Papers

Obesity is a major risk factor for breast cancer, yet how obesity-associated changes in the physical properties of white adipose tissue (WAT) influence tumor invasion remains poorly understood. Here, we combine experimental and computational approaches to investigate this question. Using mouse models and human mastectomy samples, we show that obesity not only increases adipocyte size, but also asphericity. We observe that tumor-conditioned media drives lipid loss and dedifferentiation of adipocytes into myofibroblast-like cells in vitro and that adipocytes in high-fat diet-fed mice lose lipid at a faster rate than those in normal diet-fed mice in response to mammary tumors in vivo. We then develop discrete element method (DEM) simulations to understand how these obesity-induced changes in cell and tissue properties alter breast cancer invasion under high-fat and normal diet conditions. In DEM simulations, adipocytes are modeled as deformable polygons and polyhedra, and cancer cells are modeled as soft, adhesive disks and spheres in two and three dimensions, respectively. Invasion is driven by cancer cell proliferation and tumor-induced lipid loss is modeled as corresponding decreases in adipocyte size. DEM simulations indicate that obesity-associated increases in tissue pressure induce adipocyte deformation, consistent with elevated asphericity in experimental data. At small lipid loss rates, the degree of cancer invasion is only weakly affected by tissue pressure. However, at sufficiently large lipid loss rates, we find that tissue pressure accelerates cancer invasion. Together, these results suggest that lipid loss physically remodels WAT to facilitate breast cancer invasion, and that obesity may exacerbate this effect.

Biological materials such as the cytoskeleton and confluent cell monolayers are active, dense systems continuously subjected to internal stresses and strains, making their rheological characterization essential. While activity in soft matter can be modeled across multiple length scales, its mechanical consequences remain strongly model dependent and no unified theoretical framework has yet emerged. Here, we study the rheology of dense active amorphous materials using the Soft Glassy Rheology (SGR) model, incorporating activity at the mesoscopic scale of local elements as a stochastic strain rate that is persistent on some timescale $\tau_p$. We show that activity opens a long-time relaxation channel, driving a crossover from SGR-like power-law rheology to Maxwell-like behavior at the lowest frequencies. Combining analytical arguments in limiting regimes with numerical simulations, we characterize the resulting fluidisation time scale and its dependence on the activity parameters, which shows strong analogies with effective temperatures introduced elsewhere that similarly encode activity-induced fluidisation. Our active SGR model provides a minimal mesoscopic route to understanding how driving by activity modifies the rheology of dense amorphous materials.

A fundamental problem in the field of anisotropic macromolecular materials concerns how the flow-induced orientational order connects microscopic structure to macroscopic rheological stress and optical anisotropy. This study considered cellulose nanocrystal suspensions as rigid-rod model systems for the purpose of isolating orientational effects from chain stretching. Simultaneous rheo-optical measurements of birefringence, orientation angle, and shear stress were combined with a Fokker-Planck orientation model and stress decomposition. Our results show that, at low values of the Peclet number, birefringence and total stress exhibit proportionality similar to the stress-optic rule. However, the concentration dependence indicates that this proportionality reflects stress partitioning rather than a unique material coefficient. With increasing flow strength, orientational saturation is accompanied by a reduced relative Brownian stress contribution and a corresponding change in the total stress-based relation. Referencing the optical response to an estimated Brownian stress contribution yields a substantially more unified response across concentrations and flow conditions, supporting a stress-partitioning interpretation of apparent stress-optic rule breakdown.

We investigate the nonequilibrium phase-ordering kinetics of a binary mixture of uniaxial ellipsoidal particles interacting via the anisotropic Gay-Berne potential using large-scale molecular dynamics simulations. Following a temperature quench from the isotropic and homogeneous phase into the coexistence region, the system exhibits two distinct ordering processes occurring on different time scales. At first, rapid orientational ordering leads to the formation and coarsening of nematic domains, characterized by dynamical scaling, generalized Porod-law behavior, and a growth law $\ell(t) \sim t^{1/2}$ consistent with nonconserved order-parameter dynamics. Later, the system undergoes binary phase separation driven by compositional fluctuations. This compositional ordering process shows a transition from diffusive growth $\ell(t) \sim t^{1/3}$ to hydrodynamic regimes, with finite-size scaling analysis indicating asymptotic viscous growth $\ell(t) \sim t$. Despite the presence of global orientational order, the phase-separation kinetics remains effectively isotropic. These results demonstrate a clear separation between orientational and compositional ordering dynamics, governed by distinct conservation laws, and provide a unified framework for understanding phase ordering in anisotropic particle systems.

A hot Brownian particle is driven by thermal fluctuations from a nonuniformly heated solvent and therefore obeys a fluctuation-dissipation relation with a frequency-dependent effective temperature. Existing theories assume an incompressible solvent. We show that finite sound speed qualitatively changes this effective temperature in the kinetic regime. Solving the compressible fluctuating-hydrodynamic problem for a heated sphere, we find that the effective noise temperature develops a pronounced acoustic dip when the sound wavelength becomes comparable to the particle radius. The dip occurs because weakly attenuated longitudinal modes carry mechanical energy away from the heated surface before it is dissipated, so that the dissipation is weighted by colder regions of the temperature field. Its position is set by $a\omega/c=\mathcal{O}(1)$, while its depth is controlled by the dimensionless viscous-acoustic attenuation length $a_c/a$. The result identifies an acoustic window in hot Brownian motion in which compressibility lowers, rather than raises, the kinetic noise temperature.

The temperature dependence of thermal conductivity in glasses differs characteristically from that in crystals, and is largely controlled by how sound waves are damped. The Ioffe-Regel (IR) frequency sets the high-frequency limit of well-defined sound waves. Although the transverse IR frequency has been established to coincide with the boson peak frequency and reported to be far below the longitudinal IR frequency, the quantitative relation between longitudinal and transverse IR frequencies has remained unknown. Here we examine this relation in two- (2D) and three-dimensional (3D) model glasses with vastly different stability. We observe that, in 3D glasses, the longitudinal-to-transverse IR frequency ratio is approximately equal to the ratio of the low-frequency transverse to longitudinal sound attenuation coefficient, whereas this correspondence is not observed in 2D glasses. Moreover, we find that the glass stability strongly controls the longitudinal-to-transverse IR frequency ratio in both 2D and 3D glasses: the ratio decreases significantly with increasing glass stability and approaches unity for the most stable glasses under study. Accordingly, in sufficiently stable glasses, the longitudinal sound attenuation should be comparable to the transverse attenuation, and therefore cannot be treated as negligible, challenging common assumptions adopted especially in theoretical studies. Our work is another demonstration of the glass stability as a key parameter for investigating glass properties, and cautions against simply extrapolating observations from poorly annealed glasses to stable glasses.

Bent-core liquid crystals are a canonical example of a soft matter system whose behavior is controlled by a local preference for order that cannot be universally achieved. This geometric frustration, arising from the rod's curved shape, has been shown to stabilize a variety of equilibrium phases, such as the helically ordered nematic twist-bend phase ($N_{\rm TB}$). Unlike a traditional nematic, the twist-bend state has 1D translational order arising from a periodic rotation of bend orientation along the helical axis. Here, we use molecular dynamics simulations to study the effect of shearing the $N_{\rm TB}$ phase along directions parallel and perpendicular to the helical axis. In the case of shear perpendicular to the helical axis, the nematic twist-bend phase is stable and flows without disordering. Conversely, shear along the helical axis disrupts order and leads to the emergence of fractionally charged Skyrmion defects, i.e. merons. These defects act as topological machines, locally rotating rods into a re-ordered and stable orientation of the $N_{\rm TB}$ phase. These findings reveal a new mechanism to create and control merons and highlight the potential application of bent-core liquid crystals in designing functional material with specific optical and computational properties.

Active particles confined in droplets can set their host droplet into motion. This phenomenon is usually attributed to direct hydrodynamic forcing by the enclosed particles. Here we reveal a different mechanism: we show that a self-propelled raft of active colloids confined in a thin oil droplet at the surface of water typically follows an off-centered orbit, thus periodically deforming the droplet's contact line in an anisotropic way. This non-reciprocal deformation acts as a swimming stroke and propels the droplet according to the principles of low-Reynolds-number swimming. The effect is absent for a single colloid and arises from the intrinsically many-body dynamics of the raft, which we capture with a dynamical model coupling viscous hydrodynamics and many-body active dynamics. Our results show how collective internal activity can be converted into locomotion through deformation of a soft confining boundary.

Freely suspended ferroelectric-nematic fibres combine 1D fluidity with macroscopic spontaneous polarisation. Under alternating electric fields, we observe a sequence of dynamical states, from subthreshold pulsations to polarity-dependent axial flow, and sustained transverse oscillations. We show that the oscillatory state arises from a parametric instability of a liquid string whose effective tension is dominated by the electrical polarisation-field coupling contribution. A Floquet model incorporating finite-time polarisation switching captures the observed resonance tongues, modal selection, and square-wave response. These results establish ferroelectric-nematic fibres as electrically programmable fluid resonators coupling polar order and interfacial flow with nonlinear vibration.

We uncover an emergent phase separation in a system of inertial dumbbells put into persistent rotation by a constant applied torque, breaking chiral symmetry, while interacting with each other through repulsive hard-core interactions. We numerically determine the phase diagram of the model, showing that there exists a binodal and a spinodal region where the system separates into a dense liquid and an ordered phase, which we identify as hexatic. An analysis of the system pressure unveils that the mechanism underlying the phase separation is heavily controlled by inertia. Locally injected kinetic energy is steadily stored into the system in a way that depends on density and that, at large inertia, results in a hot dilute and cool dense state, leading to a generically unstable homogeneous phase. The interplay between dumbbells' arrangement into clusters and chiral forces produces a spontaneous rigid rotation of the clusters around their centers of mass.

Granular packings undergo intermittent rearrangements, known as precursors, before avalanche onset. Using grain-scale tracking in an inclined granular layer, we show experimentally that the number and recurrence of precursors change with the compatibility between the anisotropic structure inherited from preparation and the subsequent loading direction. Preparation also modifies the propagation of the mobility front, defined as the region in which the packing undergo measurable displacement: frequent precursors produce small progressive advances, whereas rare precursors involve larger extensions. By contrast, several features remain unchanged across protocols. The ensemble-averaged displacement always decays exponentially with depth over approximately four grain diameters, while the local shear-strain variance follows a common quadratic scaling with the mean strain. A two-state model suggests that, regardless of the packing structure, local strain heterogeneities affect approximately one quarter of the elementary cells, superimposed on the exponential strain profile. The reported results separate preparation-dependent precursor activity from the robust spatial features of the deformation preceding avalanches.

Dense granular flows are commonly investigated using the soft-sphere Discrete Element Method (DEM), whereas large-scale applications generally require continuum models. Granular temperature, defined as the variance of particle velocity fluctuations, is a relevant variable to collapse rheological scaling. However, experimental forcing approaches used to control temperature also affects other aspects of the granular state. An alternative is to use a thermostat algorithm to control the fluctuation energy directly. Although thermostat algorithms are well established in Molecular Dynamics (MD), their behaviour in dissipative DEM systems has received comparatively little attention. We show that conventional Langevin and Nosé-Hoover thermostats exhibit complementary limitations: Langevin control requires strong coupling to offset collisional dissipation, thereby damping particle dynamics, whereas Nosé-Hoover does not independently disrupt the correlations and segregation generated by repeated inelastic collisions, leading to non-ergodic and numerically unstable states. To address these limitations, we introduce two pairwise hybrid formulations combining deterministic temperature regulation with stochastic decorrelation. Both enforce the prescribed temperature, while variation of the stochastic decorrelation timescale modifies velocity statistics and associated mesoscopic properties such as diffusivity. Finally, application to pressure-controlled simple shear shows that increasing granular temperature at fixed inertial number reduces the apparent friction, consistent with previously reported trends. The framework therefore provides controlled reference states for comparing differently forced granular systems and identifying the variables required for temperature-dependent constitutive models.

Soft materials linked by reversible covalent or supramolecular bonds form a diverse class of assemblies with promising applications from nanoscience to medicine. Experiments typically probe bulk phase behavior and rheology, but it remains difficult to measure how microscopic bonding kinetics and the mechanics of the constituent elements give rise to bulk properties. Coarse-grained molecular dynamics (MD) simulations can bridge these scales, but most simulation approaches do not control individual bond kinetics, and those that do were mostly developed for bespoke applications that do not readily generalize. Here we present pySNAP (Simulation and Network Assembly Pipelines), a modular open source Python platform that integrates tunable dynamic bonding with a workflow, template, and analysis setup, so that users can study a wide range of systems with only small changes to input files. The platform is built on the GPU-accelerated HOOMD-blue MD engine and integrates DyBond, a GPU-accelerated plugin that forms and breaks bonds consistent with an equilibrium distribution and supports bonding between multiple types of partner species. Around this core, the snap_simulate package compiles a directory of parameter files into a HOOMD-blue simulation, and the snap_workflow package orchestrates the resulting parameter sweeps across workstations and high-performance computing schedulers. We describe the theory behind simulated dynamic bonding and how to use the package, from setting up a parameter sweep to analyzing its results, and demonstrate the framework on a diverse range of dynamically bonded systems, showing that it accommodates distinct interaction mechanisms, geometries, and physical scenarios within a unified workflow, while enabling both reproduction of existing models and rapid construction of more complex composite systems.

Dendritic silhouettes are cheap. Pond ice neurons, diffusion-limited aggregates, wiring-minimizing arbors, and biological neurons can share a branching statistic because they share a growth instability, not because they are functionally similar. We take that observation as a modeling constraint. The ice neuron only structurally resembles a biological neuron. A biological neuron carries an internal state and a field that it helps generate, letting geometry, dynamics, and field co-sculpt one another. In our construction, the ice neuron is the zero-gain limit of an interfacial system in which a FitzHugh–Nagumo state lives on the moving front and writes back into the field that drives it, with dimensionless gain $\gamma$. At $\gamma=0$, morphology and internal dynamics decouple into a Mullins–Sekerka growth band and a damped oscillator. Finite $\gamma$ deforms the spectrum, shifts the selected instability, and opens an oscillatory region below the isolated Hopf threshold. On a dendrite grown at $\gamma=0$ and then frozen, field closure increases distal persistence without changing the geometry; its first-order effect remains positive across repeated realizations of the same growth rule and localizes to a small set of non-cable field shortcuts. Nonlinear dynamics remain finite beyond the linear instability: below threshold, closure is almost the transmission; at spike amplitude, it is a correction to a regenerative cable event. A dendritic tree therefore is not intrinsically a structural spandrel. Shape alone is morphology without an internal state or a source term. That is the dendritic silhouette of the ice neuron. Excitability adds an active cable. Field closure is the biophysical mélange in which the neuron helps write the field that acts back on it, sculpting its dynamics and, during growth, its structure. That is a biological neuron.

We prove that, for almost every uniformly random configuration of $N$ particles in a two-dimensional periodic square domain, there exists a unique nearest stealthy hyperuniform configuration, up to floppy-mode displacements, when a finite set of $m$ low-$k$ Fourier modes is constrained to vanish exactly. Under an explicit full-rank Jacobian assumption, the displacement component orthogonal to the tangent space of the finite-mode hyperuniform manifold is uniquely determined, while residual tangent-space degrees of freedom correspond to first-order floppy modes that preserve the constrained low-$k$ density fluctuations. We restrict attention to the regime of constrained-mode fraction $\chi=m/(dN)$ in which such configurations are known to remain disordered rather than crystallize. To corroborate this framework, we implement a gradient-based generator network that iteratively displaces particles to minimize a combined loss functional of hyperuniformity, short-range repulsion, and smoothness, and whose dynamics is expected to approximate the theory's minimal orthogonal projection onto the hyperuniform manifold. The network drives generic random configurations toward disordered hyperuniform representatives, progressively suppressing long-wavelength density fluctuations as measured by the structure factor and number-variance exponent\textcolor{black}{, over a reciprocal-space window that extends well beyond the explicitly constrained modes and is bounded, as we show, by the structure-factor sum rule. Local bond-orientational analysis and the absence of Bragg peaks confirm that the resulting states remain disordered}. This integrated analytical and computational approach provides a rigorous geometric foundation for understanding stealthy hyperuniformity and for generating its disordered representatives from generic random configurations.

Sliding friction lowers the jamming packing fraction of dense suspensions and, when activated by stress, drives non-inertial shear thickening. Additional rolling resistance lowers the jamming packing fraction further and can represent effects of particle roughness or angularity. How it changes particle motion on the approach to jamming remains unclear. Using stress-controlled two-dimensional discrete-element simulations, we compare a sliding-only suspension with systems having either uniform or surface-varying rolling friction. At fixed packing fraction, adding rolling friction changes continuous shear thickening into discontinuous shear thickening. At the same distance from the stress-dependent jamming point, $\Delta\phi=\phi-\phi_m(\sigma)$, however, the flow curves nearly collapse, showing that the rheological effect arises largely from the shift in $\phi_m$. Guided by this collapse, we compare particle kinematics in the high-stress thickened state at matched $\Delta\phi$, revealing differences hidden by the similar bulk response. Translational velocity correlations extend over several particle diameters, whereas rotational correlations remain local. Rolling friction promotes co-rotation at contact in place of strong counter-rotation and suppresses rotational relative to translational fluctuations. Rotation nevertheless becomes increasingly important near jamming in every case. The suspension with surface-varying rolling friction follows the behavior of a uniform system with $\mu_r\approx0.3$ because the coefficients sampled at contacts lie well below the surface average value, here $\mu_r\approx0.5$. Thus, $\Delta\phi$ largely organizes the shear-thickening rheology, but not the particle kinematics. These retain a distinct signature of the rolling constraint that must be considered when rolling friction is used to model rough or angular particles.

From interstitial space to luminal cavities, fluid pressure and flow can remodel, reshape and even redefine a biological tissue. Fluids can either govern or react to mechanical interactions between cells. However, measuring flows at cellular scales is difficult, which makes it challenging to understand tissue hydraulics. Here, we develop a theoretical approach that captures cellular mechanics and fluid flow in one framework. We find that hydraulics can drastically influence tissue behavior. Hydraulic coupling between cell shape and size governs a tissue's response to osmotic shock, while tuning a tissue's permeabilities can channel fluid either between or across cell membranes. In active tissues, hydraulics can suppress cell mobility to the point of fracture, where we discover a hydraulic ratchet that drives fluid out of cells to generate small luminal spaces. We find experimental evidence that hydraulics can suppress cell motion in early stage zebrafish embryos injected with a thickening agent, which indicates that hydraulics may generally govern the behaviors of many multicellular systems.

Active nematics can spontaneously develop flow beyond a critical activity in confined geometries. We show analytically that the onset of flow is governed by two competing instabilities: a long-wavelength mode leading to unidirectional flow and a finite-wavelength instability producing transverse rolls. A reduced description reveals how activity, flow alignment, and nematic elasticity control the competition between these modes. We identify regimes in which the finite-wavelength instability has a lower critical activity than the long-wavelength instability, causing vortices to emerge before unidirectional flow. This establishes wavelength selection as an intrinsic feature of the onset of spontaneous flow in active nematics.

Active Brownian particles confined to rigid substrates are known to accumulate near rigid boundaries and, under suitable conditions, undergo motility-induced phase separation (MIPS). A particularly intriguing manifestation of this behavior is the formation of self-sustained vortices around circular obstacles, which act as localized nucleation sites for particle aggregation. While several dynamical properties of such vortices have been previously characterized, their behavior in the thermodynamic limit remains largely unexplored. Here, we investigate how the mass and spatial extent of a dry active-matter vortex scale with system size. Using numerical simulations of repulsive active Brownian Particles interacting with a fixed circular obstacle, we measure the vortex mass, mean radius, and maximum radius as functions of the global area fraction, obstacle size, and system size. We find two distinct scaling regimes. At low densities, the vortex remains localized and its characteristic properties saturate as the system size increases. Above a critical density, however, the vortex mass grows extensively with the total number of particles, while its spatial dimensions scale linearly with the system size, indicating the emergence of an obstacle-stabilized condensed state.

We study semiflexible active polymers confined within a soft, deformable droplet suspended in a fluid using dissipative particle dynamics (DPD) simulations. Extensile and contractile force dipoles along the polymer backbone generate distinct hydrodynamic flow fields that mediate effective interactions between polymer segments. Extensile activity promotes parallel alignment and lateral attraction, whereas contractile activity favors predominantly perpendicular organization, leading to qualitatively different collective behavior. The activity-generated flows couple strongly to the deformable interface, selectively enhancing low-order spherical-harmonic modes associated with long-wavelength droplet deformations. Activity also drives the interfacial relaxation away from passive capillary behavior, with extensile and contractile droplets exhibiting distinct mode-dependent dynamics. These differences in internal organization and interfacial fluctuations strongly influence droplet motility. Extensile activity produces increasingly persistent droplet motion with increasing polymer number, whereas contractile activity can sustain long-lived near-ballistic motion whose duration depends sensitively on polymer number and activity strength. Our results demonstrate how active hydrodynamics governs the interplay between internal structure, interfacial fluctuations, and emergent motility in confined active matter systems.

Understanding how collective ion transport emerges from equilibrium fluctuations is central to electrolyte statistical mechanics. Finite-volume fluctuations provide an accessible route to this information, but their interpretation is complicated because they mix wave numbers and collective fields. Here, we extend the finite-volume counting framework for inferring collective ion diffusion by combining the exact window projection with an inertial independent-particle reference, and apply it to a symmetric 1:1 solvent primitive model. The growth of ion-number fluctuations between the ballistic and plateau regimes appears nearly ideal, but this apparent ideality results from compensation between negative structural and positive dynamical excess contributions. The coupled ion-number–solvent relaxation further reveals a signed redistribution between solvent-associated and solvent-orthogonal projections that is largely hidden in the total response. The inferred collective diffusion depends on observation length and dynamical closure: measured structure alone does not systematically improve the estimate, whereas the coupled-field description reduces the high-concentration discrepancy. These results provide a basis for analyzing more realistic electrolytes with mutually coupled ion-number, charge, and solvent fluctuations.

Quantifying the interactions between active Janus particles remains a challenge that needs to be addressed to describe their collective behaviour. Inspired by a photonic force microscopy setup where two active Janus particles are confined in separate optical tweezers, we derive the steady-state probability distribution of each particle bearing signatures of the pair phoretic interaction, which can be generalised to a broader range of interactions. This approach allows us to infer interaction forces and torques from positional configurations without any knowledge of the particle orientations. Unraveling the distance-dependent interaction between active particles is essential to harnessing them as building blocks for advanced materials with dynamic properties.

We introduce Active Model H$^{-}$, a scalar phase-field model of non-equilibrium phase separation in the overdamped hydrodynamic limit, and show that it produces filamentous networks with enhanced connections and arrested coarsening, a morphology not observed in existing scalar active field theories. Isolated filaments are unstable to spontaneous bending, and the resulting curvature drives self-propulsion towards the convex side, causing them to collide and assemble into a percolating network. The networks are locally non-equilibrium, with anomalously curved edges, disordered vertex angles and heterogeneous topological charge, yet recover Lewis's law macroscopically. Under noise they show balanced break and reform dynamics.

Nucleation rates are exponentially sensitive to the thermodynamic driving force and can therefore depend strongly on the treatment of long-range intermolecular interactions. Here, using the Lennard–Jones (LJ) system as a benchmark, we combine molecular dynamics (MD) simulations, jumpy forward-flux sampling (jFFS), and free-energy calculations to quantify the effect of potential truncation on melting thermodynamics, homogeneous crystal nucleation kinetics, and computational cost. Within the cutoff-radius range $2.5\sigma\le r_c\le 6\sigma$, the melting temperature at zero pressure varies by approximately 11%, while the nucleation rate changes by approximately ten orders of magnitude. By invoking classical nucleation theory (CNT), we show that this pronounced kinetic sensitivity originates primarily from cutoff-induced changes in the chemical potential difference between the liquid and crystalline phases. Building on this observation, we develop a CNT-based framework for extrapolating finite-cutoff rates to the full-potential limit and for estimating the expected rate deviations at other cutoff radii and temperatures. These findings also provide a systematic basis for cutoff selection: the optimal cutoff should minimize computational cost while keeping the deviation from the full-potential rate within acceptable bounds. At $kT/\epsilon=0.5$, $r_c=4\sigma$ provides a reasonable compromise according to these criteria. We further demonstrate that conventional homogeneous tail corrections do not offer a reliable alternative, as they cannot consistently account for the liquid, crystalline, and interfacial environments present during nucleation. Our findings highlight the need to specify and validate the truncation scheme as an integral component of force-field development in simulations of nucleation and other interfacial phase transitions within inhomogeneous environments.

Characterization, control, and calibration of stringiness, the propensity to form long, thin, persistent threads, are key to the design and application of polymer solutions and formulations transferred to substrates by dropwise dispensing, jetting, spraying, or coating, and are used in manufacturing fibers, membranes, or spray-dried products. For Newtonian fluids, enhancing shear viscosity translates into increasing stringiness as can be easily perceived during dripping of water vs. sugar syrups or glycerol-water mixtures. In contrast, even polymer solutions with comparable shear viscosity can display a significant contrast in extensional rheology and apparent stringiness. However, there are no quantitative maps, formulas, or scales for stringiness, which motivates this study. In this contribution, we contrast the stringiness for a series of aqueous polymer solutions by determining the filament lifespan using dripping-onto-substrate (DoS) rheometry and filament length and lifespan in using dripping-into-air (DiA). We investigate the influence of polymer chemistry and molecular weight on stringiness and rely on DoS rheometry to characterize pinching dynamics and extensional rheology response. We show that an increase in stringiness correlates with steady, terminal extensional viscosity, and extensional relaxation time, respectively. Lastly, we provide a framework, which compares the stringiness of different polymer solutions through an extensional Ohnesorge-Deborah ($Oh-De$) plot or $Oh_E-De_E$ map, by computing the two dimensionless groups $Oh_E$ using steady, terminal extensional viscosity and $De_E$ using extensional relaxation time, respectively

Buckling of thin cylindrical shells under axial compression, a classical example of a subcritical instability, is highly sensitive to small imperfections, with minute geometric variations causing large changes in buckling threshold. To uncover the origin of this sensitivity, we use numerical continuation and bifurcation analysis while systematically varying the depth and size of a single localized Gaussian defect. We show that the instabilities of the imperfect shell originate from localized equilibria already present in the perfect shell. By breaking translation symmetry, the defect pins these equilibria and changes how they connect to the imperfect base state. Small changes in defect geometry can thereby switch the bifurcation that triggers buckling, producing non-monotonic and discontinuous changes in buckling threshold and abrupt changes in buckling mode. Imperfection sensitivity is therefore not simply sensitivity to imperfection magnitude, but sensitivity of the underlying bifurcation structure to imperfection geometry.

Soft materials store, dissipate and release mechanical stresses through relaxation processes that often span many orders of magnitude in time. Such relaxation spectra are widely used to infer internal material dynamics and are usually regarded as fingerprints of microscopic complexity, disorder, or heterogeneity. Here we show that a broad relaxation spectrum can instead be generated by the geometry of mechanical excitation itself. Using rotationally driven colloidal dimers in a wormlike micellar fluid with a dominant bulk relaxation time of order one second, we demonstrate that torsional driving converts distance from the driven object into relaxation time. This produces a geometry-controlled hierarchy of relaxation modes: orientational recoils persist for hundreds of seconds and encode past torque protocols over comparably long times. Particle velocimetry reveals rapid angular-momentum transport away from the probe, in contrast to the slow relaxation of stored torsional stress. A continuum shell model captures the observed recoil dynamics and the selective suppression of long-lived contributions under spatial confinement. Our results show that geometry can transform a material with simple intrinsic relaxation into a system with long-lived, space-dependent memory, suggesting a route to tune material dynamics through mechanical excitation rather than composition, with potential implications for microscopic mechanical memory elements.

Collective dynamics in dense cell monolayers are governed by the interplay between crowding and cellular motility. Although increasing density can slow cellular motion and promote glass-like behaviour, the dynamical state of dense HeLa monolayers remains unclear. Here, we combine in vitro time-lapse imaging of HeLa cell monolayers with simulations of a deformable active-cell model to examine how cell density and motility regulate collective relaxation. Within the experimentally accessible density and time ranges, untreated HeLa monolayers remain liquid-like: structural relaxation progressively slows down with increasing density but remains observable throughout the investigated range. Under low-nutrient conditions, cell motility is strongly reduced, and structural relaxation becomes substantially slower. To elucidate the mechanisms underlying these experimental observations, we further performed simulations using a deformable-cell model. The model qualitatively reproduces the density-dependent increase in structural relaxation time and further shows that reducing self-propulsion promotes long-lived caging dynamics at high packing fractions. These results show that dense HeLa monolayers can sustain slow, heterogeneous, yet relaxing collective dynamics under untreated conditions, and indicate that persistent cellular motility is an important factor in maintaining structural relaxation at high density, which may provide insight into the metastatic potential of cancer cells.

Active matter systems can generate mechanical stresses that deform their surroundings, providing a route to transport and shape dynamics far from equilibrium. Deformable vesicles containing active particles offer a minimal setting in which such active stresses are directly coupled to boundary mechanics. Here, we use numerical simulations to investigate a two-dimensional, fixed-area vesicle filled with chiral active particles interacting through excluded volume and polar alignment. We find that the coupling between particle chirality and vesicle deformation produces distinct modes of collective motion, including run-and-tumble-like migration, rotor-like dynamics, and persistent spinning. Most notably, we show that vesicle rotation is non-monotonic in chirality: at fixed activity, an optimal chirality maximizes the rotational velocity. We develop an analytical theory that relates the vesicle rotation to the effective torque generated by the chiral active particles. The theory identifies the competition underlying the optimal chirality and predicts a scale-invariant dependence of the rotational velocity on activity and chirality. This scaling collapses simulation results obtained over different activity strengths onto a universal curve. Our results establish a general mechanism by which chirality and collective alignment regulate the transmission of active stresses to deformable boundaries, providing a framework for understanding transport and rotational dynamics in confined active systems.

Active microrheology probes a crowded medium by forcing a tracer and measuring its response. In single-file transport, where particles cannot overtake, a constant force $F$ produces a subballistic displacement $\langle X_t\rangle\simeq \sqrt{t}\,\xi(F)$ together with a persistent bath deformation. Despite decades of work, the exact nonlinear response at arbitrary force has remained confined to a few special solvable models. Here we remove this restriction by combining recent advances in hydrodynamic transport coefficients, a pressure-balance formulation of the local drive, and single-file duality, which eliminates the resulting moving boundary. This yields a closed exact boundary-value problem for general diffusive single files, determining both $\xi(F)$ and the full density profile. For overdamped Brownian particles with general interactions, all microscopic interaction details enter only through the equilibrium equation of state, bringing realistic interacting systems, including finite-width quasi-one-dimensional channels, within exact reach. The solution also reveals universal global laws; in particular, the bath-density dipole is fixed by the applied force independently of the interaction potential.