Prediction of porosity from particle scale interactions: Surface modification of fine cohesive powders

• Dry-coating reduced porosity and helped evaluate the effect of interparticle force.
• A multi-asperity interparticle force model improves van der Waals force estimation.
• An accurately determined granular Bond number better predicted powder bed porosity.
• Surface properties/asperities were ill-defined for non-dry-coated materials.
• Dry-coating induced nano-roughness better predicts/controls particle properties.

Packing or powder bed porosity is a fundamental property of solid particulate systems and is of prime importance to many industries which handle or process such material. Inter-particle forces, which may couple with particle size and shape, can significantly affect porosity. For fine dry particles, the attractive van der Waals force is dominant and can prevent the packing of particles resulting in high porosity. This study investigates the effect of the van der Waals force on porosity of powder beds consisting of fine cohesive particles. Dry coating is utilized to modify the surface roughness of particles in order to further elucidate this effect. The results indicate that dry coating nano-sized particles onto coarser particles ranging in size from 5 μm to 223 μm can significantly reduce the van der Waals force resulting in reduced porosity. The granular Bond number, defined as the ratio of the cohesion force to particle weight was shown to accurately predict porosity, provided a multiple asperity particle contact model is employed. A subsequent theoretical investigation determined the effect of surface modification, specifically the size, surface energy, and surface area coverage of asperities on porosity. It showed that the surface roughness of non-surface modified particles may be poorly defined and may lead to erroneous calculation of inter-particle forces. Therefore, in addition to dry coating being a useful process to improve powder properties such as porosity, dry coating can be used to define surface properties to accurately predict bulk level powder properties from multi-asperity particle scale interaction models.

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