Peak overlap

Further, peak overlap results in nonlinear detector response vs concentration. Therefore, some other detection method must be used in conjunction with either of these types of detection. Nevertheless, as can be seen from Figure Ilf, chiroptical detection can be advantageous if there is considerable overlap of the two peaks. In this case, chiroptical detection may reveal that the lea ding and tailing edges of the peak are enantiomerically enriched which may not be apparent from the chromatogram obtained with nonchiroptical detection (Fig. He). 

The minimum detection limit, MDL, of an isolated peak on a uniform background is proportional to the square root of the FWHM. So a 20% reduction in spectrometer resolution will produce about a 10% improvement in MDL. If there is peak overlap, however, then it can be shown that a 20% improvement in resolution can reduce the interference between overlapping peaks by a factor of 3, which gives about a 50% improvement in MDL. 

Overall a customer needs to know under what circumstances it is best to use either the electron-beam techniques of EDS and WDS or the X-ray technique of XRF for an analysis problem. If both are equally available, the choice usually resides in whether high spatial resolution is needed, as would be obtained only with electron-beam techniques. If liquids are to be analyzed, the only viable choice is XRF. If one s choice is to use electron-beam methods, the further decision between EDS and WDS is usually one of operator preference. That is, to commence study on a totally new sample most electron-beam operators will run an EDS spectrum first. If there are no serious peak overlap problems, then EDS may be sufficient. If there is peak overlap or if maximum sensitivity is desired, then WDS is usually preferred. Factored into all of this must be the beam sensitivity of the sample, since for WDS analysis the beam current required is lO-lOOx greater than for EDS. This is of special concern in the analysis of polymer materials. 

Peak overlaps can be eliminated simply by peak fitting and subtraction. 

Peak overlaps that totally obscure one of the elements in the spectrum have been shown to be separable. A Co—Ni alloy film under a Cu film is a combination that produces a spectrum where the Ni peaks are all overlapped by Cu or Co peaks, or... 

PVP K-15 and K-30 peaks are symmetric in water and water/methanol, except for the TSK GM-PWxl column in water. This suggests an interaction between PVP K-15 and K-30 with the TSK GM-PWxl column in water. System peaks overlap with the low molecular weight tails of the PVP K-15 and K-30 peaks for all four columns in water. In water/methanol the separation of the system peaks from the polymer peaks is much better for all four columns. 

GC using chiral columns coated with derivatized cyclodextrin is the analytical technique most frequently employed for the determination of the enantiomeric ratio of volatile compounds. Food products, as well as flavours and fragrances, are usually very complex matrices, so direct GC analysis of the enantiomeric ratio of certain components is usually difficult. Often, the components of interest are present in trace amounts and problems of peak overlap may occur. The literature reports many examples of the use of multidimensional gas chromatography with a combination of a non-chiral pre-column and a chiral analytical column for this type of analysis. 

Because of peak overlappings in the first- and second-derivative spectra, conventional spectrophotometry cannot be applied satisfactorily for quantitative analysis, and the interpretation cannot be resolved by the zero-crossing technique. A chemometric approach improves precision and predictability, e.g., by the application of classical least sqnares (CLS), principal component regression (PCR), partial least squares (PLS), and iterative target transformation factor analysis (ITTFA), appropriate interpretations were found from the direct and first- and second-derivative absorption spectra. When five colorant combinations of sixteen mixtures of colorants from commercial food products were evaluated, the results were compared by the application of different chemometric approaches. The ITTFA analysis offered better precision than CLS, PCR, and PLS, and calibrations based on first-derivative data provided some advantages for all four methods. ... 

To better understand the differences in their catalytic behavior, the catalysts were characterized by XRD and UV-vis DRS. Unfortunately, except for the peak at 77.6° 26 (311 diffraction), the other Au diffraction peaks overlapped with those of y-Al203. The size of the coherent domains of Au, listed in Table I, were estimated using the width of this diffraction peak and the Debye-Sherrer equation. They showed that catalysts of both groups A and C had small coherent domains, whereas those of group B had large domains. 

There is little information available on their setting and structure. Bagby Greener (1985) used Fourier transform infrared spectroscopy (FTIR) to examine the cement-forming reaction between zinc oxide and a mixture of EBA and n-hexyl vanillate. Although they found evidence for reaction between zinc oxide and EBA, they were unable to find any for reaction between zinc oxide and n-hexyl vanillate because of peak overlaps, the minor concentration of n-hexyl vanillate and the subtle nature of the spectral changes. 

The TED and XRD patterns revealed that the deposit is not amorphous carbon but nanocrystalline diamond. Nonetheless, the 514-nm excited Raman spectra do not exhibit a clear diamond peak at 1332 cm though the peak due to the sp -bonded carbon network appears at 1150 cm The Raman cross section of the sp -bonded carbon network with visible excitation is resonantly enhanced [43, 48-50]. It consequently makes the 1332 cm diamond peak overlap with the peaks due to sp -bonded carbon. 

For all degrees of peak overlap it is well established that peak height is a more accurate measure of sample size than peak area for symmetrical peaks (277,279). For either method the error increases for disproportionate peak sizes. For tailed peaks errors in either peak height or area can assume large proportions using perpendicular drop method (279,281). In general, the most... 

An automated procedure to measure peak widths for peak capacity measurements has been proposed.35 Since peak width varies through the separation, the peak capacity as conventionally measured depends on the sampling procedure. The integral of reciprocal base peak width vs. retention time provides a peak capacity independent of retention time, but requires an accurate calculation of peak width. Peak overlap complicates automation of calculation. Use of the second derivative in the magnitude-concavity method gives an accurate value of the standard deviation of the peak, from which the base peak width can be calculated. 

In principle, any type of sample can be analysed by SEC provided that it can be solubilised and that there are no enthalpic interactions between sample and packing material. By definition then, this technique cannot be carried out on vulcanisates and even unvulcanised fully compounded rubber samples can present problems due to filler-rubber interactions. The primary use of SEC is to determine the whole MWD of polymers and the various averages (number, viscosity, weight, z-average) based on a calibration curve and to allow qualitative comparisons of different samples. Many commercial polymers have a broad MWD leading to strong peak overlap in the chromatography of complex multicomponent systems. 

This book is organized into five sections (1) Theory, (2) Columns, Instrumentation, and Methods, (3) Life Science Applications, (4) Multidimensional Separations Using Capillary Electrophoresis, and (5) Industrial Applications. The first section covers theoretical topics including a theory overview chapter (Chapter 2), which deals with peak capacity, resolution, sampling, peak overlap, and other issues that have evolved the present level of understanding of multidimensional separation science. Two issues, however, are presented in more detail, and these are the effects of correlation on peak capacity (Chapter 3) and the use of sophisticated Fourier analysis methods for component estimation (Chapter 4). Chapter 11 also discusses a new approach to evaluating correlation and peak capacity. 

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