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Multivariate imaging for fast evaluation of in situ dark field microscopy hyperspectral data

  • Dark field scattering microscopy can create large hyperspectral data sets that contain a wealth of information on the properties and the molecular environment of noble metal nanoparticles. For a quick screening of samples of microscopic dimensions that contain many different types of plasmonic nanostructures, we propose a multivariate analysis of data sets of thousands to several hundreds of thousands of scattering spectra. By using non-negative matrix factorization for decomposing the spectra, components are identified that represent individual plasmon resonances and relative contributions of these resonances to particular microscopic focal volumes in the mapping data sets. Using data from silver and gold nanoparticles in the presence of different molecules, including gold nanoparticle-protein agglomerates or silver nanoparticles forming aggregates in the presence of acrylamide, plasmonic properties are observed that differ from those of the original nanoparticles. For the case of acrylamide, we show that the plasmon resonancesDark field scattering microscopy can create large hyperspectral data sets that contain a wealth of information on the properties and the molecular environment of noble metal nanoparticles. For a quick screening of samples of microscopic dimensions that contain many different types of plasmonic nanostructures, we propose a multivariate analysis of data sets of thousands to several hundreds of thousands of scattering spectra. By using non-negative matrix factorization for decomposing the spectra, components are identified that represent individual plasmon resonances and relative contributions of these resonances to particular microscopic focal volumes in the mapping data sets. Using data from silver and gold nanoparticles in the presence of different molecules, including gold nanoparticle-protein agglomerates or silver nanoparticles forming aggregates in the presence of acrylamide, plasmonic properties are observed that differ from those of the original nanoparticles. For the case of acrylamide, we show that the plasmon resonances of the silver nanoparticles are ideally suited to support surface enhanced Raman scattering (SERS) and the two-photon excited process of surface enhanced hyper Raman scattering (SEHRS). Both vibrational tools give complementary information on the in situ formed polyacrylamide and the molecular composition at the nanoparticle surface.show moreshow less

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Metadaten
Author details:Sabrina Maria DiehnORCiDGND, Helmut SchlaadORCiDGND, Janina KneippORCiD
DOI:https://doi.org/10.3390/molecules27165146
ISSN:1420-3049
Pubmed ID:https://pubmed.ncbi.nlm.nih.gov/36014387
Title of parent work (English):Molecules : a journal of synthetic chemistry and natural product chemistry
Publisher:MDPI
Place of publishing:Basel
Publication type:Article
Language:English
Date of first publication:2022/08/12
Publication year:2022
Release date:2024/08/29
Tag:acrylamide; dark field microscopy; gold nanoparticles; hyperspectral imaging; localized surface plasmon resonances; non-negative matrix factorization; silver nanoparticles; surface-enhanced Raman scattering (SERS); surface-enhanced hyper Raman scattering (SEHRS)
Volume:27
Issue:16
Article number:5146
Number of pages:15
Funding institution:Caroline von Humboldt Professorship of HU
Organizational units:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Chemie
DDC classification:5 Naturwissenschaften und Mathematik / 54 Chemie / 540 Chemie und zugeordnete Wissenschaften
Peer review:Referiert
Publishing method:Open Access / Gold Open-Access
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License (German):License LogoCC-BY - Namensnennung 4.0 International
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