arXiv subjects

Michael P. Howard

Publications and source records attributed to Michael P. Howard.

At least 19 recordsLinked to original sources

arXiv2026

Coarse-graining to create minimalist models for dynamic, end-linked star-polymer networks

Although minimalist models for patchy attractive particles have revealed powerful design rules for how particle valence directs colloidal assembly, less work has focused on comparably simple models of reversible, network-forming star polymers. Here, we use relative-entropy coarse-graining and simulation results from finer-resolution bead--spring star polymers to generate 5-bead models of dynamic, end-associating four-armed poly(ethylene glycol) macromers. Our results comparing structural correlations, network connectivity, and phase behavior of the coarse- and fine-grained models provide insight into how the accuracy and transferability of the coarse-grained models depend on the state point chosen for coarse-graining. The results also reveal intrinsic trade-offs between reducing degrees of freedom and expanding the range of effective interactions in coarse-graining that impact the total number of pairwise interactions in the resulting model, with implications for its computational efficiency.

cond-mat.soft↗

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

Approximation of anisotropic pairwise interactions for charged objects using multivariate polynomials and a multipole expansion

We formulate a physics-informed data-driven method for modeling anisotropic pairwise interactions in the presence of long-ranged electrostatics. The method separates the total interaction into a long-ranged electrostatic interaction that is approximated using a multipole expansion truncated at the dipole level and a short-ranged residual interaction that is approximated using multivariate Chebyshev polynomials fit to measurements from a limited number of configurations. We assess the approach on a sequence of aromatic molecules (benzene, benzonitrile, and phenoxide), finding that it produces satisfactory results using a modest cutoff distance for the short-ranged interaction. This method has applications for modeling complex interactions for, and conducting dynamic simulations of, synthetic and biological materials with charge.

cond-mat.soft↗

arXiv2026

Controlling Porosity in Supraparticles Composed of Colloidal Rods and Spheres

Supraparticles (SPs) are assemblies of colloidal particles whose properties can be tuned by modifying the chemistry, shape, and size of the colloidal particles as well as their arrangement in the SP. SPs with internal porosity are of particular interest for catalysis, photonics, and adsorption applications because of their high surface area and tunable pore size distribution. SPs are often fabricated by droplet drying, and the nonequilibrium nature of drying processes may provide an additional handle to control particle arrangement within the SP. Here, we use mesoscale particle-based simulations to explore the drying-induced assembly of SPs made from rod-shaped and spherical colloidal particles. We selectively remove one type of particle after drying and characterize the structure of the resulting porous SP. We find that the remaining particles form connected networks for most compositions, with rods percolating at lower volume fractions than spheres. Most of the resulting void volume forms a single contiguous space whose surface area closely follows the total surface area of the remaining component. The pore-size distribution, however, depends strongly on sphere size and on the removed component, reflecting differences in sphere-clustering and rod-bundling before removal. This work provides new insight into how particle size and shape, as well as processing conditions, might be used to manipulate porosity in SPs.

cond-mat.soft↗

arXiv2026

Axial dispersion in dilute solutions of linear and branched polymers in parallel-plate and expansion-contraction microchannels

The axial dispersion of polymers in microchannels depends on an interplay between microchannel geometry, polymer architecture, and hydrodynamics. Here, we investigate the axial dispersion of linear, comb, and star polymers in parallel-plate and sinusoidal expansion-contraction microchannels at dilute concentrations using multiparticle collision dynamics simulations. The polymers all contain the same number of monomers but differ in their architecture, and their concentration is fixed at either one value that is dilute for all polymers or the same value relative to the overlap concentration for each polymer. The dispersion coefficients measured at a nominal solvent volumetric flow rate are found to depend on both architecture and concentration. We show that the dispersion coefficients collapse as a function of the P\'eclet number after accounting for confinement effects on the polymer diffusion coefficient and polymer contributions to the flow field, and the dispersion coefficients in the parallel-plate microchannel can be reasonably predicted using a theory that accounts for inhomogeneous distribution of the polymers in the microchannel.

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↗

arXiv2026

Transport properties of monodisperse and bidisperse hard-sphere colloidal suspensions from multiparticle collision dynamics simulations

The shear viscosities, long-time self-diffusion coefficients, and sedimentation velocities in monodisperse and bidisperse hard-sphere colloidal suspensions are simulated for volume fractions up to 0.40 using multiparticle collision dynamics with a discrete particle model. The bidisperse suspensions have diameter ratios of 2 and 4 and equal amounts of each particle by volume. All measured properties for monodisperse suspensions are found to be in good agreement with prior literature; however, they highlight the sensitivity of the simulation method to discretization effects. The sedimentation velocities for the bidisperse suspensions are also in reasonable agreement with prior literature, including direction reversal for the smaller particles when the diameter ratio is 4. This work provides reference data for transport properties of colloidal suspensions and establishes the suitability of multiparticle collision dynamics for modeling suspensions of particles with different sizes.

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

Effects of skewing collision cells on transport properties in multiparticle collision dynamics simulations

Multiparticle collision dynamics (MPCD) is a mesoscale simulation technique that uses a simplified solvent to model hydrodynamic interactions. Rather than interact through pairwise forces, MPCD solvent particles undergo momentum-exchanging collisions within spatially localized cells according to prescribed rules. The conventional MPCD algorithm employs cubic collision cells, but this choice is not optimal for systems that are most naturally described using skewed simulation boxes. Here, we investigate the behavior of a modified MPCD scheme in which the collision cells are aligned with the vectors that define a triclinic (parallelepiped) simulation box. We find that skewing the collision cells has a small but statistically significant impact on the transport properties of the pure solvent. Similar, but more pronounced, effects are found for nearly hard spheres in solution, including a significant decrease in their nominal self-diffusion coefficient and unphysical anisotropy in their self-diffusion tensor. Thus, our analysis indicates that skewed MPCD collision cells may result in spurious behavior and should be used with caution. We posit that these artifacts may be mitigated by grid-free schemes for placing particles into collision cells.

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↗

arXiv2025

Mesoscale particle-based simulations of flow in expansion-contraction microchannels at low Reynolds number

We computationally study the flow of Newtonian fluids through sinusoidal expansion-contraction microchannels at low Reynolds number. We first use a perturbation method to analytically derive series solutions for the stream function and volumetric flow rate that extend prior work [P.K. Kitanidis and B.B. Dykaar, Transport in Porous Media 26, 89-98 (1997)] up to tenth order. We then employ two particle-based mesoscale methods, dissipative particle dynamics (DPD) and multiparticle collision dynamics (MPCD), to simulate the same flows. We find that the fluid velocity at the expansion and contraction points as well as the volumetric flow rate are in good agreement between DPD, MPCD, and the fourth-order series solution for a wide range of microchannel geometries. The mesoscale fluid models exhibit some slip at the walls, leading to a small but consistent overprediction of the velocity and volumetric flow rate. The series solution fails for short microchannel lengths and large amplitudes; we identify lengths and amplitudes for which it converges to a given order. Overall, we find that DPD and MPCD are convenient and reasonably accurate methods, particularly for microchannel geometries where the series solution fails or is cumbersome to implement.

physics.flu-dyn↗

arXiv2025

Designing binary mixtures of colloidal particles with simple interactions that assemble complex crystals

Computational methods for designing interactions between colloidal particles that induce self-assembly have received much attention for their promise to discover tailored materials. However, it often remains a challenge to translate computationally designed interactions to experiments because they may have features that are too complex, or even infeasible, to physically realize. Toward bridging this gap, we leverage relative-entropy minimization to design pair potentials for binary mixtures of colloidal particles that assemble crystal superlattices. We reduce the dimensionality and extent of the interaction design space by enforcing constraints on the form and parametrization of the pair potentials that are physically motivated by DNA-functionalized nanoparticles. We show that several two- and three-dimensional lattices, including honeycomb and cubic diamond, can be assembled using simple interactions despite their complex structures. We also find that the initial conditions used for the designed parameters as well as the assembly protocol play important roles in determining the outcome and success of the assembly process.

cond-mat.soft↗

arXiv2025

Effects of Ligand vs. Linker on Phase Behavior and Mechanical Properties of Nanoparticle Gels

Nanoparticle gels have attracted considerable attention due to their highly tunable properties. One strategy for producing nanoparticle gels involves using strong local attractions between polymeric molecules, such as DNA hybridization or dynamic covalent chemistry, to form percolated nanoparticle networks. These molecules can be used in two distinct roles: as "ligands" with one end grafted to a nanoparticle or as "linkers" with both ends free. Here, we explore how these roles shape the phase behavior and mechanical properties of gel-like nanoparticle assemblies using coarse-grained simulations. We systematically vary the interaction strength and bending stiffness of both ligands and linkers. We find that phase separation can be limited to low nanoparticle volume fractions by making the ligands rigid, consistent with previous studies on linked nanoparticle gels. At fixed interaction strength and volume fraction, both ligand- and linker-mediated nanoparticle assemblies show similar mechanical responses as bending stiffness is varied. However, a comparison between the two association schemes reveals that the linked nanoparticles form rigid percolated networks that are less stretchable than the ligand-grafted gels, despite exhibiting similar tensile strength. We attribute these differences between ligands and linkers to the distinct structural arrangement of nanoparticles within the gel. Our findings highlight the potential to use different association schemes to tune specific mechanical properties.

cond-mat.soft↗

arXiv2025

Approximation of anisotropic pair potentials using multivariate interpolation

The interaction between two particles with shape or interaction anisotropy can be modeled using a pairwise potential energy function that depends on their relative position and orientation; however, this function is often challenging to mathematically formulate. Data-driven approaches for approximating anisotropic pair potentials have gained significant interest due to their flexibility and generality but often require large sets of training data, potentially limiting their feasibility when training data is computationally demanding to collect. Here, we investigate the use of multivariate polynomial interpolation to approximate anisotropic pair potentials from a limited set of prescribed particle configurations. We consider both standard Chebyshev polynomial interpolation as well as mixed-basis polynomial interpolation that uses trigonometric polynomials for coordinates along which the pair potential is known to be periodic. We exploit mathematical reasoning and physical knowledge to refine the interpolation domain and to design our interpolants. We test our approach on two-dimensional and three-dimensional model anisotropic nanoparticles, finding satisfactory approximations can be constructed in all cases.

cond-mat.soft↗

arXiv2025

Exploring the role of hydrodynamic interactions in spherically-confined drying colloidal suspensions

We study the distribution of colloidal particles confined in drying spherical droplets using both dynamic density functional theory (DDFT) and particle-based simulations. In particular, we focus on the advection-dominated regime typical of aqueous droplets drying at room temperature and systematically investigate the role of hydrodynamic interactions during this nonequilibrium process. In general, drying produces transient particle concentration gradients within the droplet in this regime, with a considerable accumulation of particles at the droplet's liquid-vapor interface. We find that these gradients become significantly larger with pairwise hydrodynamic interactions between colloidal particles instead of a free-draining hydrodynamic approximation; however, the solvent's boundary conditions at the droplet's interface (unbounded, slip, or no-slip) do not have a significant effect on the particle distribution. DDFT calculations leveraging radial symmetry of the drying droplet are in excellent agreement with particle-based simulations for free-draining hydrodynamics, but DDFT unexpectedly fails for pairwise hydrodynamic interactions after the particle concentration increases during drying, manifesting as an ejection of particles from the droplet. We hypothesize that this unphysical behavior originates from an inaccurate approximation of the two-body density correlations based on the bulk pair correlation function, which we support by measuring the confined equilibrium two-body density correlations using particle-based simulations. We identify some potential strategies for addressing this issue in DDFT.

cond-mat.soft↗

arXiv2024

relentless: Transparent, reproducible molecular dynamics simulations for optimization

relentless is an open-source Python package that enables the optimization of objective functions computed using molecular dynamics simulations. It has a high-level, extensible interface for model parametrization; setting up, running, and analyzing simulations natively in established software packages; and gradient-based optimization. We describe the design and implementation of relentless in the context of relative entropy minimization, and we demonstrate its abilities to design pairwise interactions between particles that form targeted structures. relentless aims to streamline the development of computational materials design methodologies and promote the transparency and reproducibility of complex workflows integrating molecular dynamics simulations.

cond-mat.soft↗

arXiv2024

Mesoscale simulations of diffusion and sedimentation in shape-anisotropic nanoparticle suspensions

We determine the long-time self-diffusion coefficient and sedimentation coefficient for suspensions of nanoparticles with anisotropic shapes (octahedra, cubes, tetrahedra, and spherocylinders) as a function of nanoparticle concentration using mesoscale simulations. We use a discrete particle model for the nanoparticles, and we account for solvent-mediated hydrodynamic interactions between nanoparticles using the multiparticle collision dynamics method. Our simulations are compared to theoretical predictions and experimental data from existing literature, demonstrating good agreement in the majority of cases. Further, we find that the self-diffusion coefficient of the regular polyhedral shapes can be estimated from that of a sphere whose diameter is average of their inscribed and circumscribed sphere diameters.

cond-mat.soft↗

arXiv2022

Multiscale modeling of solute diffusion in triblock copolymer membranes

We develop a multiscale simulation model for diffusion of solutes through porous triblock copolymer membranes. The approach combines two techniques: self-consistent field theory (SCFT) to predict the structure of the self-assembled, solvated membrane and on-lattice kinetic Monte Carlo (kMC) simulations to model diffusion of solutes. Solvation is simulated in SCFT by constraining the glassy membrane matrix while relaxing the brush-like membrane pore coating against the solvent. The kMC simulations capture the resulting solute spatial distribution and concentration-dependent local diffusivity in the polymer-coated pores; we parameterize the latter using particle-based simulations. We apply our approach to simulate solute diffusion through nonequilibrium morphologies of a model triblock copolymer, and we correlate diffusivity with structural descriptors of the morphologies. We also compare the model's predictions to alternative approaches based on simple lattice random walks and find our multiscale model to be more robust and systematic to parameterize. Our multiscale modeling approach is general and can be readily extended in the future to other chemistries, morphologies, and models for the local solute diffusivity and interactions with the membrane.

cond-mat.soft↗