Assessing predictability of packing porosity and bulk density enhancements after dry coating of pharmaceutical powders

Document Type

Article

Publication Date

1-2-2021

Abstract

Ability to predict the porosity, and its reduction after nano-silica dry coating, based on the Bond number and cohesion force estimated via multi-asperity contact model was examined for twenty different pharmaceutical powders. A new model for first order estimates of bulk density improvements after dry coating was found to be reasonably predictive despite variations in size (10–225 μm), particle size distribution, aspect ratios (1–3.5), material density, and dispersive surface energy. For the porosity prediction model based on Bond numbers, Microcrystalline Cellulose (MCC) excipients were outliers, regardless of size (20–200 μm). Analysis of their shape, surface morphology and specific surface areas (SSA), indicated that compared to other powders, MCCs had the highest SSA compared to equivalent spheres and high macro-roughness, while having high aspect ratios. This unique characteristic made them effectively more cohesive leading to their poor packing independent of their size, which is in line with previous simulations.

Identifier

85091597642 (Scopus)

Publication Title

Powder Technology

External Full Text Location

https://doi.org/10.1016/j.powtec.2020.09.037

e-ISSN

1873328X

ISSN

00325910

First Page

709

Last Page

722

Volume

377

Grant

EEC_0540855

Fund Ref

National Science Foundation

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