Gradient parameters

A. Key Gradient Parameters (Flow Rate, Gradient Time [t ], Peak Capacity [P])... 

Gradient parameters (flow rate, gradient time, peak capacity, and dwell volume)... 

Fig. 21. Timing scheme of a STEAM sequence for diffusion measurements with a pair of diffusion weighting dephasing/rephasing gradients. Parameters 8, A, and A determine the diffusion weighting (h-value).

The peptides generated by proteolysis are separated using reverse-phase HPLC to minimize mass overlap and ionization suppression caused by ion competition in the electrospray source [40]. The optimized LC gradient parameters efficiently separate peptides while minimizing loss of deuterium through back exchange with solvent. Increased sensitivity can be achieved by using capillary HPLC columns and nanoelectrospray methods [47]. 

R-P separation of PTH-amino acids 4 gradient parameters and flow rate 77)... 

By equating the physical length L and velocity U scales in the finite-gap problem to the mathematically derived scales in the semi-infinite problem, an expression for the velocity-gradient parameter can be determined ... 

A number of investigators have modeled the Tsuji and Yamaoka data [104]. In these investigations the flame was modeled as a semi-infinite stagnation flow, with the outer potential flow characterized by the velocity-gradient parameter a (see Section 6.3.1). For the cylindrical geometry, this characterization is correct in the neighborhood of the center stagnation-flow streamline. 

Fig. 17.12 Temperature and H-atom sensitivities to various reactions for a 9% methane-air opposed-flow flame. The left-hand panel shows normalized sensitivities of the maximum temperature as a function of the velocity-gradient parameter a. The right-hand panel shows normalized sensitivities to the H-atom mole fraction in a highly strained flame (a = 2520 s-1) as a function of position in the flame (a distance of 0.0 corresponds to the symmetry plane).

A17 This cell contains a specified value of the nondimensional pressure-gradient parameter,... 

The cell A 17 refers to the pressure-gradient parameter, with the needed to identify the fact that it is always in column A and thus not shifted relatively with dragging commands that will follow. The cells D 14 and D 15 refer to rows containing the values of fj-1/2 and rj+1/2. Here the is needed to fix the row reference in subsequent dragging operations. That is, the values of fj-1/2 and rJ+1/2 are always in rows 14 and 15, but the columns must be allowed to change in a relative dragging operation. Cells C17 and E17 refer to the values of the axial velocity in the adjacent cells (i.e., uj-1 and uj+i). 

A18 This spreadsheet has been designed to solve the Couette-Poiseuille problem for several values of the pressure-gradient parameter at once. In this case, cell A18 has been programmed to have the value =A17+2. Thus each row has a pressure-gradient parameter that is two greater than the one above it. 

A8 - B8 Cell A8 contains the name PP, which is defined to have the value in cell B8, representing the nondimensional pressure-gradient parameter P. At this point a number is simply entered in to cell B8 for a particular problem. However, as we will discuss in more detail later, the number will be involved in an iteration process seeking a particular value of P for a given aspect ratio a. 

If the problem were being done for a specific value of the pressure-gradient parameter in dimensional terms, the problem would be solved once the spreadsheet has completed its iterations. The correct velocities would be contained in each of the cells. However, for the... 

There is only one value of the pressure-gradient parameter (cell B8) for which this constraint will be satisfied. Therefore, a further iteration must be accomplished to determine the correct value of P for the given aspect ratio a. 

D8 - E8 Cell E8 contains the value of the nondimensional group /Re, which is essentially the desired general solution to this problem. For every value of the aspect ratio a, entered in cell Al, there will be a corresponding value of /Re. Given a value of a, the value of /Re in cell E8 will be correct when the pressure-gradient parameter in cell B8 is chosen such that mean velocity in cell E9 is 1. Referring to Eq. 4.87, we have... 

The spreadsheet could be programmed to use the TOOLS-SOLVER function to automate the selection of the pressure-gradient parameter, cell B8, to drive the mean nondi-mensional velocity to 1.0. However, our experience in using this spreadsheet is that the iteration proceeds more efficiently if one simply guesses the value of the parameter and watches the value for the calculated mean velocity in cell E9. Making a series of successively more accurate guesses in cell B8 could be used to solve the problem for a new aspect ratio in just a few seconds. Furthermore it is fun to watch the iterations spin by ... 

If the retention vs. composition relationships for the solutes i, i + 1 and j are known, then the gradient parameters A, B and k can readily be calculated for the optimum gradient according to equation 6.6. Not unexpectedly, the value of the shape parameter K turns out to be of little significance for an optimization procedure in which only three solutes affect the result [624]. Therefore, it may be sufficient to optimize the parameters A and B for a linear gradient (k— 1). 

To obtain reliable values for the polarizabilities it is desirable to normalize to a known polarizability. By this means systematic errors that are associated with imperfect knowledge of the electric field and gradient parameters as well as of the precise position of the beam with respect to the polefaces, are minimized. The best "standard" for this purpose is atomic potassium, whose polarizability is well-known from earlier measurements on the same apparatus (10). In figure 2 we show a pair of beam profiles for potassium, with zero electric field and with a field corresponding to potential differences of 3620 V. 

TABLE 17-4. Influence of Gradient Parameters on Resolution, Retention, and Run Time... 

Table 17-4 summarizes the qualitative influence of changing the gradient parameters on resolution, retention factor, and run time. The bold rows of Table 17-4 offer the best approach to reducing analysis time and will be discussed in more detail. The nonbold rows represent parameters that should be optimized during the initial stages of method development to optimize resolution. 

Kays and associates (K2) have correlated their turbulent boundary layer data to produce the A+ correlation shown in Fig. 4. There Po is the stream ise pressure-gradient parameter... 

---