Dynamic simulation of an electrorheological fluid

A molecular-dynamics-like method is presented for the simulation of a suspension of dielectric particles in a nonconductive solvent forming an electrorheological fluid. The method accurately accounts for both hydrodynamic and electrostatic interparticle interactions from dilute volume fractions to closest packing for simultaneous shear and electric fields. The hydrodynamic interactions and rheology are determined with the Stokesian dynamics methodology, while the electrostatic interactions, in particular, the conservative electrostatic interparticle forces, are determined from the electrostatic energy of the suspension. The energy of the suspension is computed from the induced particle dipoles by a method previously developed [R. T. Bonnecaze and J. F. Brady, Proc. R. Soc. London, Ser. A 430, 285 (1990)]. Using the simulation, the dynamics can be directly correlated to the observed macroscopic rheology of the suspension for a range of the so-called Mason number, Ma, the ratio of viscous to electrostatic forces. The simulation is specifically applied to a monolayer of spherical particles of areal fraction 0.4 with a particle-to-fluid dielectric constant ratio of 4 for Ma=10^−4 to [infinity]. The effective viscosity of the suspension increases as Ma^−1 or with the square of the electric field for small Ma and has a plateau value at large Ma, as is observed experimentally. This rheological behavior can be interpreted as Bingham plastic-like with a dynamic yield stress. The first normal stress difference is negative, and its magnitude increases as Ma^−1 at small Ma with a large Ma plateau value of zero. In addition to the time averages of the rheology, the time traces of the viscosities are presented along with selected "snapshots" of the suspension microstructure. In particular, at small Ma, the suspension dynamics exhibit two distinct motions: a slow elastic-body-like deformation where electrostatic energy is stored, followed by a rapid microstructural rearrangement where energy is viscously dissipated. It is suggested that the observed dynamic yield stress is associated with these dynamics

Polymer Dissolution Model: An Energy Adaptation Of The Critical Ionization Theory

The current scale of features size in the microelectronics industry has reached the point where molecular level interactions affect process fidelity and produce excursions from the continuum world like line edge roughness (LER). Here we present a 3D molecular level model based on the adaptation of the critical ionization (CI) theory using a fundamental interaction energy approach. The model asserts that it is the favorable interaction between the ionized part of the polymer and the developer solution which renders the polymer soluble. Dynamic Monte Carlo methods were used in the current model to study the polymer dissolution phenomenon. The surface ionization was captured by employing an electric double layer at the interface, and polymer motion was simulated using the Metropolis algorithm. The approximated interaction parameters, for different species in the system, were obtained experimentally and used to calibrate the simulated dissolution rate response to polymer molecular weight and developer concentration. The predicted response is in good agreement with experimental dissolution rate data. The simulation results support the premise of the CI theory and provide an insight into the CI model from a new prospective. This model may provide a means to study the contribution of development to LER and other related defects based on molecular level interactions between distinct components in the polymer and the developer.Chemical Engineerin

Rate of diffusion-limited reactions in dispersions of spherical traps via multipole scattering

The effective reaction rate is calculated for a random array of reactive, stationary spherical traps in a medium containing a highly mobile reactant. Multipole scattering up to the quadrupole level, properly accounting for the conditionally convergent long-range interactions, plus direct addition of exact two-body interactions is employed. It is found that the addition of two-body interactions has a negligible effect on the effective reaction rates computed, in contrast to the case of the effective conductivity. Our results closely match the random walker simulation results of Lee, Kim, Miller, and Torquato [Phys. Rev. B 39, 11833 (1989)] up to 30% trap volume fraction, after which they underpredict the effective reaction rate. To accurately compute the effective reaction rate at high volume fractions, higher order many-body multipole interactions are required

Computer simulations of electrorheological fluids in the dipole-induced dipole model

We have employed the multiple image method to compute the interparticle force for a polydisperse electrorheological (ER) fluid in which the suspended particles can have various sizes and different permittivites. The point-dipole (PD) approximation being routinely adopted in computer simulation of ER fluids is shown to err considerably when the particles approach and finally touch due to multipolar interactions. The PD approximation becomes even worse when the dielectric contrast between the particles and the host medium is large. From the results, we show that the dipole-induced-dipole (DID) model yields very good agreements with the multiple image results for a wide range of dielectric contrasts and polydispersity. As an illustration, we have employed the DID model to simulate the athermal aggregation of particles in ER fluids both in uniaxial and rotating fields. We find that the aggregation time is significantly reduced. The DID model accounts for multipolar interaction partially and is simple to use in computer simulation of ER fluids.Comment: 22 pages, 7 figures, submitted to Phys. Rev.

Electrical conductivity of dispersions: from dry foams to dilute suspensions

We present new data for the electrical conductivity of foams in which the liquid fraction ranges from two to eighty percent. We compare with a comprehensive collection of prior data, and we model all results with simple empirical formul\ae. We achieve a unified description that applies equally to dry foams and emulsions, where the droplets are highly compressed, as well as to dilute suspensions of spherical particles, where the particle separation is large. In the former limit, Lemlich's result is recovered; in the latter limit, Maxwell's result is recovered

Perturbation theory for the effective diffusion constant in a medium of random scatterer

We develop perturbation theory and physically motivated resummations of the perturbation theory for the problem of a tracer particle diffusing in a random media. The random media contains point scatterers of density $\rho$ uniformly distributed through out the material. The tracer is a Langevin particle subjected to the quenched random force generated by the scatterers. Via our perturbative analysis we determine when the random potential can be approximated by a Gaussian random potential. We also develop a self-similar renormalisation group approach based on thinning out the scatterers, this scheme is similar to that used with success for diffusion in Gaussian random potentials and agrees with known exact results. To assess the accuracy of this approximation scheme its predictions are confronted with results obtained by numerical simulation.Comment: 22 pages, 6 figures, IOP (J. Phys. A. style

Transport properties of heterogeneous materials derived from Gaussian random fields: Bounds and Simulation

We investigate the effective conductivity ($\sigma_e$) of a class of amorphous media defined by the level-cut of a Gaussian random field. The three point solid-solid correlation function is derived and utilised in the evaluation of the Beran-Milton bounds. Simulations are used to calculate $\sigma_e$ for a variety of fields and volume fractions at several different conductivity contrasts. Relatively large differences in $\sigma_e$ are observed between the Gaussian media and the identical overlapping sphere model used previously as a `model' amorphous medium. In contrast $\sigma_e$ shows little variability between different Gaussian media.Comment: 15 pages, 14 figure