A well established method to study biomaterials using a confocal laser scanning microscope is Raster Image Correlation Spectroscopy (RICS) (Digman, 2005). RICS is a powerful method based on correlation function estimation, which has also been applied to models with diffusion and binding and to mapping spatial heterogeneity. In various areas such as polymer physics and sizing of biomolecules, one wants to determine diffusion properties of a sample of particles consisting of a mixture of components with different diffusion coefficients. Many systems are characterized by the presence of polydisperse mixtures of heterogeneous components. In particular, the majority of proteins fulfill their biological roles not as monomeric species but as components of larger functional complexes. Microfluidics has been used as a platform for diffusional sizing of biomolecules enabling determination of their hydrodynamic radius (Arosio, 2016). In the present paper, we present an extension of the Single Particle Raster Image Analysis (SPRIA) method (Longfils, 2017) to study systems of particles having a finite number of different diffusion coefficients. In examples with simulated and experimental data with two and three different diffusion coefficients we show that SPRIA gives accurate estimates. A simple technique for finding the number of different diffusion coefficients is also suggested. In the case of applying RICS to particle mixtures, we show by plotting the level curves of the correlation function that the quotient between different diffusion coefficients needs to be rather large to allow identifiability.
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