Papers

Advances in polymer synthesis and computational modeling are expanding the block-copolymer architecture space accessible for phase-behavior design. Machine learning can accelerate this exploration, yet a common representation capable of learning across diverse chain topologies remains lacking. Here, we present a graph neural network (GNN) representation of acyclic AB multiblock architectures, tested by random-phase approximation (RPA) instability prediction. Each chain is represented as a graph, enabling a common model to learn across diverse topologies. This representation, which organizes RPA-related information, retains predictive capability when extrapolated to architectures with more blocks and demonstrates its potential for reuse across tasks through transfer to instability-wavenumber prediction. By effectively linking block-copolymer chain architecture to field-theoretic response, this graph representation not only reconstructs stability-limit curves but also provides a practical route for future self-consistent field theory exploration of ordered phase space across complex topologies.

Synthetic active surfaces are usually designed to attain a prescribed static configuration, with dynamic shape changes typically requiring modulation of the actuation. We show that thin active shells can instead sustain dynamic morphing under a steady stimulus by harnessing flutter instability. We focus on polyelectrolyte hydrogel shells immersed in a viscous fluid and subjected to a constant and uniform electric field, and specialize the non-Euclidean framework for thin structures to account for field-induced activity through a spontaneous curvature evolving in time with the system configuration. Examining elliptic plates and cylindrical shells as test cases, we integrate linear stability analyses with nonlinear simulations to first locate the onset of flutter and then unveil the resulting dynamics, characterized by thrust-generating shape changes. In all cases, the emergent behavior stems from the interplay between active reconfiguration and elasticity in the fluid environment. For plates, the problem is purely flexural in the linear regime, while the competition between bending and stretching becomes crucial in selecting the ensuing shapes and swimming trajectories at large deformations. Conversely, for cylindrical shells bending and stretching are coupled at all levels, with the latter becoming essential to sustain flutter. Experiments on millimeter-sized hydrogel plates provide tangible support for our theoretical findings through shape reconstructions performed by combining digital image correlation with optical stereo microscopy. Flutter thus offers a route to untethered soft robotic and microfluidic devices based on active shells and operating under a stimulus carrying neither an intrinsic frequency nor a characteristic length scale.

Crack-path instabilities in solids are typically associated with high propagation velocities. In contrast, we show that nanoparticle-filled elastomers exhibit a sideways crack-path instability that is amplified as the pulling velocity decreases and nearly vanishes at high pulling velocities. The sideways deviation amplitude decreases logarithmically with increasing pulling velocity and scales as the square root of the filler fraction. Large deviations develop at low mean crack velocities and are associated with effective fracture energies up to two orders of magnitude lower. These findings are consistent with subcritical rupture kinetics and suggest that the deviation amplitude is limited by the elasto-adhesive length.

Active flows are often confined by soft, deformable boundaries that they can push against, reshape, and in turn get reorganized by. Motivated by this interplay, we combine theory and numerical simulations to analyze the morphodynamics of an elastic vesicle enclosing a dilute suspension of extensile active particles. We model the two-dimensional vesicle as a weakly extensible elastic ring with bending rigidity, immersed in a Stokesian fluid, and describe the confined active suspension using a kinetic theory. The vesicle and the suspension are coupled hydrodynamically, through the kinematic and dynamic boundary conditions at the interface, and energetically, through a single alignment interaction that simultaneously aligns active particles with the membrane and the membrane with the particles. We show that this interaction reduces to a weak-anchoring boundary condition familiar from passive liquid crystals and derive a closed-form quiescent equilibrium state in which the nematic order in the suspension organizes into a vortex with a +1 defect core. A stability analysis of this state predicts an ordered hierarchy of activity thresholds at which successive shape modes of the vesicle are destabilized, as well as a purely passive, anchoring-driven instability of floppy vesicles. Nonlinear simulations, performed with a volume-conserving immersed boundary method, reveal that each threshold crossing gives rise to a distinct emergent state: a static spindle with boundary-pinned defects, a rotor that tank treads against its own rotation, a fluctuating spinner, and a turbulent state in which the vesicle acts as a self-stirring compartment. Beyond demonstrating how boundary deformability sculpts, and is sculpted by, confined active matter, our results open the door to study hydrodynamic interactions between such active vesicles and to use membrane fluctuations as a probe of activity of suspensions.

Medium-range order (MRO) is an important feature of amorphous materials, but its nature in terms of atomic arrangement has remained elusive. Here, using large-scale machine-learning-driven atomistic simulations of amorphous silicon, we probe the MRO of this archetypal network glass. By characterizing the structure in three dimensions, we reveal that the symmetry of the atomic arrangement around a central atom shows a crossover as a function of distance. At short distances, the structure is determined by local bonding constraints, which evolve from predominantly tetrahedral environments in low-density amorphous silicon to highly coordinated and strongly disordered local environments in very-high-density amorphous silicon. At larger distances, however, distinct cubic- and octahedral-symmetry patterns emerge in the three-dimensional atomic-density distribution, despite the absence of these symmetries at shorter length scales. We find that this crossover is accompanied by a quasi-periodic spatial organization of the topological rings in the structure. The characteristic spacing between ring centers matches the length scale of the first sharp diffraction peak (FSDP) in the structure factor, establishing a direct connection between this reciprocal-space signature of MRO and its real-space organization. These results demonstrate that the FSDP, the spatial correlation of the rings, and emergent orientational symmetries are not independent manifestations of MRO, but reflect different aspects of a common structural organization. Our findings provide a unified real-space picture of MRO in amorphous silicon and suggest that intermediate-range structural order in network glasses emerges from the interplay between local bonding constraints and extended atomic arrangements driven by efficient packing.

Binary active systems offer a minimal platform for understanding how component heterogeneity organizes non-equilibrium structures. Here we show that in a binary Quincke system driven by a periodic square-wave electric field, a dynamic square lattice in which small particles occupy the lattice-cell centers which are surrounded by large particles emerges spontaneously. Particle-resolved trajectories reveal that the size separation arises from the mobility difference of large particles and small particles. Increasing the driving frequency reduces the single-cycle path lengths of both species and simultaneously decreases the lattice constant. These results show how size-dependent activity,density redistribution, and periodic forcing cooperate to generate tunable complex active patterns.

Tangles of soft filaments are ubiquitous, from living worm blobs to the cables in a desk drawer. How do such tangles, held together by friction and entanglement, respond when one embedded filament is shaken? We suspend disordered tangles of tunable cohesion and ordered stitched meshes from a single thread (the tether) and oscillate it vertically at fixed amplitude. Extraction peaks at an intermediate drive frequency ($\sim 15$ Hz) and declines at higher frequencies, although the peak drive acceleration grows quadratically. Here we combine experiments, high-speed imaging, and a tension-only spring-mass model to show that this non-monotonic response is set by timing rather than resonance. The extraction window is bounded below by a slackening threshold, where the peak drive acceleration exceeds gravity and the tether, slack for part of each cycle, creates a tensile impulse each time it snaps taut. The window is bounded above by a transmission crossover, where the transmission time across the tangle exceeds a quarter of the drive cycle, so that the tangle no longer responds as a whole and the drive's work dissipates internally. The slackening threshold depends only on the drive and gravity, while the transmission crossover is set only by the tangle's size and transmission speed. By tracing extraction to the overlap of impulse creation and impulse transmission, we identify a generic principle of driven filamentous matter and suggest frequency-selective routes to its disassembly.

Materials usually remember their past through dissipative changes of structure or through a net order. Simulations of caged colloidal ellipsoids at a fluid interface reveal a purely orientational memory. The particles stay in place, the layer has no net alignment, and a pattern written by a field is retained by capillary interactions between neighbors. It lasts hundreds of times longer than a particle takes to reorient, while every particle keeps rotating. The layer also remembers sequence: when two strong fields act one after the other on the same particles, it records which came last.

When a long liquid drop is confined in a Hele-Shaw cell, the pull of surface tension produces a rapid retraction of its tip, causing it to bulge out as it draws up the excess liquid. Using numerical simulations, we demonstrate that this retraction is self-similar at long times, with the speed of retraction slowing like $t^{-1/2}$, where $t$ is the duration of retraction. After showing how this scaling can be understood using force and mass balance, we perform an asymptotic analysis of the Hele-Shaw equations to derive both the shape of the retracting drop, as well as prefactors of the scaling laws. Excellent agreement is found between our simulations and theory, and the experimental consequences are pointed out.

Rare events, such as crystal nucleation in mildly supercooled liquids, are characterized by waiting times that can be much longer than the timescale of the underlying microscopic dynamics. The mean first-passage time (MFPT) formalism [J. Wedekind and D. Reguera, J. Phys. Chem. B 112, 11060 (2008)] provides a route to reconstruct one-dimensional free-energy profiles from the MFPT and steady-state distribution measured along a reaction coordinate, but conventional implementations become inefficient for sufficiently high barriers because spontaneous crossings are rarely observed. We introduce a "top-start" extension that initiates trajectories near the barrier top and reconstructs the free-energy profile from their subsequent evolution away from the barrier toward lower-free-energy regions. We establish the equivalence between the top-start and two-region constructions using a Markov-chain transition-matrix formulation. We validate the method using one-dimensional random-walk simulations across low, medium, and high free-energy barriers, with transition-matrix calculations providing an exact benchmark for the corresponding discretized models. The top-start reconstruction remains accurate in the high-barrier regime where conventional MFPT sampling becomes prohibitively inefficient.

Understanding why 2D materials remain suspended in solutions is essential to understanding the mechanisms of aggregation and exfoliation. These dynamics have been difficult to model because of the long timescales and large activation energies involved in these simulations. Here we describe an improved strategy for modelling the solvation and stability of 2D materials that uses the Gibbs free energy of solvation to accurately calibrate two disconnected potential energy surfaces for the fully desolvated and fully solvated 2D materials. By joining these surfaces using solvation energy, we obtain predictions for 2D material stability in various solvents that are qualitatively different than prior simulations and that have excellent agreement with experimental results. Our approach predicts a much higher barrier to full desolvation of the material, suggesting that materials that appear to be aggregated in fact still retain monolayers of solvent between adjacent layers of 2D materials. This work provides much needed understanding on the interactions between the solvent and 2D material that can guide future experimental work.

We examine how the Curie–Weiss cell fluid model can be quantitatively related to real fluids by determining its microscopic parameters from experimental critical-point data for water, carbon dioxide, and three polyol ester lubricants (POE5, POE7, and POE9). The microscopic parameters of the model are determined from the experimental values of the critical temperature and critical density: the global attraction coupling constant is fixed by the critical temperature, and the cell volume by the critical density. The critical pressure then follows as an independent model prediction, deviating from experimental values by 10–41$\%$ across the studied substances. Varying the ratio of local repulsion to global attraction $f=J_2/J_1$ over a wide range has only a weak effect on this deviation. For $f\geq1$, the model's critical compressibility factor lays within a narrow range $Z_c\approx0.382-0.386$, remaining close to the mean-field van der Waals value $Z_c=3/8=0.375$ and consistently overestimating experimental values. The best agreement with experiment is obtained for the polyol ester lubricants and improves along the POE5–POE7–POE9 series with increasing molar mass, suggesting that multiple-occupancy cell fluid models are well suited to systems of large molecules, particularly soft-matter systems with bounded interaction potentials. We further show that generalizing the model by introducing a temperature- and phase-dependent effective attraction allows it to describe a triple point and to reproduce the broad range of critical-to-triple temperature ratios $T_c/T_{\mathrm{tr}}$ characteristic of real fluids.

Living supramolecular materials such as microtubules and actin filaments assemble and function in dynamic, heterogeneous environments, subject to chemical concentration gradients. Their rapid and precise response to such gradients—via aggregation, disassembly, or autonomous motion—underlies the fine spatiotemporal control typical of living systems. Reproducing such responsiveness in synthetic materials is a central challenge in materials science and requires a molecular-level understanding of how gradients couple to supramolecular structure and dynamics, which remains difficult to access experimentally. To this end, we combine implicit-solvent coarse-grained molecular dynamics (MD) with the constant chemical potential MD (C${\mu}$MD) technique to investigate, at molecular resolution, the coupling of two prototypical supramolecular polymer models with externally imposed ionic concentration gradients. Despite their contrasting responses to homogeneous ionic conditions, both systems undergo pronounced spatial reorganization under the gradient, generating regions of locally enhanced supramolecular activity that are inaccessible to homogeneous systems with the same overall content of self-assembling species. Crucially, the local supramolecular dynamics is largely determined by the local concentrations, consistent with the formation of local quasi-equilibria: this direct connection between spatial composition and supramolecular activity emerges as a common governing principle across the two models. These findings shed light on the spatially complex supramolecular response that can be triggered by chemical gradients, and show how a single gradient simulation can encode this response across a continuous range of local chemical environments, thus providing a general strategy to investigate and design materials operating under spatially heterogeneous conditions.

Liquid marbles interface is composed by a dense network of grains trapped by capillarity at their surface. The mix of capillarity and granular character make their interfaces remarkable, allowing non wetting, high mobility and strong robustness which are a basis for numerous applications. A canonical experiment showing out of equilibrium nature of granular material is the so called tapping experiment, where a dry granular medium under vertical vibration reorganize an evolve toward a denser final state function of the vibration amplitude In this paper we explore the out of equilibrium nature of densely covered liquid marbles by measuring their shape, compaction and stresses evolution under vertical vibration. We show that liquid marble do indeed reorganize when submitted to taps, leading to higher internal pressure and lower effective surface tension.

Cavitation influences the failure of elastomers and soft adhesives, but connecting its microscopic initiation to subsequent cavity growth remains challenging. Here, we develop a discrete mesoscale framework that combines finitely extensible, breakable strands with local van der Waals interactions to examine how cohesion and network heterogeneity transform distributed dilation into localized damage. In the simulations, local cohesive instability produces a network-scale precursor whose subsequent expansion is coupled to strand stretching and rupture. Cohesive strength and intrinsic defect size govern the critical hydrostatic tension, while cohesion also controls the number and spatial distribution of cavities. Under confined loading, decreasing the layer thickness promotes multiple cavities and distributed strand rupture, extending the load-bearing response and increasing the critical work density of rupture. An energetic interpretation based on the thickness dependence of the crack-driving force connects these observations to competition between additional cavity nucleation and propagation of existing damage. The results link local cohesive instability to the collective evolution of cavities and rupture in disordered polymer networks.

By modulating the orientation of a uniform magnetic field it is possible to transport magnetic microparticles above magnetic patterns. In periodic patterns, driving control loops that wind around special orientations, which are dictated by the symmetry of the pattern, induce transport by one unit cell. The transport is topologically protected with trajectories controlled by the winding numbers of the control loop around the special orientations. In non-periodic patterns, the special orientations are position dependent, precluding a global characterization of the transport using a small set of winding numbers. We use here a reinforcement learning agent trained with Brownian dynamics simulation data that uses the local environment of the magnetic pattern to decide an action over the control loop. The agent autonomously discovers topological transport protocols directly from the particle response without prior characterization of the magnetic potential landscape. An agent trained solely on a complex non-periodic pattern directly generalizes to completely unseen periodic, quasicrystalline, and disordered substrates. Moreover, the agent dynamically adjusts the control loop to transport particles across lattice defects and to counterbalance external drift forces that would cause static topological loops to fail. By adding a pathfinding algorithm to the model, we additionally achieve simultaneous, independent transport of multiple identical colloids along different on demand trajectories. We demonstrate that the control loops can be directly transferred to an experimental setup to successfully drive magnetic microparticles across a non-uniform magnetic thin film.

We investigate how the translational motion of a compact skyrmion cluster can be converted into collective rotation through interactions with a periodic obstacle substrate. Using an effective particle model, we consider a seven-skyrmion cluster driven along a one-dimensional array of repulsive obstacle sites. For suitable obstacle spacings and interaction strengths, repeated interactions with the substrate produce coherent clockwise or counterclockwise rotation, giving rise to gear-like cluster dynamics. We characterize these states using the translational velocity, Hall angle, angular velocity, structural deformation, and a dimensionless gear ratio that relates cluster rotation to motion over the substrate periodicity. Dynamical phase diagrams identify rotating, nonrotating, wall-guided, transverse, and deformed regimes. We further show that coherent rotation persists in the overdamped limit, demonstrating that the conversion mechanism does not require an intrinsic Magnus force and may therefore extend to other driven cluster systems, including colloidal assemblies. These results provide a simple route for controlling collective rotation through structured substrates.

The nearly collinear configuration of highly stretched polymer chains before fracture motivates one-dimensional models. At fixed extension, stretching one bond redistributes length among the others, coupling rupture to the whole chain. In this work, I develop a framework for fracture-healing rates in periodic Morse chains, combining deterministic theories, equilibrium simulations and a quasi-deterministic approach using equilibrium fluxes and barrier-top trajectories. Constrained-partition calculations closely reproduce simulated populations and intact-state tensions. An intact-reservoir potential of mean force (PMF) supplies the first-fracture surface probability, while recrossing corrects the attempt flux without a rate-fitted prefactor. Independent rate tests identify an operational chain-length boundary for accurate two-state kinetics; failed-return durations decrease relative to population relaxation as chains grow. Kramers-Grote-Hynes (KGH), nonlinear reactive-flux and equilibrium rates show excellent agreement in this regime. KGH predicts rates away from coexistence and a chain-dependent local activation length dominated by the barrier response. Rates decrease approximately exponentially before declining more gently for longer chains: barrier growth dominates, additional fracture sites partly compensate, and transmission varies more weakly. Beyond coexistence, long chains can fracture practically irreversibly because healing becomes too rare to observe. Projected committor crossings, where the configuration-averaged probability of reaching the fractured core first is one half, lie near site-PMF maxima, although configurations at equal bond length retain different fracture probabilities. Multiple fractures remain negligible near coexistence through at least $N=50$. The framework could supply state-dependent rates to mesoscopic fracture models of polymer networks.

We study the spontaneous motion and collective dynamics of self-phoretic particles on a one-dimensional periodic domain. The particles act as localized chemical sources (of a particle-dependent strength) of a field and the particles themselves respond to the gradients of the field they generate (with a particle-dependent phoretic mobility). The chemical field itself diffuses and evaporates. For a single particle, we derive the exact threshold for spontaneous propulsion and establish the emergence of stable constant-velocity states near onset through a supercritical pitchfork bifurcation. We then consider an active source coupled to a non-emitting tracer and determine the conditions for slipping and stable phase-locked motion. For two mutually coupled sources, the stationary antipodal configuration can lose stability through either a pitchfork or a Hopf bifurcation, depending on the relative source strengths and phoretic mobilities. We determine the competing instability thresholds and compare them with direct numerical simulations of the coupled particle-field equations. Beyond onset, the resulting translating and oscillatory states provide qualitative counterparts to modes of motion observed experimentally for camphor disks in annular water channels. These results connect the onset of individual propulsion, tracer entrainment, and collective motion within a common analytically tractable framework.

In artificial (micro)capsules or cells such as red blood cells for example, the two-dimensional (2D) rheology of the membrane (or the shell) is viscoelastic and not only elastic. The deformation and inclination of such a capsule are theoretically studied under shear and extensional flows. The membrane mechanics is described by the Kelvin-Voigt model: the 2D dissipation with the Boussinesq-Scriven law associated to specific dilational and shear Boussinesq numbers $Bq_d$ and $Bq_d$ respectively while the elastic constitutive law is either Hookean, strain-softening (neoHookean) or strain-hardening (Skalak). The dynamics depends on the elastic capillary number $Ca$, the Poisson ratio (or $C$ in Skalak law), the viscosity ratio $\lambda$, the nonlinearities included in the constitutive law and both boussinesq numbers. Three dynamics are identified in the limit of weak deformations: a tank-treading motion in the limit of small elastic capillary number with a characteristic time depending on $\lambda$, $Bq_s$ and $Bq_d$, an oscillation without any elasticity and a damped oscillation leading to a tank-treading motion in the limit of large Boussinesq numbers. In all cases, both shear and dilational 2D dissipations contribute differently leading to non-trivial results. In the case of a Skalak law with $C=1$, $Bq=Bq_s=Bq_d$ and $Bq>>\lambda$, the deformations in the limits $Ca<<1$, $Bq=O(1)$ and $Ca=O(1)$, $Bq>>1$ determined in the seminal work of \cite{barthes1985role} are recovered.

Colloidal suspensions that are confined between two closely spaced plates and left to evaporate slowly form maze-like labyrinth patterns in the final stage of evaporation. The fingers in these patterns form bifurcations and occasionally loops, which we may quantify with a skeletonization method. We compare drying patterns formed with two different salt concentrations in the droplet which changes the screening length and therefore the effective colloid interactions. We find that the junctions generally follow Murray's law for optimal transport networks, and that the typical bifurcation angles peak around 53. Screened droplets additionally show more loopy networks, and is characterized by bands of transversal fingers before merging into a central non-fingering colloidal aggregate. Our observations suggest that colloid-colloid interactions can strongly influence the large-scale topology of the pattern while leaving the local geometry of the individual fingers unchanged.

Poorly soluble species can have mean populations below one in small systems such as nanopores. In this regime, the grand-potential minimum, which identifies the most probable particle number, differs from the ensemble-averaged solute loading. We use grand-canonical Wang-Landau sampling (GCWLS) to calculate the density of states $\Omega(N_\mathrm{A}, N_\mathrm{B})$ for a binary Lennard-Jones mixture of solute B in solvent A, both in bulk and in slit pores. One set of GCWLS simulations gives ensemble averages over a range of chemical potentials, whereas conventional grand-canonical Monte Carlo (GCMC) simulation requires a separate simulation at each state point. Independent GCMC simulations confirm the GCWLS ensemble averages. The solvent number distribution is nearly Gaussian, whereas the dilute solute distribution is skewed and Poisson-like. The most probable solute number therefore lies below the ensemble-averaged loading $\langle N_\mathrm{B}\rangle$ and is zero whenever $\langle N_\mathrm{B}\rangle<1$. Reading the solute loading from the grand-potential minimum underestimates it and can falsely indicate that no solute is present. Defining the oversolubility as $\mathcal{O}_\mathrm{B}=x_\mathrm{B}^{\mathrm{conf}}/x_\mathrm{B}^{\mathrm{bulk}}$, where $x_\mathrm{B}$ is the solute mole fraction, we find $\mathcal{O}_\mathrm{B}\approx12$ in a pore of 3.5 particle diameters width when both wall interactions are repulsive. Adding wall-solute attraction moderately raises it to $\approx13$, whereas wall-solvent attraction lowers it to $\approx3.4$. This comparison shows that the wall-solvent interaction controls most of the enhancement. As the pore widens, $\mathcal{O}_\mathrm{B}$ decreases toward unity. In bulk and in nanopores alike, the solubility of poorly soluble species should be obtained from ensemble averages rather than from grand-potential minima.

Active gels are intrinsically non-equilibrium materials whose structural and dynamical heterogeneity emerges from the interplay of attractive interactions, thermal fluctuations, and self-propulsion. We investigate a model active gel, simulated using large-scale Brownian dynamics simulations, to explore the effects of temperature $T$, active force strength $f_0$, persistence timescale $\tau_p$, and active particle concentration $\rho_a$. We characterize the structure of the evolving gel network through morphological analysis, while dynamical changes are quantified by the relaxation timescale and dynamical heterogeneity (DH). We show that an optimal choice of activity parameters yields a percolating gel network with faster gelation and larger voids and clusters, enhancing mechanical stability. Conversely, the structural relaxation timescale and DH decrease with increasing activity, indicating enhanced particle rearrangements and reduced spatial correlations of mobile and immobile regions. An effective temperature ($T_\text{eff}$) framework for colloidal gels maps structural quantities and relaxation timescales in an active gel onto those of a passive gel. More interestingly, the growth of DH with increasing swim force can also be described by the same effective-temperature framework, in stark contrast to observations in active glasses. Our findings show that, in colloidal gels, temperature and active force compete, giving rise to similar structural ordering and, consequently, similar DH at the same $T_\text{eff}$. These findings highlight the crucial role of structural ordering in governing DH in active colloidal gels, as compared to active glasses.

The yielding of amorphous solids has been extensively studied in the athermal limit, but the influence of thermal fluctuations is much less understood, in particular for glasses of different stability. Using molecular dynamics simulations of a model glass where the swap Monte Carlo algorithm can be employed, we study the yield stress at finite temperature and shear rate, both in steady flow and at shear start-up, over a broad range of glass stability. Thermal fluctuations soften both the dynamic yield stress in steady state and the start-up yield stress. In all cases, the temperature dependence is compatible with the $T^{2/3}$ law expected for thermally activated yielding near a saddle-node instability, with no systematic dependence of the exponent on stability or shear rate. Extrapolations to zero temperature recover the athermal yield stresses. The amplitude of the softening at start-up, by contrast, depends strongly on stability: highly stable glasses are much less sensitive to temperature than poorly annealed ones. A description of yielding at finite temperature must therefore account explicitly for the stability of the glass.

We formulate a Derjaguin-corrected Kelvin equation for phase transitions in finite open slits. In such pores, capillary condensation is modified by the finite wall length because the condensed phase is bounded by two terminal menisci pinned at the slit ends. Starting from the macroscopic generalized Kelvin equation, we introduce a scaling approximation which replaces the implicit edge-contact-angle condition by a closed analytic expression while preserving the exact limiting behaviours. We then incorporate mesoscopic wetting-layer contributions into the finite-slit free-energy balance. The single-wall contribution naturally separates into a planar Derjaguin term and a residual finite-length correction controlled by the competition between the wall length $H$ and the parallel correlation length $\xi_\parallel$. The resulting equation reduces to the standard Derjaguin-Kelvin equation for infinitely long slits and to the macroscopic finite-slit Kelvin equation when adsorbed layers are absent. Explicit forms are derived for long-ranged dispersion forces and for short-ranged forces. The theory is tested using classical density functional theory for finite slits with attractive Lennard-Jones walls and hard walls, corresponding respectively to capillary condensation and its drying analogue, capillary evaporation. The Derjaguin-corrected theory substantially improves on the purely macroscopic prediction, capturing both the correct infinite-slit limit and the observed dependence on wall length. For the short-ranged hard-wall system, the agreement with DFT remains nearly quantitative even for very narrow slits.

Adaptive search and travel strategies enable biological swimmers to explore complex environments, but remain difficult to encode in minimal synthetic microswimmers. Here, we unveil multiple dynamical and orientational states of rod-like Janus microswimmers actuated via electric fields: planar active, oriented chiral and persistent rods. We discover a hidden dynamical state after pre-orienting them, which allows us to switch on demand from strong chiral to persistent motion. We harness this phenomenological orientation and chirality switch for exploration in microstructured porous arrays. Here, strong chirality promotes local scanning but drives circular trapping and poor net displacement, whereas the pre-aligned dynamical state enables efficient obstacle sorting, and trap escape. Comparing experiments with simulations of active Brownian particles in the very same experimentally-extracted obstacle geometries, we quantify navigation efficiency via first-passage time statistics, revealing how chirality tuning optimizes the trade-off between local exploration and long-range transport.

Originally coined 100 years ago to represent a shear-reversible sol-gel transition, the range of the term "thixotropy" has gradually expanded to encompass time-dependent changes in viscosity. Since this risks confusing "thixotropy" with ordinary nonlinear viscoelastic behavior, in this work we seek simple, historically faithful, quantifiable, and experimentally testable definitions of "thixotropy" that avoid this confusion. By analysing both historical tradition and published experimental data, we arrive at three complementary definitions. Definition 0 provides an idealized, purely inelastic reference useful primarily for recognizing thixotropy in a constitutive equation. Definitions 1 and 2, which are more practical, require, respectively, unusually large strains to reach steady state, and unbounded growth of the material relaxation time during rest. Definition 1 can apply in either shear-rate or stress-controlled modes, with the latter encompassing the so-called "viscosity bifurcation." These criteria are tested across diverse materials that we identify as thixotropic based on their responses clearly exceeding their viscoelastic reference scales. The framework is deliberately phenomenological and does not require specific microscopic mechanisms, allowing diverse materials to be described within a common rheological language, as is typical for rheological terminology. We believe that these definitions provide a practical framework for assigning thixotropy a more definite place in rheological taxonomy.

Active matter systems composed of self-propelled entities exhibit a wide range of out-of-equilibrium phase behaviors and collective dynamics. Assemblies of active particles, e.g., in a linear structure, are particularly interesting, as they exhibit an intriguing interplay between activity and geometrical restrictions due to self-avoidance and entanglements. Using Langevin dynamics simulations of an active Brownian ring polymer with translational and rotational inertia, we uncover an inertia-driven re-entrant coil-globule transition in the absence of any attractive interactions. We show that rotational inertia plays a paramount role, leading, in the globular state, to spontaneous, nonzero, radially outward polarization of the active forces. Self-avoidance and entanglements break the rotational symmetry of active beads and effectively stabilize the globular states. The transition becomes increasingly sharp with increasing rotational inertia, yielding highly compact globular conformations at intermediate activities, whereas at high activity the polymer re-expands into a coil state. Scaling of the radius of gyration reveals crossovers from self-avoiding, phantom-like to compact-globular structures. Further, rotational inertia enhances transport properties, with an intermediate activity-induced Rouse-type bead diffusion and a long-time diffusion coefficient displaying a power-law dependence on the moment of inertia. Our study establishes a purely inertia-induced mechanism for controlling the collapse of active polymers, arising from spontaneous active-force polarization and self-avoidance.

Swap Monte Carlo dramatically accelerates the equilibration of deeply supercooled liquids while preserving the equilibrium Boltzmann distribution. Recent work has argued that swap and other accelerated algorithms act by reparameterizing time: different dynamics follow the same slow relaxation process, but with different clocks. Here we test this idea in a continuously polydisperse glass former. We confirm that mean collective overlaps satisfy an approximate time reparameterization, in agreement with earlier results. However, the associated clock depends systematically on the collective probe length and on the relaxation stage. Thus the observed collective collapse does not define a unique, observable-independent material time. Over the numerically accessible $\alpha$-relaxation regime, swap changes not only the rate of relaxation, but also its length-scale dependence. The resulting collective reparameterization is therefore only approximate and does not establish an exact dynamical equivalence between swap and reference relaxation.

Models of curvature-driven membrane sorting couple composition directly to membrane bending elasticity. Here we show that shape deformations can destabilize a homogeneous state without this composition-dependent mechanical coupling. We analyze the eigenspectrum of the Laplace-Beltrami operator on deformed spheres analytically, and verify it numerically. As the deformation amplitude increases, the spectral degeneracy breaks, and the lowest nonzero eigenvalue decreases substantially. Using Cahn-Hilliard dynamics, we show that this eigenvalue softening provides a purely geometric route to phase separation.