Data for: “Depth Prediction of Nanotags in Tissue Using Surface Enhanced Spatially Offset Raman Scattering (SESORS)”



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 available13 Jan 2022
PublisherUniversity of Strathclyde
Date of data production2021

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