Successful realization of colloidal nanoparticle products is critically dependent on reliable dimensional measurements for the correlation of nanometer-scale physical-chemical properties with functionality. Dynamic light scattering (DLS) is the method of choice for size measurements in most cases. However, both the mean and distributional DLS measurement results may be unknowably significantly biased by 25 % or more, which often lead to incorrect or unclear interpretation of structure and property relationships of nanoparticle formulations. In this talk, we critically discuss the application of DLS for the characterization of colloidal nanoparticles and provide much-needed clarification for ambiguities in the mean-value practice of commercial DLS software and documentary standards. We address the misleading way DLS size distributions are often presented, that is, as a logarithmically scaled histogram of measured relative quantities. Through the measurement of monomodal nanoparticle samples having an extensive range of sizes and polydispersity, we demonstrate that the default outputs of a frequently used DLS inversion method are ill chosen, as they are regularizer-dependent and significantly deviate from the cumulant z-average size. We also investigate the DLS polydispersity descriptors of the distributional quality and find them to be completely unreliable and misleading, both for monodisperse reference materials and broad-distribution self-assembled nanoparticles with a core/shell structure. The results are intended to bring essential improvements in existing DLS data interpretation practices and to stimulate reexamination of the role of DLS in the characterization of colloidal nanoparticles.

Characterization of colloidal nanoparticles by DLS—a word of caution

ACS Spring 2022

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