Multi-particle collision dynamics

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Multi-particle collision dynamics (MPC), also known as stochastic rotation dynamics (SRD),[1] is a particle-based mesoscale simulation technique for complex fluids which fully incorporates thermal fluctuations and hydrodynamic interactions.[2] Coupling of embedded particles to the coarse-grained solvent is achieved through molecular dynamics.[3]

Method of simulation

The solvent is modelled as a set of point particles of mass with continuous coordinates and velocities . The simulation consists of streaming and collision steps.

During the streaming step, the coordinates of the particles are updated according to

where is a chosen simulation time step which is typically much larger than a molecular dynamics time step.

After the streaming step, interactions between the solvent particles are modelled in the collision step. The particles are sorted into collision cells with a lateral size . Particle velocities within each cell are updated according to the collision rule

where is the centre of mass velocity of the particles in the collision cell and is a rotation matrix. In two dimensions, performs a rotation by an angle or with probability . In three dimensions, the rotation is performed by an angle around a random rotation axis. The same rotation is applied for all particles within a given collision cell, but the direction (axis) of rotation is statistically independent both between all cells and for a given cell in time.

If the structure of the collision grid defined by the positions of the collision cells is fixed, Galilean invariance is violated. It is restored with the introduction of a random shift of the collision grid.[4]

Explicit expressions for the diffusion coefficient and viscosity derived based on Green-Kubo relations are in excellent agreement with simulations.[5][6]

Simulation parameters

The set of parameters for the simulation of the solvent are:

  • solvent particle mass
  • average number of solvent particles per collision box
  • lateral collision box size
  • stochastic rotation angle
  • kT (energy)
  • time step

The simulation parameters define the solvent properties,[1] such as

  • mean free path
  • diffusion coefficient
  • shear viscosity
  • thermal diffusivity

where is the dimensionality of the system.

A typical choice for normalisation is . To reproduce fluid-like behaviour, the remaining parameters may be fixed as .[7]

Applications

MPC has become a notable tool in the simulations of many soft-matter systems, including

References

  1. ^ a b Gompper, G.; Ihle, T.; Kroll, D. M.; Winkler, R. G. (2009). "Multi-Particle Collision Dynamics: A Particle-Based Mesoscale Simulation Approach to the Hydrodynamics of Complex Fluids". Advanced Computer Simulation Approaches for Soft Matter Sciences III. Vol. 221. pp. 1–87. arXiv:0808.2157. Bibcode:2009acsa.book....1G. doi:10.1007/978-3-540-87706-6_1. ISBN 978-3-540-87705-9. S2CID 8433369.
  2. ^ Malevanets, Anatoly; Kapral, Raymond (1999). "Mesoscopic model for solvent dynamics". The Journal of Chemical Physics. 110 (17): 8605–8613. Bibcode:1999JChPh.110.8605M. doi:10.1063/1.478857.
  3. ^ a b Malevanets, Anatoly; Kapral, Raymond (2000). "Solute molecular dynamics in a mesoscale solvent". The Journal of Chemical Physics. 112 (16): 7260–7269. Bibcode:2000JChPh.112.7260M. doi:10.1063/1.481289. S2CID 73679245.
  4. ^ Ihle, T.; Kroll, D. M. (2003). "Stochastic rotation dynamics. I. Formalism, Galilean invariance, and Green-Kubo relations". Physical Review E. 67 (6): 066705. Bibcode:2003PhRvE..67f6705I. doi:10.1103/PhysRevE.67.066705. PMID 16241378.
  5. ^ Ihle, T.; Tüzel, E.; Kroll, D. M. (2004). "Resummed Green-Kubo relations for a fluctuating fluid-particle model". Physical Review E. 70 (3): 035701. arXiv:cond-mat/0404305. Bibcode:2004PhRvE..70c5701I. doi:10.1103/PhysRevE.70.035701. PMID 15524580. S2CID 11272882.
  6. ^ Ihle, T.; Tüzel, E.; Kroll, D. M. (2005). "Equilibrium calculation of transport coefficients for a fluid-particle model". Physical Review E. 72 (4): 046707. arXiv:cond-mat/0505434. Bibcode:2005PhRvE..72d6707I. doi:10.1103/PhysRevE.72.046707. PMID 16383567. S2CID 14413944.
  7. ^ a b J. Elgeti "Sperm and Cilia Dynamics" PhD thesis, Universität zu Köln (2006)
  8. ^ Padding, J. T.; Louis, A. A. (2004). "Hydrodynamic and Brownian Fluctuations in Sedimenting Suspensions". Physical Review Letters. 93 (22): 220601. arXiv:cond-mat/0409133. Bibcode:2004PhRvL..93v0601P. doi:10.1103/PhysRevLett.93.220601. PMID 15601076. S2CID 119504730.
  9. ^ Hecht, Martin; Harting, Jens; Bier, Markus; Reinshagen, Jörg; Herrmann, Hans J. (2006). "Shear viscosity of claylike colloids in computer simulations and experiments". Physical Review E. 74 (2): 021403. arXiv:cond-mat/0601413. Bibcode:2006PhRvE..74b1403H. doi:10.1103/PhysRevE.74.021403. PMID 17025421. S2CID 19998245.
  10. ^ Mussawisade, K.; Ripoll, M.; Winkler, R. G.; Gompper, G. (2005). "Dynamics of polymers in a particle-based mesoscopic solvent" (PDF). The Journal of Chemical Physics. 123 (14): 144905. Bibcode:2005JChPh.123n4905M. doi:10.1063/1.2041527. PMID 16238422.
  11. ^ Ripoll, M.; Winkler, R. G.; Gompper, G. (2007). "Hydrodynamic screening of star polymers in shear flow". The European Physical Journal E. 23 (4): 349–354. Bibcode:2007EPJE...23..349R. doi:10.1140/epje/i2006-10220-0. PMID 17712520. S2CID 36780360.
  12. ^ Noguchi, Hiroshi; Gompper, Gerhard (2005). "Dynamics of fluid vesicles in shear flow: Effect of membrane viscosity and thermal fluctuations" (PDF). Physical Review E. 72 (1): 011901. Bibcode:2005PhRvE..72a1901N. doi:10.1103/PhysRevE.72.011901. PMID 16089995.
  13. ^ K.-W. Lee and Marco G. Mazza (2015). "Stochastic rotation dynamics for nematic liquid crystals". Journal of Chemical Physics. 142 (16): 164110. arXiv:1502.03293. Bibcode:2015JChPh.142p4110L. doi:10.1063/1.4919310. PMID 25933755. S2CID 36839435.