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A How-To Approach to Estimating Surface Charge Density of Nano/Micro Particles through Aggregation Experiments Considering the Specific Ion Effect

Langmuir 2025 3 citations

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Researchers developed a method using dynamic light scattering aggregation experiments to estimate the surface charge density of nano/microparticles, accounting for the specific ion effect. Ignoring ion-specific effects led to large errors in surface charge estimates, while incorporating them yielded accurate and consistent results across montmorillonite and polystyrene particles.

Accurate estimation of the surface charge density of nano/micro particles is crucial for regulating their environmental fate and bioavailability in the fields of environmental science and materials engineering. However, existing analytical methods for accurately estimating surface charge density remain significant challenges. In this study, we proposed a method for estimating the surface charge density of nano/micro particles through aggregation experiments using dynamic light scattering technology. The specific ion effect had a significant effect on the accuracy of these estimations. Without considering the specific ion effect, this led to significantly different and unacceptable surface charge densities for montmorillonite particles with permanent charges. Conversely, when considering the specific ion effect, similar surface charge densities were obtained (0.1974, 0.1930, and 0.1718 C/m2), with a mean value of 0.1874 ± 0.0136 C/m2, which aligned well with the literature-reported values. Furthermore, the surface charge density of various nano/micro particles, such as microplastic polymers, graphene oxide, and nanosilver, was also estimated using this method. The migration behavior of these particles was determined by electrostatic repulsion between them, which was controlled by their surface charge density. The surface analysis method proposed herein provides a solid foundation for the directed adjustment and control of the migration dynamics of nano/micro particles in environmental systems.

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