Human memory appears to be fragile and unpredictable. Free recall of random lists of words is a standard paradigm used to probe episodic memory. We proposed an associative search process that can be reduced to a deterministic walk on random graphs defined by the structure of memory representations. The corresponding graph model can be solved analytically, resulting in a novel parameter-free prediction for the average number of memory items recalled ($R$) out of $M$ items in memory: $R=\sqrt{3\pi M/2}$. This prediction was verified with a specially designed experimental protocol combining large-scale crowd-sourced free recall and recognition experiments with randomly assembled lists of words or common facts. Our results show that human memory can be described by universal laws derived from first principles.

The highly confined flow of the liquid phase, trapped between the gas bubbles, is at the origin of the large effective viscosity of the liquid foams. Despite the industrial relevance of this complex fluid, the foam viscosity remains difficult to predict because of the lack of flow characterization at the bubble scale. Using an original deformable frame, we provide the first experimental evidence of the interface transfer between a compressed film (or a stretched film) and its first neighbor, across their common meniscus. We measure this transfer velocity, which is a key boundary condition for local flows in foams. We also show the dramatic film thickness variation induced by this interface transfer, which may play an important role in the film thickness distribution of a 3D foam sample.

Langevin dynamics simulations are performed to investigate ejection dynamics of spherically confined flexible polymers through a pore. By varying the chain length $N$ and the initial volume fraction ${\varphi }_0$ of the monomers, two scaling behaviors for the ejection velocity $v$ on the monomer number $m$ in the cavity are obtained: $v\sim m^{1.25}{\varphi }_0^{1.25}/N^{1.6}$ for large $m$ and $v\sim m^{-1.4}$ as $m$ is small. A robust scaling theory is developed by dividing the process into the confined and the nonconfined stages, and the dynamical equation is derived via the study of energy dissipation. After trimming the prior stage related to the escape of the head monomer across the pore, the evolution of $m$ is shown to be well described by the scaling theory. The ejection time exhibits two proper scaling behaviors: $N^{(2/3\nu )+y_1}{\varphi }_0^{-(2/3\nu )}$ and $N^{2+y_2}$ under the large and small ${\varphi }_0$ or $N$ conditions, respectively, where $y_1=1/3$, $y_2=1-\nu$, and $\nu$ is the Flory exponent.

We study the critical behavior of a model with nondissipative couplings aimed at describing the collective behavior of natural swarms, using the dynamical renormalization group under a fixed-network approximation. At one loop, we find a crossover between an unstable fixed point, characterized by a dynamical critical exponent $z=d/2$, and a stable fixed point with $z=2$, a result we confirm through numerical simulations. The crossover is regulated by a length scale given by the ratio between the transport coefficient and the effective friction, so that in finite-size biological systems with low dissipation, dynamics is ruled by the unstable fixed point. In three dimensions this mechanism gives $z=3/2$, a value significantly closer to the experimental window, $1.0\le z\le 1.3$, than the value $z\approx 2$ numerically found in fully dissipative models, either at or off equilibrium. This result indicates that nondissipative dynamical couplings are necessary to develop a theory of natural swarms fully consistent with experiments.

We present a microscopic theory for the nonequilibrium interfacial tension ${\gamma }_{\mathrm{gl}}$ of the free interface between gas and liquid phases of active Brownian particles. The underlying square gradient treatment and the splitting of the force balance in flow and structural contributions is general and applies to inhomogeneous nonequilibrium steady states. We find ${\gamma }_{\mathrm{gl}}\ge 0$, which opposes claims by Bialké et al. [Phys. Rev. Lett. 115, 098301 (2015)] and delivers the theoretical justification for the widely observed interfacial stability in active Brownian dynamics many-body simulations.

One of the biggest unresolved problems in crystallization phenomena is the significant discrepancy in the nucleation rate between experiments and simulations even for the simplest liquid, i.e., the hard-sphere system. A popular explanation for this discrepancy is the neglect of hydrodynamic interactions (HI) in simulation studies. By comparing simulations with and without HI, we show that the long-time diffusive dynamics of the colloids is slowed down more rapidly by hydrodynamic lubrication effects with increasing volume fraction. We find that the kinetics of both nucleation and growth are controlled by this long-time diffusion and that it is possible to account for most of the effects of HI by rescaling with this timescale. Therefore, we conclude that HI is not the primary cause of the accelerated nucleation rates observed in experiments.

Bacterial biofilms represent a major form of microbial life on Earth and serve as a model active nematic system, in which activity results from growth of the rod-shaped bacterial cells. In their natural environments, ranging from human organs to industrial pipelines, biofilms have evolved to grow robustly under significant fluid shear. Despite intense practical and theoretical interest, it is unclear how strong fluid flow alters the local and global architectures of biofilms. Here, we combine highly time-resolved single-cell live imaging with 3D multiscale modeling to investigate the mechanisms by which flow affects the dynamics of all individual cells in growing biofilms. Our experiments and cell-based simulations reveal three quantitatively different growth phases in strong external flow and the transitions between them. In the initial stages of biofilm development, flow induces a downstream gradient in cell orientation, causing asymmetrical dropletlike biofilm shapes. In the later developmental stages, when the majority of cells are sheltered from the flow by the surrounding extracellular matrix, buckling-induced cell verticalization in the biofilm core restores radially symmetric biofilm growth, in agreement with predictions of a 3D continuum model.

We study dry, dense active nematics at both particle and continuous levels. Specifically, extending the Boltzmann-Ginzburg-Landau approach, we derive well-behaved hydrodynamic equations from a Vicsek-style model with nematic alignment and pairwise repulsion. An extensive study of the phase diagram shows qualitative agreement between the two levels of description. We find in particular that the dynamics of topological defects strongly depends on parameters and can lead to “arch” solutions forming a globally polar, smecticlike arrangement of Néel walls. We show how these configurations are at the origin of the defect ordered states reported previously. This work offers a detailed understanding of the theoretical description of dense active nematics directly rooted in their microscopic dynamics.

We report on a new mode of self-propulsion exhibited by compact drops of active liquids on a substrate which, remarkably, is tractionless, i.e., which imparts no mechanical stress locally on the surface. We show, both analytically and by numerical simulation, that the equations of motion for an active nematic drop possess a simple self-propelling solution, with no traction on the solid surface and in which the direction of motion is controlled by the winding of the nematic director field across the drop height. The physics underlying this mode of motion has the same origins as that giving rise to the zero viscosity observed in bacterial suspensions. This topologically protected tractionless self-propusion provides a robust physical mechanism for efficient cell migration in crowded environments like tissues.

Despite their importance in many biological, ecological, and physical processes, microorganismal fluid flows under tight confinement have not been investigated experimentally. Strong screening of Stokelets in this geometry suggests that the flow fields of different microorganisms should be universally dominated by the 2D source dipole from the swimmer’s finite-size body. Confinement therefore is poised to collapse differences across microorganisms, which are instead well established in bulk. We combine experiments and theoretical modeling to show that, in general, this is not correct. Our results demonstrate that potentially minute details like microswimmer spinning and the physical arrangement of the propulsion appendages have in fact a leading role in setting qualitative topological properties of the hydrodynamic flow fields of microswimmers under confinement. This is well captured by an effective 2D model, even under relatively weak confinement. These results imply that active confined hydrodynamics is much richer than in bulk and depends in a subtle manner on the size, shape, and propulsion mechanisms of the active components.

We study experimentally the response of a dense sediment of Brownian particles to self-propulsion. We observe that the ergodic supercooled liquid relaxation is monotonically enhanced by activity. By contrast the nonergodic glass shows an order of magnitude slowdown at low activities with respect to the passive case, followed by fluidization at higher activities. Our results contrast with theoretical predictions of the ergodic approach to glass transition, summing up to a shift of the glass line. We propose that nonmonotonicity is due to competing effects of activity: (i) extra energy that helps breaking cages; (ii) directionality that hinders cage exploration. We call it “deadlock from the emergence of active directionality.” It suggests further theoretical works should include thermal motion.

We study the avalanche dynamics of a pile of micrometer-sized silica grains in water-filled microfluidic drums. Contrary to what is expected for classical granular materials, avalanches do not stop at a finite angle of repose. After a first rapid phase during which the angle of the pile relaxes to an angle ${\theta }_c$, a creep regime is observed where the pile slowly flows until the free surface reaches the horizontal. This relaxation is logarithmic in time and strongly depends on the ratio between the weight of the grains and the thermal agitation (gravitational Péclet number). We propose a simple one-dimensional model based on Kramers’ escape rate to describe these Brownian granular avalanches, which reproduces the main observations.

Complex distribution networks are pervasive in biology. Examples include nutrient transport in the slime mold Physarum polycephalum as well as mammalian and plant venation. Adaptive rules are believed to guide development of these networks and lead to a reticulate, hierarchically nested topology that is both efficient and resilient against perturbations. However, as of yet, no mechanism is known that can generate such networks on all scales. We show how hierarchically organized reticulation can be constructed and maintained through spatially correlated load fluctuations on a particular length scale. We demonstrate that the network topologies generated represent a trade-off between optimizing transport efficiency, construction cost, and damage robustness and identify the Pareto-efficient front that evolution is expected to favor and select for. We show that the typical fluctuation length scale controls the position of the networks on the Pareto front and thus on the spectrum of venation phenotypes.

Colloids with short range attractions self-assemble into sample-spanning structures, whose dynamic nature results in a thermokinematic memory of the deformation history, also referred to as “thixotropy.” Here, we study the origins of the thixotropic effect in these time- and rate-dependent materials by investigating hysteresis across different length scales: from particle-level local measurements of coordination number (microscale), to the appearance of density and velocity fluctuations (mesoscale), and up to the shear stress response to an imposed deformation (macroscale). The characteristic time constants at each scale become progressively shorter, and hysteretic effects become more significant as we increase the strength of the interparticle attraction. There are also strong correlations between the thixotropic effects we observe at each scale.

Dense emulsions, colloidal gels, microgels, and foams all display a solidlike behavior at rest characterized by a yield stress, above which the material flows like a liquid. Such a fluidization transition often consists of long-lasting transient flows that involve shear-banded velocity profiles. The characteristic time for full fluidization ${\tau }_f$ has been reported to decay as a power law of the shear rate $\dot{\gamma }$ and of the shear stress $\sigma$ with respective exponents $\alpha$ and $\beta$. Strikingly, the ratio of these exponents was empirically observed to coincide with the exponent of the Herschel-Bulkley law that describes the steady-state flow behavior of these complex fluids. Here we introduce a continuum model, based on the minimization of a “free energy,” that captures quantitatively all the salient features associated with such transient shear banding. More generally, our results provide a unified theoretical framework for describing the yielding transition and the steady-state flow properties of yield stress fluids.

Dense suspensions of hard particles in a Newtonian liquid can be jammed by shear when the applied stress exceeds a certain threshold. However, this jamming transition from a fluid into a solidified state cannot be probed with conventional steady-state rheology because the stress distribution inside the material cannot be controlled with sufficient precision. Here we introduce and validate a method that overcomes this obstacle. Rapidly propagating shear fronts are generated and used to establish well-controlled local stress conditions that sweep across the material. Exploiting such transient flows, we can track how a dense suspension approaches its shear-jammed state dynamically and quantitatively map out the onset stress for solidification in a state diagram.

We study first passage behaviors in the flow through three-dimensional random fracture networks. Network and flow heterogeneity lead to the emergence of heavy-tailed first passage time distributions that evolve with increasing distance between the start and target planes, and transition toward stable laws. Analysis of the spatial memory of the first passage process shows that particle motion can be quantified stochastically by a time domain random walk conditioned on the initial velocity data. This approach identifies advective tortuosity, the velocity point distribution and the average fracture link length as key quantities for the prediction of first passage times. Using this approach, we develop a theory for the evolution of first passage times with increasing distance between the start and target planes and the convergence towards stable laws.

Manipulating building-block nanomaterials to form an ordered superstructure in a dilute and spacer-free solution phase challenges the existing 5-nm node lithography and nanorobotics. The cooperative nature of nanocrystals, polymers, and cells can lead to superarrays or colloidal crystals. For known highly ordered systems, the characteristic length of materials, defined as the shortest dimension of objects, is generally larger than their separations. A spacer (small-molecule surfactant or polymer) is typically required to diminish short range van der Waals attraction, which results in a glassy or liquid state. Herein we propose a new concept of achieving highly ordered nano-objects in a dilute and spacer-free system via the synergistic effects of excellent solvation and appropriate constraints on rotational motion. As a proof of concept, this study demonstrates that aluminosilicate nanotubes (AlSiNTs) suspended in water under dilute conditions (e.g., 1.0 wt%) can spontaneously form hexagonal arrays with an intertubular distance as large as tens of nanometers. The separation distance of the ordered superstructure is also tunable via controlling the concentration and length of nanotubes. These superaligned structures are probed using small-angle x-ray scattering and cryo-TEM characterizations, with underlying mechanisms investigated at an atomic level using molecular dynamics simulations. The concept and discovery of this work can open up opportunities to a variety of applications including visible-UV photonics and nanolithography, and may be generalizable to other nano-object systems that fulfill similar requirements.

We quantify the spatiotemporal transformation of a monodisperse and well-ordered monolayer of bubbles, as they undergo Ostwald ripening, by tracking the size polydispersity of the bubbles and local ordering of the foam. After nuclei of disorder appear at random locations, the transition takes place through two successive phases: first, the disordered regions grow while the value of polydispersity increases slowly, then the polydispersity grows rapidly once the disordered zones begin to merge together. The transition is captured by a modified logistic model.