The European Physical Journal E最新文献

In this work we have monitored the multiple stages of the normal traction force response of a yield-stress fluid confined between two circular parallel plates that are separated at constant velocity. At narrow initial gaps, the air–fluid interface suffers from the Saffman–Taylor instability, confirmed by visual inspection of fingering patterns imprinted on the fluid. At larger initial gaps, the fluid preserves the initially imposed circular symmetry of the confining plates, indicating the absence of instability. Due to the system characteristics and experimental environment, the multiple traction force contributions occurred in cascade, permitting us to isolate the adhesion responses associated with viscosity, capillarity, and yield stress. Employing a standard Herschel–Bulkley model, we assessed the scaling of the traction force in multiple regimes—specifically, evaluating the dependencies of the fingering to yield-stress transitions.

We investigate electric-field effects in dilute electrolytes with nonlinear polarization. As a first example of such systems, we add a dipolar component with a relatively large dipole moment (mu _0) to an aqueous electrolyte. As a second example, the solvent itself exhibits nonlinear polarization near charged objects. For such systems, we present a Ginzburg-Landau free energy and introduce field-dependent chemical potentials, entropy density, and stress tensor, which satisfy general thermodynamic relations. In the first example, the dipoles accumulate in high-field regions, as predicted by Abrashikin et al.[Phys.Rev.Lett. 99, 077801 (2007)]. Finally, we consider the case, where Bjerrum ion pairs form a dipolar component with nonlinear polarization. The Bjerrum dipoles accumulate in high-field regions, while field-induced dissociation was predicted by Onsager [J. Chem. Phys.2, 599 (1934)]. We present an expression for the field-dependent association constant K(E), which depends on the field strength nonmonotonically.

Electrical signals may propagate along neuronal membranes in the brain, thus enabling communication between nerve cells. In doing so, lipid bilayers, fundamental scaffolds of all cell membranes, deform and restructure in response to such electrical activity. These changes impact the electromechanical properties of the membrane, which then physically store biological memory. This memory can exist either over a short or long period of time. Traditionally, biological memory is defined by the strengthening or weakening of transmissions between individual neurons. Here, we show that electrical stimulation may also alter the properties of the lipid membrane, thus pointing toward a novel mechanism for memory storage. Furthermore, based on the analysis of existing electrophysiological data, we study molecular mechanisms underlying the long-term potentiation in phospholipid membranes. Finally, we examine possible relationships between the memory capacitive properties of lipid membranes, neuronal learning, and memory.

Phase separation of biomembranes into two fluid phases, a and b, leads to the formation of vesicles with intramembrane a- and b-domains. These vesicles can attain multispherical shapes consisting of several spheres connected by closed membrane necks. Here, we study the morphological complexity of these multispheres using the theory of curvature elasticity. Vesicles with two domains form two-sphere shapes, consisting of one a- and one b-sphere, connected by a closed ab-neck. The necks’ effective mean curvature is used to distinguish positive from negative necks. Two-sphere shapes of two-domain vesicles can attain four different morphologies that are governed by two different stability conditions. The closed ab-necks are compressed by constriction forces which induce neck fission and vesicle division for large line tensions and/or large spontaneous curvatures. Multispherical shapes with one ab-neck and additional aa- and bb-necks involve several stability conditions, which act to reduce the stability regimes of the multispheres. Furthermore, vesicles with more than two domains form multispheres with more than one ab-neck. The multispherical shapes described here represent generalized constant-mean-curvature surfaces with up to four constant mean curvatures. These shapes are accessible to experimental studies using available methods for giant vesicles prepared from ternary lipid mixtures.

Plant cell growth is regulated through manipulation of the cell wall network, which consists of oriented cellulose microfibrils embedded within a ground matrix incorporating pectin and hemicellulose components. There remain many unknowns as to how this manipulation occurs. Experiments have shown that cellulose reorients in cell walls as the cell expands, while recent data suggest that growth is controlled by distinct collections of hemicellulose called biomechanical hotspots, which join the cellulose molecule together. The enzymes expansin and Cel12A have both been shown to induce growth of the cell wall; however, while Cel12A’s wall-loosening action leads to a reduction in the cell wall strength, expansin’s has been shown to increase the strength of the cell wall. In contrast, members of the XTH enzyme family hydrolyse hemicellulose but do not appear to cause wall creep. This experimentally observed behaviour still awaits a full explanation. We derive and analyse a mathematical model for the effective mechanical properties of the evolving cell wall network, incorporating cellulose microfibrils, which reorient with cell growth and are linked via biomechanical hotspots made up of regions of crosslinking hemicellulose. Assuming a visco-elastic response for the cell wall and using a continuum approach, we calculate the total stress resultant of the cell wall for a given overall growth rate. By changing appropriate parameters affecting breakage rate and viscous properties, we provide evidence for the biomechanical hotspot hypothesis and develop mechanistic understanding of the growth-inducing enzymes.

Autonomous locomotion is a ubiquitous phenomenon in biology and in physics of active systems at microscopic scale. This includes prokaryotic, eukaryotic cells (crawling and swimming) and artificial swimmers. An outstanding feature is the ability of these entities to follow complex trajectories, ranging from straight, curved (circular, helical...), to random-like ones. The non-straight nature of these trajectories is often explained as a consequence of the asymmetry of the particle or the medium in which it moves, or due to the presence of bounding walls, etc... Here, we show that for a particle driven by a concentration field of an active species, straight, circular and helical trajectories emerge naturally in the absence of asymmetry of the particle or that of suspending medium. Our proof is based on general considerations, without referring to an explicit form of a model. We show that these three trajectories correspond to self-congruent solutions. Self-congruency means that the states of the system at different moments of time can be made identical by an appropriate combination of rotation and translation of the coordinate space. We show that these solutions are exhibited by spherically symmetric particles as a result of a series of pitchfork bifurcations, leading to spontaneous symmetry breaking in the concentration field driving the particle motility. Self-congruent dynamics in one and two dimensions are analyzed as well. Finally, we present a simple explicit nonlinear exactly solvable model of fully isotropic phoretic particle that shows the transitions from a non-motile state to straight motion to circular motion to helical motion as a series of spontaneous symmetry-breaking bifurcations. Whether a system exhibits or not a given trajectory only depends on the numerical values of parameters entering the model, while asymmetry of swimmer shape, or anisotropy of the suspending medium, or influence of bounding walls are not necessary.

Many out-of-equilibrium flows present non-Gaussian fluctuations in physically relevant observables, such as energy dissipation rate. This implies extreme fluctuations that, although rarely observed, have a significant phenomenology. Recently, path integral methods for importance sampling have emerged from formalism initially devised for quantum field theory and are being successfully applied to the Burgers equation and other fluid models. We proposed exploring the domain of application of these methods using a shell model, a dynamical system for turbulent energy cascade which can be numerically sampled for extreme events in an efficient manner and presents many interesting properties. We start from a validation of the instanton-based importance sampling methodology in the heat equation limit. We explored the limits of the method as nonlinearity grows stronger, finding good qualitative results for small values of the leading nonlinear coefficient. A worst agreement between numerical simulations of the whole systems and instanton results for estimation of the distribution’s flatness is observed when increasing the nonlinear intensities.