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Raman spectroscopy is an analytical characterization technique that has been around for many years and uses the principles of inelastic scattering (of photons) – also known as the Raman effect – to provide information on the molecules in a sample. It is a technique that is often used in many scientific areas and has become a staple characterization technique in the nanotechnology space.
While Raman spectroscopy has many uses, there are also many different variations of the traditional technique, and some are used more widely than others. One of the most well-known variations – especially in the nanotechnology space – is surface-enhanced Raman spectroscopy (SERS), but here, we’re going to look at a lesser-known variation known as spatially offset Raman spectroscopy (SORS), which is used in very different circles to conventional Raman spectroscopy.
What is SORS?
SORS is a specialist Raman spectroscopy method that is primarily used to determine the chemical structure of a sample when it is located behind an obscuring surface. This surface can be any number of things, including containers, non-transparent layers, biological tissues, coatings, and bottles. This means that the application areas can be vast and include anything from analyzing a chemical substance or tablets inside a bottle, to looking for explosives inside containers, analyzing a patient’s bone beneath the skin, or looking for counterfeit pharmaceutical products, amongst many more.
SORS is not far removed from conventional Raman spectroscopy, but it can penetrate much deeper than other Raman spectroscopy methods. For example, conventional Raman spectroscopy only looks at the surface of a material (typically up to several hundred micrometers in depth) whereas SORS penetrates up to several millimeters of a barrier material and still analyzes the sample behind it.
This ability to analyze at depth makes using SORS vastly different to conventional Raman spectroscopy, despite having similar techniques (where conventional Raman spectroscopy is used to provide a high chemical specificity and mapping of a surface).
One of the key benefits of SORS compared to other techniques is that the composition of the barrier material does not need to be known to perform the analysis, nor does the spectrometer need to be in contact with the barrier layer. This makes it an ideal method for testing samples remotely (especially dangerous samples) with a high accuracy and precision.
How Does SORS Work?
Some of the basic principles of SORS are the same as conventional Raman spectroscopy, whereby inelastic light scattering is used to measure the molecules in the sample (where the light scatters due to interacting with the chemical bonds in the molecule).
However, in conventional Raman spectroscopy, the scattering is limited to near-surface objects, but SORS takes some measurements that avoid the dominant excitation region of the surface. This is because all molecules exhibit a Raman signal due to the scattering of light, and the ability to not just analyze the excitation regions of the surface molecules enables SORS to investigate much deeper than other Raman spectroscopy methods. As all molecules will provide a Raman signal, the molecules under the surface can still be ‘seen’ by the spectrometer.
In practice, this is realized by two measurements being performed on the sample. This is different to conventional Raman, which takes one, with the surface molecules being the dominant excitation region.
The first measurement is the same as a conventional Raman measurement and analyzes the molecular composition of the container. However, the second measurement is important. The second measurement is spatially offset by a few millimeters and separates the laser excitation from the spectra collection, enabling the contents of the container (or sub-surface) to be analyzed.
The two spectra then undergo a scaled subtraction process – which removes the signals from the container in the first measurement – producing a clean spectrum of the molecules inside the container.
SORS is a technique that works very well for two-layer systems, as the scaled subtraction is very effective. When there are more than two layers, it can become more complex, while advanced statistical methods (multivariate analysis) are sometimes required to analyze the sample. However, multiple offset measurements can be made, enabling these systems to be analyzed at different offset distances. There is a limit to how many times this can be performed, as the signal can become too weak to provide conclusive results if performed too often.
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