Overlapping of signals

Differentiation of simple analytical peaks is recommended whenever signals are superposed by background, as caused by turbid solutions or by opaque solids. 

The first application of differentiation to spectroscopy was, of course, the deconvolution of superposed peaks [41-43], which are frequently found in spectral investigations. From then on, many scientists analyzed peak overlapping by summation of synthetic signals, mostly of the Gaussian type [12,14,15, 44-48]. Derivatives, zero crossing, and extrema of different distribution functions such as Gauss, Lorentz, Student, T3, and others, are not difficult to estimate unless there are superpositions of two or more bands. For pure Gaussian functions, see Table 2-3. 

Some examples of peak overlapping are shown in Fig. 2-15. Tvo Gaussian peaks were added whose maxima do not have the same position on the abscissa. Even if the superposition of these two signals leads to two well-separated peaks, the positions of the maxima may not coincide with those of the original peaks. The positions will correspond only if the distance between the maxima is broad enough (Fig. 2-15 b). This will be treated quantitatively in Sec. 2.3.4. 

Whereas a mould was formed between the two maxima in Fig. 2-15 a, only a symmetrical peak with one maximum can be seen in Fig. 2-15 c. Two peaks of different height give a main peak with a shoulder (Fig. 2-15 d) or, if the original maxima are nearby and the distance between them is smaller than the greatest FWHM, only a distorted, un-symmetrical signal is developed (Fig. 2-15 f). The point at which the two peaks overlap 

Supposing two Gaussian peaks have the same amplitude (Ai =Af) and the same half width (FWHMj =FWHM2), then the shoulder limit is dependent on the 

---

Why do you suppose accidental overlap of signals is much more common in H NMR than in 13C NMR ... 

TABLE 20. Values of the H- H coupling constants as obtained from the spectra of 66-72 (, obtained by spectral simulation nd, not determined, due to overlap of signals)... 

Homonuclear coupling constants can also be determined from these subspectra with good digital resolution and relative free of overlap of signals. 

The reduction depicted in equation 53 is the basis of a method for determination of POV in the 0 to 10 meqkg range by FTNIR. Although the technical procedure is simple, data need PLS analysis because of the overlap of signals in the data acquisition region (4695 to 4553 cm- )235,435... 

If care is taken to avoid overlapping of signals from wells with high and low luciferase content, a typical sigmoid curve is obtained (Fig. 5.1). Photon emission should be considered proportional to the amount of luciferase only in the linear part of the curve. In our experience, we never found in reporter mice values of photon emission which were able to saturate the CCD camera sensor. Conversely, particular care must be taken in handling and interpreting raw measurements lower than the minimum threshold of linearity in this case, the photon emissions are not directly proportional to the amount of luciferase, and arithmetical processing like fold-induction normalization should be avoided. 

The FT-Raman spectra of the sulfur vulcanisates of the various model olefins do not contain the characteristic disulfide signal at 510 cm"1, but do contain the typical higher sulfide bands at 490, 460 and 440 cm"1 (Table 6.2). In addition, a new band at about 475 cm 1 is observed for the vulcanisates of 2-methyl-2-pentene and 3-hexene, which has not yet been assigned (hexasulfide ). Results of HPLC analysis have shown that the vulcanisate of 2,3-dimethyl-2-butene consists mainly of a mixture of disulfide to pentasulfide with about 15 mole% of disulfide [79]. This illustrates that FT-Raman spectroscopy is not very sensitive for the identification of disulfides. Because of an overlap of signals, FT-Raman does not provide detailed, quantitative information on the presence of the individual higher sulfides (S>2). 

Continuation of this process quickly becomes dreadfully complicated because of the severe overlap of signals. Many of the correlations have been drawn in with different types of lines for each of the different residues in the expanded view. The reader is invited to trace some of these correlations but cautioned to be wary of frustration. 

In most cases, structural characterization of carbosilane dendrimers is accomplished by multinuclear one-dimensional NMR spectroscopy (1H, 13C and 29Si). However, as larger dendrimers are characterized standard spectroscopic methods become less useful due to the overlap of signals. This problem has been elegantly circumvented as described in a recent paper by Tessier, Rinaldi and coworkers56. In this paper the researchers described the use of 1 H/13C/29Si triple resonance, 3D and pulse field gradient NMR techniques to... 

Hiere are two types of noise that may be evident in H NMR spectra of biological fluids namely instrument noise and chemical noise. Unlike instrument noise, chemical noise is related to the sample itself and is the result of the extensive overlap of signals from compounds that are low in abundance in the matrix and, individually, close to the detection limits of the spectrometer. Nonetheless, they give rise to apparently broad and weakly featured H NMR responses due to their frequency superimposition. It is generally true that for H NMR work on biofluids it is the chemical noise rather than instrument noise that usually limits the amount of recoverable spectral information. Normally only increasing the NMR frequency can allow recovery of the information that was in the chemical noise at lower frequencies. Furthermore, the problem of chemical noise interference varies in severity according to the biofluid type and chemical shift ranges that are under consideration for each fluid. 

---