Abstract

Mixture homogeneity values are obtained from a binary mixture in a vertically bladed mixer utilizing data extracted from a single tagged particle. X-ray radiography was performed to image the mixer vessel during the mixing process, and the location of the tagged particle was tracked throughout. Mixture homogeneity is quantified using a standard deviation-based Location Distribution Mixing Index (LDMI), the Modified Generalized Mixing Mean Mixing Index (MGMMI), and the Gini Index, all adapted to single-particle data. Mixture homogeneity values obtained using these indices were compared to data extracted using X-ray Computed Tomography (CT), which was quantified using a particle scale mixing index. It was observed that the LDMI was superior in determining the magnitude of mixing, whereas the Gini index was more suited to predicting mixing endpoints. Methods presented in this study pave the way for new process analytical technologies that extract in-line mixture homogeneity values using velocimetric methods while removing the necessity of uniquely identifying and discriminating between tagged particles.

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