Depth prediction of nanotags in tissue using Surface Enhanced Spatially Offset Raman Scattering (SESORS)

Berry, Matthew E. and McCabe, Samantha M. and Shand, Neil C. and Graham, Duncan and Faulds (She/Her), Karen (2022) Depth prediction of nanotags in tissue using Surface Enhanced Spatially Offset Raman Scattering (SESORS). Chemical Communications, 58 (11). pp. 1756-1759. ISSN 1359-7345 (https://doi.org/10.1039/D1CC04455A)

Preview

Text. Filename: Berry_etal_CC_2022_Depth_prediction_of_nanotags_in_tissue_using_Surface_Enhanced_Spatially_Offset_Raman_Scattering.pdf Final Published Version License: Download (2MB)| Preview

Abstract

A model for the prediction of the depth of two 'flavours' of surface enhanced Raman scattering (SERS) active nanotags embedded within porcine tissue is demonstrated using ratiometric analysis of the nanotag and tissue intensities in spatially offset Raman spectroscopy (SORS) measurements.

• Share and Export
  

  RDF+XMLBibTeXRIOXX2 XMLRDF+N-TriplesJSONDublin CoreAtomSimple MetadataReferMETSHTML CitationASCII CitationOpenURL ContextObjectEndNoteOpenURL ContextObject in SpanMODSMPEG-21 DIDLEP3 XMLData Cite XMLRIS (EndNote Online, Zotero, Ref manager, etc)RDF+N3Multiline CSV
• Item metadata

  Item type:	Article
  ID code:	79207
  Dates:	Date Event 14 January 2022 Published 14 January 2022 Published Online 4 January 2022 Accepted
  Subjects:	Science > Chemistry
  Department:	Faculty of Science > Pure and Applied Chemistry Technology and Innovation Centre > Bionanotechnology Strategic Research Themes > Health and Wellbeing
  Depositing user:	Pure Administrator
  Date deposited:	21 Jan 2022 10:55
  Last modified:	11 Apr 2024 02:22
  URI:	https://strathprints.strath.ac.uk/id/eprint/79207