Plate count columns

There are different ways to calculate the theoretical plate count of a column. PSS SEC column plate counts are measured using the so-called half-height method. Figure 9.9 shows a graphic representation of this test. 

All packing materials produced at PSS are tested for all relevant properties. This includes physical tests (e.g., pressure stability, temperature stability, permeability, particle size distribution, porosity) as well as chromatographic tests using packed columns (plate count, resolution, peak symmetry, calibration curves). PSS uses inverse SEC methodology (26,27) to determine chromatographic-active sorbent properties such as surface area, pore volume, average pore size, and pore size distribution. Table 9.10 shows details on inverse SEC tests on PSS SDV sorbent as an example. Pig. 9.10 shows the dependence... 

FIGURE 9.12 Quality control chart of PSS SDV columns plate count (per m) measurements over a I0>year period 5% limits are also shown. 

The column plate count was determined from the expression... 

Column Type Length m Internal Diameter mm Film Thickness /tm Phase Ratio Capacity Factor lU mm opi cm/s Column Plate Count Plates Per Meter... 

Column Length (cm) Particle Diameter (micrometers) Column Plate Count Plates Per Meter Relative Operating Pressure... 

Establish control charts of instrumental performance. Day-to-day variations in pump flow rate, relative response factors, absolute response to a standard, column plate counts, and standard retention times or capacity factors are all useful monitors of the performance of a system. By requiring that operators maintain control charts, troubleshooting is made much easier. The maintenance of control charts should be limited to a few minutes per day. 

First, we look at isocratic separations. Let us assume that the analysis can be accomplished within a retention factor of 10. We also suppose that the analysis is carried out with a typical reversed-phase solvent and a sample with a typical molecular weight of a pharmaceutical entity. In order to manipulate the analysis time, we will keep the mobile phase composition the same and vary the flow rate. The maximum backpressure that we will be able to apply is 25MPa (250 bar, 4000psi). In Figure 1, we have plotted the plate count as a function of the analysis time for a 5 J,m 15-cm column. We see that the column plate count is low at short analysis times and reaches a maximum at an analysis time of about 1 h. A further increase in analysis time is not useful, since the column plate count declines again. This is the point where longitudinal diffusion limits the column performance. The graph also stops at an analysis time of just under 5 min. This is the point when the maximum allowable pressure drop has been reached. 

The most commonly used criterion for judging column performance is efficiency as measured by the number of theoretical plates or column plate count (N) exhibited by the column during the separation of a test mixture. The larger the number of theoretical plates, the more likely it is that the column will produce the desired separations. However, while popular, N is not a complete performance parameter for making comparisons. For example, N does not take into account particle size as does the reduced plate height, h. Another measurement, hmin, accounts for all of these factors as well as the mobile phase linear velocity and sample diffusion. However, N is the term most commonly recognized as being related to resolution (2), as shown in Equation 1 ... 

The equations in terms of Smin are especially attractive, since no estimate of the column plate count is required. If Rs is used, an estimate of the peak width or plate count is required twice, but since Rs oc Vn the plate count cancels in eqns.(4.41) and (4.42). This becomes clear when the two equations are expressed in terms of S. 

Note PI = purity index, r = coefficient of linear regression, Rs = resolution, N = column plate count, S/N = signal-to-noise ratio. Except for vitamin C, which is unstable in water. Reprinted with permission from reference 17. 

The detected concentration depends on the column plate count. We can increase the sensitivity by increasing the efficiency, which means that the analyst must select the flow rate according to the optimum. 

Column plate count Hold-up Particle time or column (s) diameter (p.m) Length (m) Flow rate (pl/s) Peak standard deviation k = 0 (p,l)... 

Column plate count Column hold-up time (s) Column length (m) Reduced plate height Reduced velocity Separation impedance... 

Tf = final program temperature. To = initial program temperature, t = time, tp = program time for a linear temperature program, tM = column hold-up time, k = initial value of the retention factor at the start of the temperature program, wp = peak width at base and N = column plate count. 

The column plate count is scrutinized next. The plate count, by convention normalized per meter of column length, is expected to correlate primarily with the average particle size of the column packing, Table 4.20. These values are approximate upper limit values and depend on the experimental conditions and solute properties. Plate counts exceeding about 75 % of the tabulated values for well-retained solutes... 

Theoretical column plate count and relative operating pressure at the optimum mobile phase velocity for conventional liquid chromatography columns... 

Column length (cm) Average particle diameter (pm) Column plate count N/m Relative operating pressure... 

SEC resolution may be broken down into the contributing components of column plate count (A ), pore volume (K,), and calibration curve slope ( ). 

Here, tg is the gradient duration, and w is the (average) peak width. The peak width itself is a function of the column plate count N, the retention factor at the column outlet k, as well as the colurrm dead time... 

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