Description
The purpose of this dataset was to predict the depth of two flavours of nanotags in tissue using handheld spatially offset Raman spectroscopy (SORS) and a new ratiometric analysis technique. The nose cone of the handheld spectrometer was used to apply pressure to the tissue surface and the nanotags were then detected through the tissue using a constant spatial offset of 8 mm. Calibration models were created by relating the intensity ratio of the nanotag and tissue Raman intensities through increasing thicknesses of the tissue barrier. The maximum depth at which the nanotags could be detected was determined using principal component analysis. Then, the calibration models were used to predict the depth of the nanotags through tissue. For more information please consult the file 'dataset_readme.docx.'
| Date made available | 13 Jan 2022 |
|---|---|
| Publisher | University of Strathclyde |
| Date of data production | 2021 |
Research output
- 1 Article
-
Depth prediction of nanotags in tissue using Surface Enhanced Spatially Offset Raman Scattering (SESORS)
Berry, M. E., McCabe, S. M., Shand, N. C., Graham, D. & Faulds (She/Her), K., 14 Jan 2022, In: Chemical Communications. 58, 11, p. 1756-1759 4 p.Research output: Contribution to journal › Article › peer-review
Open AccessFile18 Link opens in a new tab Citations (Scopus)35 Downloads (Pure)
Projects
- 1 Finished
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EPSRC Centre for Doctoral Training in Optical Medical Imaging - Training the next generation of scientific entrepreneurs in healthcare technologies (OPTIMA)
Graham, D. (Principal Investigator) & Faulds, K. (Co-investigator)
EPSRC (Engineering and Physical Sciences Research Council)
1/05/14 → 31/10/23
Project: Research - Studentship
Cite this
- DataSetCite