Selection of Silica Type and Amount for Flowability Enhancements via Dry Coating: Contact Mechanics Based Predictive Approach

Kuriakose T. Kunnath, Siddharth Tripathi, Sangah S. Kim, Liang Chen, Kai Zheng, Rajesh N. Davé

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


Purpose: To investigate the effect of dry coating the amount and type of silica on powder flowability enhancement using a comprehensive set of 19 pharmaceutical powders having different sizes, surface roughness, morphology, and aspect ratios, as well as assess flow predictability via Bond number estimated using a mechanistic multi-asperity particle contact model. Method: Particle size, shape, density, surface energy and area, SEM-based morphology, and FFC were assessed for all powders. Hydrophobic (R972P) or hydrophilic (A200) nano-silica were dry coated for each powder at 25%, 50%, and 100% surface area coverage (SAC). Flow predictability was assessed via particle size and Bond number. Results: Nearly maximal flow enhancement, one or more flow category, was observed for all powders at 50% SAC of either type of silica, equivalent to 1 wt% or less for both the hydrophobic R972P or hydrophilic A200, while R972P generally performed slightly better. Silica amount as SAC better helped understand the relative performance. The power-law relation between FFC and Bond number was observed. Conclusion: Significant flow enhancements were achieved at 50% SAC, validating previous models. Most uncoated very cohesive powders improved by two flow categories, attaining easy flow. Flowability could not be predicted for both the uncoated and dry coated powders via particle size alone. Prediction was significantly better using Bond number computed via the mechanistic multi-asperity particle contact model accounting for the particle size, surface energy, roughness, and the amount and type of silica. The widely accepted 200 nm surface roughness was not valid for most pharmaceutical powders.

Original languageEnglish (US)
Pages (from-to)2917-2933
Number of pages17
JournalPharmaceutical Research
Issue number12
StatePublished - Dec 2023

All Science Journal Classification (ASJC) codes

  • Biotechnology
  • Molecular Medicine
  • Pharmacology
  • Pharmaceutical Science
  • Organic Chemistry
  • Pharmacology (medical)


  • dry coating
  • flow enhancement
  • flowability prediction
  • granular bond number
  • hydrophobic or hydrophilic nano-silica


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