arXiv subjects

Michaela Bush

Publications and source records attributed to Michaela Bush.

4 recordsLinked to original sources

arXiv2026

Discretization strategies for colloidal particles in multiparticle collision dynamics simulations

Discrete models are frequently used in multiparticle dynamics simulations to capture hydrodynamic interactions between colloidal particles and the solvent as well as to represent anisotropic pairwise interactions between colloidal particles; however, there is currently limited guidance on how to reliably parameterize these models. Here, we first compare strategies for selecting the density and mass of discrete surface sites used to couple colloidal particles to the solvent, finding that using a minimum of 2 sites per unit area with a scheme that matches the total mass and moment of inertia for a neutrally buoyant solid particle produces reliable and accurate results for the transport properties of colloidal particles at both infinite dilution and in suspension. We then compare strategies for representing the excluded volume of nearly-hard shape-anisotropic colloidal particles using a collection of discrete interaction sites with isotropic repulsion, finding that having a discrepancy between the nominal volume and the excluded volume of the particle can significantly affect suspension transport properties. This discrepancy can be mitigated by placing the interaction sites inside and tangent to the surface of the colloidal particle. We expect these findings to help construct discrete models for colloidal particles with less sensitivity to parameterization.

cond-mat.soft↗

arXiv2026

Simulating hydrodynamic interactions in colloidal suspensions using multiparticle collision dynamics with rigid-body constraints

We develop a method for simulating colloidal suspensions using multiparticle collision dynamics (MPCD) with a discrete particle model represented as a rigid body. The key steps for incorporating the rigid-body constraints are to thermalize the velocities of the discrete sites before they participate in the MPCD collision step, then transfer momentum from the sites to the rigid body. We demonstrate that the rigid-body model produces the expected statistics for a single spherical particle and the same transport properties for a hard-sphere colloidal suspension as an equivalent model using harmonic bonds to maintain the site geometry. Importantly, the rigid-body model has less computational overhead and permits a larger simulation timestep than the harmonic-bond model, leading to a nearly order of magnitude speedup in benchmark simulations of hard-sphere colloidal suspensions. Our method is compatible with arbitrary discretization, so it enables more efficient MPCD simulations of suspensions of colloidal particles with complex shapes.

cond-mat.soft↗

arXiv2025

Approximation of forces and torques from anisotropic pairwise interactions using multivariate polynomials

The dynamics of anisotropic particles are dictated by forces and torques that can be challenging to mathematically represent in computer simulations. Several data-driven approaches have been developed to approximate these interactions, but they often rely on having large amounts of training data that may be practically difficult to generate. Here, we extend a framework we recently developed for approximating anisotropic pair potentials to the approximation of pairwise forces and torques. The framework uses multivariate polynomials and physics-motivated coordinate transformations to produce accurate approximations using limited amounts of data. We first derive expressions relating the force and torque to partial derivatives of the potential energy with respect to the transformed coordinates used to represent the particle configuration. We then explore several options for approximating the forces and torques, and we critically assess their accuracy using model two- and three-dimensional shape-anisotropic nanoparticles as test cases. We find that interpolation of the pairwise potential energy produces the best result when it is known, but force and torque matching (regression) is a viable strategy when only the force and torque is available.

cond-mat.soft↗

arXiv2025

Inverse design of drying-induced assembly of multicomponent colloidal-particle films using surrogate models

The properties of films assembled by drying colloidal-particle suspensions depend sensitively on both the particles and the processing conditions, making them challenging to engineer. In this work, we develop and test an inverse-design strategy based on surrogate modeling to identify conditions that yield a target film structure. We consider a two-component hard-sphere colloidal suspension whose designable parameters are the particle sizes, the initial composition of particles, and the drying rate. Film drying is simulated approximately using Brownian dynamics. Surrogate models based on Gaussian process regression (GPR) and Chebyshev polynomial interpolation are trained on a loss function, computed from the simulated film structures, that guides the design process. We find the surrogate models to be effective for both approximation and optimization using only a small number of samples of the loss function. The GPR models are typically slightly more accurate than polynomial interpolants trained using comparable amounts of data, but the polynomial interpolants are more computationally convenient. This work has important implications not only for designing colloidal materials but also more broadly as a strategy for engineering nonequilibrium assembly processes.

cond-mat.soft↗