Shape Assessment by Forward Light Scattering: Modeling and Patern Recognition with Neural Networks.

The morphology of particles affects the properties of particulate materials. The quantitative assessment of the complete morphological characterization entails significant difficulties especially when analysis must be performed quickly on a large number of particles. In order to reduced to a size distribution determination. One of the emerging methods for a fast size distribution measurement is forward light scattering. Hence, many efforts have been send forparticle sizing by this method. However, up to now, relatively little work was done on the shape determination with forward light scattering. So, the main aim of this proposal is to assess marticle shape by forward light scattering.