Origins of spectra

The frequency emitted or absorbed when an atomic or molecular system undergoes a change in state is related to the absolute value of the difference in energy between the two states by 

Transitions of the outer (or valence) electrons in the atom or molecule 

Change of spin orientation of nucleus in a magnetic field 

Details of electronic structure and bond energies in molecules 

Magnetic environment of the spinning nucleus from which structure is inferred 

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For literature see Franck, Phys. Zeits. (1918), or Foote and Mohler, Origin of Spectra, Chem. Publishing Co. 

Spectroscopic processes rely on the fact that electromagnetic radiation (EMR) interacts with atoms and molecules in discrete ways to produce characteristic absorption or emission profiles. This is examined in more detail in Section 2.2. Before we can look into the origin of spectra, we have to look at some of the properties of EMR. 

The origin of spectra, absorption of radiation by atoms, ions and molecules... 

The practice of analytical spectroscopy preceded the development of the theories concerning the origin of spectra by a number of years. Bunsen and Kirchhoff studied spectra produced by salts and salt solutions heated in flames and noted the characteristic spectral line emissions of a number of elements. They also observed that substances absorb energy most strongly at the same wavelengths at which emission occurs. Their results led Kirchhoff to state that the power of emission is equal to the power of absorption for all... 

Multivariate data analysis usually starts with generating a set of spectra and the corresponding chemical structures as a result of a spectrum similarity search in a spectrum database. The peak data are transformed into a set of spectral features and the chemical structures are encoded into molecular descriptors [80]. A spectral feature is a property that can be automatically computed from a mass spectrum. Typical spectral features are the peak intensity at a particular mass/charge value, or logarithmic intensity ratios. The goal of transformation of peak data into spectral features is to obtain descriptors of spectral properties that are more suitable than the original peak list data. 

There is a small peak one mass unit higher than M m the mass spectrum of ben zene What is the origin of this peak d What we see m Figure 13 40 as a single mass spectrum is actually a superposition of the spectra of three isotopically distinct benzenes Most of the benzene molecules contain only and H and have a molecular mass of 78 Smaller proportions of benzene molecules contain m place of one of the atoms or m place of one of the protons Both these species have a molecular mass of 79... 

The production of characteristic X rays is determined by the cross sections discussed above, but the observed X-ray spectra include both these characteristic peaks and a continuous background radiation. A detailed investigation of the origin of... 

A second type of structural information can be deduced from the hyperfine splitting in EPR spectra. The origin of this splitting is closely related to the factors that cause spin-spin splitting in proton NMR spectra. Certain nuclei have a magnetic moment. Those which are of particular interest in organic chemistry include H, " N, F, and P. 

Detailed discussions of some of the remaining peaks in Figures 7 and 8 and in the mass spectra of 10a and the D20-exchanged analogs is of more interest to the mass spectrometrist than to the carbohydrate chemist. The probable origins of these peaks will be discussed here, however, because there will be occasions when the carbohydrate chemist must dig into a spectrum in order to satisfy himself that he has interpreted the spectrum in terms of a correct structure. 

A detailed discussion of the origin of emission spectra is beyond the scope of this book but a simplified treatment is given in Chapter 21, Sections 21.1 and 21.2. 

In similar fashion, we have plotted the spectrum of a third sample which contains 3 concentration units of Component I and none of Component 2. Of course, this spectrum also lies in the same direction from the origin as the first spectrum and at 3 times the distance. It is clear that, when we use this approach to plot the spectra of samples which contain only Component 1, each such spectrum must lie somewhere along a line extending from the origin of the data space in some unique direction that is determined by the relative absorbances of Component 1 at each of the wavelengths plotted. 

Normalization, is an adjustment to a data set that equalizes the magnitude of each sample. In other words, normalization removes all information about the distance each data point lies from the origin of the data space but preserves the direction. Normalization has a relatively limited number of special applications. For example, it is frequently used a pre-processing step in preparing reference spectra for a qualitative identification library. The idea is to retain only the information that qualitatively distinguishes one sample from another while removing all information that could separate two samples of identical composition but different concentrations. 

After the possible structures are obtained, predict their mass spectra by examining the mass spectra of similar structures. Also, the GC retention time may eliminate certain structures or isomers. Discuss these results with the originator of the sample to determine the most probable structure. With experience, it is usually possible to determine which fragment peaks are reasonable for a given type of structure. 

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