>eng</language><licence>https://creativecommons.org/licenses/by-nc-nd/4.0/</licence></document></documents><OutputDurs/></rfc1807>
spelling v2 61679 2022-10-31 High optical storage density using three-dimensional hybrid nanostructures based on machine learning ed2c658b77679a28e4c1dcf95af06bd6 0000-0003-4630-7692 Lijie Li Lijie Li true false 2022-10-31 ACEM Journal Article Optics and Lasers in Engineering 161 107347 Elsevier BV 0143-8166 High density optical storage; Nanostructures; Deep learning; 3D lithography 1 2 2023 2023-02-01 10.1016/j.optlaseng.2022.107347 COLLEGE NANME Aerospace, Civil, Electrical, and Mechanical Engineering COLLEGE CODE ACEM Swansea University This work was supported by the National Key Research and Development Program of China, under Grant No. 2019YFB1704600; the Hubei Provincial Natural Science Foundation of China, under Grant No. 2020CFA032. 2024-07-17T15:30:35.1445163 2022-10-31T10:46:55.4216951 Faculty of Science and Engineering School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Electronic and Electrical Engineering Dekun Yang 1 Zhidan Lei 2 Lijie Li 0000-0003-4630-7692 3 Wei Shen 4 Hui Li 5 Chengqun Gui 6 Yi Song 0000-0001-9632-404x 7 61679__25618__9fcfe6c0aee544c48b20b187d2037571.pdf manuscript-revised_accepted.pdf 2022-10-31T23:45:38.9514995 Output 1535474 application/pdf Accepted Manuscript true 2023-10-28T00:00:00.0000000 ©2022 All rights reserved. All article content, except where otherwise noted, is licensed under a Creative Commons Attribution Non-Commercial No Derivatives License (CC-BY-NC-ND) true eng https://creativecommons.org/licenses/by-nc-nd/4.0/
title High optical storage density using three-dimensional hybrid nanostructures based on machine learning
spellingShingle High optical storage density using three-dimensional hybrid nanostructures based on machine learning
Lijie Li
title_short High optical storage density using three-dimensional hybrid nanostructures based on machine learning
title_full High optical storage density using three-dimensional hybrid nanostructures based on machine learning
title_fullStr High optical storage density using three-dimensional hybrid nanostructures based on machine learning
title_full_unstemmed High optical storage density using three-dimensional hybrid nanostructures based on machine learning
title_sort High optical storage density using three-dimensional hybrid nanostructures based on machine learning
author_id_str_mv ed2c658b77679a28e4c1dcf95af06bd6
author_id_fullname_str_mv ed2c658b77679a28e4c1dcf95af06bd6_***_Lijie Li
author Lijie Li
author2 Dekun Yang
Zhidan Lei
Lijie Li
Wei Shen
Hui Li
Chengqun Gui
Yi Song
format Journal article
container_title Optics and Lasers in Engineering
container_volume 161
container_start_page 107347
publishDate 2023
institution Swansea University
issn 0143-8166
doi_str_mv 10.1016/j.optlaseng.2022.107347
publisher Elsevier BV
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Electronic and Electrical Engineering{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Electronic and Electrical Engineering
document_store_str 1
active_str 0
published_date 2023-02-01T15:30:33Z
_version_ 1804836938734108672
score 11.016258

Similar Items