Ellen Miseo, PhD, Hamamatsu Corporation
June 14, 2016
In laboratory-based analysis of optical spectra, one of the standard methods of reducing the data is to search a spectrum of a sample against a library of spectra of known materials. This is the approach that is used in many college-level chemistry classes, and it leads a novice user to assume that you need libraries for any spectroscopic analysis. But this assumption is not really valid. In this note, we discuss when libraries are necessary and when they are not.
Optical spectroscopic analytical techniques are divided into the classes of ultraviolet, visible, near- and mid-infrared based on the type of electromagnetic change that is being measured, the instrument being used, and the definition used by the scientist. All the definitions in the discussion below are definitions used by chemists and are also dependent on instrumentation, particularly the detectors used in the instrumentation.
When a spectroscopist measures a spectrum, they are typically interested in either the identification of the material (qualitative analysis) or how much of a particular compound is present (quantitative analysis).
In the ultraviolet and visible region of the spectrum (220 to 750 nm), the spectra are due to electronic transitions. These transitions are electronic in nature and many molecules with similar structures have similar transitions. For example, most compounds that have an aromatic ring absorb ultraviolet light at 254 nm. This means that a spectrum might be class specific but not indicative of the molecule itself.
The near-infrared region of the spectrum is typically defined as 750 nanometers to 2,500 nanometers. Spectra in this region are due to overtones of the fundamental absorbances in the mid-infrared. These overtones result from fundamental vibrations of C-H, N-H, and O-H bonds in molecules, and unfortunately overlap with each other. This means that although identification of a material is possible from its near-infrared spectrum, it is not as straightforward as it can be in the mid-infrared.
An infrared spectrum results from the absorbance of infrared radiation — usually in the range of 4,000 to 400 cm-1 (2,500 to 25,000 nanometers) — by a sample. This region of spectral absorbance corresponds to the energy necessary to excite bonds in most organic molecules and in some inorganic molecules. Since the absorbance frequency is impacted by the environment of the bond, and there are many bonds in an organic molecule, the collection of these absorbances provides a unique signature for a compound.
A Raman spectrum, although a different measurement technique, results from the same vibrational transitions as the infrared. So a Raman spectrum is also specific for the molecule of interest. The problem with Raman is that it is a very weak effect. To combat that, surface-enhanced Raman spectroscopy (SERS) is employed. Unfortunately as you change the measurement conditions, such as employing SERS rather than normal Raman, intensities of the Raman bands and sometimes their positions will change.
Analytical spectral regions and the physical processes responsible for absorption in that region.
|UV/Vis||200 to 750 nm||Absorptions are due to transitions of electrons|
|Near IR||750 to 2000 nm||Absorptions are due to the absorptions from overtones and combinations of bands of fundamental vibrations mainly of atoms bonded to hydrogen such as -OH, -NH, CH|
|Mid IR||2 μm (2000 nm) to 25 μm
Also expressed as cm-1
4000 to 400 cm-1
|Absorptions are due to fundamental vibration of atoms bonded to other atoms including CH, OH, CO, CN, etc.|
In 1905, William W. Coblentz compiled the first information on structure/spectral correlations in many classes of compounds.1 This compilation — and the recognition of chemists that there was a correlation between spectrum and structure—began the science of infrared spectroscopy.
Following the work of Coblentz, scientists recognized that infrared light can be used as an identification method. With that recognition, scientists began to generate collections of spectra of known materials for qualitative analysis. These spectra, whether infrared or Raman, show sharp absorbances indicative of chemical functionality. The shape and position can also indicate the environment surrounding that functionality. Taking into account all the factors that impact a peak position and intensity, a skilled person can interpret the spectrum to deduce the structure.
Since Raman scattering and infrared absorbance are complementary techniques (both are due to the same chemical structures, but different due to the mechanism producing the spectral feature), the two spectra can be used to unequivocally interpret and identify a chemical structure. This has led to the demand for libraries of known materials.
When building a library, there are a number of factors that can impact the spectral signature. How the material is sampled, how it is presented to the spectrometer, and even instrument and data processing parameters can all change the appearance of a spectrum. Once the spectrum is collected, it is typically normalized (strongest peak set to 1) for inclusion in the library. Finally, if the spectrum is collected at a high spectral resolution, then it may be de-resolved before inclusion in the library.
Searching has come a long way since the days of opening a book and looking for the strongest peak, but the technique also has its limitations. With the advent of computerized data systems a number of algorithms were developed to search through extensive databases. Results of searches are usually reported as a numerical result called a Hit Quality Index (HQI) from the search software. This HQI can be interpreted as a goodness of fit of the experimental spectrum to the library standards if the user understands the parameters that they represent. Figure 1 shows an example of a library search, but this search used a library that was not appropriate for the sample. In Figure 2, the chosen library, an adhesives database, was used and the identification was appropriate.
Figure 1. Results of using a library for a search of an infrared spectrum. The libraries chosen were not appropriate for the sample, thus the identification is not correct.
Figure 2. Results of using a library for a search of an infrared spectrum where the libraries chosen were appropriate for the sample. The identification is correct.
The HQI represents mathematically, based on the search algorithm used, how well the library spectrum fits to the experimental spectrum. But baseline effects, noise, contaminants, and how the spectrum was collected all will impact this number. Another factor that will directly impact the search results is the algorithm used. And all these factors are dependent on the unknown actually being in the library and the library being appropriate to the nature of the sample.2
In a quantitative analysis, the important point is the calibration curve (the relationship between the changes in absorbance in the spectrum to the concentration). This requires that you have the spectrum of the material of interest, and accurately vary the concentration while measuring the absorbance at a particular pathlength. This type of analysis relies on the Beer-Lambert law, which relates concentration to pathlength and absorbance.3 Since the purpose of a quantitative analysis is to determine how much of a material is present, the analyst must know beforehand the spectrum of the material he is quantifying. A good calibration curve is necessary, but libraries are not because in the method development spectra are collected at different concentrations. Figure 3 illustrates a calibration curve in good agreement with Beer’s law and can be used to determine the amount of high fructose corn syrup in soft drinks.
Figure 3. Beer's law calibration for high fructose corn syrup in soft drinks. The inset spectrum is of the highest concentration in water, 20% (w/v).
For qualitative analysis, the situation is different. Many of the applications for which Hamamatsu spectral devices are used are aimed at identification of a small set of materials. When spectral searching is used, the most accurate results are obtained when the spectra of known materials are collected on the same class of instrument, with the same sampling procedure, under the same conditions. The most effective implementations of spectra searching use libraries that have been acquired with these constraints in mind.
As the above discussion shows, there are few applications that Hamamatsu customers will encounter where library spectra are necessary. But when a library is necessary, where do you get them? Since libraries are used in chemical quantitative analysis, there are a number of sources of this information. The most accurate libraries are from commercial vendors who sell libraries. These libraries have been subjected to quality control procedures and generally are good quality spectra that represent the compound of interest. Companies such as Bio-Rad, ACD/Labs, and S.T. Japan-USA all supply both infrared and Raman libraries. For near-infrared libraries, Bio-Rad and S.T. Japan-USA can provide databases. In the UV and visible, Bio-Rad can provide commercial databases.
It should be noted that these libraries contain common materials collected under "standard spectral conditions," which means that they will not be exact matches to a spectra collected under different conditions. The instrument design and sampling both impact the spectrum and, in the case of Raman, the excitation wavelength. Finally, a user of libraries should recognize that even the most diligent library vendor can make a mistake and so the user should verify the spectrum themselves.
Libraries can help in the interpretation of a spectrum of a material. They are best used in a situation where there are a large number of choices for identification. Since many of the applications where Hamamatsu mini- and micro-spectrometers are applied are a very small subset of compounds or systems, it is much better to collect a spectrum of the material of interest under conditions representing the final analysis. If libraries are important, then commercial libraries can be purchased as long as the user recognizes the limitation of these libraries.
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