Whilst being able to measure particles of below 1 nm size, DLS is preferentially sensitive to larger particles due to the 6th power relationship between particle radius and scattering intensity. This means that sample preparation typically needs to be scrupulous, especially for low scattering samples such a proteins and biological molecules. The contribution to contaminants such as dust and aggregates can be mitigated by filtering, however this may not always be practical or possible depending on the volume and fragility of the sample. Filtration of samples can also constitute a financial burden, both in terms of additional sample preparation time and consumables costs. This application note introduces a new DLS data capture process called Adaptive Correlation which helps address these issues. Adaptive Correlation uses a statistically driven approach to produce the best correlation data, which in turn gives more reliable DLS size data. It can reduce the need for filtering and give added confidence in you DLS results.
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