Commercial spectral libraries

Identification of known compounds The most common application of NMR in forensic analysis is its use in the identification of materials in drug seizures. For this purpose the analyst compares the NMR spectra for the exhibit with those for authentic materials, in much the same way as for IR spectra, allowing the rapid identification of illicit drugs. When the spectra being compared are from spectrometers of different magnetic field strengths, or if they are determined using different solvents or at different concentrations, the analyst must be aware that the appearance of spectra may appear to be very different. Because these kinds of differences are usually minor for NMR spectra (which are also much simpler in appearance than spectra), most commercial spectral libraries are for spectra. However, modern spectrometers allow users to create, maintain, and search their own proton spectral libraries. Also, a number of books are available that contain collections of proton spectra of chemicals of forensic interest. 

Eatty acids from commercial fats and oils, such as peanut oil, are extracted with methanolic NaOH and made volatile by derivatizing with a solution of methanol/BE3. Separations are carried out using a capillary 5% phenylmethyl silicone column with MS detection. By searching the associated spectral library students are able to identify the fatty acids present in their sample. Quantitative analysis is by external standards. 

Decades of combined spectral and chemistry expertise have led to vast collections of searchable user databases containing over 300 000 UV, IR, Raman and NMR spectra, covering pure compounds, a broad range of commercial products and special libraries for applications in polymer chemistry (cf. Section 1.4.3). Spectral libraries are now on the hard disks of computers. Interpretation of spectra is frequently made only by computer-aided search for the nearest match in a digitised library. The spectroscopic literature has been used to establish computer-driven assignment programs (artificial intelligence). 

Whatever the analyser and the analytical conditions chosen, the spectrum obtained corresponds to the sum of the spectra of all the individual compounds present in the sample investigated. Spectra have thus to be cautiously interpreted using a set of reference data from single commercial or synthesised compounds, reference raw and aged natural substances and mass spectral libraries. 

A common method for identification of organic compounds is mass spectrometry (MS) in combination with GC. After separation of the component by GC the mass spectrometer transform the analyte into gaseous ions in vacuum in the ion source. For electron impact ionization this results in different mass fragmentation patterns with different mass-to-charge ratios (m/z). From this fragmentation pattern it will be possible to identify the compound by comparison with commercial mass spectral libraries. Identification of unknown compounds can be facilitated by... 

The Wiley Registry of Mass Spectral Data, commercially available at John Wiley Sons, Inc., http //www.wiley.com/cda/ product/0 0471515930 desc 3047,00.html - The NIST98-NIST/EPA/NIH Mass Spectral Library, commercially available at the National Institute of Standards and Technology, http //www.sisweb.com/software/ ms/nist98.htm) and... 

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... 

Numerous mass spectra of tocopherols and tocotrienols have been published and many are available in the NIST/EPA/NIH Mass Spectral Library (2011) and MassBank (2011). In addition to the above chromatographic and nonchromatographic methods for tocol analysis, kits are also commercially available for the ELISA (Enzyme-linked im-munoabsorbent assay) of vitamin E. 

The peak identification for the chromatogram shown in Figure 6.1.25 was done using MS spectral library searches. This identification is not always possible, since most compounds with a higher MW are not found in the commercial mass spectral libraries (such as NIST 2002, Wiley 7. etc.). The similarity between the spectra in each series of compounds can be used for peak identification, even when the compound is not found in the mass spectral library. This is exemplified in Figure 6.1.26, which shows the spectra of the B series of compounds shown in Table 6.1.10. 

Some of the peak assignments in Tabie 6.7.20 are tentative because the mass spectra of many compounds in poiy(methyi methacrylate) pyrolysate are not available in the commercial mass spectral libraries. For example, 2-methylene-4,4-dimethyl-pentanedioic acid dimethyl ester (MW = 200) and 2,4,4 frimethyl-2-pentenedioic acid dimethyl ester (MW = 200) were assigned based on the mass spectra shovm in Figures 6.7.28 a and 6.7.28 b. 

The spectrum of 2-methyl-2-propenoic acid dodecyl ester is available in commercial mass spectral libraries (NIST 2002, Wiley 7 and previous versions) and is shown in Figure 6.7.36. 

The spectrum of 4-phenylbenzene-1-thiol is almost identical to that of diphenyl sulfide (retention time 91.83 min.), which has the spectrum shown in Figure 12.1.4 and is available in commercial mass spectral libraries. 

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. 

Spectral libraries play a key role in the work of the modern-day spectroscopist (39). Applications include contaminant analysis/identification, identity testing of bulk drug substances and intermediates, and as a tool for the structural elucidation of new chemical entities. A list of some of the types of commercially available spectral libraries is found in Table 1. Although few FT-Raman spectral libraries are presently available (40), with the growing interest in the technique, many libraries are in development. In addition, the creation of spectral libraries of proprietary compounds in the pharmaceutical analytical laboratory allows for rapid and efficient identity testing of key intermediates and proprietary bulk drug substances. 

Table 1 Listing of Commercially Available IR and Raman Spectral Libraries... 

Despite recent advances, the problem of spectral libraries size build-up, and search speed receives still considerable amount of attention. Most of the commercial databases to date use Fast Fourier Transform (FFT) for spectra compression. However, the past ten years have brought explosive growth of wavelet applications in signal processing. The IR spectra show many ab-... 

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