Library searches infrared spectra

Figure 35 High contact pressure ATR infrared spectrum of the yellow contamination (top) along with the three best library matches for a search confined to the region... 

Searching the spectrum of an unknown chemical against a spectral library is a routine method used to identify chemicals. Most of the commercial infrared instruments include library search software that has several search algorithms to choose from. The search algorithm can sometimes have a strong effect on the library search result. This is due to the different ways the actual comparison between the spectra is done. Especially when the library and the unknown spectra have been measured differently (e.g. using solid KBr disk and cryodeposition GC/FTIR), the... 

In Figure 16.7, the infrared spectrum of a very small amount of a substance that was found as a contaminant on a printed-circuit board is shown. This infrared spectrum was measured by the microscopic transmission-reflection method, utilizing the reflection from the base metal. By a search of spectral data library, it became clear that this substance consisted mainly of abietic acid contained in the solder. 

FIGURE 3.28 An example of a normalized infrared spectrum, a spectral processing step frequently used before library searching. Note the zero to one y-axis scale. 

More frequently than chemical techniques, the spectroscopic methods of analysis are used for the determination of polymer chemical composition. Among these techniques the use of infrared (IR) absorption spectra as fingerprints for polymer identification is probably the most common. The IR absorption is produced tjy the transition of the molecules from one vibrational quantum state into another, and most polymers generate characteristic spectra. Large databases containing polymer spectra (typically obtained using Fourier transform infra-red spectroscopy or FTIR) are available, and modern instruments have efficient search routines for polymer identification based on matching an unknown spectrum with those from the library. For specific polymers, the IR spectra can reveal even some subtle composition characteristics such as interactions between polymer molecules in polymeric blends. 

RDF descriptors exhibit a series of unique properties that correlate well with the similarity of structure models. Thus, it would be possible to retrieve a similar molecular model from a descriptor database by selecting the most similar descriptor. It sounds strange to use again a database retrieval method to elucidate the structure, and the question lies at hand Why not directly use an infrared spectra database The answer is simple. Spectral library identification is extremely limited with respect to about 28 million chemical compounds reported in the literature and only about 150,000 spectra available in the largest commercial database. However, in most cases scientists work in a well-defined area of structural chemistry. Structure identification can then be restricted to special databases that already exist. The advantage of the prediction of a descriptor and a subsequent search in a descriptor database is that we can enhance the descriptor database easily with any arbitrary compound, whether or not a corresponding spectrum exists. Thus, the structure space can be enhanced arbitrarily, or extrapolated, whereas the spectrum space is limited. 

Peak identification is based on the comparison of normalized spectra representative for the peak with spectra of one or several standard compounds run in the same separation system and stored in a spectral library [107,116]. This approach is less powerful than for mass or infrared spectral searches due to the rather broad and featureless bands that typify absorption spectra. Absorption spectra of similar compounds and compounds with a chromophore well separated from the variation in molecular structure are often virtually identical. Also, spectral changes dependent on the experimental conditions (pH, mobile phase composition, temperature, etc.) occur frequently. For this reason user prepared local libraries tend to predominate over general libraries, in contrast to common practices in infrared and mass spectral searches. A favorable spectral match for an absorption spectrum by itself is not acceptable for absolute identification. 

As is true with infrared and nuclear magnetic resonance spectroscopy, large libraries of mass spectra (>150,000 entries) are available in computer-compatible formats,- Most commercial mass spectrometer computer systems have the ability to rapidly search all or pari of such files for spectra that match or closely match the spectrum of an analyte. 

Spectrometers are routinely attached to computers that can search for matches between the spectrum of an unknown and a library of known spectra. As with mass spectrometry, gas chromatographs can be attached to IR spectrometers and spectra can be determined as the individual components of a mixture elute from a column. As noted in Section 15.2, this technique is called gas chromatography/infrared spectroscopy, or GC/IR. 

Various infrared spectral databases or libraries are available, which contain collections of the infrared spectra of a number of specific chemical species. Spectral search or data retrieval is a technique enabling one to identify a material of unknown origin by comparing its spectrum with library spectra, or to make a guess at the chemical structure of the unknown material from the similarity of its spectmm to some library spectra. 

Searching spectral libraries may involve the use of inverted lists. These consist of each characteristic absorption band or emission line along with a list of corresponding numbered library spectra that include that particular band or line. A list for the spectrum of an unknown analyte can then be rapidly checked against the library lists. An example of part of an inverted list for an infrared spectral library is shown in Figure 1. It includes spectrum No. 66 among those listed with an absorbance band at 1220 cm and spectrum No. 105 among those listed with an absorbance band at 2730 cm . ... 

The use of computer programs to predict spectra from a knowledge of the molecular structure of the sample is still in its infancy. However, although a fair amount of work still needs to be done, there is no doubt that this type of approach will be of great importance to the analysts of the future. Certainly, the experience of a spectroscopist in the characterisation of infrared and Raman spectra will be essential for many years to come, just as is the ability of computer programs to search through libraries of spectra to find the best match to a sample s spectrum. 

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