4.7 Article

Visualization and quantitative profiling of mixing and segregation of granules using synchrotron radiation X-ray microtomography and three dimensional reconstruction

Journal

INTERNATIONAL JOURNAL OF PHARMACEUTICS
Volume 445, Issue 1-2, Pages 125-133

Publisher

ELSEVIER SCIENCE BV
DOI: 10.1016/j.ijpharm.2013.02.010

Keywords

Mixing; Segregation; Synchrotron radiation X-ray computed; microtomography; Three dimensional reconstruction; Frequency distribution; Mixing index

Funding

  1. Drug Technology Innovation and Industrialization Strategic Alliance Project of China - CSPS/ZMC Union Candidate Innovative Drug Research Project [2010ZX09401-402]
  2. Natural Science Foundation of China [81273453]

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Tomographic imaging techniques have great potential for improving understanding of the dynamics of granular materials during manufacturing, handling, and storage. In this study, the synchrotron radiation X-ray computed microtomography (SR-mu CT) was used non-invasively to monitor blend homogeneity of binary mixtures. Granular samples of microcrystalline cellulose and starch were characterized using the SR-mu CT individually. Simultaneously, particle distribution was investigated by calculating the frequency distribution of a statistic for testing sphericity. Then, the microcrystalline cellulose and starch granules were blended in a cylindrical container. Influences of the time of rotations T-R and the time of vibration TV on the mixture homogeneity were studied with the SR-mu CT and statistical evaluation. The mixing index is also adopted to evaluate the mixture homogeneity of the particle system. The results showed that mixture homogeneity is improved with increasing TR. Furthermore, segregation increased with longer TV when particles are different in size and shape. The larger starch granules of non-spherical shape have a tendency to rise to the top, while the smaller microcrystalline cellulose granules which are spherical tend to migrate to the bottom of the mixture. Therefore, we demonstrate that SR-mu CT can investigate the mixing and segregation of granular materials in three-dimensions combined with statistic method. (C) 2013 Elsevier B.V. All rights reserved.

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