Publications

22nd April 2021 | Analytical Chemistry

Spatially Offset Raman Spectroscopy — How Deep?

Sara Mosca, Priyanka Dey, Marzieh Salimi, Benjamin Gardner, Francesca Palombo, Nick Stone & Pavel Matousek


Abstract

Spatially offset Raman spectroscopy (SORS) is a technique for interrogating the subsurface composition of turbid samples noninvasively. This study generically addresses a fundamental question relevant to a wide range of SORS studies, which is how deep SORS probes for any specific spatial offset when analyzing a turbid sample or, in turn, what magnitude of spatial offset one should select to probe a specific depth. This issue is addressed by using Monte Carlo simulations, under the assumption of negligible absorption, which establishes that the key parameter governing the extent of the probed zone for a point-like illumination and point-like collection SORS geometry is the reduced scattering coefficient of the medium. This can either be deduced from literature data or directly estimated from a SORS measurement by evaluating the Raman intensity profile from multiple spatial offsets. Once this is known, the extent of the probed zone can be determined for any specific SORS spatial offset using the Monte Carlo simulation results presented here. The proposed method was tested using experimental data on stratified samples by analyzing the signal detected from a thin layer that was moved through a stack of layers using both non-absorbing and absorbing samples. The proposed simple methodology provides important additional information on SORS measurements with direct relevance to a wide range of SORS applications including biomedical, pharmaceutical, security, forensics, and cultural heritage.

11th March 2021 | Nature Reviews Methods Primers

Spatially Offset Raman Spectroscopy

Sara Mosca, Claudia Conti, Nick Stone & Pavel Matousek


Abstract

Spatially offset Raman spectroscopy (SORS) is a spectroscopic technique that allows for the non-invasive chemical characterization of diffusely scattering materials, ranging from opaque plastics to biological tissues. SORS has been explored for a range of applications, including disease diagnosis, the detection of explosives through unopened containers and the in-depth, non-destructive analysis of pharmaceutical products and objects of art. This Primer introduces the reader to the basic concepts underpinning SORS, details best practices for its implementation, highlights its use across multiple fields and provides insight into its limitations. The Primer concludes by discussing potential applications and envisaging future developments in the field.

11th February 2021 | Analytical Chemistry

Estimating the Reduced Scattering Coefficient of Turbid Media Using Spatially Offset Raman Spectroscopy

Sara Mosca, Priyanka Dey, Marzieh Salimi, Benjamin Gardner, Francesca Palombo, Nick Stone & Pavel Matousek


Abstract

We propose a new method for estimating the reduced scattering coefficient, μs′, of turbid homogeneous samples using Spatially Offset Raman Spectroscopy (SORS). The concept is based around the variation of Raman signal with SORS spatial offset that is strongly μs′-dependent, as such, permitting the determination of μs′. The evaluation is carried out under the assumptions that absorption is negligible at the laser and Raman wavelengths and μs′ is approximately the same for those two wavelengths. These conditions are often satisfied for samples analyzed in the NIR region of the spectrum where SORS is traditionally deployed. Through a calibration procedure on a PTFE model sample, it was possible to estimate the μs′ coefficient of different turbid samples with an error (RMSEP) below 18%. The knowledge of μs′ in the NIR range is highly valuable for facilitating accurate numerical simulations to optimize illumination and collection geometries in SORS, to derive in-depth information about the properties of SORS measurements or in other photon applications, dependent on photon propagation in turbid media with general impact across fields such as biomedical, pharmaceutical, security, forensic, and cultural sciences.