New Developments in Chemical Spectral Analysis
While the chemicals in your laboratory may be clearly labeled and easily distinguished from one another, it's significantly more difficult to analyze a substance and determine exactly what chemicals constitute the mixture. Researchers from the Institute of Physical Chemistry of the Polish Academy of Sciences, or IPC PAS, in Warsaw, Poland have developed a new method for finding which chemicals and compounds are in a given substance.
Rethinking spectral analysis
The researchers developed a new algorithm to improve the effectiveness of spectral analysis, according to IPC PAS. Chemical analysis using light has been promising, but unreliable. By looking at the way that light is scattered by a substance, as one does with spectral analysis, you can examine the unique way in which light interacts with individual molecules or atoms. The radiation they give off or absorb and other data that can be determined from light interaction can help people determine the exact chemical compounds in a mixture.
However, this type of chemical analysis has not always been reliable in the past. In some cases it would fail to identify every compound, or worse, give off false positives, indicating that a compound was in the substance that was not. Additionally some elements or compounds would have similar markers that could lead to confusion and overlap results.
The IPC PAS researchers compare the issues of spectral analysis to talking at a concert, where the plethora of sounds can interfere with communication. To avoid this inevitable confusion, the scientists shifted their focus from the intensity of spectral analysis results, turning instead to looking at the shapes and features that make each signature unique, like facial recognition software, Tomasz Rolinski from the IPC PAS explained.
"When examining the structure of the light that is registered – that is, in the course of spectral analysis – the whole trick is to pick out only the most important elements characteristic of a given substance from the spectrum of the mixture," Rolinski said in a statement.
"This approach is somewhat similar to the automatic face detection method used, for example, in security systems at airports. This does not involve a comparison of the appearance of every detail of the face, but a search for similarities in simple relationships, such as eye spacing, the position of the mouth or the end of the nose. Then it no longer matters if the wanted person is wearing a hat or not, or whether he has a suntan or has shaved off his mustache."
By examining the shape and relative position of spectral lines, the researchers were able to perform better than traditional spectral analysis when testing 20 substances. In addition to identifying the substances regularly, the test found that the new approach produces zero false positive matches for substances not present in the mixture.
Potential uses for this new technology
NPR explained that one of the only downsides of the hugely success food production system in the U.S. is that pesticides can travel from farms into nearby water ways, affecting the ecosystem and polluting the rivers, streams and lakes.
More effective tests, like the light spectral method developed by IPC PAS may be able to play a significant role in addressing these concerns. By testing water, soil or other natural substances, everyone from farmers to the community will have a better idea about what chemicals are contaminating the land and how the issue can be addressed. For example, NPR pointed to an example where Missouri's Clarence Cannon Wholesale Water Commission was treating water with powder activated carbon to remove atrazine (1) from the water supply.
(1) Atrazine is also known as 2-Chloro-4-ethylamino-6-isopropylamino-s-triazine; Aatrex®; Gesaprim®; Atratol®;
The first step to addressing a problem like pollution or contamination is to find the cause of the problem and understand what substances you're working with. This will allow for the best treatment and prevention methods.
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