Chromatographic data

EthynodlolDia.ceta.te, Ethynodiol diacetate has been used alone, and in combination with an strogen, as an oral contraceptive and to treat disorders associated with progesterone deficiency (76). It may be crystallised from aqueous methanol (77) and is soluble in chloroform, ether, and ethanol sparingly soluble in fixed oils and insoluble in water (76). Extensive spectral and chromatographic data have been compiled (78). 

Constmction and checking of caUbrated curves Direct data acquisition from chromatographs Data collection for analytical instmments Entry of instmmental readings Manual results entry... 

Probably the best compromise for silica based stationary phases is to use corrected retention volume data for solutes eluted at a (k ) of greater than 5 and only compare chromatographic data for solutes of approximately the same molecular size. 

Mobile Phase Compressibility Its Effect on the Interpretation of Chromatographic Data in LC... 

Table 1. Physical and Chromatographic Data for 70 Solutes in 5 %v/v Ethyl Acetate in n-Hexane...

Whether the optimum phase system is arrived at by a computer system, or by trial and error experiments (which are often carried out, even after computer optimization), the basic chromatographic data needed in column design will be... 

Data analysis is one aspect of multidimensional analyses that must be optimized in the future. The analysis of chromatographic data beyond one dimension is still exceedingly problematic, especially in the analyses of highly complex mixtures. Better software may need to be developed in order to analyze two- and three-dimensional peaks due to their complexity. Three-dimensional data is only useful today in terms of fingerprinting and often that even requires extensive data analysis. A great deal of research must still be carried out to make the interpretation and quantification of multidimensional data easier. 

Data queries for chromatographic data, literature references, analytical conditions... 

The four queries were examined against a list of samples tested on Whelk CSP that constitutes our search domain. Search results are summarized in Table 4-3. Of the 616 3D structures in this database list, 370 fit at least one of the query (one sample may fit more than one query) and 335 are given as resolved according to chromatographic data or information reported in the field comment. Query 2 retrieved the largest number of compounds with a high percentage of resolved samples in the hit list. While the number of hits retrieved with Query 1 is lower, this query provided a similar proportion of resolved samples (93 %). 

Such an expert system can also be adapted for the evaluation of data in the published literature. However, this point raises a number of practical questions. A better exploitation of chromatographic data in this field would require an important effort to be made by analysts to constitute standards for quality control and interpretation... 

The mixture is identical in each example. The peaks are shown separated by 2, 3, 4, 5 and 6 (a) and it is clear that a separation of 6a would appear to be ideal for accurate quantitative results. Such a resolution, however, will often require very high efficiencies which will be accompanied by very long analysis times. Furthermore, a separation of 6o is not necessary for accurate quantitative analysis. Even with manual measurements made directly on the chromatogram from a strip chart recorder, accurate quantitative results can be obtained with a separation of only 4a. That is to say that duplicate measurements of peak area or peak height should not differ by more than 2%. (A separation of 4a means that the distance between the maxima of the two peaks is equal to twice the peak widths). If the chromatographic data is acquired and processed by a computer, then with modem software, a separation of 4a is quite adequate. 

The method of calculating chemical composition of solubilized polymer was tested in two different ways. The sum of polymerized monomers calculated from chromatographic data should approximate total solids in the latex samples. Figure 5 compares calculated solids contents with total solids measiured by the conventional gravimetric method. A good correlation was... 

Figure 9. Chromatographic data on AN/S latex ((O) amount of soluble polymer ( J]) composition of soluble polymer, % acrylonitrile (A) amount of insoluble...

According to this relation, the distribution function K can be estimated from the chromatographic data of a solute using pure solvents as the mobile phase. Equation 4.25 shows that the difference j for each component of the mobile phase can be calculated without the adsorption isotherm data. 

The A2 parameter ean be ealeulated from chromatographic data by transfomfing the fundamental equation (Equation 4.22) and substituting values obtained from ehromatograms for eoneentration 0.3, 0.5, and 0.7 of one of the components, or by transformation of Equation 4.22 to the linear form assuming that... 

Based on the partitioning of the solute between a polar mobile and an apolar sta-honary phase (RPLC), the chromatographic data were expressed as retention factors (logfe) given by ... 

O. M. Kvalheim, Interpretation of direct latent-variable projection methods and their aims and use in the analysis of multicomponent spectroscopic and chromatographic data. Chemom. Intell. Lab. Syst., 4 (1988) 11-25. 

Sometimes it is claimed that the double-centered biplot of latent variables 1 and 2 is identical to the column-centered biplot of latent variables 2 and 3. This is only the case when the first latent variable coincides with the main diagonal of the data space (i.e. the line that makes equal angles with all coordinate axes). In the present application of chromatographic data this is certainly not the case and the results are different. Note that projection of the compounds upon the main diagonal produces the size component. 

P.J. Dunlop, C.M. Bignell, J.F. Jackson, D.B. Hibbert, Chemometric analysis of gas chromatographic data of oils from Eucalyptus species. Chemom. Intell. Lab. Systems 30 (1995) 59-67. K. Varmuza, F. Stangl, H. Lohninger and W. Werther, Automatic recognition of substance classes from data obtained by gas chromatography, mass spectrometry. Lab. Automation Inf. Manage., 31 (1996) 221-224. 

In some cases a principal components analysis of a spectroscopic- chromatographic data-set detects only one significant PC. This indicates that only one chemical species is present and that the chromatographic peak is pure. However, by the presence of noise and artifacts, such as a drifting baseline or a nonlinear response, conclusions on peak purity may be wrong. Because the peak purity assessment is the first step in the detection and identification of an impurity by factor analysis, we give some attention to this subject in this chapter. 

P.J. Gemperline, Target transformation factor analysis with linear inequality constraints applied to spectroscopic-chromatographic data. Anal. Chem., 58 (1986) 2656-2663. 

L.S. Ramos, E. Sanchez and B.R. Kowalski, Generalized rank annihilation method. II Analysis of bimodal chromatographic data. J. Chromatog., 385 (1987) 165-180. 

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