arXiv · 1906.11312
Computational assessment of an effective-sphere model for characterizing colloidal fractal aggregates with holographic microscopy
Abstract
We perform simulations to evaluate a recent experimental technique for using in-line holographic microscopy and an effective-sphere model to measure the population-averaged fractal dimension $D_f$ of an ensemble of colloidal fractal aggregates. In this technique, models based on Lorenz-Mie scattering by a uniform sphere are fit to digital holograms of a population of fractal aggregates to determine the effective refractive indices $n_{eff}$ and effective radii $a_{eff}$ of the aggregates. A scaling relationship between $n_{eff}$ and $a_{eff}$ based on the Maxwell Garnett effective-medium theory then determines $D_f$. Here we use a multisphere superposition code to calculate the exact holograms produced by aggregates with tunable fractal dimensions $D_f$. We show that $n_{eff}$ and $a_{eff}$ become less sensitive to the aggregate orientation as $D_f$ increases. We also show that the Maxwell Garnett scaling relationship correctly determines $D_f$ to within 10.5\% when multiple scattering is negligible and the population-averaged coefficient of determination $\langle R^2\rangle_p > 0.6$, indicating that the holograms are well-described by the effective-sphere model.
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Jerome Fung, Samantha Hoang. 2019-06-26. Computational assessment of an effective-sphere model for characterizing colloidal fractal aggregates with holographic microscopy. https://doi.org/10.1016/j.jqsrt.2019.106591
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