Selection of Flow Aids: Model-based Prediction of Flow Properties Enhancements

The project aimed to develop a comprehensive set of models and decision tools for selecting and optimizing flow aids for the purpose of tackling the inherent challenges associated with the flowability of fine, cohesive powders. These powders often exhibit poor flow due to cohesion, which is influenced by factors such as particle size, shape, surface roughness, and environmental conditions. The project aimed to develop predictive models and decision tools that help select and optimize flow aids to improve powder processing. Over the past three years, significant progress has been made toward this goal, with several key accomplishments. Critical gaps have also been identified that will be addressed in the renewed project. 

Major Accomplishments:

• Model guided dry coating (flow aid amount, size, and surface area coverage):
• Single and multi-asperity mechanistic contact models were surveyed and assessed for their ability to guide flow aid selection based on their effectiveness 
• A multi-asperity model, developed earlier in our group, was identified for its ability to explain how dry coated nano-flow aids work and result in improved powder flow as they lower the inter-particle cohesion by one to two orders of magnitude. This model, which uses a surface area coverage-based approach, accounts for factors such as the amount of silica, particles surface energy, particle surface roughness, and surface roughness distribution
• Comprehensive validation of contact mechanics-based predictive models was conducted, focusing on selecting type and amount of silica for best flowability enhancements
• An interactive mixture model provided a framework for assessing host-guest compatibility based on surface energy considerations
• Material Characterization and Database:
• A database of industry-relevant materials was established to support informed decision-making for flow aid selection and suitability of dry coating
• The functionality of different silicas (hydrophilic and hydrophobic) with varied sizes was examined to understand their impact on reducing cohesion in powders.
• Processibility Guidance:
• Ideal processing conditions using bench-marking dry coating devices like LabRAM were identified for the purpose of demonstrating that high-intensity mixing can significantly improve the use and efficacy of flow aids. This is expected to help explore the use of conventional mixing devices which will be further addressed in the renewal project.   
• Synergistic effects in the flowability of blend were having a minor dry-coated component discovered, demonstrating improved blend flowability compared to that of its constituents 
• The effect of blend mixing time on this synergy when a dry-coated component is blended with other uncoated constituents was examined 
• Predictive Approaches:
• A dimensionless parameter, the granular Bond Number, based predictability of powder bulk properties was incorporated so that the same mechanistic model could be used for predicting the properties of uncoated as well as dry-coated powders
• A size class-dependent Bond number approach was introduced to account for variations in cohesion for fine powders having broad and/or bimodal particle size distributions
• Comprehensive approach for predicting flow aid, e.g., silica, performance in reducing cohesion was proposed by combining multiple models:
  1. Chen’s multi-asperity contact model: Explains the effect of host-guest sizes, guest surface energy, and host surface roughness on cohesion reduction
  2. Deng’s stick and bounce model: Describes the aggregation tendency of nanoflow aids (e.g., silica) based on process intensity and guest-host particle sizes
  3. Interactive mixture model: Based on host-guest total surface energy differential, predicts host-guest compatibility and coating efficacy

These models provide a more nuanced understanding of how different flow aids, e.g., silica,  perform under varying conditions, particularly concerning process intensity, nano flow aid particle size, and its surface energy.

• Industry Relevance:
• The findings underscore the importance of dry coating as a critical tool for enhancing powder flowability in industrial settings
• Insights into powder blend design and processing have significant implications for improving end-product quality
• A key highlight of this project is the successful evaluation and benchmarking of dry coating methods at both laboratory and pilot scales, achieved through collaborations with industry partners, including Merck, and support from NSF. Pilot-scale testing using scalable devices such as the COMIL-U10 validated the processability, scalability, and practicality of dry coating methods at pilot scale. 

Industry liaisons provided important feedback and support during the project period including the quarterly project meetings . Consequently, several critical gaps have been identified that will be addressed in the renewal project.