TY - JOUR
T1 - Assessing predictability of packing porosity and bulk density enhancements after dry coating of pharmaceutical powders
AU - Kunnath, Kuriakose
AU - Chen, Liang
AU - Zheng, Kai
AU - Davé, Rajesh N.
N1 - Publisher Copyright:
© 2020 Elsevier B.V.
PY - 2021/1/2
Y1 - 2021/1/2
N2 - 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.
AB - 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.
KW - Dry coating
KW - Granular bond number
KW - Particle surface roughness
KW - Porosity reduction
KW - Powder bed porosity prediction
UR - https://www.scopus.com/pages/publications/85091597642
UR - https://www.scopus.com/pages/publications/85091597642#tab=citedBy
U2 - 10.1016/j.powtec.2020.09.037
DO - 10.1016/j.powtec.2020.09.037
M3 - Article
AN - SCOPUS:85091597642
SN - 0032-5910
VL - 377
SP - 709
EP - 722
JO - Powder Technology
JF - Powder Technology
ER -