Searcharxiv⌕ Search

arXiv · cond-mat/0603391

Hydrodynamic interactions and Brownian forces in colloidal suspensions: Coarse-graining over time and length-scales

Abstract

We describe in detail how to implement a coarse-grained hybrid Molecular Dynamics and Stochastic Rotation Dynamics simulation technique that captures the combined effects of Brownian and hydrodynamic forces in colloidal suspensions. The importance of carefully tuning the simulation parameters to correctly resolve the multiple time and length-scales of this problem is emphasized. We systematically analyze how our coarse-graining scheme resolves dimensionless hydrodynamic numbers such as the Reynolds number, the Schmidt number, the Mach number, the Knudsen number, and the Peclet number. The many Brownian and hydrodynamic time-scales can be telescoped together to maximize computational efficiency while still correctly resolving the physically relevant physical processes. We also show how to control a number of numerical artifacts, such as finite size effects and solvent induced attractive depletion interactions. When all these considerations are properly taken into account, the measured colloidal velocity auto-correlation functions and related self diffusion and friction coefficients compare quantitatively with theoretical calculations. By contrast, these calculations demonstrate that, notwithstanding its seductive simplicity, the basic Langevin equation does a remarkably poor job of capturing the decay rate of the velocity auto-correlation function in the colloidal regime, strongly underestimating it at short times and strongly overestimating it at long times. Finally, we discuss in detail how to map the parameters of our method onto physical systems, and from this extract more general lessons that may be relevant for other coarse-graining schemes such as Lattice Boltzmann or Dissipative Particle Dynamics.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

J. T. Padding, A. A. Louis. 2006-09-08. Hydrodynamic interactions and Brownian forces in colloidal suspensions: Coarse-graining over time and length-scales. https://doi.org/10.1103/physreve.74.031402

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Dynamic clustering of active chemotactic Janus particles

Modeling self-propulsion as an emergent diffusiophoretic effect, we come back to the dynamic clustering experiment of active Janus colloids. Working in the original three-dimensional geometry, and using the chemical solute concentration as a control parameter, we find that the dynamic clustering region occupies a robust fraction of the phase diagram. This behavior is rationalized using a linear stability analysis that efficiently captures the instability of the gas phase to dynamic clusters. We also find that dynamic clustering results from the combined effects of a Keller-Segel collapse and of a motility-induced phase separation, either being arrested by the orientational coupling to the chemical field in agreement with previous work.

cond-mat.soft↗

Multi-Fidelity Machine Learning for Predicting Startup Stress Growth and Strain Hardening in Wormlike Micellar Solutions

Wormlike micellar solutions exhibit formulation-dependent nonlinear startup responses, including stress overshoot, undershoot, and strain hardening, making prediction across compositions and shear rates challenging. We developed a multi-fidelity machine-learning framework to predict stress-growth curves in cetylpyridinium chloride (CPyCl)-based wormlike micelles from sparse experimental measurements. The framework combines a low-fidelity analytical model describing the overall startup response with high-fidelity experimental data capturing formulation-specific nonlinear features. This approach addresses the limited and uneven coverage of salt chemistry, concentration, and shear rate without relying solely on data-intensive neural-network training. The trained model predicts complete stress-growth responses at untested shear rates and enables extraction of strain-hardening characteristics from interpolated curves. By augmenting sparse rheological measurements, the framework provides a basis for exploring relationships among formulation variables, linear viscoelastic properties, and nonlinear startup behavior, while supporting more efficient characterization of wormlike micellar solutions.

cond-mat.soft↗

Topology Does Not Determine Defect Mobility in Active Polar Matter

Topological defects are commonly characterized by their charge, although defects with the same charge can have different internal morphologies. We study the annihilation of isolated $\pm1$ defect pairs in a two-dimensional compressible Toner--Tu model, varying the morphology of the $+1$ defect while keeping the initial charges and separation fixed. Activity produces a morphology-dependent mobility asymmetry: reversing the radial orientation of an aster reverses which defect travels farther, and asters show the strongest response. An early-time analysis reveals that the initial morphology selects distinct density modes whose gradients subsequently feed back on the polarization. Consistently, removing the density-gradient coupling strongly suppresses the asymmetry. These results establish defect morphology, in addition to topological charge, as a dynamical variable governing defect-pair motion in active polar matter.

cond-mat.soft↗