We study jamming in model freely rotating polymers as a function of chain length $N$ and bond angle ${\theta }_0$. The volume fraction at jamming ${\varphi }_J({\theta }_0)$ is minimal for rigid-rodlike chains (${\theta }_0=0$), and increases monotonically with increasing ${\theta }_0\le \pi /2$. In contrast to flexible polymers, marginally jammed states of freely rotating polymers are highly hypostatic, even when bond and angle constraints are accounted for. Large-aspect-ratio (small ${\theta }_0$) chains behave comparably to stiff fibers: resistance to large-scale bending plays a major role in their jamming phenomenology. Low-aspect-ratio (large ${\theta }_0$) chains behave more like flexible polymers, but still jam at much lower densities due to the presence of frozen-in three-body correlations corresponding to the fixed bond angles. Long-chain systems jam at lower $\varphi$ and are more hypostatic at jamming than short-chain systems. Implications of these findings for polymer solidification are discussed.

This work studies the symmetry between colloidal dynamics and the dynamics of the Euro–U.S. dollar currency exchange market (EURUSD). We consider the EURUSD price in the time range between 2001 and 2015, where we find significant qualitative symmetry between fluctuation distributions from this market and the ones belonging to colloidal particles in supercooled or arrested states. In particular, we find that models used for arrested physical systems are suitable for describing the EURUSD fluctuation distributions. Whereas the corresponding mean-squared price displacement (MSPD) to the EURUSD is diffusive for all years, when focusing in selected time frames within a day, we find a two-step MSPD when the New York Stock Exchange market closes, comparable to the dynamics in supercooled systems. This is corroborated by looking at the price correlation functions and non-Gaussian parameters and can be described by the theoretical model. We discuss the origin and implications of this analogy.

The reptation mechanism, introduced by de Gennes and Edwards, where a polymer diffuses along a fluffy tube, defined by the constraints imposed by its surroundings, convincingly describes the relaxation of long polymers in concentrated solutions and melts. We propose that the scale for the tube diameter is set by local chain segregation, which we study analytically. We show that the concept of local segregation is especially operational for confined geometries, where segregation extends over mesoscopic domains, drastically reducing binary contacts, and provide an estimate of the entanglement length. Our predictions are quantitatively supported by extensive molecular dynamics simulations on systems consisting of long, entangled chains.

Nanoparticles functionalized with multiple ligands can be programed to bind biological targets depending on the receptors they express, providing a general mechanism exploited in various technologies, from selective drug delivery to biosensing. For binding to be highly selective, ligands should exclusively interact with specific targeted receptors, because the formation of bonds with other, untargeted ones would lead to nonspecific binding and potentially harmful behavior. This poses a particular problem for multivalent nanoparticles, because even very weak bonds can collectively lead to strong binding. A statistical mechanical model is used here to describe how competition between different receptors together with multivalent effects can be harnessed to design ligand-functionalized nanoparticles insensitive to the presence of untargeted receptors, preventing nonspecific binding.

Studying dynamical phenomena in finite populations often involves Markov processes of significant mathematical and/or computational complexity, which rapidly becomes prohibitive with increasing population size or an increasing number of individual configuration states. Here, we develop a framework that allows us to define a hierarchy of approximations to the stationary distribution of general systems that can be described as discrete Markov processes with time invariant transition probabilities and (possibly) a large number of states. This results in an efficient method for studying social and biological communities in the presence of stochastic effects—such as mutations in evolutionary dynamics and a random exploration of choices in social systems—including situations where the dynamics encompasses the existence of stable polymorphic configurations, thus overcoming the limitations of existing methods. The present formalism is shown to be general in scope, widely applicable, and of relevance to a variety of interdisciplinary problems.

A recent granular rheology based on an implicit “granular fluidity” field has been shown to quantitatively predict many nonlocal phenomena. However, the physical nature of the field has not been identified. Here, the granular fluidity is found to be a kinematic variable given by the velocity fluctuation and packing fraction. This is verified with many discrete element simulations, which show that the operational fluidity definition, solutions of the fluidity model, and the proposed microscopic formula all agree. Kinetic theoretical and Eyring-like explanations shed insight into the obtained form.

Confinement induces various modifications in the dynamics of polymers as compared to bulk. We focus here on the role of dynamical heterogeneities on the mechanics of confined polymers. Using a simple model that allows computation of the mechanical response over 10 decades in frequency, we show that the local mechanical coupling controlling the macroscopic response in the bulk disappears in a confined geometry. The slowest domains significantly contribute to the mechanical response for increasing confinement. As a consequence, the apparent glass transition is broadened and shifted towards lower frequencies as confinement increases. We compare our numerical predictions with experiments performed on poly(ethylacrylate) chains in model filled elastomers. We suggest that the change of elastic coupling between domains induced by confinement should contribute significantly to the polymer mobility shift observed on filled systems.

The drainage of vertical foam films governs their lifetime. For a foam film supported on a rectangular solid frame, when the interface presents a low resistance to shear, the drainage dynamics involves a complex flow pattern at the film scale, leading to a drainage time proportional to the frame width. Using an original velocimetry technique, based on fluorescent foam films and photobleaching, we measure the horizontal and vertical components of the velocity in a draining film, thus providing the first quantitative experimental evidence of this flow pattern. Upward velocities up to $10\mathrm{cm}/\mathrm{s}$ are measured close to the lateral menisci, whereas a slower velocity field is obtained in the center of the film, with comparable downwards and horizontal components. Scaling laws are proposed for all characteristic velocities, coupling gravitational effects, and capillary suction.

We investigate with experiments and computer simulations the nonequilibrium dynamics of DNA polymers crossing arrays of entropic barriers in nanofluidic devices in a pressure-driven flow. With increasing driving pressure, the effective diffusivity of DNA rises and then peaks at a value that is many times higher than the equilibrium diffusivity. This is an entropic manifestation of “giant acceleration of diffusion.” The phenomenon is sensitive to the effective energy landscape; thus, it offers a unique probe of entropic barriers in a system driven away from equilibrium.

We identify the sequence of microstructural changes that characterize the evolution of an attractive particulate gel under flow and discuss their implications on macroscopic rheology. Dissipative particle dynamics is used to monitor shear-driven evolution of a fabric tensor constructed from the ensemble spatial configuration of individual attractive constituents within the gel. By decomposing this tensor into isotropic and nonisotropic components we show that the average coordination number correlates directly with the flow curve of the shear stress versus shear rate, consistent with theoretical predictions for attractive systems. We show that the evolution in nonisotropic local particle rearrangements are primarily responsible for stress overshoots (strain-hardening) at the inception of steady shear flow and also lead, at larger times and longer scales, to microstructural localization phenomena such as shear banding flow-induced structure formation in the vorticity direction.

Predicting the large-amplitude deformations of thin elastic sheets is difficult due to the complications of self contact, geometric nonlinearities, and a multitude of low-lying energy states. We study a simple two-dimensional setting where an annular polymer sheet floating on an air-water interface is subjected to different tensions on the inner and outer rims. The sheet folds and wrinkles into many distinct morphologies that break axisymmetry. These states can be understood within a recent geometric approach for determining the gross shape of extremely bendable yet inextensible sheets by extremizing an appropriate area functional. Our analysis explains the remarkable feature that the observed buckling transitions between wrinkled and folded shapes are insensitive to the bending rigidity of the sheet.

Cells utilize waves of polymerizing actin to reshape their morphologies, which is central to physiological and pathological processes alike. Here, we force dorsal actin waves to propagate on one-dimensional domains with periodic boundary conditions, which results in striking spatiotemporal patterns with a clear signature of noise-driven dynamics. We show that these patterns can be very closely reproduced with a noise-driven active medium at coherence resonance.

Organisms shape their own environment, which in turn affects their survival. This feedback becomes especially important for communities containing a large number of species; however, few existing approaches allow studying this regime, except in simulations. Here, we use methods of statistical physics to analytically solve a classic ecological model of resource competition introduced by MacArthur in 1969. We show that the nonintuitive phenomenology of highly diverse ecosystems includes a phase where the environment constructed by the community becomes fully decoupled from the outside world.

The mechanical properties of eukaryotic cells are to a great extent determined by the cytoskeleton, a composite network of different filamentous proteins. Among these, intermediate filaments (IFs) are exceptional in their molecular architecture and mechanical properties. Here we directly record stress-strain curves of individual vimentin IFs using optical traps and atomic force microscopy. We find a strong loading rate dependence of the mechanical response, supporting the hypothesis that IFs could serve to protect eukaryotic cells from fast, large deformations. Our experimental results show different unfolding regimes, which we can quantitatively reproduce by an elastically coupled system of multiple two-state elements.

We investigate the response of dense hard sphere glasses to a shear strain in a wide range of pressures ranging from the glass transition to the infinite-pressure jamming point. The phase diagram in the density-shear strain plane is calculated analytically using the mean-field infinite-dimensional solution. We find that just above the glass transition, the glass generically yields at a finite shear strain. The yielding transition in the mean-field picture is a spinodal point in presence of disorder. At higher densities, instead, we find that the glass generically jams at a finite shear strain: the jamming transition prevents yielding. The shear yielding and shear jamming lines merge in a critical point, close to which the system yields at extremely large shear stress. Around this point, highly nontrivial yielding dynamics, characterized by system-spanning disordered fractures, is expected.

Quantitative predictions for the spread of mutations in bacterial populations are essential to interpret evolution experiments and to improve the stability of synthetic gene circuits. We derive analytical expressions for the suppression factor for beneficial mutations in populations that undergo periodic dilutions, covering arbitrary population sizes, dilution factors, and growth advantages in a single stochastic model. We find that the suppression factor grows with the dilution factor and depends nontrivially on the growth advantage, resulting in the preferential elimination of mutations with certain growth advantages. We confirm our results by extensive numerical simulations.