Mass spectral interpretation applications

There is no one-and-only approach to the wide field of mass spectrometry. At least, it can be concluded from the preceding pages that it is necessary to learn about the ways of sample introduction, generation of ions, their mass analysis and their detection as well as about registration and presentation of mass spectra. The still missing issue is not inherent to a mass spectrometer, but of key importance for the successful application of mass spectrometry. This is mass spectral interpretation. All these items are correlated to each other in many ways and contribute to what we call mass spectrometry (Fig. 1.4). 

Another approach to mass spectral interpretation is to compare the spectrum of an unknown with those of compounds believed to be related to the unknown. This method is particularly applicable in natural product studies, in which complete fragmentation patterns are difficult to rationalize. The large and complex molecules often have a tendency to rearrange either before or after electron. The spectra are nonetheless reproducible and can be used for comparative purposes. 

An example of how information from fragmentation patterns can be used to solve structural problems is given in Worked Example 12.1. This example is a simple one, but the principles used are broadly applicable for organic structure determination by mass spectrometry. We ll see in the next section and in later chapters that specific functional groups, such as alcohols, ketones, aldehydes, and amines, show specific kinds of mass spectral fragmentations that can be interpreted to provide structural information. 

The batch must comply to the requirements of the monograph. However, the most important control is the application of the test(s) for which the substance is intended. It is usual for at least one laboratory (usually the Ph. Eur. laboratory) to apply all tests of the monograph. The structure of the substance must be clearly identified by comparison of the IR spectrum to spectra published in the literature and interpretation of the NMR and mass spectral data. 

N.A.B. Gray, A. Buchs, D.H. Smith and C. Djerassi, Application of artificial intelligence for chemical inference. Part XXXVI. Computer assisted structural interpretation of mass spectral data, Helv. Chim. Acta, 64 (1981) 458-470. 

The above experiments are generally difficult to perform and the interpretation of the results may not necessarily be straightforward. The low abundance of the neutral products collected and the likelihood of mass spectral interference between reagents and products make these techniques applicable only to special cases. An independent approach to this problem has been proposed by Marinelli and Morton (1978) who have used an electron-bombardment flow reactor allowing in principle for larger collection of neutral products followed by glc and mass spectral analysis. 

Many types of organic compounds exhibit characteristic mass spectral behaviour, a knowledge of which is useful in the interpretation of their spectra. The following section provides an introduction to the interpretation of mass spectra of simple organic compounds but readers should consult the texts listed in the references.4 Some caution is needed in the application of this information since... 

Mass Spectrometry Basics provides authoritative yet plain-spoken explanations of the basic concepts of this powerful analytical method without elaborate mathematical derivations. The authors describe processes, applications, and the underlying science in a concise manner supported by figures and graphics to further comprehension. The text provides practical approaches to interpreting mass spectral data and step-by-step guides for identifying chemically relevant compounds. Additionally, the authors have included an extensive reference section and a quick guide to each chapter that offers immediate access to key information. 

A second aspect of analytical methodology that concerns me is the lack of suitable standards. In my laboratory and certainly in many other laboratories the application of HPLC, glass capillary GC, and glass capillary GC-mass spectrometry-computer systems allows us to separate relatively easily hundreds of individual aromatic compounds, e.g., 9 to 12 isomers of C-3 phenanthrenes. However, there are no commercial sources for standards to verify our identifications or calibrate the quantification of these compounds. Synthesis of all isomers is clearly a monumental task. In the interim, perhaps the analytical chemists interested in this problem should be encouraged to develop systematic rules for interpreting glass capillary GC and HPLC retention indices, subtle mass spectral differences, and UV-fluorescence spectra. 

Differences between different formulations were detected using a mass spectral based chemical sensor with static headspace introduction. Results were validated using traditional GC/MS with SBSE-thermal desorption introduction. Advantages of using the chemical sensor include fast sample throughput and easy to interpret results. For this particular application, flavor formula 1 was found to be very similar to flavor formula 4. This result was also confirmed by the flavor supplier. 

The application of MS/MS or in-source-CID for identification of pollutants brought problems, since no product ion libraries were available. Product ion spectra either had to be interpreted for compound identification or standard comparison had to be performed provided that standards were available. To overcome this disadvantage, analysts prepared their own libraries suitable for the instrument generated on or for instruments of the same type. Attempts at generating mass spectral libraries for polar compounds determined by API methods were reported and the results obtained with their application in real environmental samples were discussed [291, 292]. The generation of IT-MS product ion spectra and their use for identification provided the most promising results so far. The preparation of a universally applicable product ion library for the identification of polar compounds, i.e. of a library which could work with various equipments for identification, still remains wishful thinking. 

Kleywegt, G. J., van t Klooster, H. A. Chemical Applications of PROLOG. Interpretation of Mass Spectral Peaks. Trends Anal. Chem. 1987, 6, 55-57. 

Intensive applications of pattern recognition methods in chemistry were started with pioneering works about spectral interpretations by Isenhour, Jurs, and Kowalski (1969 - 1971). Numerous papers deal with the automatic prediction of molecular structures from mass spectra, infrared spectra and nuclear magnetic resonance spectra (Chapter 13). Predictive abilities of 80 to 95 % are typical of these applications. 

Interpretation of low resolution mass spectra is the field with the greatest number of applications of pattern recognition techniques in chemistry. Numerous methods of preprocessing, feature selection, training, and evaluation have been tested with mass spectral data in about 100 papers. Probably the first application of pattern recognition ideas in mass spectrometry has been reported by Raznikov and Talroze C235J this Russian paper is summarized in C224J. 

This edition has been completely updated, revised, and expanded. To achieve this, the previous approach of having each chapter be self-contained has been abandoned repetition has been reduced to a minimum so that more topics could be covered in more detail. The topics of chromatography and mass spectrometry have been greatly expanded, when compared with the sixth edition, to better reflect the predominance of chromatography and mass spectrometry instrumentation in modern laboratories. The equally important topic of NMR, expanded in the last edition to focus on ETNMR, C, and 2D NMR spectral interpretation, now includes time domain NMR (relaxometry) and an overview of low-field, benchtop, and miniature instrumentation. The topic of electron spin resonance spectroscopy (ESR, EPR) has been added due to the recent availability of small, low-cost ESR instrumentation and its impact on materials characterization and bioanalysis. Chapter 3 has therefore been renamed to reflect the inclusion of ESR/EPR. Eorensic science applications have been added in appropriate chapters. 

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