Papers

We develop a family of control protocols for finite-time transitions between active nonequilibrium steady states using the noise-color (correlation rate) as the sole control parameter. By reverse-engineering the second moment dynamics of an active Ornstein-Uhlenbeck process, we determine the time-dependent correlation rate required to realize a prescribed evolution of the system's state. We experimentally implement these protocols with a micrometer-sized optically trapped particle coupled to an engineered active bath, demonstrating transitions substantially faster than the natural relaxation while keeping the confining potential, noise amplitude, and temperature fixed. Our approach extends engineered swift-equilibration methods to far-from-equilibrium steady states by directly controlling the temporal correlations of an active environment. We show how physical constraints impose a speed limit on finite-time transitions, while the freedom in choosing the prescribed system evolution can be exploited to eliminate control discontinuities, minimize the admissible transition time, or optimize a thermodynamic cost.

Thermodynamic cycles are the foundation of energy conversion across natural and engineered systems, transforming heat into useful work. However, these cycles traditionally operate between fixed thermal reservoirs, restricting them to specific locations and temperature differences. Here, we introduce autonomous thermodynamic cycles enabled by robotic mobility and sensing, allowing robots to perform thermodynamic cycles by accessing spatially varying temperature fields. We experimentally realize this concept using multistable gas-filled capsules that circulate within the system across a thermal gradient. Our model reveals that rapid transitions in the capsules' energy states allow the system to operate as a mobile heat engine that harvests and stores energy. By linking the capsule-scale internal energy dynamics to the robot's large-scale navigation strategy, we optimize locomotion paths that balance motion cost and energy harvesting. These findings demonstrate that thermodynamic cycles can emerge when autonomous systems navigate their environments, offering an artificial analog of organisms that forage for energy across spatial resources.

Excitation of absorbing colloids in liquid by pulsed laser irradiation creates highly non-equilibrium states of matter that relax via defined pathways of thermal and non-thermal dissipation channels. The structural fingerprint of these channels can be probed by ultrafast in situ x-ray scattering methods and classified as a function of temporal delay of excitation excitation density, or specifically laser fluence. We study the example of photo-excitation of a gold colloid by picosecond laser pulses at the interband absorption band at 400 nm in water. By quantifying lattice temperature, crystalline fraction, particle sizes and the structural response of the water around the nanoparticles a reaction map is constructed that allows to pinpoint heating, particle melting, water bubble formation and finally particle fragmentation to form nanoclusters of predominant sizes of < 3 nm for applications in theranostics, photonics or catalysis.

A Poisson's ratio near -1 indicates only that the bulk modulus is small compared with the shear modulus. In solid-void structures, the mechanism that frees the dilation usually weakens the resistance to shear as well, resulting in both moduli becoming small. In two-dimensional linear elasticity, we demonstrate that this loss is not inevitable. We consider a honeycomb of regular hexagonal blocks of a single incompressible isotropic elastic solid, joined along their whole edges by ideal interfaces that allow relative sliding along a direction inclined to the edge normal. Collective infinitesimal block rotations produce an exact dilational mechanism, so the effective bulk modulus vanishes, while sixfold symmetry ensures isotropy. The interfaces, however, transmit traction along their whole length. In a solid-void realization, each interface is replaced with fine solid plates separated by void, which bend easily yet retain their capacity to transmit axial force. Such dilational materials, which expand or contract freely while resisting every change of shape, could serve as interlayers that accommodate thermal or swelling mismatch while still transmitting shear, and as components in stents and deployable structures that change size without changing shape. An explicit, statically admissible stress field and the complementary energy principle yield a rigorous lower bound on the retained shear modulus, and a limiting argument transfers this bound to the solid-void mixtures. The honeycomb retains more than four-fifths of its constituent's shear modulus at zero bulk modulus: the supremum S of the normalized shear modulus of such mixtures satisfies S > 0.8528 > 4/5, exceeding the value attained by Milton's construction.

Flocking results from dynamical alignment among neighbors in a collection of active self-propelling objects. The intervening medium, typically a fluid, however, is not considered to be important for alignment, except for acting as a momentum sink. The flocking system is therefore described as momentum nonconserving "dry" active matter. Here we investigate a confined system of self-propelled Marangoni swimmers where feedback from the fluid medium, which crucially depends on the shape of the swimmers, influences their alignment. Using up to thirty partially camphor-coated triangular paper boats as polar swimmers, we uncover a disorder-to-order transition, and an unusual re-entrant order-to-disorder transition, as functions of camphor concentration and swimmer density, respectively. We reproduce these transitions by formulating a reaction-diffusion model for the camphor field, coupled to the swimmer dynamics, where propulsion forces arise from surface tension gradients. The shape-dependent hydrodynamic interaction discussed here could be central to efficient flocking in living organisms too.

Translational and helical symmetries provide idealized descriptions of many flows encountered in nature and engineering. While translationally symmetric flows have been extensively studied within kinetic and continuum frameworks, the corresponding connection between microscopic dynamics and continuum behaviour for helical flows is less developed. Here, we investigate this connection for a dilute gas with time-dependent helical symmetry. Using the objective molecular dynamics framework, we derive a reduced Boltzmann equation that retains radial variations while preserving the classical collision operator under helical symmetry. Formal hydrodynamic expansions then yield the corresponding Euler and Navier-Stokes-Fourier equations. The resulting models describe how cylindrical geometry and axial deformation influence transport, including viscous transport and heat conduction, and how deformation generates unequal stresses along and across the axis in competition with collisional relaxation. Comparisons with direct simulation Monte Carlo solutions examine both spatially uniform and radially varying flows. In the cases studied, the first-order fluid corrections capture the leading stress anisotropy and improve the prediction of radial temperature variations, while larger Knudsen numbers expose limitations of the approximation.

We introduce a method for controlling the lateral motion of droplets bouncing on a vibrated liquid bath by superimposing a small periodic rocking motion onto the conventional vertical forcing. We show experimentally that the lateral velocity varies linearly with the rocking amplitude $\alpha$ and sinusoidally with its phase $\phi$ relative to the vertical forcing, while the response depends strongly on the droplet's vertical bouncing mode. A time-averaged model of a harmonic bouncer yields a time-averaged lateral force $\overline{F}_x=mg\alpha\sin(\Phi_b+\phi)$, where $\Phi_b$ is the droplet impact phase. Periodic rocking thus provides a simple, programmable means of exerting lateral forces on bouncing droplets, enabling controlled manipulation of passive and active droplets in pilot-wave hydrodynamics.

Filamentous cyanobacteria form extensive kilometer-scale mats in aquatic environments, yet the physical mechanisms driving their macroscopic self-organization remain elusive. Here, we investigate the dynamics of filamentous cyanobacterial assemblies within a quasi-two-dimensional confinement. Our observations reveal that chiral gliding drives active tangling between individual filaments, inducing rapid network contraction and the formation of densely packed aggregates. By quantifying single-contact forces, we demonstrate that these mechanical interactions generate significant contractile stresses. Together, our findings sug- gest that chiral gliding has evolved as a physical mechanism to maximize inter-filament interactions and drive large-scale collective organization.

Bayesian inference was combined with Unified Fit to resolve the effects of the mixing history on polymer nanocomposites whose ultra-small-angle X-ray scattering profiles are nearly indistinguishable by conventional analysis. Bayesian Unified Fit was applied to comparing the aggregate size, internal mass-fractal structure, and surface roughness for three carbon black–filled ethylene propylene diene copolymer rubber samples prepared by different mixing processes. Whereas conventional Unified Fit reported essentially identical carbon-black dispersions, the radius of gyration, mass fractal dimension, and surface fractal dimension for the three samples all followed the same ordering, which coincides with the reported ordering of the tensile strength and elongation at break and suggests that the inferred aggregate hierarchy is physically meaningful for the macroscopic mechanical response. These results identify the aggregate size as a candidate structural descriptor of rubber reinforcement and provide an uncertainty-aware basis for examining processing–structure–property relationships in polymer nanocomposites.

A recently introduced anharmonic mean-field model unifiedly reproduced a broad range of low-temperature glass phenomena — including harmonic nonphononic spectral properties, linear micromechanics and strongly driven elasto-plastic dynamics — indicating that its underlying energy landscape is intrinsically glassy. Here, we apply a nonlinear modes framework to the model and derive analytic predictions for the asymptotic distributions of activation barriers $p(\Delta{U})\!\sim\!(\Delta{U})^{1/4}$ and the external force needed for the onset of plasticity $p(f_{\rm c})\sim f_{\rm c}^{2/3}$, for their extreme-value scaling and for $\langle\Delta{U}\rangle$ beyond the asymptotic regime. These predictions are expected to equally apply to the mean-field model and to finite-dimensional glasses. We develop efficient algorithms for sampling minima and saddles of the model's glassy potential energy landscape, and quantitatively confirm the theoretical predictions. This progress is enabled by identifying a subset of collective degrees of freedom that are physically relevant for activated glassy dynamics, which like the theoretical predictions should apply to realistic glasses.

Membrane composition plays a central role in determining how antimicrobial peptides (AMPs) interact with and alter the physical properties of lipid membranes. Here, we investigate the composition-dependent mechanical and structural response of lipid membranes to the AMP aurein using neutron spin-echo (NSE) spectroscopy, neutron membrane diffraction (NMD), and pressure (P)-area (A) isotherms, complemented by previously reported quasielastic neutron scattering (QENS) measurements. In a zwitterionic DMPC membrane, aurein induces progressive softening, manifested by a concentration-dependent decrease in both the bending rigidity and area compressibility modulus. NMD reveals a slight bilayer thinning but no prominent peptide-associated contribution within the deuterated hydrocarbon region, indicating that the progressive mechanical softening is not accompanied by increasingly deep peptide penetration into the hydrophobic core. In contrast, anionic phosphatidylglycerol (PG)-containing DMPC/DMPG membranes exhibit a non-monotonic response, with initial softening followed by pronounced stiffening at higher peptide concentrations. Complementary P-A isotherm measurements independently reproduce these contrasting mechanical responses, showing progressive softening of DMPC but stiffening of DMPC/DMPG. Most importantly, the combined NSE and QENS results reveal a striking multiscale decoupling: aurein suppresses molecular-scale lipid lateral diffusion while simultaneously reducing collective membrane stiffness at the mesoscopic scale, demonstrating that molecular lipid dynamics and collective membrane mechanics can evolve in opposite directions under the same peptide perturbation.Together, these results show that membrane composition governs the collective mechanical response to aurein, while molecular lipid dynamics can respond independently at shorter length and time scales.

Active rods are elongated, self-propelled particles that serve as effective models for motile microorganisms, such as bacteria and sperm cells. When confined to a microfluidic channel, active rods exhibit a distinctive motility pattern: they tend to swim against the fluid flow along channel walls. In pressure-driven channel flow, they alternate between long upstream runs along the walls and short downstream spurts in the bulk. This behavior has practical implications for bacterial contamination of catheters and microfluidic devices against the flow. We study the spreading of a population of active rods along long microchannels using a hierarchy of models. Monte Carlo simulations of a three-dimensional model show that net upstream transport depends non-monotonically on the flow rate, decreases with rotational diffusion, and depends on the shape of the channel cross-section. The simulations also show that upstream and downstream persistence times follow exponentially decaying distributions. This motivates the derivation of a one-dimensional, two-state velocity-jump model. For exponentially distributed persistence times, we derive the evolution equation for the concentration of continuously injected rods and determine its long-time limit in closed form. This analysis reveals a concentration plateau upstream of the source when the mean upstream velocity is positive and exponential decay otherwise. Using parameters measured from the three-dimensional simulations, the one-dimensional model reproduces the concentration profiles from the Monte Carlo simulations, and these results are consistent with recent experimental observations of bacterial contamination in microfluidic devices.

Thin elastic flexible structures exploit large geometric deformation to achieve mechanical functionality, making their fracture behavior strongly coupled with the evolving structural configuration. This work presents a unified discrete differential geometry (DDG) phase-field framework for fracture in highly deformable thin structures. Membrane and bending elasticity are formulated from discrete geometric measures on a triangulated midsurface, while the phase field is defined on the same discrete surface to describe onset of crack growth and subsequent propagation. The coupled problem is solved using a staggered scheme, with phase-field irreversibility enforced by an active-set method. A degradation-deletion procedure removes nearly fully failed elements and reconstructs the DDG topology, enabling complete crack opening and substantial post-fracture reconfiguration. For two-dimensional in-plane fracture problems, the DDG predictions agree closely with geometrically nonlinear finite element results in both crack evolution and mechanical response. In three-dimensional tearing, the framework resolves the interaction between out-of-plane deformation and crack propagation, including the experimentally observed convergence and coalescence of initially parallel cracks. Its engineering applicability is further demonstrated using an island–bridge structure representative of flexible electronics. The simulations capture direction-dependent deformation modes, instability and snap-through during loading, and the coupled evolution of structural configuration and fracture. These results establish the proposed framework as an effective tool for investigating geometry-dependent fracture and supporting the damage-tolerant design of flexible thin structures.

We study a semiflexible magnetic polymer in which each monomer carries a two-state spin, giving rise to coupled conformational, stiffness, and magnetic degrees of freedom. The model provides a minimal representation of nucleoprotein complexes in vivo, in which DNA bending rigidity and bridging proteins must be simultaneously accommodated. We employ Monte Carlo simulations on a face-centered-cubic (FCC) lattice, complemented by a variational free-energy upper-bound approach, to characterize the zero-field phase diagram as a function of bending stiffness and temperature. At low stiffness, we identify a first-order transition combining coil-to-globule collapse with a ferromagnetic-to-paramagnetic transition. At lower temperatures, an additional first-order transition separates the disordered globule from an ordered crystal characterized by nematic-like orientational order of the bond tangents. At high stiffness, the globule disappears, resulting in a direct first-order coil-to-crystal transition. These results demonstrate how chain stiffness and magnetic degrees of freedom couple to polymer conformation and reorganize the zero-field phase diagram. Our model connects the two limiting cases of flexible magnetic polymers and semiflexible homopolymers, the latter corresponding to the strong-field limit in which all spins are aligned.

Broadly studied origami crease patterns such as the Miura-ori are capable of rigid folding that maintains their spatial periodicity. However, periodic crease patterns generically require additional creases and fold into quasi-cylindrical shapes. Here, using group theory, we show that the folding properties of such sheets are largely determined by their spatial symmetries, known as layer groups. Within each symmetry class, the allowed linear shape-periodic modes of sheets are constrained and classified by the irreducible representation they belong to. Such classification further gives a sufficient condition, containing a symmetry constraint and a topological constraint, for the existence of a nonlinear strain mode. In this way, familiar special cases are placed within a unified framework that connects symmetry, network topology, and deployability. Finally, we turn our classification results into a predictive design principle that enables the rapid design of novel sheets with prescribed properties.

We study the $d$-dimensional generalization of Models II ($d=2$) and V ($d=3$) for liquid crystals introduced by Heilmann–Lieb (1979), which consists of dimers on the hypercubic lattice at chemical potential $\mu$, interacting via a hard-core repulsion and a lateral attraction between parallel dimers with coupling constant $b>0$. For $d\in\{2,3\}$, these models were conjectured to exhibit liquid-crystalline order at low temperatures provided that $\mu+2(d-1)b>0$. We establish nematic order for all $d\ge 2$ under the additional condition $(4d-6)b>\mu$, which corresponds to the physical regime in which misaligned dimers are rare on scales comparable to the correlation length of the one-dimensional reference system. While the treatment of orientational order here follows the approach of our recent work on Model I, the proof of the absence of translational order relies on a custom implementation of cluster swapping in the sense of Sheffield (2005). Consequently, we deduce uniqueness of Gibbs measure and anisotropic exponential decay of correlations within each oriented phase.

In colloids, anisotropy in either shape or particle interactions can steer assemblies away from close-packed monolayers and towards more intricate structures. In this study we utilize both shape and interaction anisotropy to stabilize porous surface assemblies of triblock elliptical particles, whose surfaces are decorated with two attractive patches at opposite poles. The resulting structures display a tunable degree of crystalline kagome order, controlled by quenching the temperature and/or changing the chemical potential. In particular, we find evidence that nucleation into the kagome lattice proceeds via a one-step pathway, in contrast to the two-step route widely reported in spherical triblock systems, making triblock ellipses an interesting model system for studying how self-assembly pathways change with particle shape. Beyond ordered crystalline structures, we find disordered porous networks with complex internal geometry. To characterize this range of assemblies, we introduce a particle-patch graph that explicitly captures the localization of bonds at distinct patches. Bonding motifs follow directly from this representation, while the loops, that we identify as the pore boundaries, can be determined from the graph's planar embedding. We detect all loops as the face boundaries in the planar embedding by means of a face-walking algorithm, distinct from shortest-path approaches used in ring detection. Together with a new local and global order parameter measuring the loop network's regularity with respect to a selected loop size, this framework connects microscopic bonding motifs to mesoscopic pore properties and quantifies the tunable order of these porous assemblies.

Physical crosslinks in conventional gels are static and spatially localised, fundamentally limiting their capacity to adapt, self-heal, or perform mechanical work. Topological gels, which are held together by physical entanglements such as threadings, links, and mechanical interlocks, constitute a different paradigm by treating connectivity as a mobile, dynamic degree of freedom. Here, by using molecular dynamics simulations of semiflexible polymers and threadable colloidal rings, we establish some general design principles that transform self-assembled topological gels into programmable soft materials. We present three different modes of control. First, by controlling the mobility of the entanglements, one can tune the mechanical response of the material. Quenched anchoring forces the network to store elastic stress and yield, whereas with annealed anchoring the material can relax stresses by redistributing its entanglements whilst preserving global connectivity. Second, by controlling the degree or type of geometric confinement, it is possible to template macroscopic architecture, converting for instance 3D isotropic gels into surface-spanning 2D nets or quasi-1D topological rings with distinct graph-spectral signatures. Third, by allowing dynamical rewiring of entanglements through polymer reconnection, the material topology can be rewritten after assembly, yielding interlocked structures dominated by simple pairwise links rather than the highly complex linked states previously observed in reconnecting flexible polymers. By establishing a direct link between microscopic entanglement dynamics and emerging mechanical function, our work offers design principles for adaptive soft metamaterials and provides insights into biological topological networks such as kinetoplast DNA and chromatin loop networks.

We derive the local pressure tensor generated by the original Rosenfeld fundamental measure theory (FMT) for hard-sphere fluids from an arbitrary infinitesimal deformation. The variation of a finite-distance FMT kernel is written via the line integrals of the local deformation gradient along the straight segment connecting its endpoints. The resulting symmetric pressure tensor consists of a local term expressed through the standard FMT weighted densities and a finite-range chord term. For a monodisperse hard-sphere fluid, differential relations between the Rosenfeld measures reduce the tensor to a closed one-body form. We demonstrate that no independent pair density or inhomogeneous Ornstein–Zernike equation is required. In the limit of homogeneous fluid the tensor reproduces the Percus–Yevick compressibility equation of state. In planar confinement the normal stress satisfies the hard-wall contact relation, the mechanical surface tension agrees with the surface excess grand potential, and the disjoining pressure agrees with the derivative of the confined grand potential with respect to slit width. The finite-range chord term extends the deformation method from local field theories to nonlocal weighted-density functionals.

We study size fluctuations of chemically active droplets in the regime of weak reactions and strong phase separation. By combining a thin-interface model for the deterministic droplet growth with stochastic noise based on fluctuation-dissipation arguments, we report excellent quantitative agreement between our theory and numerical field simulations. Finally, we use our model to infer the effective non-equilibrium potential that governs droplet growth, and show that active reactions that enable size control suppress nucleation.

We propose an algorithm for identifying low-energy minima in systems containing thousands of particles, at moderate computational cost. We focus on spherical crystals, in which particles form ordered structures on the surface of a sphere. Our method uses symmetric seed configurations, or known structures, to initialize searches across contiguous ranges of system sizes. Newly identified minima are then used to guide searches at neighbouring sizes, allowing information to propagate efficiently through configuration space. We have tested this approach on the Thomson problem, one of the few interacting-particle systems for which global optimization has been considered for systems of this size. We substantially improve on many previous solutions, particularly at larger system sizes, where systematic global optimization is computationally expensive. Since favourable packings for the Thomson problem are reflected in systems spanning atomistic to mesoscopic length scales, the newly characterized defect patterns may inform structure prediction for a broad range of problems with spherical topology.

We study a heterogeneous diffusion process with a position-dependent diffusion coefficient in the presence of independent recruitment and mortality. This framework generalises heterogeneous diffusion under stochastic resetting, which is recovered as the special case of equal recruitment and mortality rates. At long times, the system approaches a non-equilibrium stationary state with a mean squared displacement that saturates to a value independent of the recruitment rate. Crucially, this saturation limit directly encodes the underlying transport regime via an effective exponent applied to the diffusion coefficient, and we characterise the non-trivial transition to this stationary regime. We further derive the mean first-passage time to a target and show that, for a fixed recruitment-to-mortality ratio, an optimal mortality rate minimises the search time. This "mortality-assisted search" effect is confirmed by numerical evaluation. Reinterpreting recruitment and mortality as infection and removal processes, we apply the model to epidemic spreading and show that a moderate removal rate can counter-intuitively accelerate, rather than delay, the arrival of infection at a new spatial region. Beyond epidemiology, our framework offers broad relevance to systems featuring concurrent particle creation and destruction, such as bacterial growth, tracer diffusion in reactive fluids, or cellular population dynamics in crowded environments.

Phase-field models offer an efficient alternative to self-consistent field theory (SCFT), but quantitative predictions of block-copolymer phase behavior remain challenging. We develop a quadratic-connectivity entropic (QCE) density functional and its adaptive extension (AQCE). QCE combines quadratic nonlocal connectivity with a nonlinear binary relative-entropy term, while AQCE adds bounded interfacial stiffness that preserves the homogeneous response. In lamellar benchmarks, QCE gives the lowest mean profile error among the tested models and AQCE the lowest mean period error. Compared with the optimized phase-field (OPF) model fitted to SCFT force and stress data, AQCE reduces strong-segregation period and profile errors by more than fivefold and sixfold, respectively. AQCE further reproduces the topology of the SCFT phase diagram for AB diblocks, a more demanding test of free-energy rankings among competing morphologies. Because architecture enters through ideal-chain correlations, the same nonlinear construction extends to other A/B architectures. We demonstrate this transfer for symmetric linear ABA lamellae, accurately predicting their profiles, periods, and ordering threshold.

The origin of segregated axial bands for size-bidisperse particles in long rotating tumblers is a long-standing question in granular flows and a problem of both fundamental and practical interest. Using DEM simulations, we consider the streamwise and time-dependent development of the underlying instability as well as performing a broad parametric study over a wide range of particle size ratios, tumbler lengths and diameters, species fractions, and fill levels to determine the conditions under which axially segregated bands appear. We show that initial radial segregation of the small and large particles in the surface flowing layer results in a layer of mixed particles with a higher bulk density due to more efficient packing over a layer of nearly monodisperse small particles with a lower bulk density. This leads to a granular Rayleigh-Taylor-like instability that produces recirculation cells driving axial band formation. The appearance of a layer of high-density mixed particles over a layer of lower-density monodisperse particles can be directly connected to the operating conditions, explaining why axially segregated bands appear only under certain conditions. Typically, increasing the particle size ratio improves packing and increases the density of the mixed layer, enhancing the Rayleigh-Taylor instability and accelerating axial segregation.

The Distorted Wave Born Approximation (DWBA) is established for X-ray interface scattering, yet its domain of applicability has never been stated explicitly. The DWBA implicitly rests on the small refractive index deviation (SRID) condition - satisfied by X-rays ($|n-1| \sim 10^{-6}$) but violated by visible light ($|n-1| \sim 0.5$). The DWBA mixes microscopic and macroscopic Maxwell equations, whereas a rigorous optical theory must be built on the macroscopic Maxwell equations and constitutive relations. Rigorous alternatives for two specific inconsistencies in the standard DWBA are discussed. The Extended Transfer Matrix Approach (ETMA) for visible-light interface scattering is outlined.

We present a study of the shapes and mechanical properties of a knitted loop made of elastic and frictional yarns. First, for non-frictional yarns, we investigate how the elastic energy of a loop varies with its shape. This allows us to quantify the energetic contributions of stretching and bending, and to identify energetically favorable loop configurations. We then consider the case of thin frictional yarns. In this case, the stability of a loop can be reduced, even in the presence of friction, to a simple planar elastica problem. Friction gives rise to a multiplicity of stable loop shapes in a knitted fabric at rest, i.e., in the absence of externally applied forces. We show that, in the limit of thin yarns, a 2D elastica model can predict these rest shapes. Furthermore, the force-deformation curves under uniaxial stretching can be obtained straightforwardly within this framework. Measurements of loop dimensions and forces during uniaxial stretching of nylon knitted fabrics allow us to assess the qualitative and quantitative validity of the planar elastica model. Finally, we examine the limitations of this model for dense knitted fabrics.

Nonreciprocal mechanical response is usually associated with built-in directional couplings, structural chirality, or external driving. Whether an achiral active body can instead generate and reverse such directionality through its own motion remains less clear. Here we show that spontaneous rotation makes an active elastic ring with reciprocal passive interactions mechanically nonreciprocal. Off-center elastic forces reorient propulsion, coupling deformation back to motion. Reversing the rotation reverses the antisymmetric response, while a compensating control preserves finite directionality but strongly suppresses the near-Hopf resonance. Approaching Hopf, the selected response grows inversely with distance to onset and becomes a self-sustained traveling deformation above threshold. Thus nonreciprocity is selected by the dynamical state, while active feedback controls its critical amplification.

Topological entanglements are central to understanding and predicting the properties of polymer melts. Yet, they make equilibrium sampling computationally challenging, as decorrelation times grow rapidly with chain length. Here, we introduce a Monte Carlo scheme that bypasses typical computational bottlenecks by working in a self-assembly ensemble rather than at fixed composition. Strictly local moves efficiently propagate backbone reconnections across scales while conserving the number of linear chains, achieving near-linear scaling of decorrelation time with system size, $\tau_{\rm eq}\sim V^{1.0}$. With this method, formulated for a fully-packed lattice, we equilibrate periodic systems totalling up to $\simeq 1.1\times 10^9$ monomers, accessing a universal melt regime insensitive to lattice details. We analyze intra- and inter-chain entanglements for chains of up to $N\simeq 5 \times 10^5$ monomers, revealing that they manifest as localized knots and links rather than as global tangles. Finally, we show that the magnitude of the Gauss linking integral between neighbouring chains grows only as $N^{1/4}$.

How do neural representations of neighbors become collective material behavior? Harmonic Theory (HT) reduces bearing representations to signed perceptual channels traceable to sensory acuity, decision dynamics, and interaction distance. Here we derive a nonlocal kinetic and hydrodynamic theory from the HT particle law without introducing heading alignment. The resulting fields retain HT's order-resolved perceptual spectrum and keep the neural and sensory origin of each coefficient visible. The theory predicts a torque-driven density instability: HT's direct-approach channel turns agents toward density excesses, while self-propulsion carries them inward. For isotropic spatial interactions and positive rotational diffusion, perceptual channel $n$ generically first affects conserved density at spatial order $k^{2n}$, and the full radial transforms select finite pattern wavelengths. Two populations can share the same long-wave instability threshold yet select different initial pattern spacings because their higher perceptual channels differ. Beyond onset, the one-particle continuum sustains a bidirectional nematic column; a prescribed, symmetry-allowed two-stream response amplifies a directional imbalance into sustained polar flow. In a distinct pure-repulsion regime, one-particle calculations show polar transport and translating transverse bands, with late pattern selection sensitive to numerical transport. The framework connects neural and sensory mechanisms to continuum coefficients, instabilities, and alignment-free collective motion.

We investigate the translational and rotational dynamics of cyclically sheared suspensions over a broad range of particle concentrations. The transition to an irreversible state is studied using a custom confocal-rheometer and colloidal particles synthesized with chemically identical smooth and lobed surfaces. The particle trajectories and rotations are tracked in three dimensions to reveal enhanced effective diffusivities that exhibit flow induced anisotropy that depends on particle concentration and particle morphology. We show that within the irreversible state, the shear induced anisotropy is determined by interparticle friction and interlocking mechanisms that promote mixing and enforce rotational isotropy.