Computer-simulated chromatogram

All three sources of noise combine to form the type of trace shown at the bottom of figure 3. In general, the sensitivity of the detector should never be set above the level where the combined noise exceeds 2% of the FSD (full scale deflection) of the recorder (if one is used) or appears as more than 2% FSD of the computer simulation of the chromatogram. 

Free energies of activation for the enantiomerization of a series of iV-aryl-1,3,2-benzodithiazole 1-oxides 41 have been determined by dynamic high-performance liquid chromatography (DHPLC) on a chiral stationary phase <1999JOC1483>. From a comparison of experimental and computer-simulated chromatograms, the barriers to stereoinversion at sulfur were found to be around 80 kj mol 1 and relatively insensitive to effects from substituents in the iV-aryl group. 

If the PP method is used in a multi-component case it should also be noted that the determined isotherm parameters could not be assigned to specific components without additional information, e.g., by comparing computer simulations with an experimental chromatogram where the peaks can be identified. 

Figure 18.2 The decision for gradient (top) or isocratic (bottom) separation with a gradient scouting run from 10 to 100% B. The initial delay in the gradient profile comes from the dwell volume ofthe system. Hypothetical chromatograms are from a computer simulation.

Figure 18.15 Optimization of gradient runtime and temperature [after J.W. Dolan etal., J. Chromatogr. A, 803,1 (1998)]. Conditions sample, algal pigments column, 25cm x 3.2 mm i.d. stationary phase, Vydac 201tp Ci8 5 j,m mobile phase, 0.65 ml min gradient from 70 to 100% methanol in 28 mM tetrabutylammonium acetate buffer pH 7.1. Top computer simulation of a separation at 57 C and 80 min gradient runtime middle computer simulation with three fused peak pairs at 55 °C and 54 min bottom experimental chromatogram underthese conditions.

A series of computer-simulated chromatograms has been generated to test the validity of a procedure derived from the statistical model for calculating the number of randomly distributed components when many of them are obscured by overlap. Plots of the logarithm of the peak count versus reciprocal peak capacity are used for this purposTI TRese plots are shown to provide reasonable estimates of the total number of components In the synthetic chromatograms. 

Band width, and plate number, 38 Baseline peak, computer-simulated chromatograms, I8,20f Baseline separation, peak-counting methodology, 17,18 Benzenethiol, RPLC, 99f Benzo(e)pyrene, excitation spectra, I9lf,l92f Bls(chloromethyl) ether, air monitor, 20>lf... 

The experimental optimization procedures outlined above can be replaced with others based on computer simulations [64,65], which make use of the chromatographic theory and of one or two prior experiments intended to define critical parameters such as the sample, mobile phase, column, temperature, flow-rate and pressure. Simulated chromatograms are obtained for different experimental conditions (column dimensions, particle size, mobile phase composition, flow-rate, temperature, etc.) until the required resolution is achieved. In essence, the procedure is similar to experimental optimization, although the chromatograph functioning is replaced with programming. The information obtained can be checked experimentally or be used for designing new approached to experimental optimization. 

Once the selectivity is optimized, a system optimization can be performed to improve resolution or to minimize the separation time. Unlike selectivity optimization, system optimization is usually predictable, since only kinetic parameters are generally considered. Typical experimental variables include column length, particle size, flow rate, instrument configuration, sample injection size, etc. Many of these parameters are connected to the chromatogram through reliable equations, and therefore, computer simulation approaches have been successful in providing a stmctured approach to this problem [375,557,558]. 

Schlinge et al. (2011) presented an alternative method that requires a lot of preliminary computer simulations but estimates isotherm parameters as well as mass transfer coefficients on the basis of only a few experiments and very small amounts of samples in short time. The basic idea is to simulate HPLC chromatograms for given isotherm equations and to vary the isotherm parameters vdthin the range of practical applications. The calculated data are then used to train and validate neural... 

Visual inspection is difficult to handle since the 1681 chromatograms were simulated. To overcome this problem, another use of computer simulation is the construction of contour diagrams of the two-dimensional solvent domain [44]. An example of such a diagram for the separation of a mixture of steroids was described. Good agreement was obtained between the simulated and the experimental results on a dual plate consisting of a strip of C g layer adjacent to silica gel. 

A chromatogram obtained from this detector is shown in Figure 33. It is seen that the output from the detector is somewhat confusing and difficult to interpret. The response of the detector has been examined by computer simulation by Smuts et al. (63) and an explicit equation describing the temperature change as a function of the concentration profile of the eluted peak and the thermal properties of the detector cell and column has been derived by Scott (64). 

P-isomer), (b) the qrcle time was about 30 min, and (c) isolation losses were expected, the predicted throughput was a (satisfactory) 500 mg h . The chromatogram shown in Fig. 12 illustrates the optimized full-scale semi-preparative separation of the crude mixture. This example shows the value of systematic method development based on computer-assisted modeling. From the first trial experiment to the recovery of more than 2 g of pure product (ready for roto-vap isolation), less than a single 8 h shift had elapsed. The use of computer simulation with no guesswork or wasted laboratory experiments led to the fastest possible result... 

There was a good agreement between computer prediction and actual experimental separations. Computer-simulated and experimental chromatograms of isoleucine, leucine, phenylalanine, and arginine, were compared and, are shown in Figure 15.4. 

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