How does a cell locate the source of molecular guidance cues from within a concentration gradient? We present a computational approach to recover the source from the absorbed fluxes at narrow receptor windows located on the surface of the cell. In the limit of fast binding, we solve the steady-state diffusion equation using an asymptotic approach and hybrid stochastic-analytical simulations. We show that the sensitivity to the gradient direction decays too rapidly to enable long-distance sensing. We illustrate how this constraint can be alleviated when triangulating the source with an increasing number of receptor windows and quantify the susceptibility of this process to flux perturbations.

In periodically sheared suspensions there is a dynamical phase transition, characterized by a critical strain amplitude ${\gamma }_c$, between an absorbing state where particle trajectories are reversible and an active state where trajectories are chaotic and diffusive. Repulsive nonhydrodynamic interactions between “colliding” particles’ surfaces have been proposed as a source of this broken time reversal symmetry. A simple toy model called random organization qualitatively reproduces the dynamical features of this transition. Random organization and other absorbing state models exhibit hyperuniformity, a strong suppression of density fluctuations on long length scales quantified by a structure factor $S(q\to 0)\sim q^{\alpha }$ with $\alpha >0$, at criticality. Here we show experimentally that the particles in periodically sheared suspensions organize into structures with anisotropic short-range order but isotropic, long-range hyperuniform order when oscillatory shear amplitudes approach ${\gamma }_c$.

We use active nematohydrodynamics to study the flow of an active fluid in a 3D microchannel, finding a transition between active turbulence and regimes where there is a net flow along the channel. We show that the net flow is only possible if the active nematic is flow aligning and that, in agreement with experiments, the appearance of the net flow depends on the aspect ratio of the channel cross section. We explain our results in terms of when the hydrodynamic screening due to the channel walls allows the emergence of vortex rolls across the channel.

Shearing granular materials induces nonaffine displacements. Such nonaffine displacements have been studied extensively, and are known to correlate with plasticity and other mechanical features of amorphous packings. A well known example is shear transformation zones as captured by the local deviation from affine deformation, $D_{\min }^2$, and their relevance to failure and stress fluctuations. We analyze sheared frictional athermal disc packings and show that there exists at least one additional mesoscopic transport mechanism that superimposes itself on top of local diffusive motion. We evidence this second transport mechanism in a homogeneous system via a diffusion tensor analysis and show that the trace of the diffusion tensor equals the classic $D_{\min }^2$ when this second mesoscopic transport is corrected for. The new transport mechanism is consistently observed over a wide range of volume fractions and even for particles with different friction coefficients and is consistently observed also upon shear reversal, hinting at its relevance for memory effects.

The Hawkes self-excited point process provides an efficient representation of the bursty intermittent dynamics of many physical, biological, geological, and economic systems. By expressing the probability for the next event per unit time (called “intensity”), say of an earthquake, as a sum over all past events of (possibly) long-memory kernels, the Hawkes model is non-Markovian. By mapping the Hawkes model onto stochastic partial differential equations that are Markovian, we develop a field theoretical approach in terms of probability density functionals. Solving the steady-state equations, we predict a power law scaling of the probability density function of the intensities close to the critical point $n=1$ of the Hawkes process, with a nonuniversal exponent, function of the background intensity ${\nu }_0$ of the Hawkes intensity, the average timescale of the memory kernel and the branching ratio $n$. Our theoretical predictions are confirmed by numerical simulations.

Using a minimal algebraic model for the thermodynamics of binary rod-polymer mixtures, we provide evidence for a quintuple phase equilibrium; an observation that seems to be at odds with the Gibbs phase rule for two-component systems. Our model is based on equations of state for the relevant liquid crystal phases that are in quantitative agreement with computer simulations. We argue that the appearance of a quintuple equilibrium, involving an isotropic fluid, a nematic and smectic liquid crystal, and two solid phases, can be reconciled with a generalized Gibbs phase rule in which the two intrinsic length scales of the athermal colloid-polymer mixture act as additional field variables.

We correlate the terminal relaxation of supramolecular polymer networks, based on unentangled telechelic poly(isobutylene) linear chains forming micellar end-group clusters, with the microscopic chain dynamics as probed by proton NMR. For a series of samples with increasing molecular weight, we find a quantitative agreement between the terminal relaxation times and their activation energies provided by rheology and NMR. This finding corroborates the validity of the transient-network model and the special case of the sticky Rouse model, and dismisses more dedicated approaches treating the terminal relaxation in terms of micellar rearrangements. Also, we confirm previous results showing reduction of the activation energy of supramolecular dissociation with increasing molecular weight and explain this trend with an increasing elastic penalty, as corroborated by small angle x-ray scattering data.

Using in situ nanodielectric spectroscopy we demonstrate that the imbibition kinetics of cis-1,4-polyisoprene in native alumina nanopores proceeds in two time regimes both with higher effective viscosity than bulk. This finding is discussed by a microscopic picture that considers the competition from an increasing number of chains entering the pores and a decreasing number of fluctuating chain ends. The latter is a direct manifestation of increasing adsorption sites during flow. At the same time, the longest normal mode is somewhat longer than in bulk. This could reflect an increasing density of topological constraints of chains entering the pores with the longer loops formed by other chains.

Neurodegenerative diseases, such as Alzheimer’s or Parkinson’s disease, show characteristic degradation of structural brain networks. This degradation eventually leads to changes in the network dynamics and degradation of cognitive functions. Here, we model the progression in terms of coupled physical processes: The accumulation of toxic proteins, given by a nonlinear reaction-diffusion transport process, yields an evolving brain connectome characterized by weighted edges on which a neuronal-mass model evolves. The progression of the brain functions can be tested by simulating the resting-state activity on the evolving brain network. We show that while the evolution of edge weights plays a minor role in the overall progression of the disease, dynamic biomarkers predict a transition over a period of 10 years associated with strong cognitive decline.

The efficiency of a virus to establish its infection in host cells varies broadly among viruses. It remains unclear if there is a key step in this process that controls viral infectivity. To address this question, we use single-particle tracking and Brownian dynamics simulation to examine human immunodeficiency virus type 1 (HIV-1) infection in cell culture. We find that the frequency of viral-cell encounters is consistent with diffusion-limited interactions. However, even under the most favorable conditions, only 1% of the viruses can become immobilized on cell surface and subsequently enter the cell. This is a result of weak interaction between viral surface gp120 and CD4 receptor, which is insufficient to form a stable complex the majority of the time. We provide the first direct quantitation for efficiencies of these events relevant to measured HIV-1 infectivity and demonstrate that immobilization on host cell surface post-virion-diffusion is the key step in viral infection. Variation of its probability controls the efficiency of a virus to infect its host cells. These results explain the low infectivity of cell-free HIV-1 in vitro and offer a potential rationale for the pervasive high efficiency of cell-to-cell transmission of animal viruses.

Field theoretic simulations are used to predict the equilibrium phase diagram of symmetric blends of $AB$ diblock copolymer with $A$- and $B$-type homopolymers. Experiments generally observe a channel of bicontinuous microemulsion ($\mathrm{B}\mu \mathrm{E}$) separating the ordered lamellar (LAM) phase from coexisting homopolymer-rich ($A+B$) phases. However, our simulations find that the channel is unstable with respect to macrophase separation, in particular, $A+B+\mathrm{B}\mu \mathrm{E}$ coexistence at high $T$ and $A+B+\mathrm{LAM}$ coexistence at low $T$. The preference for three-phase coexistence is attributed to a weak attractive interaction between diblock monolayers.

The mechanical response of naturally abundant amorphous solids such as gels, jammed grains, and biological tissues are not described by the conventional paradigm of broken symmetry that defines crystalline elasticity. In contrast, the response of such athermal solids are governed by local conditions of mechanical equilibrium, i.e., force and torque balance of its constituents. Here we show that these constraints have the mathematical structure of a generalized electromagnetism, where the electrostatic limit successfully captures the anisotropic elasticity of amorphous solids. The emergence of elasticity from local mechanical constraints offers a new paradigm for systems with no broken symmetry, analogous to emergent gauge theories of quantum spin liquids. Specifically, our $U(1)$ rank-2 symmetric tensor gauge theory of elasticity translates to the electromagnetism of fractonic phases of matter with the stress mapped to electric displacement and forces to vector charges. We corroborate our theoretical results with numerical simulations of soft frictionless disks in both two and three dimensions, and experiments on frictional disks in two dimensions. We also present experimental evidence indicating that force chains in granular media are subdimensional excitations of amorphous elasticity similar to fractons.

One of the fundamental goals of nanotechnology is to exploit selective and directional interactions between molecules to design particles that self-assemble into desired structures, from capsids, to nanoclusters, to fully formed crystals with target properties (e.g., optical, mechanical, etc.). Here, we provide a general framework which transforms the inverse problem of self-assembly of colloidal crystals into a Boolean satisfiability problem for which solutions can be found numerically. Given a reference structure and the desired number of components, our approach produces designs for which the target structure is an energy minimum, and also allows us to exclude solutions that correspond to competing structures. We demonstrate the effectiveness of our approach by designing model particles that spontaneously nucleate milestone structures such as the cubic diamond, the pyrochlore, and the clathrate lattices.

Solids built out of active components can exhibit nonreciprocal elastic coefficients that give rise to non-Hermitian wave phenomena. Here, we investigate non-Hermitian effects present at the boundary of two-dimensional active elastic media obeying two general assumptions: their microscopic forces conserve linear momentum and arise only from static deformations. Using continuum equations, we demonstrate the existence of the non-Hermitian skin effect in which the boundary hosts an extensive number of localized modes. Furthermore, lattice models reveal non-Hermitian topological transitions mediated by exceptional rings driven by the activity level of individual bonds.

Impulsive deformation is widely observed in biological systems to generate movement with high acceleration and velocity. By storing elastic energy in a quasistatic loading and releasing it through an impulsive elastic recoil, organisms circumvent the intrinsic trade-off between force and velocity and achieve power amplified motion. However, such asymmetry in strain rate in loading and unloading often results in reduced efficiency in converting elastic energy to kinetic energy for homogeneous materials. Here, we demonstrate that specific internal structural designs can offer the ability to tune quasistatic and high-speed recoil independently to control energy storage and conversion processes. Experimental demonstrations with mechanical metamaterials reveal that certain internal structures optimize energy conversion far beyond unstructured materials under the same conditions. Our results provide the first quantitative model and experimental demonstration for tuning energy conversion processes through internal structures of metamaterials.

Finite dimensional signatures of spinodal criticality are notoriously difficult to come by. The dynamical transition of glass-forming liquids, first described by mode-coupling theory, is a spinodal instability preempted by thermally activated processes that also limit how close the instability can be approached. We combine numerical tools to directly observe vestiges of the spinodal criticality in finite dimensional glass formers. We use the swap Monte Carlo algorithm to efficiently thermalize configurations beyond the mode-coupling crossover, and analyze their dynamics using a scheme to screen out activated processes, in spatial dimensions ranging from $d=3$ to $d=10$. We observe a strong softening of the mean-field square-root singularity in $d=3$ that is progressively restored as $d$ increases above $d=8$, in surprisingly good agreement with perturbation theory.