Generating chemical image is the most powerful function of a Raman
or IR microscope. In this video, I will explain what it is and how to get it.
OK, let me give an example. Here we have three substances A, B, and C. And they
have a certain pattern of distribution, in micro-scale. This is our ground truth.
However, if we place the sample under an optical microscope,
not all information is there. For instance, optical microscope shows the colors of the
substances are different from the background, but from the color we are not able to identify them.
This is a typical situation of particle analysis. Raman and IR microscopes can
obtain vibrational spectra on these points, which are chemical sensitive and can be used
for identification of the substances. In this case, we only need to measure 3 points.
Let’s make it more difficult. Now the distribution of the substances is also missing. This is often
happening when the targets are optically similar. Pharmaceutical tablet for instance, most active
ingredients are white, and we are not able to see the distribution with an optical microscope. But
with a Raman or IR microscope, we can assign a number of measurement points distributed in
the region of interest and we let the device take spectrum from each of them automatically.
This way, we have not only spectra but also the spatial coordinates of the measurement points. If
we can interpret and visualize the data properly, the missing chemical distribution is found. This
is the chemical imaging function, and it is not available with a conventional optical microscope.
So far, we learned, that a chemical image gives us the chance to evaluate a sample by its chemical
properties – a feature that we cannot achieve by optical microscopy alone. Basically, we use
an FT-IR, Raman or IR laser microscope, record a spectrum in a certain amount of measurement spots.
As the device take spectrum from each of the point, let’s say 30 by 20 points,
there are 600 spectra. In the end, we need to abstract information from
these spectra and make an image out of it. The most common way
of generating chemical images is using the characteristic peak in the spectra.
Assuming that there is a peak in the spectra of substance A, but not in the spectra
of substances B or C, we can plot the peak height of each spectrum with a color. This
is then a concentration map of substance A, as the characteristic peak indicates the existence of it.
We can also do the same to B and C and finally put these 3 layers together.
However, this procedure will be tricky if we are not familiar with their spectra. So,
commonly, in this case, the user must pick a handful of measurement points randomly and
try to spot differences. This way, we may find characteristic peaks that can show contrast.
After some rounds of trail-and-error, characteristic peak can be found,
and the corresponding substance can be identified with the help
of spectra libraries or reference measurements.
That was what researchers did for decades but in recent times they have found a new strategy.
The need of knowledge of spectra before generating chemical image is history.
It is no longer necessary to spend hours of work to find differences among spectra.
Software tools can now do this for you. For example, it can recognize the
spectral differences and visualize them with spatial information together automatically.
This sort of smart function is running in the
backstage during the measurement and creates the chemical image on the fly,
and allows us to see the chemical distribution which was not visible with an optical microscope.
But there is more to it. Let’s take the same measurement and use an adaptive chemical
imaging function. This software will check every single spectrum and assign it to a certain class.
For this, the AI does not need any further knowledge of the sample,
and judges the classes by spectra only. For the present dataset,
we end up with three groups of similar spectra that are descriptive of the sample.
From here on out the software can find a match in the spectra library for the average spectrum
of each group. A thorough analysis of the Raman or IR microscopic data is now finished,
without need of expertise with the spectra. Chemical imaging was never so easy before.