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    A numerical simulation study on the interaction of particles with rough surface and soft structures in suspension systems

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    Embargoed until Sept. 17, 2023 (7.287Mb)
    Date
    2022
    Author
    Duowei, Lu
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    Abstract
    Particle interactions in complex colloidal systems are essential in a variety of traditional and emerging industrial processes. This thesis applied the extended Derjaguin-Landau-Verwey-Overbeek (XDLVO) theory to calculate the interactions between particles of different shapes and surface morphologies under different conditions. The past constructed models systematically assessed the critical roles of surface topography on the interfacial interactions of particles of various sizes and shapes. In this research, the surface morphology (via considering asperity size and number, randomness, fractional dimension, and fractional roughness), particle size, particle aspect ratio, particle shape (spherical and ellipsoidal), orientation angle, particle softness, and geometrical structure (solid and hollow) were considered as primary variables in constructing particles. Then, the interaction of assembled particles was simulated according to the rippled particle theory, fractal geometry theory, and three-step model combined with the surface element integral technique. Overall, it was discovered that the shape of particles played a critical role in controlling the interfacial behavior of particles and ellipsoidal particles had more interaction than spherical ones did. The present numerical model also predicted that deformable particles interact more aggressively than rigid particles. Additionally, the simulated results showed that the constructed hollow deformable particles were more easily aggregated compared with the solid ones. As the present work included important parameters of particles found in naturally or industrially produced colloidal systems, such as sludge particles, bacteria, or viruses, the results of this work will provide a guideline for simulating the behavior of such colloidal systems accurately, which can be used in the design of industrial processes or understanding behavior of natural phenomenon.
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    https://knowledgecommons.lakeheadu.ca/handle/2453/5101
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    • Electronic Theses and Dissertations from 2009 [1409]

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