Chromatogram interpretation

C. Chromatogram Interpretation. Tables III and IV show the distinction between using averages and heights of GPC in kinetic modeling. 

Gel permeation chromatography Is the method of choice for analysis of thermoplastic resin systems. Corrected for imperfect resolution, chromatogram interpretation yields accurate molecular descriptions, including theoretical, kinetic distributions (, ) The current research is designed to extend the utility of this analytical tool to the analysis of thermoset resins. 

Detector Nonlinearity Assessment. Detector linearity is implicitly assumed when conventional chromatogram Interpretation is accomplished. This assumption must be checked by plotting the the area under a narrow chrcmatogram versus concentration for various concentrations and fitting the data with a polynomicil to see if Beer s law holds. That is, the polynomial ... 

Pattern recognition and chromatogram interpretation can be a very difficult task in arson analysis. An excellent checklist in obtaining a chromatogram suitable for pattern recognition interpretation and steps used to interpret the chromatogram are given in Reference 156. 

Water-soluble polymers obtained through a radical polymerization [e.g., poly(acrylic acid) PAA] often contain sodium sulfate Na2S04 as a decomposition product of the initiator. The peak of Na2S04 is eluted before the dimer. In the interpretation of the chromatogram, a typical GPC program has to be truncated before the Na2S04 peak, or at a Mpaa value of about 200. The calibration curve in this region can be flattened by an additive small pore column as well, but the principle problem remains unsolved. 

Note With the mobile phase described a pale colored B-front appeared at h/ f 5-10, but it did not affect the interpretation of the chromatogram. 

ESI-MS has emerged as a powerful technique for the characterization of biomolecules, and is the most versatile ionization technique in existence today. This highly sensitive and soft ionization technique allows mass spectrometric analysis of thermolabile, non-volatile, and polar compounds and produces intact ions from large and complex species in solution. In addition, it has the ability to introduce liquid samples to a mass detector with minimum manipulation. Volatile acids (such as formic acid and acetic acid) are often added to the mobile phase as well to protonate anthocyanins. A chromatogram with only the base peak for every mass spectrum provides more readily interpretable data because of fewer interference peaks. Cleaner mass spectra are achieved if anthocyanins are isolated from other phenolics by the use of C18 solid phase purification. - ... 

In analysis of homopolymers the critical interpretation problems are calibration of retention time for molecular weight and allowance for the imperfect re >lution of the GPC. In copolymer analysis these interpretation problems remain but are ven added dimensions by the simultaneous presence of molecular weight distribution, copolymer composition distribution and monomer sequence length distribution. Since, the GPC usu y separates on the basis of "molecular size" in solution and not on the basB of any one of these particular properties, this means that at any retention time there can be distributions of all three. The usual GPC chromatogram then represents a r onse to the concentration of some avera of e h of these properties at each retention time. 

B. Measurement of Property Distributions for Copolymers. Figure 12 shows chromatograms of typical products in the copolymerization study (Column Code B2). Since the detector is responding to concentration, composition, and periiaps sequence length, the direct single detector interpretation as described for PMMA is not immediately applicable here. Tacticity variation is yet another consideration but ]s assumed of sa ond order importance for th samples (22). 

Interpretation of copolymer chromatograms in the literature does not include axial dispersion correction (3, 6) and little is known regarding it (5). The usual approach( is to utilize dual detectors and to assume that both detectors respond to at mos both composition and concentration. The two chromatograms then provide two equations in these two unknowns at each retention time. 

Time, wavelength and added volume in the above-mentioned examples are the domains of the measurement. A chromatogram is measured in the time domain, whereas a spectrum is measured in the wavelength domain. Usually, signals in these domains are directly translated into chemical information. In spectrometry for example peak positions are calculated in the wavelength domain and in chromatography they are calculated in the time domain. Signals in these domains are directly interpretable in terms of the identity or amount of chemical substances in the sample. 

Interpretive methods Involve modeling the retention surface (as opposed to the response surface) on the basis of experimental retention time data [478-480,485,525,541]. The model for the retention surface may be graphical or algebraic and based on mathematical or statistical theories. The retention surface is generally much simpler than the response surface and can be describe by an accurate model on the basis of a small number of experiments, typically 7 to 10. Solute recognition in all chromatograms is essential, however, and the accuracy of any predictions is dependent on the quality of the model. 

Vivo-Truyols, G., Schoenmakers, P.J. (2006). Chemical variance, a useful tool for the interpretation and analysis of two-dimensional chromatograms. J. Chromatogr. A 1120, 273-281. 

Because online separations provide such a wealth of information about target proteins, interpretation becomes of critical importance in order to make full use of the data. The first step in any analysis of LC-MS data involves integration and deconvolution of sample spectra to determine protein mass and intensity. In manual analysis (Hamler et al., 2004), users identify protein umbrellas, create a total ion chromatogram (TIC), integrate the protein peak, and deconvolute the resulting spectrum. Deconvolution of ESI spectra employs a maximum entropy deconvolution algorithm often referred to as MaxEnt (Ferrige et al., 1991). MaxEnt calculates... 

Rasmussen [82] describes a gas chromatographic analysis and a method for data interpretation that he has successfully used to identify crude oil and bunker fuel spills. Samples were analysed using a Dexsil-300 support coated open tube (SCOT) column and a flame ionisation detector. The high-resolution chromatogram was mathematically treated to give GC patterns that were a characteristic of the oil and were relatively unaffected by moderate weathering. He compiled the GC patterns of 20 crude oils. Rasmussen [82] uses metal and sulfur determinations and infrared spectroscopy to complement the capillary gas chromatographic technique. 

As early GC peaks elute in a few seconds or less, rapid scanning of the mass range of interest is necessary. Fast scanning also allows partially resolved GC peaks to be sampled several times,peak slicing, to facilitate identification of the individual components (Figure 12.5) provided that the dead volume of the interface is small compared to peak volumes. For the speedy interpretation of spectral data from complex chromatograms a... 

Sommerville, B.A., McCormick, J.P. and Broom D.M. (1994) Analysis of human sweat volatiles -an example of pattern-recognition in the analysis and interpretation of gas chromatograms. Pestic. Sci. 41, 365-368. 

Interpretation/report The GC retention time of a naphthalene standard and the mass spectrum of this peak confirm its presence. Because of the complexity of the chromatograms of the petroleum products and the pesticide sample, you find it impossible to examine the chromatogram of each. However, a comparison of the GC fingerprints (i.e., the matching of chromatographic peaks and comparison of peak ratios) clearly shows that the sample consists of naphthalene dissolved in kerosene. 

Figure 2.2 shows the total ion current trace and a number of appropriate mass chromatograms obtained from the pyrolysis gas chromatography-mass spectrometry analysis of the polluted soil sample. The upper trace represents a part of the total ion current magnified eight times. The peak numbers correspond with the numbers mentioned in Table 2.1 and refer to the identified compounds. The identification was based on manual comparison of mass spectra and relative gas chromatographic retention times with literature data [34, 35] and with data of standards available. In some cases unknown compounds were tentatively identified on the basis of a priori interpretation of their mass spectra (labelled tentative in Table 2.1). 

Representative multiple ion mass chromatograms of soil samples are presented in Fig. 5.4. These gas chromatography-mass spectrometric determinations of polychlorodibenzo-p-dioxin and polychlorodibenzofurans, and non-ortho polychlorobiphenyls in differing types of samples serve to exemplify the versatility of the procedure for such analyses. The gas chromatography-mass spectrometric data were usually uncluttered by extraneous components, and interpretation of the data was routinely straightforward. 

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