Peak identification, qualitative analysis

Multidimensional gas chromatography has also been used in the qualitative analysis of contaminated environmental extracts by using spectral detection techniques Such as infrared (IR) spectroscopy and mass spectrometry (MS) (20). These techniques produce the most reliable identification only when they are dealing with pure substances this means that the chromatographic process should avoid overlapping of the peaks. 

The identification of the major peaks in the spectrum is accomplished by comparison with reference data (e.g. Wagner et al. 1978). The qualitative analysis of XPS spectra is more complex than for AES due to the presence of Auger peaks in addition to photoelectron peaks. If a photoelectron line of one element is close in energy to an Auger line of another, the problem may be resolved by taking spectra at two different photon energies. 

When a solution is tested, both analyte and solvent absorption bands will be present in the spectrum, and identification, if that is the purpose of the experiment, is hindered. Some solvents have rather simple IR spectra and are thus considered more desirable as solvents for qualitative analysis. Examples are carbon tetrachloride (CC14, only C-Cl bonds), choloroform (CHC13), and methylene chloride (CH2C12). The infrared spectra of carbon tetrachloride and methylene chloride are shown in Figure 8.21. There is a problem with toxicity with these solvents, however. For quantitative analysis, such absorption band interference is less of a problem because one needs only to have a single absorption band of the analyte isolated from the other bands. This one band can be the source of the data for the standard curve since the peak absorption increases with increasing concentration (see Section 8.11 and Experiment 25). See Workplace Scene 8.2. 

Once the spectrum is obtained, the question remains as to how to interpret it. We stated previously (Section 8.6) that IR spectra are characterized by rather sharp absorption bands (peaks) and each such peak is characteristic of a particular covalent bond in a molecule in the path of the light. Thus for qualitative analysis (identification and purity characterization), the analyst correlates the location (the wavenumber), the shape, and the relative intensity of a given peak observed in a spectrum with a particular type of bond. 

Another parameter often measured is the adjusted retention time, Ur. This is the difference between the retention time of a given component and the retention time of an unretained substance, tM, which is often air for GC and the sample solvent for HPLC. Thus, the adjusted retention time is a measure of the exact time a mixture component spends in the stationary phase. Figure 11.17 shows how this measurement is made. The most important use of this retention time information is in peak identification, or qualitative analysis. This subject will be discussed in more detail in Chapter 12. 

Qualitative and quantitative analyses with HPLC are very similar to those with GC (Sections 12.7 and 12.8). In the absence of diode array, mass spectrometric, and FTIR detectors that give additional identification information, qualitative analysis depends solely on retention time data, tR and C (Remember that tR is the time from when the solvent front is evident to the peak) Under a given set of HPLC conditions, namely, the mobile and stationary phase compositions, mobile phase flow rate, column length, temperature (when the optional column oven is used), and instrument dead volume, the retention time is a particular value for each component. It changes only when one of the above parameters changes. Refer to Section 12.7 for further discussion of qualitative analysis. 

For qualitative analysis, two detectors that can identify compounds are the mass spectrometer (Section 22-4) and the Fourier transform infrared spectrometer (Section 20-5). A peak can be identified by comparing its spectrum with a library of spectra recorded in a computer. For mass spectral identification, sometimes two prominent peaks are selected in the electron ionization spectrum. The quantitation ion is used for quantitative analysis. The confinnation ion is used for qualitative identification. For example, the confirmation ion might be expected to be 65% as abundant as the quantitation ion. If the observed abundance is not close to 65%, then we suspect that the compound is misidentified. 

X-ray spectrometry has benefited, as have other physico-chemical analysis methods, from the many recent advances in electronics and micro-computing. We have seen that, for qualitative analysis, software is used for the automatic identification of peaks. For quantitative analysis, the majority of equipment manufacturers provide highly extensive correction software packages. Finally, the automatic handling of samples in the spectrometer is well established (sample handlers with a capacity of 72 to 100 samples). 

While luminescence in vapor-deposited matrices accordingly should be a powerful technique for detection and quantitation of subnanogram quantities of PAH in complex samples, it suffers from two major limitations. First, it is obviously limited to the detection of molecules which fluoresce or phosphoresce, and a number of important constituents of liquid fuels (especially nitrogen heterocyclics) luminesce weakly, if at all. Second, the identification of a specific sample constituent by fluorescence (or phosphorescence) spectrometry is strictly an exercise in empirical peak matching of the unknown spectrum against standard fluorescence spectra of pure compounds in a hbrary. It is virtually impossible to assign a structure to an unknown species a priori from its fluorescence spectrum qualitative analysis by fluorometry depends upon the availabihty of a standard spectrum of every possible sample constituent of interest. Inasmuch as this latter condition cannot be satisfied (particularly in view of the paucity of standard samples of many important PAH), it is apparent that fluorescence spectrometry can seldom, if ever, provide a complete characterization of the polycyclic aromatic content of a complex sample. 

Modern X-ray spectrometers are equipped with computer software that is fully capable of identifying the possible elements from a spectrum. We can input the elements that possibly exist in the specimen into the software for qualitative analysis. The computer software will mark peak positions of the input elements in the spectrum. Also, the software will generate such peak lines with correct relative intensities in a spectrum, for example, a correct intensity ratio of Ka to Kfi. With computer assistance, the errors in element identification can be reduced to minimum. 

Peak identification in spectra is the primary task in qualitative analysis. For example, data in Figure 7.13 can be used to identify peaks in AES spectra. Table 7.1 lists the binding energies of elements in core levels. Such energies are the primary source for peak identification of XPS spectra. Peak identification is a non-trivial task in electron spectroscopy such as XPS. In additional to the spectrum features discussed in the previous section, other factors such as chemical shift and surface charge can complicate peak identification. The following section briefly reviews the important factors that, particularly for XPS, affect peak identification. 

Qualitative analysis depends on identification of the peaks on the video display of the MCA, which shows the counts accumulated vs. x-ray energy. The analyst should have a table or chart of the energies of all K and L lines arranged consecutively, as in Vol. 4 of [G.ll]. (Only ATa-line energies are listed in Appendix 7.) Or these data may be stored in the memory of the MCA, to be retrieved when needed. 

Real-time and data-dependent software [61] has also become an essential component of qualitative analysis applications such as metabolite identification [62] and quantitative analysis such as PK screening [63], Specialized software packages are able to perform tasks such as molecular weight confirmation, metabolite identification, peak integration, and calibration regression. 

Chromatographic methods also introduce a high level of uncertainty in qualitative and quantitative analysis, especially when low concentration levels are involved (e.g., CGC used for nanoliter samples of inorganic ions assay, with a limit of detection on the order of 10"9 mol/1, has an RSD larger than 5.0% 308). Because of the impossibility of having an ideal standard or RM for the analysis of most samples, the uncertainty of the qualitative analysis or peaks identification is high in chromatography.309... 

The energy of the peaks leads to the identification of the elements present in the sample (qualitative analysis), while the peak intensity provides the relevant or absolute elemental concentration (semi-quantitative or quantitative analysis) of lead. In the L XRF technique, electrons from the L shell are excited in a similar way and electrons from the M shell drop down to fill the vacancy. 

Qualitative analysis is, in principle, very simple with XRF and is based on the accurate measurement of the energy, or wavelength, of the fluorescent lines observed. Since many WD-XRF spectrometers operate sequentially, a 20 scan needs to be performed. The identification of trace constituents in a sample can sometimes be complicated by the presence of higher order reflections or satellite lines from major elements. With energy-dispersive XRF, the entire X-ray spectrum is acquired simultaneously. The identification of the peaks, however, is rendered difficult by the comparatively low resolution of the ED detector. In qualitative analysis programs, the process is simplified by overplotting so called KLM markers onto... 

MS is used for both quantitative and qualitative analysis (principally identification). Figure 8.18 is an analysis of air. The most abundant species is detected at an amu (atomic mass unit) equal to 28 and its value was 2.87 x 10 , which represents nitrogen. The second most abundant peak is at amu 32 at a value of 0.63 x 10 —oxygen. These values are representative of partial... 

While GC-FID is the traditional method for essential oil quantification, GC-MS is the most common analytical method for component identification. However, the wide concentration range of the analytes (from ppb to percentage levels), as well as the presence of numerous isomers (terpenes and oxygenated terpene structures), make qualitative analysis difficult. In addition, the mass spectra of these compoxmds are usually very similar, so peak identification often becomes very difficult and sometimes impossible. 

Qualitative Analysis. The retention time of a pure compound is constant under a specified set of experimental conditions, including the column, temperature, and flowrate. Consequently, this property may be used as a first step to identify an unknown compound or the individual components in a mixture. In a typical experiment, an unknown compound or mixture is injected into the injection port of a GLC, and the retention time(s) of the component(s) is (are) measiued. A series of known samples are then injected under the same conditions. Comparison of the retention times of the standard samples with those of the unknown allows a preliminary identification of the component(s) of the unknown. A convenient way of confirming that the retention times of a standard and the unknown are the same involves injecting a sample prepared by combining equal amounts of the two. If a single peak is observed in the chromatogram, the retention times of the standard and the unknown are identical. However, observation of the same retention time for a known and an unknown substance is a necessary but not sufficient condition to establish identity, because it is possible for two different compounds to have the same retention time. Independent confirmation of the identity of the unknown by spectral (Chap. 8) or other means is imperative. 

For qualitative analysis of polymers, it is not necessary to know the product of the reaction, since identification can be based on temperatures and relative heights at the maximum of several of the more prominent fragments once these have been established for known materials. Additional information about the degradation chemistry can be secured if one chooses peaks characteristic of specific products. 

The successful use of the adsorption chromatc ram for the qualitative analysis of the urinary ketosteroid complex depends upon very careful standardization of conditions. In particular, small changes in the moisture content of the adsorbent may lead to marked alteration in its properties, with consequent shifts in the positions of compounds in the elution pattern. It is, therefore, important that some independent parameter be used for the identification of the individual compounds present. It should also be mentioned that the peaks in the chromatographic elution patterns seldom consist of single individuals. 

Relative mass is an intrinsic molecular property which, when measured with high accuracy, becomes a unique and unusually effective parameter for characterization of synthetic or natural biomolecules. Mass spectrometry based methods can be broadly applied not only to unmodified synthetic biomolecules, but also to modified synthetic and natural biomolecules (e.g. glycosylated proteins). The level of mass accuracy one obtains during the measurement will depend on the capabilities of the mass analyser used. Quad-rupole and TOE instruments yield lower mass accuracies than sector or Fourier transform ion cyclotron resonance (FTICR) instruments. High mass accuracy is not only necessary for qualitative analysis of biomolecules present in a sample, but is necessary to provide unambiguous peak identification in a mass spectrum. 

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