Papers

Tissues are active composites in which multicellular collectives and extracellular matrices mechanically reorganize one another. We develop a three-dimensional micromechanical model that couples deformable, rearranging cell clusters to a disordered network of semiflexible fibers through a dynamic, force-generating interface. Cell clusters are represented as solid-like or fluid-like vertex-model spheroids and coupled to the matrix by passive or contractile linkers renewed as the cluster boundary reorganizes. Matched intact, voided, and passive-linker controls separate cavity formation, interfacial tethering, and active loading. At small strain, passive tethering provides modest reinforcement, whereas active contraction prestresses and strongly stiffens the matrix. Solid-like clusters preserve coherent force transmission and exhibit an excess modulus scaling approximately as $|\sigma|^{1.4}$ across changes in activity, cluster size, and cluster number. Fluid-like clusters undergo greater interfacial renewal, producing weaker and nonmonotonic coupling between prestress and stiffness. Increasing cluster number produces collective stiffening when prestressed regions become connected through sufficiently persistent interfaces. At large strain, both solid-like and fluid-like systems approach the corresponding voided-network response as the residual fiber backbone becomes mechanically dominant. Thus, cell-generated prestress controls macroscopic stiffness only together with the organization and persistence of its transmission across the cell-matrix interface.

We study search processes in a complex environment using the strategy of stochastic resetting. A common occurrence in these environments is targets with finite reactivity. Stochastic resetting has emerged as a powerful mechanism for optimizing search processes by curtailing long, unproductive excursions inherent to diffusive dynamics. Most theoretical studies, however, assume perfectly absorbing targets – an idealization that overlooks the finite reactivity commonly encountered in realistic chemical and biological systems. In this work, we investigate the interplay between stochastic resetting and finite-target reactivity in reaction - diffusion processes. Considering a one-dimensional system with multiple reactive targets, we demonstrated that the target reactivity modifies the optimization landscape. We uncover distinct regimes in which resetting enhances transport efficiency towards specific targets based on their chemical kinetics. As a consequence, the optimal resetting rate becomes intrinsically reactivity dependent. Our results identify target reactivity as a crucial control parameter governing stochastic transport and provide insights into reaction-diffusion processes in complex media.

We identify the slowest-decaying nonequilibrium perturbations near the three-dimensional conserved Ising critical point and determine their impact on finite-size observables. We study two classes of perturbations: a field-dependent noise-to-mobility ratio $\Theta(\phi)=D(\phi)/M(\phi)$ and the gradient activity of Active Model B+. Starting from the Martin-Siggia-Rose-Janssen-De Dominicis action, we compute the linearized flow using the functional renormalization group. The transport sector is block triangular, with leading odd eigenvalue $y_{\Theta_1}=-\Delta_\phi$, where $\Delta_\phi=(d-2+\eta)/2$. In the gradient sector, removing the detailed-balance direction leaves two genuinely nonequilibrium modes, chemical and current-like. Two smooth regulators give $y_{\Theta_1}\simeq-0.52$, $y_J\simeq-0.56$, and $y_{\rm ch}\simeq-0.89$. A translation Ward identity expresses the current operator as the divergence of the stress tensor. Together with conservation and Itô causality, this forbids chemical operators from generating the current mode, making the nonequilibrium stability matrix triangular; an independent two-loop calculation in $d=4-\varepsilon$ finds no additional current contact counterterm. Within the FRG truncation, $y_J-y_{\Theta_1}=-\eta$; beyond it, this relation requires the absence of an additional contact anomaly. Using the 3D Ising value $\eta=0.0362978(20)$ [Kos et al., 2016] gives $y_{\Theta_1}\simeq-0.5181$ and $y_J\simeq-0.5544$. Because these exponents nearly coincide, single-power fits yield amplitude-dependent apparent exponents and crossover lengths may exceed accessible system sizes. We derive the resulting finite-size scaling rules: odd block observables respond linearly to activity, while even observables receive only quadratic corrections.

Motile microorganisms often navigate crowded and structurally complex environments, where surrounding obstacles can strongly influence locomotion. The bloodstream form of the flagellate parasite Trypanosoma brucei circulates in blood, a dense suspension of red blood cells (RBCs), yet the physical mechanisms governing its locomotion under such conditions remain poorly understood because direct experimental observations are challenging. Here, we combine numerical simulations with in vitro experiments to investigate trypanosome motility in concentrated RBC suspensions and in suspensions of spherical colloidal particles. Simulations reveal that the parasite swimming speed increases by up to $50\%$ at RBC volume fractions comparable to those in blood. To identify the origin of this enhancement, we perform controlled studies in colloidal suspensions with particles of different sizes. We find that suspended particles substantially increase the anisotropy between the perpendicular and parallel friction coefficients acting on the beating flagellum, thereby enhancing propulsion. This effect is most pronounced when the suspended particles are comparable to or smaller than the characteristic wavelength of the flagellar beat. Experiments with microparticle suspensions confirm an increase in trypanosome propulsion with increasing particle concentration, in qualitative agreement with the simulations. Our results uncover a general physical mechanism by which concentrated particle suspensions can enhance flagellar-beat-driven locomotion and suggest that the densely crowded, particulate environment of blood may facilitate trypanosome propulsion. These findings provide new insight into trypanosome motility in the bloodstream and may apply broadly to other flagellated microswimmers in complex suspensions.

Understanding how individual protection and population density influence epidemic spreading remains a central challenge in epidemiology. While classical compartmental models successfully describe the temporal evolution of epidemics, they do not explicitly account for the microscopic motion and spatial organisation of individuals. Here, we investigate contagion dynamics using an agent-based model of Active Brownian Particles (ABPs), where self-propelled agents interact through local contact and a prescribed fraction of the population is protected. By systematically varying the protected-agent fraction and the population density, we identify two distinct contagion regimes separated by a crossover protection of approximately $30\%$. Below this threshold, the maximum contagion rate follows the universal scaling $\nu_{\mathrm{max}}\propto\phi^{1/2}$, indicating that disease transmission is governed primarily by frequency of encounters. Above the threshold, universal scaling is lost and protection becomes the dominant mechanism controlling epidemic spreading, with the strongest suppression occurring in low-density populations. These results demonstrate that microscopic active-matter models provide a powerful framework for investigating epidemic dynamics beyond the assumptions of well-mixed population models and reveal how spatial organisation and individual protection jointly determine contagion dynamics.

The physical mechanisms controlling the onset of gravity-driven spreading of elastoviscoplastic drops remain unclear because yielding, elastic deformation, and viscous dissipation can occur simultaneously in different regions of the material. To isolate these mechanisms, we perform direct numerical simulations of large axisymmetric drops resting on a thin precursor layer of the same material. Each drop is first equilibrated under gravity, $g$, before being subjected to an additional constant downward acceleration of varying magnitude. The drop rheology is described by the Saramito–Herschel–Bulkley model. Once the rate of deformation becomes negligible under the enhanced forcing, the additional acceleration is removed and the drop is allowed to relax again under gravity alone, enabling the global deformation to be separated into recoverable and unrecoverable components. We find that spreading does not occur simply because some portion of the material yields locally. At low imposed accelerations, yielded regions remain confined within a predominantly solid-like viscoelastic matrix, and the resulting deformation is mostly recoverable. Appreciable spreading is observed when these yielded regions connect to form a continuous fluidised pathway from the drop interior to the free surface, allowing radial material transport. The acceleration required for this transition is governed primarily by the yield stress, whereas elasticity controls the partition between recoverable deformation and spreading by regulating the extent and spatial distribution of yielded regions.

Information engines convert information into extractable work through measurements and feedback. We realize an engine that employs information to compress a gas of self-propelled bristle bots. Its work per measurement, $\bar{W}$, is controlled by the size of the detection region $\Delta x$ and the probability $p_1$ that this region is vacant. In thermal systems, $\bar{W}$ follows the universal form $-p_1 \ln p_1$, whereas the active engine shows a qualitatively modified relation. As particle density increases, the maximum of $\bar{W}(\Delta x)$ switches between two distinct operating regimes. Notably, this transition is also found in the solutions that maximize power output for finite-time cycles with dynamics affected by dry friction. We attribute this nonequilibrium feature to the accumulation of active particles near the boundaries.

Odd viscosity is a nondissipative component of the viscosity tensor that arises in fluids with broken time-reversal symmetry. Despite conserving energy, we show that odd viscosity can qualitatively alter hydrodynamic stability by generating exponentially growing modes that are absent in conventional fluids. For plane Poiseuille flow, we derive the odd-viscous generalization of the Orr–Sommerfeld–Squire equations and find a new instability that first emerges for spanwise perturbations and extends to oblique modes through the amplification of odd-viscous forces in critical layers. The instability originates from the non-normal dynamics of shear flows: conventional fluids support transiently growing disturbances through the lift-up mechanism, while odd viscosity provides a feedback between wall-normal velocity and vorticity that converts this transient growth into a self-sustaining exponentially growing mode. More generally, we show that an energy-conserving perturbation can destabilize a non-normal dynamical system only when the unperturbed system supports transient growth. Our results establish a direct connection between transient growth, non-normality, and instability induced by nondissipative forces, with implications extending beyond odd-viscous hydrodynamics.

Asymmetric cell division – in which a mother cell divides into two daughter cells of unequal size – is a fundamental problem in biology. It is believed that the asymmetry originates from the prior polarization of the mother cell. Here we show that division asymmetry can occur spontaneously even in unpolarized mother cells. Specifically, curvature-dependent active stresses in the cell cortex can lead to this symmetry breaking without any molecular polarity cue if the mother cell is confined within a restricted space. Either reducing the cell size or tightening mechanical confinement triggers the same spontaneous symmetry-breaking instability, in which the contractile ring slips off the equator to yield daughters of unequal volume. In the presence of a polarity cue, this instability cooperates with the cue to program the division asymmetry. The model prediction is compared with the imaging data of C. elegans embryogenesis, in which successive cell divisions in a confined eggshell lead to smaller and smaller cell sizes. The measured division asymmetry indeed increases as the cells shrink, and is further amplified when the embryo is mechanically compressed, both in agreement with the model prediction.

We experimentally investigate the dynamics of a spherical intruder driven horizontally at a constant force in a granular medium subjected to a localized surface overload. While intruder motion beneath a free surface exhibits constant acceleration in the quasistatic regime, the presence of a surface load induces a pronounced transient deceleration when the intruder passes below the loaded region. The magnitude of this deceleration increases with the applied overload and saturates at large overloads, while it decreases with intruder depth. Introducing a characteristic timescale and an overload-based Froude number, we show that the deceleration dynamics collapse onto master curves. We further develop a model incorporating stress transmission from the surface, which partially captures the intruder deceleration. In this approach, this deceleration is shown to depend on two parameters: the overload and the area on which this overload is applied. These results provide a framework to quantify how localized surface stresses influence subsurface intruder dynamics, with implications for locomotion, root growth, and underground transport in granular media.

We study linear instabilities and pattern formation in a spatially extended Selkov model for glycolysis with diffusion and chemotactic interactions between two species. Linear stability analysis reveals two distinct bifurcations: a zero-wavevector, finite-frequency Hopf bifurcation leading to spatially homogeneous oscillations, and a finite-wavevector Turing instability with a saddle-node bifurcation leading to stationary inhomogeneous patterns. The selected wavevector, $k_c$, depends sensitively on the nature and strength of chemotaxis and varies nonmonotonically with the chemotaxis parameters, allowing re-entrant transitions between homogeneous and patterned states. For sufficiently strong chemotaxis, when the two species mutually attract or mutually repel each other, an unusual instability emerges in which the preferred wavevector diverges as a finite threshold in chemotactic strength is approached. We complement the linear analysis with extensive direct numerical simulations (DNS) of the nonlinear partial differential equations in two dimensions. The DNS confirm the predicted instabilities and their nonmonotonic and re-entrant character, and also reveal spatially uniform oscillatory states for suitable parameters. The stationary patterns include spots and, unexpectedly, stable stripes. We further uncover transitions between spot and stripe morphologies controlled by chemotactic strength and diffusivity ratios. The stability of the striped states is consistent with linear amplitude equations, whereas the spot-stripe transition is attributed to nonlinear effects beyond linear stability. Our results demonstrate that chemotaxis can act as a nonmonotonic control parameter for instability selection, wavelength selection, re-entrant pattern formation, and nonlinear pattern morphology in reaction-diffusion systems.

We investigate pattern formation in generic two-species reaction-diffusion systems with mutual chemotaxis. We show that tuning the chemotaxis strength can give rise to striking nonmonotonic variation of patterns, opening the possibility of re-entrant transitions between patterned and spatially uniform steady states. In certain regimes, chemotaxis also induces additional heretofore unexplored instabilities. Furthermore, varying the strength of chemotaxis can drive morphological transitions between spot and stripe patterns.

Polymer gelation involves the emergence of a system-spanning network from growing polymer-rich domains, yet conventional percolation models typically prescribe particle size independently of material consumption. We formulate gelation as a locally mass-conserving growth-percolation process in which Voronoi capture zones define finite material reservoirs for individual nuclei. Local depletion determines the evolving supersaturation and limiting particle size, while particle contacts generate a dynamic network whose first spanning cluster defines the gel point. Three mechanisms, namely, interface-, diffusion-, and polymer-blob-controlled growth produce distinct gelation kinetics while sharing the same accessible final state. Spatial fluctuations in nucleation further generate a distribution of gelation times. The framework separates gelation from saturation and naturally captures post-gel aging as continued growth and topological maturation.

Transport in certain systems fails when diffusion cannot replenish or remove material from a boundary rapidly enough, causing the boundary concentration to reach a critical minimum or maximum. Motivated by experiments in electrochemical systems that demonstrate this diffusion-limited failure of charge transport, we determine dynamic current protocols that maximize charge transfer subject to a prescribed concentration constraint. The optimal protocol has a "bang-ride" structure: the maximum feasible current is used until the boundary concentration reaches its critical value, after which the current is progressively reduced to maintain that value. For semi-infinite domains, we derive the optimal currents analytically and obtain system-independent upper bounds on their improvement over constant-current operation. We also extend the framework to finite and multilayer domains and show that the same formulation applies to both charging and discharging.

Standard rheological measurements yield only selected stress components; thus, inferring tensorial constitutive equations from experimentally accessible observables is complicated. We propose a constitutive formulation written in terms of a deviatoric stress tensor, whose trace is zero, rather than the extra stress tensor. From rheometric data including shear stress, first and second normal stress differences under shear, and elongational stress under uniaxial elongation, we can construct a deviatoric stress state without the indeterminate isotropic stress. The deviatoric-stress dynamics is represented by a closure inferred through symbolic regression, constrained to satisfy material objectivity and a given linear Maxwell response. To demonstrate the proposed formulation, two closures inferred from stress responses of the Giesekus and Larson models successfully captured untrained transient-flow responses under planar elongation and mixed shear/uniaxial elongations at deformation rates around an inverse relaxation time. Steady rheological functions of the closures agreed with the original models in the linear-response regime and over a deformation-rate range connected to the training data, whereas deviations and divergent responses appeared at larger deformation rates outside the training regime. These results demonstrate that the proposed deviatoric-stress formulation provides a practical route for constitutive modeling of observable linear and nonlinear viscoelastic dynamics, while clarifying its range of validity under strong deformation.

Cohesive granular materials derive their mechanical stability not only from the strength of individual interparticle bonds but also from the number of bonds forming the load-bearing network. However, these two effects are difficult to separate experimentally because conventional control parameters, such as liquid content, generally alter both simultaneously. Here, we use a mixed granular system composed of cohesive and noncohesive grains to control the cohesive bond number while keeping the bond strength approximately unchanged. We investigate the failure lifetime under repeated vibration and find that the number of cycles to failure, $N_f$, depends strongly on the mixing ratio $\alpha$. In a mean-field picture of random mixing, the fraction of cohesive contacts scales as $\alpha^2$, and $N_f$ increases approximately exponentially with $\alpha^2$. By contrast, although the lifetime tends to decrease with increasing vibration intensity $G$, its dependence on $G$ is comparatively weak over the present experimental range. Remarkably, although the Young's modulus is nearly independent of $\alpha$ above the rigidity threshold, the lifetime continues to increase strongly with $\alpha$. This demonstrates that mechanical rigidity and durability against repeated perturbations exhibit distinct dependences on the cohesive network. These results identify bond number as a key control parameter for the durability of cohesive granular materials.

At the water-land interface, amphibious fishes encounter wet flowable substrates made of granular solid-water mixtures, which can stay solid or flow like a fluid. As these substrates become wetter or drier, their yield strength (at which solid-fluid transition occurs) and cohesion (how sticky they are) both change, challenging locomotion. Despite substantial understanding of tetrapod locomotion on flowable substrates (mostly dry sand), we know little about how amphibious fishes cope with wet flowable substrates of various wetness. Here, we studied mudskippers on clay mud of controlled, variable wetness over the range where solid-fluid transition occurs. As mud became wetter, its strength decreased by 100-fold, leading the animal to sink deeper, with larger areas of body and fins contacting mud. By contrast, mud stuck most easily at intermediate wetness. The increased sinkage and contact and stickiness change caused more mud to stick to and pull against the animal on wetter mud. We also tested dry mud, which stuck to animal fins as its mucus dried. Despite these challenges, the mudskipper predominately used a conserved crutching gait on all except the wettest mud tested, with a modest performance reduction. When normal crutching became less effective, the animal assisted it with tail thrusting, by bending and straightening it to push downward and backward to generate additional thrust and lift, or even thrusting the tail to jump. These observations suggest that mudskipper's crutching motor program is well adapted to its native muddy substrates but inflexible, with most novelty in tail use.

Animals and robots encounter mud at the water-land interface. Like sand, mud can stay solid or flow like a fluid. Unlike sand, the yield strength of mud at which solid-fluid transitions occur depends on not only the amount of solid relative to fluid (water in mud, air in dry sand), but also how much coarse grains and fine clay are within the solid. Despite understanding of locomotion on/within dry sand dominated by coarse grains with repulsive normal forces and friction, little is known for mud dominated by fine clay with strong cohesion. Here, we developed methods to prepare uniform mud of controlled, variable yield strength and characterize and track its drift from water evaporation. Compared to other flowable substrates, mud strength measured by upward force during penetration is weaker and can vary more, and mud sticks more during extraction to pull downward, making it more challenging for locomotion.

Lattice-based metamaterials provide lightweight platforms where local instabilities can govern the global mechanical response, enabling applications in energy routing, vibration isolation, and impact mitigation. Although much progress has been made in controlling deformation and buckling sequences through geometric design, the behavior of coupled nonlinear units over a large range of strain rates and their history-dependent response is less explored. Here, we investigate lattice-based mechanical metamaterials whose nonlinear buckling behavior can be harnessed through modular architectures. By combining modular units in series, we show that their interaction gives rise to emergent force responses, including transient weakening and enhanced force attenuation, that are absent in the individual modules. Furthermore, selected designs exhibit training behavior under cyclic loading, transitioning between distinct buckling states and revealing a history-dependent mechanical response. Our results demonstrate that modular, instability-driven metamaterials can be programmed and tuned not only through geometry but also through loading history, opening new avenues for designing a nonlinear stress-response in mechanical systems.

Dynamical heterogeneities are one of the hallmarks of supercooled liquids, and their properties and relevance have been studied with theory, simulations and experiments. In this work, we propose to monitor the dynamics of tracer particles (passive microrheology) to analyze the dynamical heterogeneities in a system of hard colloids close to the glass transition density, using Langevin dynamics simulations and mode coupling theory. Different observables, typical in the study of the dynamical heterogeneities are adapted to be calculated from the trajectory of a single tracer particle. The tracer dynamics shows a transition from a regime where it is most decoupled from the bath for small tracer size to a strong coupling regime for large tracers. Both theory and simulations show that the non-Gaussian parameter of the tracer is maximal for tracer sizes at the crossover between both regimes, and is highly dependent on the bath density. The dynamic susceptibility is also studied, but this parameter shows a minor dependence on both the tracer size or the bath density. Finally, the existence of regions with different mobility is also studied with microrheology. Although the tracer trajectory indeed shows stages with increased mobility, the estimated size of the regions decreases with the bath density, contrary to the results from cluster analysis in the bulk.

We explore the hypothesis that ions form loosely connected clusters at high ionic strength in aqueous solutions, and that these clusters have relevance to the experimentally observed phenomenon usually referred to as "anomalous underscreening". Cluster formation lowers the ionic strength below its nominal value, slowing the decay of the screening length but not reversing it. Here we focus on an additional contribution, cluster polarisation. We demonstrate that this effect produces longer-ranged repulsive interactions between like-charged surfaces or particles in concentrated salt solutions. We derive an analytical bulk relation in which the entire architecture of a cluster enters through a single quantity, the charge-weighted second moment of its intramolecular charge structure factor, which quantifies the polarisation response of an arbitrary cluster topology. We also make numerical calculations using classical polymer Density Functional Theory, cDFT, for a model based on star-like clusters in which satellite ions are weakly bonded by a harmonic spring to a common central ion. The corona of satellite ions is assumed to be net neutral, since the formation of highly charged clusters would be accompanied by a significant self-energy cost. Using this model, we calculate surface interactions and screening lengths at various overall salt concentrations. We show that, under the assumption that the fraction of ions belonging to clusters increases with salt concentration, one may qualitatively arrive at "anomalous underscreening", i.e., an effective screening length that displays a minimum at an overall (monovalent) salt concentration of about 1 M. Quantitatively, we note that the predicted growth of the screening length beyond this threshold value is weaker than typically found by experimental surface force measurements.

We study Bayesian tracking of a diffusing target monitored by a noisy distributed sensor array. Building on an earlier mapping to KPZ growth with a moving defect (or an equivalent directed polymer pinning problem) we determine the phase structure, beyond the previously-studied one-dimensional case, for both Bayes-optimal and suboptimal inference. In $d=2$, theoretical analysis and numerical simulations both give a depinning transition between a successful tracking phase and a failure phase. Weak-coupling RG shows that Bayes-optimal tracking is always successful in $d=2$, but failure can arise from overconfident (suboptimal) inference. In $d=3$, tracking can succeed, or can fail in two distinct ways: the posterior probability distribution may delocalize (no detection), or may become sharply localized, but at the wrong position (a false detection). The two possibilities correspond to Edwards-Wilkinson or Kardar-Parisi-Zhang statistics for the log-posterior. The three phases meet at a Nishimori-like multicritical point on a Bayes-optimal line in a two-parameter phase diagram. (Model misspecification alone can drive depinning into either unpinned phase: underconfidence gives diffuse failure, while overconfidence gives localized-but-wrong failure.) We analyze the transitions between the various phases numerically and with renormalization group arguments. We show that some of these have unusual critical behavior, which the conventional $\epsilon$ expansion fails to describe. Recent rigorous results for directed polymers indicate an alternative scenario. Many of our results, including a scaling relation for exponents at pinning transitions and results for RG flows, are relevant to other phase transitions that involve surface growth or directed polymers in 2+1D or 3+1D.

Porous triboelectric materials offer significant potential for enhancing the performance of triboelectric nanogenerators, yet their practical application is limited by structural instability and humidity-induced performance degradation. In this work, a bio-derived, sustainable polyamide containing disulfide linkages was developed to enable spontaneous formation of a porous dielectric without external templating. Hydrophilic MOF fillers comprising HKUST-1 crystals are incorporated within the porous matrix to reinforce the membrane structure and regulate moisture effects. Mechanical characterization demonstrates that HKUST-1 suppresses pore collapse and improves structural robustness under repeated deformation, while analysis of stress-strain behaviour reveals the critical role of pore stability in achieving stable triboelectric output. In addition, HKUST-1 mitigates humidity-induced charge dissipation by confining water molecules within its framework, giving enhanced triboelectric output stability and reduced performance degradation under increasing relative humidity compared to the neat porous system. This work demonstrates a strategy that integrates self-foamed porous structures, sustainable polymer design, and functional filler reinforcement to engineer mechanically robust and environmentally stable triboelectric systems.

We investigate the flow and segregation of binary granular mixtures with density differences down a long chute using a continuum framework that couples a particle-force-based segregation model with an inertial-number-based local rheology. The steady-state momentum and convection-diffusion-segregation equations are solved simultaneously, explicitly accounting for the two-way coupling between segregation and flow. Predicted concentration and velocity fields at different streamwise locations are validated against representative DEM simulations. The validated model is then used to examine the influence of density ratio, mixture composition, and chute inclination on segregation over a wide range of conditions. The chute length required to achieve fully developed segregation is quantified and compared with the development length for monodisperse granular flow. At low density ratios and/or low inclinations, segregation develops over much longer distances than the velocity field. In contrast, at higher inclinations and larger density contrasts, the two length scales become comparable, demonstrating that neglecting flow development can significantly underestimate segregation evolution.

We study how colloidal inclusions modify the formation energy of dislocation pairs in lamellar block copolymer systems. Using a hybrid particle/Ginzburg–Landau model, we calculate defect formation energies by comparing defect-free and defect-containing states with and without embedded colloids. Finite-size scaling is used to obtain formation energies in the thermodynamic limit. The effect of colloid insertion depends strongly on particle sizes and surface patterning. Homogeneous particles increasingly stabilize dislocation pairs with increasing particle sizes. Particles larger than one lamellar domain preferentially occupy the dislocation cores, where they replace strained polymer rather than deforming defect-free lamellae. The magnitude of this stabilization depends on surface affinity. Balanced Janus particles instead increase the formation energy, because their competing surface preferences cannot be satisfied simultaneously near the curved core. Varying the patch ratio interpolates between these limits. Surface patterning has little effect for particles smaller than one lamellar domain but changes the formation energy by several tens of $k_BT$ for larger particles. These results provide quantitative guidelines for controlling topological defect stability in lamellar block copolymer systems.

Disclinations are elementary topological defects in two-dimensional (2D) crystalline membranes, yet their elastic properties remain largely unexplored. Using atomistic simulations, we address the energetics, morphology, and interactions of disclinations in free-standing graphene, a prototypical 2D crystal. We find that while disclinations with positive topological charges follow an expected behavior, negative disclinations exhibit sublinear energy scaling with charge as well as equilibrium shape that deviates sharply from the conventional saddle ansatz. This breakdown of charge-conjugation symmetry leads to qualitatively distinct interactions: positive disclinations repel, whereas negative disclinations display a robust long-range attraction. These trends are shown to be further amplified by self-adhesion in folded membranes. Our results uncover a fundamentally different energetic landscape for negative curvature defects and provide a basis for understanding the stability, self-folding behavior, and defect-driven morphology of graphene and other 2D membranes.

We study kinetics of phase transitions within a single component Lennard-Jones model. For low enough particle densities disconnected clusters form that can move ballistically in an inviscid vapor background. The clusters undergo sticky collisions, thereby forming larger aggregates, which can be of fractal nature at ultra cold temperatures. As the temperature is varied, the exponent of the algebraic growth of average cluster mass changes, exhibiting pronounced nonmonotonic character. We capture this anomalous behavior, in two and three space dimensions, within a ballistic aggregation theory. We show that the scope of the theory is much broader than the typically considered case where cluster motions are uncorrelated. An analysis of the theory shows that ballistic aggregation can even occur exponentially fast. This is in sharp contrast with the conventional algebraic picture, regarding passive matter phase transitions. We discuss scenario where such explosive growth can be realized. In addition, our results are widely relevant in understanding structure and growth in aerosols, cosmic dust and other aggregation processes.

Diffusion processes involving membranes are of fundamental importance in both science and technology, since membranes serve as selective interfaces that regulate the transport of mass, charge, and information across multiple length and time scales. In this study, we employ molecular dynamics (MD) simulations to calculate the self-diffusion coefficient, tetrahedral order parameter and hydrogen-bond (HB) lifetime of SPC/E water over a wide high-temperature range in the presence of thermally activated membranes (TAMs). These membranes exhibit thermally controlled stochastic behavior that locally influences particle dynamics by probabilistically inducing elastic scattering events as particles traverse the membrane. The stochastic behavior of the membranes is governed by a sigmoidal profile, which depend on the reduced temperature of the system. The effective activation energy for diffusion is estimated for several membrane configurations. It is found that the diffusion coefficients generally decrease with an increase in the number of membranes and are in reasonable agreement with the Arrhenius approximation at high temperatures. Additionally, both the tetrahedral order parameter and the HB lifetime are only locally sensitive to the action of the membranes.

We numerically investigate the behavior of a system of initially unlinked nicked dsDNA rings confined into an annular square nanochannel in the presence of TopoII. Channel confinement can enhance the catenation likelihood by bringing highly bent regions from different rings in close proximity, while at the same time reducing the emergence of knots. The annular channel topology simplifies the characterization of the system by removing periodic boundary conditions and can lead to the formation of circular catenanes.We characterize the equilibrium and dynamical properties of the steady-state system, including the amount of catenation and the topologies explored by the system, under different parameters of the model and for different levels of confinement. We argue that a similar setup could allow for a direct comparison between experiments and simulations under well characterized and controlled conditions, thus providing a way to select and tune computational models of TopoII, as well as provide a way to obtain dsDNA interlocked materials in a controlled fashion.

We introduce a Hamiltonian Active Brownian Particle (HABP) model that connects equilibrium dynamics with the non-equilibrium, two-dimensional overdamped behavior of standard Active Brownian Particles (ABPs). In equilibrium, the system follows overdamped Langevin equations that strictly satisfy the fluctuation-dissipation theorem. Coupling translational and rotational degrees of freedom to separate heat baths ($T_{\theta} > T_{\textrm{tr}}$), drives the system out of equilibrium. In free space, matching the diffusion coefficients yields quantitative agreement with the ABP model in the limit $T_\theta/T_{\textrm{tr}}\to \infty$, whereas in a harmonic potential, this matching is recovered even at finite temperature ratios. Entropy production analysis demonstrates that in the ABP limit, all energy injected by the swim force dissipates into the translational bath, leaving the rotational bath as a zero-cost entropy source. These insights provide the first steps toward equilibrium-inspired descriptions of active matter, facilitating the development of new theoretical frameworks to study activity-induced fluctuations, transport, and phase behavior in living and non-living soft matter systems far from equilibrium.