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Spatially Offset Raman Spectroscopy-How Deep?

delete2021-04-22
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OA
AI
S
Sara Mosca
P
Priyanka Dey
M
Marzieh Salimi
B
Benjamin Gardner
F
Francesca Palombo
S
Stone, Nick *
P
Pavel Matousek *
DOI:10.1021/acs.analchem.1c00490delete
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摘要

摘要

En 中文
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.
Keyword:
TIME-RESOLVED REFLECTANCE
OPTICAL-PROPERTIES
BIOLOGICAL TISSUES
PHOTON MIGRATION
SCATTERING
DEPTH
MODEL
NM
SIMULATIONS
ABSORPTION
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期刊

Analytical Chemistry 封面图
Analytical Chemistry
IF:
6.7
论文数:
4.7W
被引数:
15.9W

机构

S
science & technology facilities council (stfc)
学者数:
4.6K
论文数: 3.3K
被引数: 8
U
uk research & innovation (ukri)
学者数:
2.7W
论文数: 2.3W
被引数: 32
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