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Generalized 2D Correlation Spectroscopy in Practice
4.3 FEATURES ARISING FROM FACTORS OTHER THAN BAND INTENSITY CHANGES
In this section, we present a systematic way to handle some complex features appearing in 2D correlation spectra due to factors not related to the straightforward spectral intensity changes. In particular, the effect of band position shift and line broadening on 2D spectra will be discussed. Features generated from such effects belong to special cases, which cannot be readily interpreted in terms of the simple cross peak sign rules established in Section 2.3 of Chapter 2.
4.3.1 EFFECT OF BAND POSITION SHIFT AND LINE SHAPE CHANGE
The 2D correlation scheme described in this book is focused on the analysis of changes in spectral features induced by an external perturbation. The most common variations in the spectral features are a simple increase or decrease in the band intensities. Such intensity variations can be easily interpreted as a reflection of some perturbation-induced population change in moieties contributing to the spectral intensities. However, there are many other cases where more complex changes in spectral features beyond simple intensity variations are involved.818 Two important examples of complex spectral feature variations are: band position shift and line broadening phenomena. Both cases are very commonly observed when the perturbation used in 2D correlation analysis strongly affects the system environment such that the nature of the constituent response to the spectral probe itself is altered. Typical examples include the composition-or temperature-induced changes in the wavenumber position and line shape of IR bands caused by the altered strength of hydrogen bonding interactions which affect molecular vibrations.
The effect of spectral variations other than intensity changes cannot be analyzed in a simple manner based on the basic assumption of one-to-one correspondence between the position of a correlation peak and spectral band. Very often, surprisingly complex (but fortunately very characteristic) features comprising a cluster of multiple correlation peaks may appear from a single band with varying position or width in the corresponding 2D correlation spectra. Such 2D spectral features are not an artifact but legitimate signature patterns of complex spectral changes manifested in the correlation spectra. However, overlooking the possible existence of multiple correlation peaks assignable to a single spectral band often leads to erroneous interpretation of 2D spectra. This section, therefore, provides a guide to the detection and interpretation of such complex spectral features.
The existence of a characteristic cluster of multiple correlation peaks in 2D spectra arising from the position shift of a single band was well recognized from the very early days of 2D correlation spectroscopy.8 The so-called four-leaf-clover cluster pattern of synchronous peaks generated from X-ray scattering data was interpreted as the result of a position shift of the scattering maximum.
Features Arising from Factors other than Band Intensity Changes
Gericke et al. reported the first systematic study of the effect of position shift and broadening of an IR band on 2D correlation spectra using simulated data.9 Similar simulation studies were carried out by Czarnecki,1011 Elmore and Dluhy,1213 and others1415 to identify the characteristic features of 2D peak patterns arising from the position shift and broadening of bands. Kim and Jeon compiled an extensive list of simulation results for cases where multiple band shift and broadening possibilities were combined.16 These studies based on simulation analysis all point to the fact that the characteristic cluster patterns of 2D spectra arising from band shift and broadening are distinct and well recognizable. The pitfall of overinterpretation of multiple correlation peak clusters arising from a single band as the false indication of a multiple band feature is discussed.1718
4.3.2 SIMULATION STUDIES
The effects of complex spectral feature variations, such as band shift and line broadening, are best visualized with simulated model data emphasizing the specific aspect of spectral changes. Figure 4.7 shows four examples of such simulated spectral data comprising Lorentzian peaks in an arbitrary spectral region between 1000 and 2000 cm-1. Fig. 4.7(A) represents the case for spectral variations arising from the classical intensity changes of two highly overlapped bands with fixed band position and relative line shape. One band (located at 1450 cm-1) decreases in the intensity quickly, while the other band (at 1550 cm-1) increases in intensity much more gradually, as indicated by the two arrows. For this simulation study, less than 20 % of intensities are changed for any part of the spectrum.
Figure 4.7(B) shows the case where the position of an isolated single band, with a fixed intensity and line shape, is gradually shifted along the spectral axis in the direction of the arrow. For illustrative purpose, the extent of band shift in this figure is carried out to about 25 % of the band width. It should be pointed out that even a much lower extent of band shift, say less than 0.5 % of the band width, will also generate detectable characteristic features of band shift in the corresponding 2D spectra. Such a small level of band shift cannot be readily detected in a typical stack of 1D spectra such as that shown in Fig. 4.7(B). The high sensitivity of 2D spectra to band shift is not really a burden, but actually a useful asset to be exploited for the detection of subtle features, as long as the expected characteristic pattern of 2D spectra is known.