A cloud of nanodust particles is created in a reactive argon-acetylene plasma. It is then transformed into a dusty magnetized argon plasma. Plasma parameters are obtained with the dust-density wave diagnostic introduced by Tadsen et al. [Phys. Plasmas 22, 113701 (2015)]. A change from an open to a cylindrically enclosed nanodust cloud, which was observed earlier, can now be explained by a stronger electric confinement if a vertical magnetic field is present. Using two-dimensional extinction measurements and the inverse Abel transform to determine the dust density, a redistribution of the dust with increasing magnetic induction is found. The dust-density profile changes from being peaked around the central void to being peaked at an outer torus ring resulting in a hollow profile. As the plasma parameters cannot explain this behavior, we propose a rotation of the nanodust cloud in the magnetized plasma as the origin of the modified profile.

We present a lattice Boltzmann model for charged leaky dielectric multiphase fluids in the context of electrified jet simulations, which are of interest for a number of production technologies including electrospinning. The role of nonlinear rheology on the dynamics of electrified jets is considered by exploiting the Carreau model for pseudoplastic fluids. We report exploratory simulations of charged droplets at rest and under a constant electric field, and we provide results for charged jet formation under electrospinning conditions.

Two decades ago, Wang and Ong, [Phys. Rev. A 55, 1522 (1997)] hypothesized that the local box-counting dimension of a discrete quantum spectrum should depend exclusively on the nearest-neighbor spacing distribution (NNSD) of the spectrum. In this Rapid Communication, we validate their hypothesis by deriving an explicit formula for the local box-counting dimension of a countably-infinite discrete quantum spectrum. This formula expresses the local box-counting dimension of a spectrum in terms of single and double integrals of the NNSD of the spectrum. As applications, we derive an analytical formula for Poisson spectra and closed-form approximations to the local box-counting dimension for spectra having Gaussian orthogonal ensemble (GOE), Gaussian unitary ensemble (GUE), and Gaussian symplectic ensemble (GSE) spacing statistics. In the Poisson and GOE cases, we compare our theoretical formulas with the published numerical data of Wang and Ong and observe excellent agreement between their data and our theory. We also study numerically the local box-counting dimensions of the Riemann zeta function zeros and the alternate levels of GOE spectra, which are often used as numerical models of spectra possessing GUE and GSE spacing statistics, respectively. In each case, the corresponding theoretical formula is found to accurately describe the numerically computed local box-counting dimension.

Lower bounds on fluctuations of thermodynamic currents depend on the nature of time, discrete or continuous. To understand the physical reason, we compare current fluctuations in discrete-time Markov chains and continuous-time master equations. We prove that current fluctuations in the master equations are always more likely, due to random timings of transitions. This comparison leads to a mapping of the moments of a current between discrete and continuous time. We exploit this mapping to obtain uncertainty bounds. Our results reduce the quests for uncertainty bounds in discrete and continuous time to a single problem.

Boolean networks have attracted much attention due to their wide applications in describing dynamics of biological systems. During past decades, much effort has been invested in unveiling how network structure and update rules affect the stability of Boolean networks. In this paper, we aim to identify and control a minimal set of influential nodes that is capable of stabilizing an unstable Boolean network. For locally treelike Boolean networks with biased truth tables, we propose a greedy algorithm to identify influential nodes in Boolean networks by minimizing the largest eigenvalue of a modified nonbacktracking matrix. We test the performance of the proposed collective influence algorithm on four different networks. Results show that the collective influence algorithm can stabilize each network with a smaller set of nodes compared with other heuristic algorithms. Our work provides a new insight into the mechanism that determines the stability of Boolean networks, which may find applications in identifying virulence genes that lead to serious diseases.

Complex dynamical systems often have tipping points and exhibit catastrophic regime shift. Despite the notorious difficulty of predicting such transitions, accumulating studies have suggested the existence of generic early-warning signals (EWSs) preceding upcoming transitions. However, previous theories and models were based on the effect of the intrinsic noise (IN) when a system is approaching a critical point, and did not consider the pervasive environmental fluctuations or the extrinsic noise (EN). Here, we extend previous theory to investigate how the interplay of EN and IN affects EWSs. Stochastic simulations of model systems subject to both IN and EN have verified our theory and demonstrated that EN can dramatically alter and diminish the EWS. This effect is stronger with increasing amplitude and correlation time scale of the EN. In the presence of EN, the EWS can fail to predict or even give a false alarm of critical transitions.

We employ molecular dynamics (MD) simulations and develop scaling theories to quantify the equilibrium behavior of polyelectrolyte (PE) brush bilayers (BBLs) in the weakly interpenetrated regime, which is characterized by $d_0<d_g<2d_0$, where $d_g$ is the gap between the opposing plates where the PE brushes are grafted and $d_0$ is the unperturbed height of a PE brush grafted at a single plate. Scaling predictions establish that, for the weakly interpenetrated osmotic PE BBLs $\delta \sim N^{1/2}{(2-d_g/d_0)}^{1/2}$ (where $\delta$ is the interpenetration length and $N$ is the number of Kuhn segments in PE brush). MD simulations excellently recover this dependence of $\delta$ on $N$ and the extent of interpenetration (quantified by $d_g/d_0$). These predictions, unlike the existing studies, establish a finite interpenetration for all values of $d_g/d_0$ as long as $d_g<2d_0$. Finally, we quantify the monomer and counterion concentration distributions and point out that these two distributions may quantitatively deviate from each other at locations very close to the channel centerline, where the interpenetration-induced monomer concentration can be significantly low.

Reducing the complexity of cross-linked polymer networks by preserving their main macroscale properties is key to understanding them, and a crucial issue is to relate individual properties of the polymer constituents to those of the reduced network. Here we study polymer networks in a good solvent, by considering star polymers as their unit elements, and first quantify the interaction between their centers of masses. We then reduce the complexity of a network by replacing sets of its bridged star polymers by equivalent effective soft particles with dense cores. Our coarse graining allows us to approximate complex polymer networks by much simpler ones, keeping their relevant mechanical properties, as illustrated in computer experiments.

The competing effect of surface anchoring of dispersed microparticles and elasticity of nematic and cholesteric liquid crystals has been shown to stabilize a variety of topological defects. Here we study a pair of colloidal microparticles with homeotropic and planar surface anchoring across $N\text{−}\mathrm{Sm}A\text{−}\mathrm{Sm}C$ phase transitions. We show that below the $\mathrm{Sm}A\text{−}\mathrm{Sm}C$ phase transition the temperature dependence of interparticle separation $\left(D\right)$ of colloids with homeotropic anchoring shows a power-law behavior; $D\sim {(1-T/T_{AC})}^{\alpha }$, with an exponent $\alpha \approx 0.5$. For colloids with planar surface anchoring the angle between the joining line of the centers of the two colloids and the far field director shows characteristic variation elucidating the phase transitions.

Coupling between the defect mode of a cholesteric liquid crystal and the localized mode of a cholesteric liquid crystal–phase plate–metal structure is theoretically demonstrated. It is shown that the transmittance spectrum can be tuned by changing the twist-defect angle and helix pitch, which are governed by external factors. The spectra for different circular polarizations of the incident light are different; specifically, at the nondiffracting polarization, there is no defect-mode transmittance peak.

In this work, a regularized lattice Boltzmann color-gradient model is developed for the simulation of immiscible two-phase flows with power-law rheology. This model is as simple as the Bhatnagar-Gross-Krook (BGK) color-gradient model except that an additional regularization step is introduced prior to the collision step. In the regularization step, the pseudo-inverse method is adopted as an alternative solution for the nonequilibrium part of the total distribution function, and it can be easily extended to other discrete velocity models no matter whether a forcing term is considered or not. The obtained expressions for the nonequilibrium part are merely related to macroscopic variables and velocity gradients that can be evaluated locally. Several numerical examples, including the single-phase and two-phase layered power-law fluid flows between two parallel plates, and the droplet deformation and breakup in a simple shear flow, are conducted to test the capability and accuracy of the proposed color-gradient model. Results show that the present model is more stable and accurate than the BGK color-gradient model for power-law fluids with a wide range of power-law indices. Compared to its multiple-relaxation-time counterpart, the present model can increase the computing efficiency by around 15%, while keeping the same accuracy and stability. Also, the present model is found to be capable of reasonably predicting the critical capillary number of droplet breakup.

We study the effect of backscattering of the Brownian particles as they escape out of a metastable state overcoming the potential barrier. For this aim, we model this process numerically using the Langevin equations. This modeling is performed for the wide range of the friction constant covering both the energy and spatial diffusion regimes. It is shown how the influence of the descent stage on the quasistationary decay rate gradually disappears as the friction constant decreases. It is found that, in the energy diffusion regime, the rescattering absents and the descent stage does not influence the decay rate. As the value of friction increases, the descent alters the value of the rate by more than 50% for different values of thermal energy and different shapes of the potential. To study the influence of the backscattering on the decay rate, four potentials have been considered which coincide near the potential well and the barrier but differ beyond the barrier. It is shown that the potential for which the well and the barrier are described by two smoothly joined parabolas (“the parabolic potential”) plays a role of a dividing range for the mutual layout of the quasistationary dynamical rate and the widely used in the literature Kramers rate. Namely, for the potentials with steeper tails, the Kramers rate $R_{\mathrm{KM}}$ underestimates the true quasistationary dynamical rate $R_D$, whereas for the less steep tails the opposite holds (inversion of $R_D/R_{\mathrm{KM}}$). It is demonstrated that the mutual layout of the values of $R_D$ for different potentials is explained by the rescattering of the particles from the potential tail.

In many situations we are interested in the propagation of energy in some portions of a three-dimensional system with dilute long-range links. In this paper, a sandpile model is defined on the three-dimensional small-world network with real dissipative boundaries and the energy propagation is studied in three dimensions as well as the two-dimensional cross-sections. Two types of cross-sections are defined in the system, one in the bulk and another in the system boundary. The motivation of this is to make clear how the statistics of the avalanches in the bulk cross-section tend to the statistics of the dissipative avalanches, defined in the boundaries as the concentration of long-range links ($\alpha$) increases. This trend is numerically shown to be a power law in a manner described in the paper. Two regimes of $\alpha$ are considered in this work. For sufficiently small $\alpha \mathrm{s}$ the dominant behavior of the system is just like that of the regular BTW, whereas for the intermediate values the behavior is nontrivial with some exponents that are reported in the paper. It is shown that the spatial extent up to which the statistics is similar to the regular BTW model scales with $\alpha$ just like the dissipative BTW model with the dissipation factor (mass in the corresponding ghost model) $m^2\sim \alpha$ for the three-dimensional system as well as its two-dimensional cross-sections.

Collective decision-making regarding direction of travel is observed during natural motion of animal and cellular groups. This phenomenon is exemplified, in the simplest case, by a group that contains two informed subgroups that hold conflicting preferred directions of motion. Under such circumstances, simulations, subsequently supported by experimental data with birds and primates, have demonstrated that the resulting motion is either towards a compromise direction or towards one of the preferred targets (even when the two subgroups are equal in size). However, the nature of this transition is not well understood. We present a theoretical study that combines simulations and a spin model for mobile animal groups, the latter providing an equilibrium representation, and exact solution in the thermodynamic limit. This allows us to identify the nature of this transition at a critical angular difference between the two preferred directions: in both flocking and spin models the transition coincides with the change in the group dynamics from Brownian to persistent collective motion. The groups undergo this transition as the number of uninformed individuals (those in the group that do not exhibit a directional preference) increases, which acts as an inverse of the temperature (noise) of the spin model. When the two informed subgroups are not equal in size, there is a tendency for the group to reach the target preferred by the larger subgroup. We find that the spin model captures effectively the essence of the collective decision-making transition and allows us to reveal a noise-dependent trade-off between the decision-making speed and the ability to achieve majority (democratic) consensus.

Vesicles or biological cells under simultaneous shear and electric field can be encountered in dielectrophoretic devices or designs used for continuous flow electrofusion or electroporation. In this work, the dynamics of a vesicle subjected to simultaneous shear and uniform alternating current (ac) electric field is investigated in the small deformation limit. The coupled equations for vesicle orientation and shape evolution are derived theoretically, and the resulting nonlinear equations are handled numerically to generate relevant phase diagrams that demonstrate the effect of electrical parameters on the different dynamical regimes such as tank treading (TT), vacillating breathing (VB) [called trembling (TR) in this work], and tumbling (TU). It is found that while the electric Mason number ($\text{Mn}$), which represents the relative strength of the electrical forces to the shear forces, promotes the TT regime, the response itself is found to be sensitive to the applied frequency as well as the conductivity ratio. While higher outer conductivity promotes orientation along the flow axis, orientation along the electric field is favored when the inner conductivity is higher. Similarly a switch of orientation from the direction of the electric field to the direction of flow is possible by a mere change of frequency when the outer conductivity is higher. Interestingly, in some cases, a coupling between electric field-induced deformation and shear can result in the system admitting an intermediate TU regime while attaining the TT regime at high $\text{Mn}$. The results could enable designing better dielectrophoretic devices wherein the residence time as well as the dynamical states of the vesicular suspension can be controlled as per the application.

Circadian clocks are biochemical oscillators that allow organisms to estimate the time of the day. These oscillators are inherently noisy due to the discrete nature of the reactants and the stochastic character of their interactions. To keep these oscillators in sync with the daily day-night rhythm in the presence of noise, circadian clocks must be coupled to the dark-light cycle. In this paper, we study the entrainment of phase oscillators as a function of the intrinsic noise in the system. Using stochastic simulations, we compute the optimal coupling strength, intrinsic frequency, and shape of the phase-response curve, that maximize the mutual information between the phase of the clock and time. We show that the optimal coupling strength and intrinsic frequency increase with the noise, but that the shape of the phase-response curve varies nonmonotonically with the noise: in the low-noise regime, it features a dead zone that increases in width as the noise increases, while in the high-noise regime, the width decreases with the noise. These results arise from a tradeoff between maximizing stability—noise suppression—and maximizing linearity of the input-output, i.e., time-phase, relation. We also show that three analytic approximations—the linear-noise approximation, the phase-averaging method, and linear-response theory—accurately describe different regimes of the coupling strength and the noise.

The slip of a fluid layer in contact with a solid confining surface is investigated for different temperatures and densities using molecular dynamic simulations. We show that for an anomalous waterlike fluid the slip goes as follows: for low levels of shear, defect slip appears and is related to the particle exchange between the fluid layers; at high levels of shear, global slip occurs and is related to the homogeneous distribution of the fluid in the confining surfaces. The oscillations in the transition velocity from defect to global slip are shown to be associated with changes in the layering distribution in the anomalous fluid.

Pseudopotential lattice Boltzmann methods (LBMs) can simulate a phase transition in high-density ratio multiphase flow systems. If coupled with thermal LBMs through equation of state, they can be used to study instantaneous phase transition phenomena with a high-temperature gradient where only one set of formulations in an LBM system can handle liquid, vapor, phase transition, and heat transport. However, at lower temperatures an unrealistic spurious current at the interface introduces instability and limits its application in real flow system. In this study, we proposed new modifications to the LBM system to minimize a spurious current which enables us to study nucleation dynamic at room temperature. To demonstrate the capabilities of this approach, the thermal ejection process is modeled as one example of a complex flow system. In an inkjet printer, a thermal pulse instantly heats up the liquid in a microfluidic chamber and nucleates bubble vapor providing the pressure pulse necessary to eject droplets at high speed. Our modified method can present a more realistic model of the explosive vaporization process since it can also capture a high-temperature/density gradient at nucleation region. Thermal inkjet technology has been successfully applied for printing cells, but cells are susceptible to mechanical damage or death as they squeeze out of the nozzle head. To study cell deformation, a spring network model, representing cells, is connected to the LBM through the immersed boundary method. Looking into strain and stress distribution of a cell membrane at its most deformed state, it is found that a high stretching rate effectively increases the rupture tension. In other words, membrane deformation energy is released through creation of multiple smaller nanopores rather than big pores. Overall, concurrently simulating multiphase flow, phase transition, heat transfer, and cell deformation in one unified LB platform, we are able to provide a better insight into the bubble dynamic and cell mechanical damage during the printing process.

An effect which suppresses recombination in ion plasmas is considered both theoretically and experimentally. Experimental results are presented for the ion recombination rate in fluorine plasma, which are obtained from data for the gas discharge afterglow. To interpret them, a suppression factor is considered: ion solvation in weakly ionized plasma. It is shown that the recombination process has a two-stage character with the formation of intermediate metastable ion pairs. The pairs consist of negative and positive ion-molecular clusters. A theoretical explanation is given for the slowing down of the ion recombination with the increase of the Coulomb coupling compared to the ion recombination rate calculated in the ideal plasma approximation. The approximate similarity of the recombination rate of the ion temperature and concentration and reasons for the slight deviation from the similarity are elucidated.

Molecular dynamics (MD) electrospray simulations of 1-ethyl-3-methylimidazolium tetrafluoroborate (EMIM-${\mathrm{BF}}_4$) ion liquid were performed with the goal of evaluating the influence of long-range Coulomb models on ion emission characteristics. The direct Coulomb (DC), shifted force Coulomb sum (SFCS), and particle-particle particle-mesh (PPPM) long-range Coulomb models were considered in this work. The DC method with a sufficiently large cutoff radius was found to be the most accurate approach for modeling electrosprays, but, it is computationally expensive. The Coulomb potential energy modeled by the DC method in combination with the radial electric fields were found to be necessary to generate the Taylor cone. The differences observed between the SFCS and the DC in terms of predicting the total ion emission suggest that the former should not be used in MD electrospray simulations. Furthermore, the common assumption of domain periodicity was observed to be detrimental to the accuracy of the capillary-based electrospray simulations.