ALT Insect exoskeletons abruptly acquire complex three-dimensional forms during metamorphosis from larva to pupa. This transformation occurs through the unfolding of preformed wrinkle structures inside the larval body under internal pressure. Inspired by this process, we investigate an inverse-origami strategy for fabricating curved surfaces. Whereas conventional origami produces three-dimensional objects by folding a flat sheet, this strategy produces curved surfaces by unfolding preformed wrinkle structures. The central design problem is to derive a wrinkle structure from a prescribed target surface. Our key idea is to regard a wrinkle structure as a unidirectional stretching field, which specifies at each point the stretch produced when the structure unfolds. We first derive such a field from the target surface geometry and then translate it into spatially varying wrinkle directions and spacing, so that the wrinkle structure unfolds into the target. The resulting numerical designs appro

ALT Aqueous dispersions of hydrophobic carbon black (CB) particles can be stabilized by carboxymethylcellulose (CMC), forming CB-CMC hydrogels whose microstructure is controlled by the relative CB-to-polymer content. At low CMC content, CB particles form a percolated, electrically conductive network, whereas at higher polymer content, CB particles act as isolated physical crosslinkers within an electrically insulating polymer matrix [see Legrand et al., Macromolecules 56, 2298-2308 (2023)]. Combining rheology and electrical impedance spectroscopy, we show that these two regimes exhibit markedly different aging dynamics. Conductive hydrogels exhibit logarithmic elastic recovery associated with a percolated CB network, whereas insulating hydrogels exhibit a combination of logarithmic and power-law stiffening, accompanied by dielectric polarization associated with confined ionic motion. The insulating hydrogels further exhibit a time-aging superposition principle, as their viscoelastic spectr

ALT Buffer chemistry modulates colloidal impedance critically for label-free biosensing and electrokinetic diagnostics, yet classical models neglect buffer-specific interactions. We studied carboxylated polystyrene (PS) microspheres in conductivity-matched zwitterionic 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid (HEPES) and phosphate-buffered saline (PBS). Two concentration-dependent regimes emerged: oscillatory at ultradilute concentrations (<0.02 w/v%; Region 1) and monotonic at higher concentrations (Region 2). In Region 1, HEPES at pH 6.9 (approximately 80% zwitterionic) produced the largest deviation of delta Z from the O'Brien prediction. The conductivity increment was opposite in sign to classical expectation. We attribute this to zwitterion-driven interfacial ordering that enhances local conductivity and promotes self-limiting particle clustering. Dynamic light scattering detected cluster formation at 0.008 w/v%, well below aggregation thresholds. Changing pH from 6.9 to 8.1

ALT Micro- and nanoswimmers diffusing in a fluid flow confined to microchannels are often described by overdamped active Brownian particle dynamics, in which viscous effects dominate and inertia is negligible. Here, we investigate the diffusive behavior of chiral self-propelled particles in a two-dimensional microchannel with oscillatory Poiseuille flow. Using numerical simulations, we show that the effective diffusion coefficient strongly depends on the oscillation frequency, flow strength, intrinsic angular velocity, and rotational diffusion rate. Interestingly, the effective diffusion coefficient can oscillate with oscillation frequency and flow strength, exhibiting distinct maxima and minima. The enhanced diffusion peaks arise from resonant diffusion associated with the matching between the flow oscillation time scale and the intrinsic characteristic diffusion time scale. Moreover, we identify an additional vorticity matching mechanism, leading to alternating channel wall accumulation

ALT Many industries rely on models of colloidal gelation and phase behavior to predict how processing equipment will handle new product formulations. In colloidal systems with nearly uniform particle size it is possible to predict the formation of a gel from only three state variables; however, the extension of this model to bimodal and multimodal systems is not well described. Here we present a systematic simulation study of the attractive bimodal depletion gel phase diagram. For these systems, we find that gelation is highly dependent on total volume fraction, attraction conditions, and bimodal composition. Attraction and composition can be effectively collapsed into a single parameter using the contact-weighted second virial coefficient. This successfully projects the bimodal phase diagram onto the established monodisperse phase diagram, including accurately describing most bulk assembly properties; however, the underlying network structure of these gels remains highly dependent on the

ALT In this perspective article, we introduce elasto-plastocapillarity: surface-tension-driven free-surface flows of yield-stress fluids in which capillary stresses compete with yielding and elastic relaxation. We frame the relevant parameter space, and highlight representative problems (drops, bubbles, jets/filaments, thin films, and porous media) that are central to applications ranging from additive manufacturing and coatings to biological flows. We then outline a set of timely open challenges, including surface-tension measurements, breakdown of scale separation near the microstructures, coupled bulk-interface flow experimental diagnosis, interfacial rheology and surface stresses, history dependence, constitutive models and boundary conditions, reduced theoretical models, and the emerging opportunity provided by artificial intelligence and microgravity; aimed at guiding future experiments, theory, and computation.

ALT Controlling the folding of biopolymers in crowded and confined environments, such as the interior of biological cells, remains a significant challenge. Macromolecular crowding and spatial confinement can strongly influence transition pathways between folded and unfolded states of proteins. Such environments can be mimicked in experiments by confining polymers within soft, tunable media, such as hydrogels – cross-linked polymer networks that swell by absorbing solvent and exhibit stimulus-dependent responsiveness. Here, we develop a self-consistent mean-field theory for the equilibrium swelling and internal composition of a hydrogel immersed in a solution of free polymer coils. The theory extends the Flory-Rehner framework by incorporating free polymer coils, modeled as fluctuating ellipsoids, whose sizes and shapes are characterized by the eigenvalues of the gyration tensor. Confinement of the coils within gel pores is characterized by an effective free-volume fraction, parametrized fr

ALT Inferring constitutive laws from transient response data is a central inverse problem in soft condensed-matter physics, particularly when the relevant relaxation spectrum extends beyond the time window of a single experiment. Time-temperature superposition (TTS) constrains this problem for thermorheologically simple materials in the linear viscoelastic regime by allowing temperature to rescale the characteristic relaxation time without changing the underlying shape of the relaxation spectrum. We incorporate this constraint into a physics-informed machine-learning framework for time-resolved mechanical spectroscopy via chirp rheometry. We encode compact fractional viscoelastic models as causal convolutional features derived from the Boltzmann superposition principle, and we jointly fit multi-temperature chirp records using sparse variational Gaussian process regression. The model infers horizontal shift factors, constitutive parameters, and an observational-noise scale directly from tim

ALT We investigate the field-directed assembly of patchy colloidal particles composed of magnetic hematite cubes encapsulated in TPM shells. These Pacman-like particles exhibit specific interactions via their magnetic patch, enabling tunable structures under external fields. A magnetic field drives patch-to-patch interactions, while an AC electric field induces stacking and spreading. By using this multi-field combination and by varying field parameters, such as frequency and amplitude, we achieve programmable transitions between distinct assembly modes. Our work offers a versatile platform for designing reconfigurable colloidal architectures with potential applications in micro-robotics and smart materials.

ALT Many solvated materials, from nanoparticles to polyelectrolytes, acquire charge through the dissociation or association of surface groups, a phenomenon known as charge regulation (CR). Recent methods use hybrid charge regulation Monte Carlo (CR-MC)/molecular dynamics (MD) to evolve the system while dynamically adjusting charges on the surface groups. However, this approach is computationally expensive, as Monte Carlo sampling can be as costly as the accompanying MD. In this work, we introduce charge regulation machine learning (CR-ML), a graph attention network that predicts the ionization probability of every surface site from the instantaneous configuration, the dissociation constant of surface groups, and the solution conditions. We show that CR-ML reproduces the equilibrium conformations and degree of ionization obtained with CR-MC for a hydrophobic polyanion. We further test CR-ML on the more complex system of two nanoparticles mediated by a polyelectrolyte, where it accurately pr

ALT Understanding the microscopic behavior of materials in response to mechanical perturbations is a central challenge in soft matter, yet existing methods, which typically rely on microscopy-based imaging, often struggle with spatial heterogeneity and low signal-to-noise that are characteristic of many soft and biological materials. Additionally, many existing rheo-optical methods focus on the response to macro-scale forces rather than localized perturbations despite the importance of local stresses in biological and industrial applications of soft materials. Here, we present STroboscopically Averaged, time-Resolved Differential Dynamic Microscopy (starDDM) to investigate a sample's deformation across time and distance due to a cyclically applied local force. As proof-of-principle, we use this model-independent and tracer-free approach to map the motions of active cytoskeleton composites imposed by the movement of an optically trapped probe particle embedded within the complex network. We

ALT Various types of electrohydrodynamic instabilities in liquid crystals (LCs) are a recurring theme in LC research. The nonlinear stage of the flexoelectric instability in nematics remains the least studied aspect of this phenomenon. This work highlights a key advancement in nonlinear physics, providing a compelling example of nonlinear dynamical system behavior. By solving the system of nonlinear equations for a nematic in an alternating external field, we derive from first principles the unique "dancing" behavior of truly two-dimensional patterns above the flexoelectric instability threshold. Our analysis is restricted to liquid crystals with negative dielectric permittivity and electrical conductivity anisotropies. The resulting solution represents a stable limit cycle near above the Hopf bifurcation, valid within the parameters range where the solutions characteristic exponent is complex. The generalized two-dimensional Ginzburg-Landau-like phenomenological theory of the phenomenon i

ALT Biomedical devices, wearable interfaces, and soft robots require compliant soft materials with reliable mechanical performance, yet the molecular principles needed to design such materials are not always fully understood. Thus, there is an urgent need to understand how to design novel stretchable and soft hydrogels with enhanced toughness, i.e. resistance to breakage. Slide-ring gels (SRGs) are a class of unconventional soft materials formed by polyrotaxanes (PR) building blocks whereby sliding cyclodextrins (CD) replace traditional chemical and physical crosslinks and in turn enhance toughness and stretchability by several orders of magnitude. The rational design of SRGs re- mains challenging due to a lack of a mechanistic understanding of the role played by individual components. In this work, we implement simple synthetic perturbations that individually target polymer-CD and CD-CD interactions in unstoppered pseudopolyrotaxanes (pPR) solutions and measure the consequent changes in v

ALT Collective decision-making requires individuals to reconcile diverse, often conflicting opinions to reach a common course of action. However, within a group, they rarely exert equal influence, leading to non-reciprocal communication patterns manifested as leader-follower relationships and social hierarchies. Here, using homing pigeon flocks as a model system, we develop a trajectory-based framework to infer and quantify hierarchy within navigating living collectives. We find that while small flocks exhibit pronounced hierarchy, increasing flock size progressively weakens it, driving the collection toward more egalitarian decision-making. We provide a physical basis of this observation using a thermodynamic framework in which non-reciprocal communication between birds carries an information-entropy cost. Our calculations reveal that hierarchy weakening observed in larger flocks is a direct consequence of maintaining a constant per-individual entropy production rate across flock sizes. T

ALT Improving the particle surface frictional behavior is of considerable importance in several industries so as to manipulate the powder flowability and handling. In this work, we have studied the lubrication phenomena in an assembly of flowing bulk powder particles in presence of a fine powder lubricant. Experiments were conducted in two different shear environments, for two different levels of confinement and using three different bulk powder particles having distinct surface morphology. The added lubricant particles tend to adhere to the surface of bulk particles thereby altering their surface morphology. This results in altered inter-particle friction, which typically reduces for small addition of lubricant, but increases on its excess addition, thereby altering the particle flowability. While this behavior is generally understood through previous studies, the current work explores how the effect of confinement, shear environment and particle surface characteristics combine in a uniqu

ALT Chemical reactions can sustain polymer motion without necessarily generating the compression required for buckling. Theory and simulations show that tension-dependent chemical transitions coupled to bond elasticity generate finite-wavelength traveling strain waves in a semiflexible polymer. In the straight chain at fixed axial span, the waves reduce mean active contraction while leaving mean elastic tension unchanged, generating compression that drives bending above a threshold. Releasing the mean load allows longitudinal waves to persist while transverse perturbations decay.

ALT We present a phenomenological, mean-field model for condensates of intrinsically disordered proteins that describes inverse phase transitions and qualitatively predicts reentrant phase behavior as a function of salt concentration. The model is based on a matrix-based formulation of the Flory-Huggins free energy, in which the enthalpic interaction parameter and the protein valence, defined here as the number of effective "sticky patches", are treated as free parameters. Its central insight is that integrating out dynamics of fast-moving molecular species generates an effective entropic force that increases the free-energy barrier to mixing, even within a mean-field description. We account for this by linking Gaussian integration of co-solutes to the Schur complement of the matrix-based Flory-Huggins free energy. This provides a general thermodynamic framework illustrating how enthalpic interactions that increase the number of available microstates necessarily induce effective entropic f

ALT In sheared aggregating suspensions, flow drives both the formation and breakage of particle clusters, whose dynamic evolution influences transport and rheological properties. Understanding these mechanisms remains challenging due to the complex interplay between interparticle forces, hydrodynamic interactions, and shear flow. Using parallelized Accelerated Stokesian Dynamics (PASD) simulations, we investigate cluster microstructure and rotational dynamics, and how their coupling produces suspension stress in sheared, attractive non-Brownian suspensions. When interparticle attraction dominates over separating shear forces, clusters grow until mechanical loading balances maximum interparticle bond strength. We examine how the cluster stresslet depends on cluster size, with both quantities normalized by their mechanical yielding scales. Scaled cluster stresslets collapse onto a master curve exhibiting three distinct regimes: cubic, quadratic, and linear with respect to the scaled radius o

ALT Non-destructive early detection of water stress is critical for precision agriculture, yet current detection methods are often labor-intensive or destructive. We propose a rapid, non-invasive method based on Spectral Submanifold (SSM) reduction to analyze the nonlinear vibration dynamics of soybean plants. Unlike traditional linear modal analysis, our data-driven approach reveals a distinct transition in the dominant dynamics of the plant stem as drought progresses. Specifically, we uncover a sign reversal in the nonlinear damping coefficient within SSM-reduced models of full plants. Our finding reveals a fundamental transition in the plant's dissipative mechanics from a pressurized, fluid-rich vessel exhibiting superlinear (viscoelastic) damping to a dry, cellular solid dominated by sublinear (frictional) damping. This transition is closely correlated with the onset of physiological stress indicated by a significant decrease in the values of mature-leaf soil plant analysis development

ALT We study the response of compressible microtubule-based active fluids to sinusoidally varying activity patterns, using experiments and theory. Microtubules accumulate in low-activity regions and are depleted from high activity ones, with the density difference controlled by the wavelength of the activity pattern. To explain these observations the continuum model needs to account for both active stresses that are proportional to nematic order tensor and the isotropic active pressure. At short wavelengths, active vortices spanning adjacent high and low activity regions suppress density modulation. At larger wavelengths, vortical flows confined to the low or high activity region allow for the emergence of the density contrast. Our work shows that a minimal theoretical model of active compressible fluids accurately reproduces experiments, while elucidating the fundamental constraints on control protocols that seek to tame their chaotic dynamics.