We study the nonequilibrium phase transition of the contact process with aperiodic transition rates using a real-space renormalization group as well as Monte Carlo simulations. The transition rates are modulated according to the generalized Fibonacci sequences defined by the inflation rules A $\to$ AB${}^k$ and B $\to$ A. For $k=1$ and 2, the aperiodic fluctuations are irrelevant, and the nonequilibrium transition is in the clean directed percolation universality class. For $k\ge 3$, the aperiodic fluctuations are relevant. We develop a complete theory of the resulting unconventional “infinite-modulation” critical point, which is characterized by activated dynamical scaling. Moreover, observables such as the survival probability and the size of the active cloud display pronounced double-log periodic oscillations in time which reflect the discrete scale invariance of the aperiodic chains. We illustrate our theory by extensive numerical results, and we discuss relations to phase transitions in other quasiperiodic systems.

Fast slip flow was identified for water inside the interlayer gallery between graphene layers or carbon nanotubes. We report here that this significant flow rate enhancement (over two orders) breaks down with the presence of chemical functionalization and relaxation of nanoconfinement in graphene oxides. Molecular dynamics simulation results show that hydrodynamics applies in this circumstance, even at length scales down to nanometers. However, corrections to the slip boundary condition and apparent viscosity of nanoconfined flow must be included to make quantitative predictions. These results were discussed with the structural characteristics of liquid water and hydrogen-bond networks.

The time rate of generalized entropic forms, defined in terms of discrete probabilities following a master equation, is investigated. Both contributions, namely entropy production and flux, are obtained, extending works carried previously for the Boltzmann-Gibbs entropy to a wide class of entropic forms. Particularly, it is shown that the entropy-production contribution is always non-negative for such entropies. Some illustrative examples for known generalized entropic forms in the literature are also worked out. Since generalized entropies have been lately associated with several complex systems in nature, the present analysis should be applicable to irreversible processes in these systems.

We consider scaled Brownian motion (sBm), a random process described by a diffusion equation with explicitly time-dependent diffusion coefficient $D\left(t\right)=\alpha D_0{t}^{\alpha -1}$ (Batchelor's equation) which, for $\alpha <1$, is often used for fitting experimental data for subdiffusion of unclear genesis. We show that this process is a close relative of subdiffusive continuous-time random walks and describes the motion of the rescaled mean position of a cloud of independent walkers. It shares with subdiffusive continuous-time random walks its nonstationary and nonergodic properties. The nonergodicity of sBm does not however go hand in hand with strong difference between its different realizations: its heterogeneity (“ergodicity breaking”) parameter tends to zero for long trajectories.

Motivated by experiments on activity in neuronal cultures [J. Soriano, M. Rodríguez Martínez, T. Tlusty, and E. Moses, Proc. Natl. Acad. Sci. 105, 13758 (2008)], we investigate the percolation transition and critical exponents of spatially embedded Erdős-Rényi networks with degree correlations. In our model networks, nodes are randomly distributed in a two-dimensional spatial domain, and the connection probability depends on Euclidian link length by a power law as well as on the degrees of linked nodes. Generally, spatial constraints lead to higher percolation thresholds in the sense that more links are needed to achieve global connectivity. However, degree correlations favor or do not favor percolation depending on the connectivity rules. We employ two construction methods to introduce degree correlations. In the first one, nodes stay homogeneously distributed and are connected via a distance- and degree-dependent probability. We observe that assortativity in the resulting network leads to a decrease of the percolation threshold. In the second construction methods, nodes are first spatially segregated depending on their degree and afterwards connected with a distance-dependent probability. In this segregated model, we find a threshold increase that accompanies the rising assortativity. Additionally, when the network is constructed in a disassortative way, we observe that this property has little effect on the percolation transition.

Fluid imbibition via diffusion in a deformable solid results in solid stresses that may, in turn, alter subsequent fluid uptake. To examine this interplay between diffusional and elastic fields, we employed a hybrid Monte Carlo–molecular dynamics scheme to model the coupling of a fluid reservoir to a deformable solid, and then simulated the resulting fluid permeation into the solid. By monitoring the instantaneous structure factor and solid dimensions, we were able to determine the compositional strain associated with imbibition, and the diffusion coefficient in the Fickian regime was obtained from the time dependence of the fluid uptake. Finally, for large, mobile fluid atoms, a non-Fickian regime was highlighted and possible mechanisms for this behavior were identified.

Phase transitions in two-dimensional (2D) systems are of considerable fundamental and practical importance. However, the kinetics of these processes are difficult to predict and understand, even in simple systems for which equilibrium states are properly described, owing to the difficulty of studying crystallites with single-particle resolution and free of defects. Here we introduce an alternative method for the sublimation of 2D colloidal crystallites by a sudden induction of repulsive forces between the particles. The sublimation kinetics, studied in real space by microscopy and by computer simulations, shows a scaling behavior that suggests a universal mechanism fundamentally different from the one usually accepted for thermal sublimation. The universal behavior found for the early stages of the process may be useful for understanding the dynamic features of particle systems at liquid interfaces and for designing technological applications without the need of performing extensive experimental studies.

We provide a theory to analyze the impact of finite ion sizes (or steric effect) in electrostatic potential distribution for a charged soft surface in contact with an electrolyte solution. The theory is based on a free energy model that appropriately accounts for the contribution of finite ion sizes as well as the structural characteristics of a soft interface, represented by a combination of a rigid surface and a fixed charge layer (FCL), with the FCL being in contact with an electrolyte solution forming an electric double layer (EDL). This FCL contains a particular kind of ion which is impermeable to the electrolyte solution, and this impermeability is quantified in terms of the corresponding Donnan potential of the “membrane” represented by the FCL-electrolyte interface. We find that consideration of the finite ion size increases the magnitude of this Donnan potential, with the extent of increase being dictated by three length scales, namely, the thickness of the FCL, the thickness of the electrolyte EDL, and the thickness of an equivalent EDL within the FCL. Such regulation of the Donnan potential strongly affects the distribution of the permeable electrolyte ions within the FCL, which in turn will have significant implications in several processes involving “soft” biological membranes.

The role of lipid bilayer viscoelasticity and the substrate-bilayer interactions on the spreading behavior of supported phospholipid bilayer membranes is studied using fluorescence microscopy. Unlike the monotonic roughening observed on silica or in other dynamic interface growth systems, a unique rough-smooth-rough (RSR) interface transition occurred on chromium oxide with a roughness exponent of 0.45 ± 0.04. This RSR transition is attributed to the elasticity of the lipid bilayer which is initially under compression due to surface interactions, and is well approximated by adding an elastic term to the quenched noise Edwards-Wilkinson equation. A phase diagram depicting the conditions necessary to observe RSR transitions in dynamic interface systems is derived, revealing the classes of dynamically evolving systems is broader than previously thought, and the viscoelastic nature of the lipid bilayer may play a role in supported membrane behavior.

By using the phase field crystal model, we simulate the morphological transition of the crystal growth of equilibrium crystal shape, dendrite, and spherical crystal shape. The relationship among growth morphology, velocity, and density distribution is investigated. The competition between interface energy anisotropy and interface kinetic anisotropy gives rise to the pattern selection of dendritic growth in the diffusion controlled regime under low-crystal-growth velocities. The trapping effect in density diffusion suppresses morphological instabilities under high-crystal-growth velocities, resulting in isotropic growth of spherical crystal. Finally, a morphological phase diagram of crystal growth is constructed as function of the phase field crystal model parameters.

In ratchet-based models describing actomyosin contraction the activity is usually associated with actin binding potential while the power-stroke mechanism, residing inside myosin heads, is viewed as passive. To show that contraction can be propelled directly through a conformational change, we propose an alternative model where the power stroke is the only active mechanism. The asymmetry, ensuring directional motion, resides in steric interaction between the externally driven power-stroke element and the passive nonpolar actin filament. The proposed model can reproduce all four discrete states of the minimal actomyosin catalytic cycle even though it is formulated in terms of continuous Langevin dynamics. We build a conceptual bridge between processive and nonprocessive molecular motors by demonstrating that not only the former but also the latter can use structural transformation as the main driving force.

We present an efficient algorithm for the inference of stochastic block models in large networks. The algorithm can be used as an optimized Markov chain Monte Carlo (MCMC) method, with a fast mixing time and a much reduced susceptibility to getting trapped in metastable states, or as a greedy agglomerative heuristic, with an almost linear $O\left(N{ln}^{2}N\right)$ complexity, where $N$ is the number of nodes in the network, independent of the number of blocks being inferred. We show that the heuristic is capable of delivering results which are indistinguishable from the more exact and numerically expensive MCMC method in many artificial and empirical networks, despite being much faster. The method is entirely unbiased towards any specific mixing pattern, and in particular it does not favor assortative community structures.

We study the growth of London's street network in its dual representation, as the city has evolved over the past 224 years. The dual representation of a planar graph is a content-based network, where each node is a set of edges of the planar graph and represents a transportation unit in the so-called information space, i.e., the space where information is handled in order to navigate through the city. First, we discuss a novel hybrid technique to extract dual graphs from planar graphs, called the hierarchical intersection continuity negotiation principle. Then we show that the growth of the network can be analytically described by logistic laws and that the topological properties of the network are governed by robust log-normal distributions characterizing the network's connectivity and small-world properties that are consistent over time. Moreover, we find that the double-Pareto-like distributions for the connectivity emerge for major roads and can be modeled via a stochastic content-based network model using simple space-filling principles.

A weakly nonlinear spectrum and a strongly nonlinear spectrum coexist in a statistically steady state of elastic wave turbulence. The analytical representation of the nonlinear frequency is obtained by evaluating the extended self-nonlinear interactions. The critical wave numbers at which the nonlinear frequencies are comparable with the linear frequencies agree with the separation wave numbers between the weak and strong turbulence spectra. We also confirm the validity of our analytical representation of the separation wave numbers through comparison with the results of direct numerical simulations by changing the material parameters of a vibrating plate.

As a paradigmatic model, the Kuramoto model has provided a platform for investigating synchronization among nonidentical oscillators. In this work, we consider the Kuramoto model consisting of conformists with positive coupling strength and contrarians with negative coupling strength. We introduce the correlation between the distributions of natural frequencies and the coupling strengths of oscillators. Three different types of correlations are considered. We find rich dynamics result from the correlation such as different types of traveling wave states and, most interestingly, another type of nonstationary state: an oscillating $\pi$ state.

We model chaotic diffusion in a symplectic four-dimensional (4D) map by using the result of a theorem that was developed for stochastically perturbed integrable Hamiltonian systems. We explicitly consider a map defined by a free rotator (FR) coupled to a standard map (SM). We focus on the diffusion process in the action $I$ of the FR, obtaining a seminumerical method to compute the diffusion coefficient. We study two cases corresponding to a thick and a thin chaotic layer in the SM phase space and we discuss a related conjecture stated in the past. In the first case, the numerically computed probability density function for the action $I$ is well interpolated by the solution of a Fokker-Planck (FP) equation, whereas it presents a nonconstant time shift with respect to the concomitant FP solution in the second case suggesting the presence of an anomalous diffusion time scale. The explicit calculation of a diffusion coefficient for a 4D symplectic map can be useful to understand the slow diffusion observed in celestial mechanics and accelerator physics.

A digital holographic microscope has been used to trace the trajectory of a tracer particle inside the liquid phase of an evaporating meniscus formed at the mouth of a 1-mm${}^2$ borosilicate tube filled with ethanol. The Marangoni flow cells are generated by the self-induced differential evaporating cooling along the meniscus interface that creates gradients of surface tension which drive the convection. The competition between surface tension and gravity forces along the curved meniscus interface disrupts the symmetry due to surface tension alone. This distorts the shape of the toroidal Marangoni vortex. Thermocapillary instabilities of the evaporating meniscus are reported by analyzing the trajectories of the tracer particle. It is found that the trajectory of the tracer particle makes different three-dimensional loops and every four loops it returns to the first loop. By analyzing several loops it was found that the characteristic frequency of the periodic oscillatory motion is around 0.125 Hz.

Red blood cell (RBC) deformability plays a key role in microcirculation, especially in vessels that have diameters even smaller than the nominal cell size. In this study, we numerically investigate the dynamics of an RBC in a thin micropore. The RBC is modeled as a capsule with a thin hyperelastic membrane. In a numerical simulation, we employ a boundary element method for fluid mechanics and a finite element method for membrane mechanics. The resulting RBC deformation towards the flow direction is suppressed considerably by increased cytoplasm viscosity, whereas the gap between the cell membrane and solid wall becomes smaller with higher cytoplasm viscosity. We also measure the transit time of the RBC and find that nondimensional transit time increases nonlinearly with respect to the viscosity ratio, whereas it is invariant to the capillary number. In conclusion, cytoplasmic viscosity plays a key role in the dynamics of an RBC in a thin pore. The results of this study will be useful for designing a microfluidic device to measure cytoplasmic viscosity.

Interaction of high-intensity laser pulses with solid targets results in generation of large quantities of energetic electrons that are the origin of various effects such as intense x-ray emission, ion acceleration, and so on. Some of these electrons are escaping the target, leaving behind a significant positive electric charge and creating a strong electromagnetic pulse long after the end of the laser pulse. We propose here a detailed model of the target electric polarization induced by a short and intense laser pulse and an escaping electron bunch. A specially designed experiment provides direct measurements of the target polarization and the discharge current in the function of the laser energy, pulse duration, and target size. Large-scale numerical simulations describe the energetic electron generation and their emission from the target. The model, experiment, and numerical simulations demonstrate that the hot-electron ejection may continue long after the laser pulse ends, enhancing significantly the polarization charge.

In a plasma containing charged dust grains, the dust acoustic instability (DAI) can be driven by ions streaming through the dust with speed less than the ion thermal speed. When the dust is strongly coupled in the liquid phase, the dispersion relation of the dust acoustic modes changes in a way that leads to an enhancement of the growth rate of the DAI. In this paper, we show how strong coupling enhances the DAI growth rate and consider application to microgravity experiments where subthermal ion flows are in general possible.