The interpretation of particle size data gathered by Dynamic Light Scattering can be fraught with confusion, especially when DLS results don’t appear to agree with orthogonal characterisation methods.
In this webinar we will discuss some common puzzles posed in interpreting DLS particle size data and discuss a number of factors that can skew our results. We will then introduce the Zetasizer Pro and Ultra’s new approach of assessing DLS data quality that uses machine learning artificial intelligence to identify sub optimal sample conditions and provide smart actionable advice for the user.

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