Water is widely assumed to be essential for protein dynamics and function. In particular, the well-documented “dynamical” transition at $\sim 200\mathrm{K}$, at which the protein changes from a rigid, nonfunctional form to a flexible, functional state, as detected in hydrogenated protein by incoherent neutron scattering, requires hydration. Here, we report on coherent neutron scattering experiments on perdeuterated proteins and reveal that a transition occurs in dry proteins at the same temperature resulting primarily from the collective heavy-atom motions. The dynamical transition discovered is intrinsic to the energy landscape of dry proteins.

Recent studies of active matter have stimulated interest in the driven self-assembly of complex structures. Phenomenological modeling of particular examples has yielded insight, but general thermodynamic principles unifying the rich diversity of behaviors observed have been elusive. Here, we study the stochastic search of a toy chemical space by a collection of reacting Brownian particles subject to periodic forcing. We observe the emergence of an adaptive resonance in the system matched to the drive frequency, and show that the increased work absorption by these resonant structures is key to their stabilization. Our findings are consistent with a recently proposed thermodynamic mechanism for far-from-equilibrium self-organization.

Thermo-osmotic slip—the flow induced by a thermal gradient along a surface—is a well-known phenomenon, but curiously there is a lack of robust molecular-simulation techniques to predict its magnitude. Here, we compare three different molecular-simulation techniques to compute the thermo-osmotic slip at a simple solid-fluid interface. Although we do not expect the different approaches to be in perfect agreement, we find that the differences are barely significant for a range of different physical conditions, suggesting that practical molecular simulations of thermo-osmotic slip are feasible.

A virus binding to a surface causes stress of the virus cage near the contact area. Here, we investigate the potential role of substrate-induced structural perturbation in the mechanical response of virus particles to adsorption. This is particularly relevant to the broad category of viruses stabilized by weak noncovalent interactions. We utilize atomic force microscopy to measure height distributions of the brome mosaic virus upon adsorption from solution on atomically flat substrates and present a continuum model that captures our observations and provides estimates of elastic properties and of the interfacial energy of the virus, without recourse to indentation.

The shape of a polymer plays an important role in its interactions with surrounding molecules. We characterize the shape and the orientational properties of a polymer chain under tension in a good solvent, a physical condition that is often realized both in single-molecule experiments and in vivo. Our findings reveal the existence of hitherto unobserved universal laws encompassing polymers with different rigidities and including the possible presence of excluded-volume effects, showing that both shape and orientation are solely determined by the force contribution to the free energy. In doing so, they also provide a simple way to retrieve these quantities from the knowledge of the force-versus-extension curve.

We study theoretically the edge fracture instability in sheared complex fluids, by means of linear stability analysis and direct nonlinear simulations. We derive an exact analytical expression for the onset of edge fracture in terms of the shear-rate derivative of the fluid’s second normal stress difference, the shear-rate derivative of the shear stress, the jump in shear stress across the interface between the fluid and the outside medium (usually air), the surface tension of that interface, and the rheometer gap size. We provide a full mechanistic understanding of the edge fracture instability, carefully validated against our simulations. These findings, which are robust with respect to choice of rheological constitutive model, also suggest a possible route to mitigating edge fracture, potentially allowing experimentalists to achieve and accurately measure flows stronger than hitherto possible.

Coherent, large-scale dynamics in many nonequilibrium physical, biological, or information transport networks are driven by small-scale local energy input. Here, we introduce and explore an analytically tractable nonlinear model for compressible active flow networks. In contrast to thermally driven systems, we find that active friction selects discrete states with a limited number of oscillation modes activated at distinct fixed amplitudes. Using perturbation theory, we systematically predict the stationary states of noisy networks and find good agreement with a Bayesian state estimation based on a hidden Markov model applied to simulated time series data. Our results suggest that the macroscopic response of active network structures, from actomyosin force networks to cytoplasmic flows, can be dominated by a significantly reduced number of modes, in contrast to energy equipartition in thermal equilibrium. The model is also well suited to study topological sound modes and spectral band gaps in active matter.

Boolean network models describe genetic, neural, and social dynamics in complex networks, where the dynamics depend generally on network topology. Fixed points in a genetic regulatory network are typically considered to correspond to cell types in an organism. We prove that the expected number of fixed points in a Boolean network, with Boolean functions drawn from probability distributions that are not required to be uniform or identical, is one, and is independent of network topology if only a feedback arc set satisfies a stochastic neutrality condition. We also demonstrate that the expected number is increased by the predominance of positive feedback in a cycle.

Random sequential adsorption (RSA) of particles of a particular shape is used in a large variety of contexts to model particle aggregation and jamming. A key feature of these models is the observed algebraic time dependence of the asymptotic jamming coverage $\sim t^{-\nu }$ as $t\to \infty$. However, the exact value of the exponent $\nu$ is not known apart from the simplest case of the RSA of monodisperse spheres adsorbed on a line (Renyi’s seminal “car parking problem”), where $\nu =1$ can be derived analytically. Empirical simulation studies have conjectured on a case-by-case basis that for general nonspherical particles, $\nu =1/(d+\tilde{d})$, where $d$ denotes the dimension of the domain, and $\tilde{d}$ the number of orientational degrees of freedom of a particle. Here, we solve this long-standing problem analytically for the $d=1$ case—the “Paris car parking problem.” We prove, in particular, that the scaling exponent depends on the particle shape, contrary to the original conjecture and, remarkably, falls into two universality classes: (i) $\nu =1/(1+\tilde{d}/2)$ for shapes with a smooth contact distance, e.g., ellipsoids, and (ii) $\nu =1/(1+\tilde{d})$ for shapes with a singular contact distance, e.g., spherocylinders and polyhedra. The exact solution explains, in particular, why many empirically observed scalings fall in between these two limits.

Among the key insights into the glass transition has been the identification of a nonequilibrium phase transition in trajectory space which reveals phase coexistence between the normal supercooled liquid (active phase) and a glassy state (inactive phase). Here, we present evidence that such a transition occurs in experiments. In colloidal hard spheres, we find a non-Gaussian distribution of trajectories leaning towards those rich in locally favored structures (LFSs), associated with the emergence of slow dynamics. This we interpret as evidence for a nonequilibrium transition to an inactive LFS-rich phase. Reweighting trajectories reveals a first-order phase transition in trajectory space between a normal liquid and a LFS-rich phase. We also find evidence for a purely dynamical transition in trajectory space.

Efficient bacterial chromosome segregation typically requires the coordinated action of a three-component machinery, fueled by adenosine triphosphate, called the partition complex. We present a phenomenological model accounting for the dynamic activity of this system that is also relevant for the physics of catalytic particles in active environments. The model is obtained by coupling simple linear reaction-diffusion equations with a proteophoresis, or “volumetric” chemophoresis, force field that arises from protein-protein interactions and provides a physically viable mechanism for complex translocation. This minimal description captures most known experimental observations: dynamic oscillations of complex components, complex separation, and subsequent symmetrical positioning. The predictions of our model are in phenomenological agreement with and provide substantial insight into recent experiments. From a nonlinear physics view point, this system explores the active separation of matter at micrometric scales with a dynamical instability between static positioning and traveling wave regimes triggered by the dynamical spontaneous breaking of rotational symmetry.

The emergence of structure through aggregation is a fascinating topic and of both fundamental and practical interest. Here we demonstrate that self-generated solvent flow can be used to generate long-range attractions on the colloidal scale, with subpiconewton forces extending into the millimeter range. We observe a rich dynamic behavior with the formation and fusion of small clusters resembling molecules. The dynamics of this assembly is governed by an effective conservative energy that for large separations $r$ decays as $1/r$. Breaking the flow symmetry, these clusters can be made active.

We introduce a method, based on a novel thermodynamic integration scheme, to extract the Flory-Huggins $\chi$ parameter as small as ${10}^{-3}kT$ for polymer blends from molecular dynamics (MD) simulations. We obtain $\chi$ for the archetypical coarse-grained model of nonpolar polymer blends: flexible bead-spring chains with different Lennard-Jones interactions between $A$ and $B$ monomers. Using these $\chi$ values and a lattice version of self-consistent field theory (SCFT), we predict the shape of planar interfaces for phase-separated binary blends. Our SCFT results agree with MD simulations, validating both the predicted $\chi$ values and our thermodynamic integration method. Combined with atomistic simulations, our method can be applied to predict $\chi$ for new polymers from their chemical structures.

We study the response of a film of colloidal spherocylinders to compression by combining pressure-area isotherm measurements, microscopy, and computer simulations. We find that the behavior of the film depends strongly on the geometry of the particles. For a small aspect ratio, a uniform monolayer forms and then buckles. For a higher aspect ratio, particles flip to orient perpendicular to the interface; we show that flipping occurs in locations where the nematic ordering is low. Our experiments and simulations further demonstrate that the longest particles rearrange to self-assemble a colloidal bilayer, which is stable due to the unique geometry of spherocylinders at an interface.

We present a numerical study of dense colloidal suspensions in a pressure-driven microchannel flow in two dimensions. The colloids are modeled as elastic and frictional spheres suspended in a Newtonian fluid, which we simulate using the method of multiparticle collision dynamics. The model reproduces periodic velocity and density pulse trains, traveling upstream in the microchannel, which are found in experiments conducted by Isa et al. [Phys. Rev. Lett. 102, 058302 (2009)]. We show that colloid-wall friction and the resultant force chains are crucial for the formation of these pulses. With an increasing colloid density, first solitary jams occur, which become periodic pulse trains at intermediate densities and unstable solitary pulses at high densities. We formulate a phenomenological continuum model and show how these spatiotemporal flow and density profiles can be understood as homoclinic and periodic orbits in traveling-wave equations.

Bacterial swimming in confined two-dimensional environments is ubiquitous in nature and in clinical settings. Characterizing individual interactions between swimming bacteria in 2D confinement will help to understand diverse microbial processes, such as bacterial swarming and biofilm formation. Here we report a novel motion pattern displayed by flagellated bacteria in 2D confinement: When two nearby cells align their moving directions, they tend to engage in cohesive swimming without direct cell body contact, as a result of hydrodynamic interaction but not flagellar intertwining. We further found that cells in cohesive swimming move with higher directional persistence, which can increase the effective diffusivity of cells by $\sim 3$ times as predicted by computational modeling. As a conserved behavior for peritrichously flagellated bacteria, cohesive swimming in 2D confinement may be key to collective motion and self-organization in bacterial swarms; it may also promote bacterial dispersal in unsaturated soils and in interstitial space during infections.

Experimental and theoretical studies suggest that cortical networks are chaotic and coding relies on averages over large populations. However, there is evidence that rats can respond to the short stimulation of a single cortical cell, a theoretically unexplained fact. We study effects of single-cell stimulation on a large recurrent network of integrate-and-fire neurons and propose a simple way to detect the perturbation. Detection rates obtained from simulations and analytical estimates are similar to experimental response rates if the readout is slightly biased towards specific neurons. Near-optimal detection is attained for a broad range of intermediate values of the mean coupling between neurons.