QELS Batch Regularization and Cumulants

As opposed to online QELS analysis, batch QELS measurements use the WyattQELS instrument to characterize unfractionated samples. Batch QELS analysis methods can provide information on the distribution of sizes in a sample.

Regularization analysis, ASTRA uses the sophisticated DYNALS regularization algorithm from ALANGO. This truly modern algorithm replaces old industry standbys, such as CONTIN, which are computationally slow and lack the adaptive adjustment of the regularization parameter based upon the noise of the data.

DYNALS provides this adaptive feature along with lightning-fast performance. The DYNALS regularization scheme can be used to determine semi-quantitative distributions for broadly (i.e. over several orders of magnitude) polydisperse samples, and even to resolve two different species in an unfractionated sample if the size difference is at least a factor of five.

The DYNALS regularization analysis is fully integrated into ASTRA. As shown in the experiment at right, baselines and peaks are set as usual, with the regularization analysis as part of the experiment template. Results include hydrodynamic radius (Rh) and translational diffusion (Dt) intensity distributions, and Rh weight distributions based on an assumed sphere or random coil model. The report also contains information on the peaks in the distribution.

QELS regularization analysis GUI
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The interface for the regularization procedure brings together all of the relevent analysis parameters and results into one view. Changes to the analysis parameters result in immediate feedback from graphs and numerical information.
    Features:
  • Average of correlation functions over a region to enhance signal to noise.
  • Prefiltering of correlation functions based on single exponential fit.
  • Suppression of distribution peaks below a user-defined size.
  • Display can be toggled between Rh and Dt distributions or correlation function and fit.
  • Correlation function fit and residuals can be displayed.
  • Conversion from intensity to weight distributions based on either sphere or random coil model.
  • Regularization resolution reported.
  • Fully 21 CFR Part 11 compliant with ASTRA Security Pack tier.

The correlation function view for the regularization analysis can be used to assess the regularization fit quality. Residuals can be viewed, and portions of the correlation function that have been disabled for analysis are marked in red. The correlation function and residuals below for a mixture of polystyrene spheres demonstrate how the residuals can be used to identify systematic deviations in the fit.

Cumulants
An alternative analysis technique for characterizing QELS batch Gaussian form, defined by a mean radius and width (polydisperisty) indicitive of the homogeneity of the population. This is referred to as the Cumulants fit. These results are presented in real time, in numerical and graphical form.
    Features:
  • Average of correlation functions over a region to enhance signal to noise.
  • Prefiltering of correlation functions based on single exponential fit.
  • Correlation function fit and residuals can be displayed.
  • Graphical display of range of one standard deviation showing mean and range of sizes for each aquisition.
  • Fully 21 CFR Part 11 compliant with ASTRA Security Pack tier.

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