The way to derive pdI is to fit the correlation function to a power law series. a+b*t+c*t2. The slope, b, is for calculating the intensity average diffusion coefficient, and consequently the average size. Coefficient, c, is related to the polydispersity.
The attached paper "Revisiting the method of cumulants for the analysis of
dynamic light-scattering data " published by Barbara J. Frisken will be beneficial to read.
The way to derive pdI is to fit the correlation function to a power law series. a+b*t+c*t2. The slope, b, is for calculating the intensity average diffusion coefficient, and consequently the average size. Coefficient, c, is related to the polydispersity.
The attached paper "Revisiting the method of cumulants for the analysis of
dynamic light-scattering data " published by Barbara J. Frisken will be beneficial to read.
Strictly, the square of the (deviation / mean size) is only valid for a Gaussian distribution assumption. However, the PDI is often used as a concept from engineering, adapted to describe general distributions that are not Gaussian. Going to the extreme, one could even define a polydispersity index for a peak within a size distribution. Please note that PDI in chromatography and in dynamic light scattering are very different.
It assumed a single size population following a Gaussian distribution and analyzed as the square of the ratio of the standard deviation to mean droplet size which indicates the uniformity of droplet size.
My Article: Developing a Topical Nanoemulsion for Permeation of Bee Venom through the Skin in Franz Diffusion Cell
It assumed a single size population following a Gaussian distribution and analyzed as the square of the ratio of the standard deviation to mean droplet size which indicates the uniformity of droplet size.
My Article: Developing a Topical Nanoemulsion for Permeation of Bee Venom through the Skin in Franz Diffusion Cell