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Machine learning ensures rapid and precise selection of gold sea-urchin-like nanoparticles for desired light-to-plasmon resonance.
Pan, Fei; Wu, Chia-Chen; Chen, Yu-Lin; Kung, Po-Yen; Su, Yen-Hsun.
Affiliation
  • Pan F; Department of Materials Science and Engineering, National Cheng Kung University, Tainan 70101, Taiwan. yhsu@mail.ncku.edu.tw.
  • Wu CC; Physics Department, Technische Universität München, James-Franck-Straße 1, Garching 85748, Germany.
  • Chen YL; Department of Materials Science and Engineering, National Cheng Kung University, Tainan 70101, Taiwan. yhsu@mail.ncku.edu.tw.
  • Kung PY; Department of Materials Science and Engineering, National Cheng Kung University, Tainan 70101, Taiwan. yhsu@mail.ncku.edu.tw.
  • Su YH; Department of Materials Science and Engineering, National Cheng Kung University, Tainan 70101, Taiwan. yhsu@mail.ncku.edu.tw.
Nanoscale ; 14(37): 13532-13541, 2022 Sep 29.
Article in En | MEDLINE | ID: mdl-36004452
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Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies Language: En Journal: Nanoscale Year: 2022 Document type: Article Affiliation country: Taiwan Country of publication: United kingdom
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Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies Language: En Journal: Nanoscale Year: 2022 Document type: Article Affiliation country: Taiwan Country of publication: United kingdom