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Introduction to the real-coded lattice gas model of colloidal systems

Introduction to the real-coded lattice gas model of colloidal systems. Yasuhiro Inoue Hirotada Ohashi, Yu Chen, Yasuhiro Hashimoto, Shinnosuke Masuda, Shingo Sato, Tasuku Otani University of Tokyo, JAPAN. 1 nm. 10 m m. Background - Colloid -. Colloid -> particles + a solvent fluid.

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Introduction to the real-coded lattice gas model of colloidal systems

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  1. Introduction to the real-coded lattice gas model of colloidal systems Yasuhiro Inoue Hirotada Ohashi, Yu Chen, Yasuhiro Hashimoto, Shinnosuke Masuda, Shingo Sato, Tasuku Otani University of Tokyo, JAPAN

  2. 1 nm 10 mm Background - Colloid - Colloid -> particles + a solvent fluid Particle foods Milk, mayonnaise, iced cream manufacture Paintings, cosmetics, concrete Nature Fog, smoke, polluted water, blood solvent Innovate new materials, Analysis on flows in micro devices

  3. Interactions Particle - Particle Particle - Molecule fluctuate Electrochemical, DLVO Brownian motion Dispersion stability Internal structure External field induce fluid flows and affected by others Multi-physics and Multi-scale

  4. How to approach ? Macro scale Continuum dynamics Navier-Stokes eq. + Visco-elastic model Meso scale solute + solvent dynamics Micro scale Molecular dynamics

  5. Numerical Models Meso scale solute + solvent Navier-Stokes eq. FDM, FVM Boltzmann eq. LBM, FDLBM Newtonian eq. Top down SPH, MPS LGA, RLG Bottom up A particle-model is free from the difficulty of mesh generations Complex phenomena might be reproduced or mimicked from bottom-up

  6. Algorithm of real-coded lattice gas Streaming (inertia) after before Multi-particle collision

  7. Colloid Particles • Rigid Particle • Deformable Particle

  8. solid cell RLG particle A rigid particle model • The solvent fluid is represented by RLG particles. • Rigid objects are composed of solid cells. For example . . . Object Solvent

  9. A rigid particle model τ time step interval Algorithm The RLG streaming process The RLG - Object interaction Translations and rotations The rigid objects’ motions Collisions Δt += τ; if ( Δt < 1 time step ) else 1 time step interval The RLG collision process

  10. Object rule 1 The reflection of RLG particles • Solid Cell and RLG particles are exclusive to each other. Solid Cell RLG particle before after • Forces exerted on the rigid object surface by bombardments of RLG particles. Calculate the RLG particles’ collision with the object, Calculate the change of their momentum ΔP. The momentum of rigid object is changed with -ΔP.

  11. Object rule 1 The reflection of RLG particles An assumption: A rigid object is regarded as a heat bath. : The normal direction of the solid surface : The tangential direction where A new velocity vector is generated randomly from the above probability density distributions. n n Vrigid_suface Vrigid_suface vrlg after before

  12. Object Motion before after Objects Collision before Calculate the impulse (white arrows) after Object rule 2 Translational velocity vector Angular velocity vector

  13. Application

  14. A simpler model on spherical particles Colloid particle r Colloid particle An electrochemical potential energy is defined between “center to center” normal RLG The colliding point and its normal vector

  15. DLVO particles van der Waals attractions Electrostatic repulsions DLVO potential curve varied with h a: Amplitude of van der Waals h: Amplitude of a repulsive barrier k: Screen length ratio DLVO is the superposition of van der Waals and repulsions

  16. Internal structures of a colloid h=0 h=10 h=0,10 : Attractive h=20,30 : Repulsive h=20 h=30 The amplitude of the repulsive barrier could affect the internal structure t = 5000

  17. Aggregate forms varied with h

  18. Aggregate forms varied with h

  19. Summary: a rigid particle model • Any shape of rigid objects could be modeled by solid cells • Hydrodynamic and electrochemical interparticle interactions could be implemented • Various aggregate forms depending on h are demonstrated

  20. A deformable particle model • Red blood cells • Vesicles

  21. Background on vesicles Vesicles are closed thin membrane separating the internal fluid from the external solvent 5nm Fundamental structure of a bio-cell Drug delivery systems • vesicles could deliver medicines to the target of tissues Contrast agents • improve the contrast of Doppler images vesicle The size of vesicle should be of the order of micro meter or smaller

  22. Flow of vesicles 1 cm Vesicles are regarded as a passive scalar Artery Re > 100 100 Arteriole Re < 1 The correlation between vesicles and blood could not be neglected 10 Capillary Re << 1 1 A direct modeling of dynamics in this field is required

  23. A vesicle model 5nm Neglect membrane Immiscible droplet vesicle Assuming that vesicles would be regarded as immiscible droplets,

  24. Immiscible multi-component fluids Existence of membrane prohibits vesicles from coalescing Immiscible droplets Immiscible multi-component fluid Vesicle dispersion A vesicle dispersion could be modeled as an immiscible multi-component fluid

  25. Algorithm of immiscible multi-component rlg fluid • A rlg particle is colored by either red, blue, green or so on color • Color is for difference species • Define interparticle interactions based on color repulsive attractive Same color Different color Interfaces of multi-component could be reproduced by the above rules

  26. Algorithm: color collision The Color field is the color gradient The Color flux is relative velocities to CM. Color potential energy The color collision is done by a rotation matrix, where U takes the minimum

  27. Phase segregation: 3 species

  28. An example of an immiscible multi-component fluid 6 vesicles + 1 suspending fluid = 7 fluids 1 3 1 2 3 2 7 7 5 6 4 5 6 4 Time evolution

  29. Brownian motion Stable dispersion time Aggregate form

  30. Micro bifurcation Re ~ 2, Ca ~ 0.001 time Zipper-like flow

  31. Flows in a complex network

  32. Summary: a deformable model • Vesicles are regarded as immiscible droplets. • The dispersion stability is able to be controlled by model parameters. • A preliminary example for the application of flows of a vesicle-dispersion in a micro-bifurcation was demonstrated

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