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 mu m), 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 mu m). 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. (C) 2020 Elsevier B.V. All rights reserved.