Statistical numerical investigation of translational-rotational ultrafast image-based dynamic light scattering to measure a bimodal Gaussian sample of cylindrical nanoparticles

Abstract

In a translational-rotational ultrafast image-based dynamic light scattering (TR-UIDLS) experiment, nanoparticles in Brownian motion in a solvent are illuminated by a focused Gaussian beam and scatter the light toward a camera. If both vertical-vertical and vertical-horizontal polarization geometries are recorded at the same time, using a polarization camera, a distribution of “equivalent cylindrical particles” is determined from the cross-correlation coefficients between the pairs of pictures recorded by the camera in both polarization geometries. The equivalent cylindrical particles are the monodisperse cylindrical particles that scatter the same light fluctuations as the polydisperse particles in the measurement volume. The distribution of equivalent cylindrical particles is not strictly the distribution of the particles in the sample, and our purpose is to measure characteristic information about the size and shape of the particles in the sample from the distribution of the equivalent cylindrical particles. With this purpose, we propose in the present paper a model of numerical simulation of the TR-UIDLS experiment for polydisperse arbitrary distributions of cylindrical particles. The TR-UIDLS has been simulated for the bimodal Gaussian distribution of gold cylindrical nanorods immersed in water. In view of these simulations, a strategy is discussed to retrieve characteristic information about the bimodal Gaussian distribution of cylindrical particles.