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Handbook of Size Exclusion Chromatography and Related ...

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5 THE IMPORTANCE OF SOFTWARE<br />

Like any other analytical procedure, MALS requires special interpretive<br />

s<strong>of</strong>tware to insure the precision <strong>of</strong> results derived from such measurements.<br />

Foremost among the objectives <strong>of</strong> the s<strong>of</strong>tware is the determination at each<br />

elution slice <strong>of</strong> the molar mass <strong>and</strong> root-mean-square radius <strong>of</strong> the sample<br />

within that slice. Following separation in SEC columns (or by other<br />

fractionation processes such as field flow fractionation or reversed phase<br />

chromatography), the concentration <strong>of</strong> the fractionated polymer at each such<br />

elution slice is assumed to be so low that the second term on the right-h<strong>and</strong>-side<br />

<strong>of</strong> Eq. (1) may be neglected. [In other words, at such low concentrations, the<br />

second virial coefficient may not be determined directly.However, the value <strong>of</strong><br />

A2 determined <strong>of</strong>f-line, following Zimm’s method (5,13), may be supplied<br />

directly as an input parameter for the s<strong>of</strong>tware.]<br />

Figure 3 shows in graphical form the calculational basis for the<br />

determination <strong>of</strong> the weight-average molar mass Mj <strong>and</strong> average mean-square<br />

radius kr 2 g l j based on the Zimm plot procedure when there is no 2nd virial<br />

coefficient dependence <strong>of</strong> the derived Rayleigh ratios, Rj(ui; cj). At each slice j <strong>and</strong><br />

corresponding concentration cj, the ratios K cj=Rj(ui; cj) for each measured<br />

scattering angle ui are plotted as a function <strong>of</strong> sin 2 ui=2. Associated with each<br />

measured Rj(ui; cj) is a corresponding st<strong>and</strong>ard deviation based upon the plethora<br />

<strong>of</strong> multiple measurements characteristic <strong>of</strong> the MALS method, as well as errors in<br />

measurement <strong>of</strong> the corresponding concentration. The data fit shown in Fig. 3 is<br />

obtained by a least-squares fitting <strong>of</strong> a linear function in sin 2 ui=2 to the<br />

correspondingly weighted deviations <strong>of</strong> the data to the function. The associated<br />

weights are taken proportional to the square <strong>of</strong> the reciprocal st<strong>and</strong>ard deviations.<br />

Once the least-square fit has been determined, the intercept with the ordinate axis<br />

is readily calculated to yield the weight average molar mass value Mj for that slice.<br />

The initial slope <strong>of</strong> the least squares fit with respect to sin 2 ui=2 yields<br />

This may be written also as<br />

i<br />

1<br />

Mj<br />

16p 2 n 2 0<br />

3l 2 0<br />

[ordinate intercept] 16p2 n 2 0<br />

3l 2 0<br />

kr 2 gl (4)<br />

kr 2 gl (5)<br />

Using the concept <strong>of</strong> error propagation, the st<strong>and</strong>ard deviation <strong>of</strong> the derived value<br />

Mj may be calculated directly from<br />

ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi<br />

X<br />

2<br />

@Mj<br />

DMj ¼<br />

[DRj(ui; cj)]<br />

@Rj(ui; cj)<br />

2 þ @Mj<br />

2<br />

(Dcj)<br />

@cj<br />

2<br />

s<br />

(6)<br />

© 2004 by Marcel Dekker, Inc.

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