We extend the classic study of the motion of small ellipsoidal particles under shear, focusing on simplifications obtained by considerations of the extreme aspect ratios typical of rheoscopic particles (e.g., Kalliroscope). Specifically, we study conditions under which the long-time behavior of scalene (i.e., triaxial or nonaxisymmetric) ellipsoids are well approximated by a model that is low order in the appropriate aspect ratios. After enumerating and describing the generic long-time motions of such particles in the lowest-order model, we investigate corrections induced by the physically appropriate lowest-order correction to the base model, with special attention to a periodic wobbling motion special to scalene ellipsoids.

Using a previously developed coarse-grained model, we conducted large-scale ($\sim 85\times 85\times 85{\mathrm{nm}}^3$) molecular dynamics simulations of uniaxial-strain deformation to study the tensile behavior of an epoxy molding compound, epoxy phenol novolacs (EPN) bisphenol A (BPA). Under the uniaxial-strain deformation, the material is found to exhibit cavity nucleation and growth, followed by stretching of the ligaments separated by the cavities, until the ultimate failure through ligament scissions. The nucleation sites of cavities are rather random and the subsequent cavity growth accounts for much (87%) of the volumetric change during the uniaxial-strain deformation. Ultimate failure of the materials occurs when the cavity volume fraction reaches ∼60%. During the entire deformation process, polymer strands in the network are continuously extended to their linear states and broken in the postyielding strain hardening stage. When most of the strands are stretched to their taut configurations, rapid scission of a large number of strands occurs within a small strain increment, which eventually leads to fracture. Finally, through extensive numerical simulations of various loading conditions in addition to uniaxial strain, we find that yielding of the EPN-BPA can be described by the pressure-modified von Mises yield criterion.

Understanding neural variability is currently one of the biggest challenges in neuroscience. Using theory and computational modeling, we study the behavior of a globally coupled inhibitory neural network, in which each neuron follows a purely stochastic two-state spiking process. We investigate the role of both this intrinsic randomness and the conduction delay on the emergence of fast (e.g., gamma) oscillations. Toward that end, we expand the recently proposed linear noise approximation (LNA) technique to this non-Markovian “delay” case. The analysis first leads to a nonlinear delay-differential equation (DDE) with multiplicative noise for the mean activity. The LNA then yields two coupled DDEs, one of which is driven by additive Gaussian white noise. These equations on their own provide an excellent approximation to the full network dynamics, which are much longer to integrate. They further allow us to compute a theoretical expression for the power spectrum of the population activity. Our analytical result is in good agreement with the power spectrum obtained via numerical simulations of the full network dynamics, for the large range of parameters where both the intrinsic stochasticity and the conduction delay are necessary for the occurrence of oscillations. The intrinsic noise arises from the probabilistic description of each neuron, yet it is expressed at the system activity level, and it can only be controlled by the system size. In fact, its effect on the fluctuations in system activity disappears in the infinite network size limit, but the characteristics of the oscillatory activity depend on all model parameters including the system size. Using the Hilbert transform, we further show that the intrinsic noise causes sporadic strong fluctuations in the phase of the gamma rhythm.

We derive exact and approximate localized solutions for the Manakov-type continuous and discrete equations. We establish the correspondence between the solutions of the coupled Ablowitz-Ladik equations and the solutions of the coupled higher-order Manakov equations.

We investigate a two-dimensional tiling model. Even though the degrees of freedom in this model are discrete, it has a hidden continuous global symmetry in the infinite lattice limit, whose corresponding Goldstone modes are the quasicrystalline phasonic degrees of freedom. We show that due to this continuous symmetry and despite the apparent discrete nature of the model, a topological phase transition from a quasi-long-range ordered to a disordered phase occurs at a finite temperature, driven by vortex proliferation. We argue that some of the results are universal properties of two-dimensional systems whose ground state is a quasicrystalline state.

The purely repulsive soft-sphere system, where the interaction potential is inversely proportional to the pair separation raised to the power $n$, is considered. The Laplace transform technique is used to derive its thermodynamic properties in terms of the potential energy and its density derivative obtained from molecular dynamics simulations. The derived expressions provide an analytic framework with which to explore soft-sphere thermodynamics across the whole softness-density fluid domain. The trends in the isochoric and isobaric heat capacity, thermal expansion coefficient, isothermal and adiabatic bulk moduli, Grüneisen parameter, isothermal pressure, and the Joule-Thomson coefficient as a function of fluid density and potential softness are described using these formulas supplemented by the simulation-derived equation of state. At low densities a minimum in the isobaric heat capacity with density is found, which is a new feature for a purely repulsive pair interaction. The hard-sphere and $n=3$ limits are obtained, and the low density limit specified analytically for any $n$ is discussed. The softness dependence of calculated quantities indicates freezing criteria based on features of the radial distribution function or derived functions of it are not expected to be universal. A new and accurate formula linking the self-diffusion coefficient to the excess entropy for the entire fluid softness-density domain is proposed, which incorporates the kinetic theory solution for the low density limit and an entropy-dependent function in an exponential form. The thermodynamic properties (or their derivatives), structural quantities, and diffusion coefficient indicate that three regions specified by a convex, concave, and intermediate density dependence can be expected as a function of $n$, with a narrow transition region within the range $5<n<8$.

We analyze the trajectory of suspended spherical particles moving through a square array of obstacles, in the deterministic limit and at zero Reynolds number. We show that in the dilute approximation of widely separated obstacles, the average motion of the particles is equivalent to the trajectory followed by a point particle moving through an array of obstacles with an effective radius. The effective radius accounts for the hydrodynamic as well as short-range repulsive nonhydrodynamic interactions between the suspended particles and the obstacles, and is equal to the critical offset at which particle trajectories become irreversible. Using this equivalent system we demonstrate the presence of directional locking in the trajectory of the particles and derive an inequality that accurately describes the “devil's staircase” type of structure observed in the migration angle as a function of the forcing direction. We use these results to determine the optimum resolution in the fractionation of binary mixtures using deterministic lateral-displacement microfluidic separation systems as well as to comment on the collision frequencies when the arrays of posts are utilized as immunocapture devices.

We investigate the multiorder parameter phase field model of Steinbach and Pezzolla [Physica D 134, 385 (1999)] concerning its ability to describe grain boundary premelting. For a single order parameter situation solid-melt interfaces are always attractive, which allows us to have (unstable) equilibrium solid-melt-solid coexistence above the bulk melting point. The temperature-dependent melt layer thickness and the disjoining potential, which describe the interface interaction, are affected by the choice of the thermal coupling function and the measure to define the amount of the liquid phase. Due to the strictly finite interface thickness the interaction range also is finite. For a multiorder parameter model we find either purely attractive or purely repulsive finite-ranged interactions. The premelting transition is then directly linked to the ratio of the grain boundary and solid-melt interfacial energy.

A thin layer of nematic liquid crystal (NLC) across which an electric field is applied is a setup of great industrial importance in liquid crystal display devices. There is thus a large literature modeling this situation and related scenarios. A commonly used assumption is that an electric field generated by electrodes at the two bounding surfaces of the layer will produce a field that is uniform: that is, the presence of NLC does not affect the electric field. In this paper, we use calculus of variations to derive the equations coupling the electric potential to the orientation of the NLC's director field, and use a simple one-dimensional model to investigate the limitations of the uniform field assumption in the case of a steady applied field. The extension of the model to the unsteady case is also briefly discussed.

We numerically examine the transport of active run-and-tumble particles with steric particle-particle interactions driven with a drift force over random disordered landscapes composed of fixed obstacles. For increasing run lengths, the net particle transport initially increases before reaching a maximum and decreasing at larger run lengths. The transport reduction is associated with the formation of cluster or living crystal states that become locally jammed or clogged by the obstacles. We also find that the system dynamically jams at lower particle densities when the run length is increased. Our results indicate that there is an optimal activity level for transport of run-and-tumble type active matter through quenched disorder and could be important for understanding biological transport in complex environments or for applications of active matter particles in random media.

We study the collective dynamics of modular networks consisting of map-based neurons which generate irregular spike sequences. Three types of intramodule topology are considered: a random Erdös-Rényi network, a small-world Watts-Strogatz network, and a scale-free Barabási-Albert network. The interaction between the neurons of different modules is organized by relatively sparse connections with time delay. For all the types of the network topology considered, we found that with increasing delay two regimes of module synchronization alternate with each other: inphase and antiphase. At the same time, the average rate of collective oscillations decreases within each of the time-delay intervals corresponding to a particular synchronization regime. A dual role of the time delay is thus established: controlling a synchronization mode and degree and controlling an average network frequency. Furthermore, we investigate the influence on the modular synchronization by other parameters: the strength of intermodule coupling and the individual firing rate.

The influence of the texture of a hydrophobic surface on the electro-osmotic slip of the second kind and the electrokinetic instability near charge selective surfaces (permselective membranes, electrodes, or systems of microchannels and nanochannels) is investigated theoretically using a simple model based on the Rubinstein-Zaltzman approach. A simple formula is derived to evaluate the decrease in the instability threshold due to hydrophobicity. The study is complemented by numerical investigations both of linear and nonlinear instabilities near a hydrophobic membrane surface. Theory predicts a significant enhancement of the ion flux to the surface and shows a good qualitative agreement with the available experimental data.

A boundary scheme in the lattice Boltzmann method (LBM) for the convection-diffusion equation, which correctly realizes the internal boundary condition at the interface between two phases with different transport properties, is presented. The difficulty in satisfying the continuity of flux at the interface in a transient analysis, which is inherent in the conventional LBM, is overcome by modifying the collision operator and the streaming process of the LBM. An asymptotic analysis of the scheme is carried out in order to clarify the role played by the adjustable parameters involved in the scheme. As a result, the internal boundary condition is shown to be satisfied with second-order accuracy with respect to the lattice interval, if we assign appropriate values to the adjustable parameters. In addition, two specific problems are numerically analyzed, and comparison with the analytical solutions of the problems numerically validates the proposed scheme.

The anomalous preasymptotic transport of colloids in a microfluidic capillary flow due to hydrodynamic dispersion is measured by noninvasive nuclear magnetic resonance (NMR). The data indicate a reduced scaling of mean squared displacement with time from the ${\langle z{\left(t\right)}^2\rangle }_c\sim t^3$ behavior for the interaction of a normal diffusion process with a simple shear flow. This nonequilibrium steady-state system is shown to be modeled by a continuous time random walk (CTRW) on a moving fluid. The full propagator of the motion is measured by NMR, providing verification of the assumption of Gaussian jump length distributions in the CTRW model. The connection of the data to microrheology measurements by NMR, in which every particle in a suspension contributes information, is established.

Driven elastic manifolds in random media exhibit a depinning transition to a state with nonvanishing velocity at a critical driving force. We study the depinning of stiff directed lines, which are governed by a bending rigidity rather than line tension. Their equation of motion is the (quenched) Herring-Mullins equation, which also describes surface growth governed by surface diffusion. Stiff directed lines are particularly interesting as there is a localization transition in the static problem at a finite temperature and the commonly exploited time ordering of states by means of Middleton's theorems [Phys. Rev. Lett. 68, 670 (1992)] is not applicable. We employ analytical arguments and numerical simulations to determine the critical exponents and compare our findings with previous works and functional renormalization group results, which we extend to the different line elasticity. We see evidence for two distinct correlation length exponents.

The critical exponent $\eta$ for three-dimensional systems with an $n$-vector order parameter is evaluated in the framework of the pseudo-$\epsilon$ expansion approach. The pseudo-$\epsilon$ expansion ($\tau$ series) for $\eta$ found up to the ${\tau }^7$ term for $n$ = 0, 1, 2, 3 and within the ${\tau }^6$ order for general $n$ is shown to have a structure that is rather favorable for getting numerical estimates. The use of Padé approximants and direct summation of the $\tau$ series result in iteration procedures rapidly converging to the asymptotic values that are very close to the most reliable numerical estimates of $\eta$ known today. The origin of such an efficiency is discussed and shown to lie in the general properties of the pseudo-$\epsilon$ expansion machinery interfering with some peculiarities of the renormalization group expansion of $\eta$.

We introduced simple microscopic non-Markovian walk models which describe the underlying mechanism of anomalous diffusions. In the models, we considered the competitions between randomness and memory effects of previous history by introducing the probability parameters. The memory effects were considered in two aspects: one is the perfect memory of whole history and the other is the latest memory enhanced with time. In the perfect memory model superdiffusion was induced with the relation of the Hurst exponent $H$ to the controlling parameter $p$ as $H=p$ for $p>1/2$, while in the latest memory enhancement models, anomalous diffusions involving both superdiffusion and subdiffusion were induced with the relations $H=(1+\alpha )/2$ and $H=(1-\alpha )/2$ for $0\le \alpha \le 1$, where $\alpha$ is the parameter controlling the degree of the latest memory enhancement. Also we found that, although the latest memory was only considered, the memory improved with time results in the long-range correlations between steps and the correlations increase as time goes on. Thus we suggest the memory enhancement as a key origin describing anomalous diffusions.

With Monte Carlo simulations, the nonsteady dynamic properties of a domain wall have been systematically investigated for the thermally activated creep state under an alternating driving field. Taking the driven random-field Ising model in two dimensions as an example, two distinct growth stages of the domain interface are identified with both the correlation length and roughness function. One stage belongs to the universality class of the random depositions, and the other to that of the quenched Edwards-Wilkinson equation. In the latter case, due to the dynamic effect of overhangs, the domain interface may exhibit an intrinsic anomalous scaling behavior, different from that of the quenched Edwards-Wilkinson equation.

We study the order-disorder transition of horizontally swirled dry and wet granular disks by means of computer simulations. Our systematic investigation of the local order formation as a function of amplitude and period of the external driving force shows that a large cluster of hexagonally ordered particles forms for both dry and wet granular particles at intermediate driving energies. Disordered states are found at small and large driving energies. Wet granular particles reach a higher degree of local hexagonal order with respect to the dry case. For both cases we report a qualitative phase diagram showing the amount of local order at different state points. Furthermore, we find that the transition from hexagonal order to a disordered state is characterized by the appearance of particles with square local order.