This viewing is accomplished using a Residuals display and/or a Fit display. The fit of the Cumulants and NNLS algorithms to the measured data can also be viewed graphically in the DTS software. The "Cumulants Fit Error" and "Multimodal Fit Error" parameters are the c 2 values for the fitting of the measured correlogram data using the Cumulants (single exponential) and the NNLS (multi-exponential) methods, with c 2 being calculated according to the following expression.
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#Dls malvern zetasizer nano series software software#
The DTS software also includes parameters that can be used as metrics for the quality of the correlogram fitting algorithms. Merit values 100 indicate the likely presence of number fluctuations or large contaminants. The Size Merit is calculated using the following expression, and should range between 0 and 100.
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The Size Merit is representative of a normalized signal to noise ratio, expressed as a percentage. The Intercept is the amplitude or Y intercept of the intensity autocorrelation function, g 1 ( t ), and is calculated via the following expression, where g 1 ( t 2 ) and g 1 ( t 3 ) are the correlation values from the 2 nd and 3 rd channels of the digital correlator. The "Intercept" and "Size Merit" are Zetasizer Nano software available parameters that can be used as quality metrics for the raw data. While checking the measured correlogram should always be the first step when evaluating the quality of a DLS measurement, there are also a variety of analytical parameters that can be used. The table below Figure 1 lists the symptoms, indications of, and the recommendations for each of the low quality correlograms shown in the figure.įigure 1: Comparison of a high quality DLS correlogram to a few correlograms indicative of common light scattering problems.
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The high quality correlogram in this figure can be described as having a high amplitude (Y intercept) and a smooth exponential decay all the way to a single, flat, and zero baseline. When attempting to evaluate DLS data quality then, the best practice is to always look first at the measured correlogram.įigure 1 shows a comparison of a high quality DLS correlogram to a few correlograms indicative of common light scattering problems. The obvious down side to this approach is that the fitting algorithms cannot always distinguish high from low quality raw data, and will generally give a size distribution result, even for raw data that indicates user attention is needed. Typical DLS users however, tend to jump immediately to the distribution result, without looking first at the correlogram to insure that the quality of the raw data is acceptable. In the dynamic light scattering technique, the size distribution is derived from an exponential fitting of the measured correlogram. Evaluating_DLS_data_quality Evaluating DLS data quality