Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
235259 | Powder Technology | 2015 | 11 Pages |
•The flow function coefficients (ffc) of pharmaceutical materials were evaluated.•Dry coating was also used to modify the surface properties of the materials.•The ffc was found to correlate well with the granular Bond number.•A granular Bond number for multi-component mixtures (i.e. blends) was formulated.•The multi-component Bond number predicted the ffc of 2, 3, and 5 component blends.
In order to improve fundamental understanding of powder flow behavior which is essential to the success of many pharmaceutical processes, this study investigates the relationship between particle-scale interactions dominated by the cohesive van der Waals force and the flow function coefficient. This study finds that the granular Bond number, defined as the ratio of the inter-particle cohesion force to particle weight, correlates well to the flow function coefficient, a metric used to assess powder flow performance and defined as the ratio of consolidation stress to unconfined yield strength. The inter-particle cohesion force was calculated by the so-called multi-asperity model which is a modification of the well-known Rumpf equation. As a major novelty, a granular Bond number is defined for multi-component mixtures (i.e. powder blends) and used to predict the flow function coefficient of binary, ternary, and quinary mixtures of a model API, acetaminophen, and two common pharmaceutical excipients, microcrystalline cellulose and pregelatinized starch. Surface modification via dry-coating was also used to alter the inter-particle force and more thoroughly investigate the effect of particle interactions on powder flow performance. Since the multi-component granular Bond number takes into account particle properties and particle interactions of all components in the powder blend, this novel approach shows good predictability for powder mixtures. Although the flow function coefficient alone is not a stringent prediction of powder flow, the modeling effort put forth in this study can be used to better guide formulation development.
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