Magnetically driven microparticles provide a versatile platform for probing and manipulating biological systems, yet the physical framework governing their actuation in complex environments remains only partially explored. Within the field of cellular magneto-mechanical stimulation, vortex microdiscs have emerged as particularly promising candidates for developing novel therapeutic approaches. Here, we introduce a simplified two-dimensional model describing the magneto-mechanical response of such particles embedded in viscoelastic media under varying magnetic fields. Using a Maxwell description of the medium combined with simplified elasticity assumptions, we derive analytical expressions and support them with numerical simulations of particle motion under both oscillating and rotating magnetic fields. Our results show that rotating fields typically induce oscillatory dynamics and that the transition to asynchronous motion occurs at a critical frequency determined by viscosity and stiffness. The amplitude and phase of this motion is governed by the competition between magnetic and viscoelastic contributions, with particle motion being strongly impaired when the latter dominate. Energy-based considerations further demonstrate that, within the frequency range explored of few tens of Hertz, no heat is generated -- distinguishing this approach from magnetic hyperthermia -- while the elastic energy transferred to the surrounding medium is, in principle, sufficient to perturb major cellular processes. This work provides a simple framework to anticipate the first-order influence of rheological properties on magnetically driven microdisc dynamics, thereby enabling a better understanding of their impact in cells or extracellular materials and bridging the gap between experimental observations and theoretical modelling.

We extensively study the phenomenology of one dimensional Nonreciprocal Cahn Hilliard model for varying nonreciprocity $(\alpha)$ and different boundary conditions. At small $\alpha$, a perturbed uniform state evolves to a defect laden configuration that lacks global polar order. Defects are the sources and sinks of travelling waves and nonreciprocity selects defects with a unique wave number that increases monotonically with $\alpha_c$. A critical threshold $\alpha_c$ marks the onset of a transition to states with finite global polar order. For periodic boundaries, above $\alpha_c$, the system shows travelling waves that are completely ordered. In contrast, travelling waves are incompatible with Dirichlet and Neumann boundaries. Instead, for $\alpha \gtrsim \alpha_c$, we find fluctuating domains that show intermittent polar order and at large $\alpha$, the system partitions into two domains with opposite polar order.

Rotational migration is one specific form of collective cell migration when epithelial cells are confined in a spherical geometry, such as in the epithelial acini. This tissue-level rotation motion is crucial for the morphogenesis of multiple epithelial systems. Here, we introduce a new primary human model for the study of rotational migration, pancreatic ductal organoids. Live imaging revealed the persistent rotation of the organoids over time. By tracking the nuclei, the three-dimensional trajectory of the cellular movement was reconstructed and the velocity of the rotation was quantified. The presence of focal adhesion clusters and prominent actin stress fibers were observed at the basal side of the organoids, suggesting the interactions between the cells and the surrounding extracellular matrix. Finally, our inhibition study showed the dependence of pancreatic ductal organoid rotational migration on myosin activity, actin polymerization, and actin branching. We hope that this model will enable future studies with human primary cells, which are more faithful to normal epithelial cells.

Across development, the morphology of fluid-filled lumina enclosed by epithelial tissues arises from an interplay of lumen pressure, mechanics of the cell cortex, and cell-cell adhesion. Here, we explore the mechanical basis for the control of this interplay using the shape space of MDCK cysts and the instability of their apical surfaces under tight junction perturbations [Mukenhirn et al., Dev. Cell 59, 2886 (2024)]. We discover that the cysts respond to these perturbations by significantly modulating their lateral and basal tensions, in addition to the known modulations of pressure and apical belt tension. We develop a mean-field three-dimensional vertex model of these cysts that reproduces the experimental shape instability quantitatively. This reveals that the observed increase of lateral contractility is a cellular response that counters the instability. Our work thus shows how regulation of the mechanics of all cell surfaces conspires to control lumen morphology.

Dense stabilized emulsions are mixtures of immiscible fluids where the high-volume fraction droplet dispersed phase is stabilized against coalescence by steric interactions. The production of emulsions involves high-shear flows and it is well known that at a critical volume fraction the emulsion loses stability, undergoing an extremely rapid process where the fluid components in the emulsion exchange roles. This process, called catastrophic phase inversion, which resembles in several respects a dynamical phase transition, has remained widely elusive from an experimental and theoretical point of view. In this work, we present state-of-the-art experimental and numerical data to support a dynamical-system framework capable of precisely highlighting the dynamics occurring in the system as it approaches the catastrophic phase inversion. Our study clearly highlights that at high volume fractions, dynamical changes in the emulsion morphology, due to coalescence and breakup of droplets, play a critical role in determining emulsion's rheology and stability. Additionally, we show that at approaching the critical volume fractions, the dynamics can be simplified as being controlled by the dynamics of a correlation length represented, in our systems, by the size of the largest droplet. This dynamics shares a close connection with non-reciprocal phase transition where two different physical mechanisms, coalescence and breakups, can get out of balance leading to large non-symmetric periodic excursions in phase space. We clarify the phenomenology observed and quantitatively explain the essential aspect of the highly complex dynamics of stabilized emulsions undergoing catastrophic phase inversion.

From the flutter of aircraft wings to an umbrella flipping inside out in the wind, fluid-induced elastic instabilities are a major concern in aeroelastic design. However, Nature often harnesses these instabilities to achieve new functionalities, such as the mechanical snap-through of the Venus flytrap. Inspired by this, engineers and physicists have increasingly exploited elastic instabilities to enable rapid shape changes in metamaterials and soft robots, provided the structure remains elastic throughout the transition. Here, we study the fluid-induced snapping instability of a spherical elastic shell at low Reynolds numbers, the umbrella flipping problem when life is at low Reynolds numbers. We combine precision desktop-scale experiments, fluid-structure simulations, shell theory, fluid mechanics, and scaling analysis to determine the instability threshold as a function of the geometrical and material parameters of the system. Building on these findings, we devise a snapping-based valve that passively and abruptly alters the hydraulic resistance of a channel, offering robust flow control without active components. These valves could be deployed in soft robotics and, because our results are expressed in terms of key dimensionless parameters, we speculate that the system can be miniaturized for use in microfluidic circuits. Beyond the application, our study presents what we believe to be a prototypical example of fluid-induced elastic instability at low Reynolds numbers, providing a foundation for future explorations in soft hydraulics and flow-responsive structures.

Inspired by recent experimental observations of a harmonically excited elastic foil hovering near a wall while supporting substantial weight, we develop a theoretical framework that describes the underlying physical effects. Using elastohydrodynamic lubrication theory, we quantify how the dynamic deformation of the soft foil couples to the viscous fluid flow in the intervening gap. Our analysis shows that the soft foil rectifies the reversible forcing, breaking time-reversal symmetry; the relative spatial support of the forcing determines whether the sheet is attracted to or repelled from the wall. A simple scaling law predicts the time-averaged equilibrium hovering height and the maximum weight the sheet can sustain before detaching from the surface. Numerical simulations of the governing equation corroborate our theoretical predictions, are in qualitative agreement with experiments, and might explain the behavior of organisms while providing design principles for soft robotics.

In a recent paper, Di Lisio et al. [J. Chem. Phys. 159 064505 (2023)] analyzed a series of temperature down-jumps using the single-parameter aging (SPA) ansatz combined with a specific assumption about density scaling in the out-of-equilibrium system and did not find a good prediction for the largest down-jumps. In this paper we show that SPA in its original form does work for all their data including large jumps of \Delta T > 20 K. Furthermore, we discuss different approaches to the extension of the density scaling concept to out-of-equilibrium systems.

The settling of highly elastic non-Brownian closed fibres (called loops) under gravity in a viscous fluid is investigated numerically. The loops are represented using a bead-spring model with harmonic bending potential and finitely extensible nonlinear elastic (FENE) stretching potential. Numerical solutions to the Stokes equations are obtained with the use of HYDROMULTIPOLE numerical codes, which are based on the multipole method corrected for lubrication to calculate hydrodynamic interactions between spherical particles with high precision. Depending on the elasto-gravitation number B, a ratio of gravitation to bending forces, the loop approaches different attracting dynamical modes, as described by Gruziel-Slomka et al. (Soft Matter, vol. 15, 2019, pp. 7262-7274) with the use of the Rotne-Prager mobility of the elastic loop made of beads. Here, using a more precise method, we find and characterise a new mode, analyse typical timescales, velocities, and orientations of all the modes, compare them, and investigate their coexistence. We analyse the transitions (bifurcations) to a different mode at certain critical values of the elasto-gravitation number B.

Recent advances in synthetic methods enable designing subunits that self-assemble into structures with well-defined sizes and architectures, but yields are frequently suppressed by the formation of off-target metastable structures. Increasing the complexity (number of distinct inter-subunit interaction types) can inhibit off-target structures, but leads to slower kinetics and higher synthesis costs. Here, we use icosahedral shells formed of programmable triangular subunits as a model system, and identify design principles that produce the highest target yield at the lowest complexity. We use a symmetry-based construction to create a range of design complexities, starting from the maximal symmetry Caspar-Klug assembly up to the fully addressable, zero-symmetry assembly. Kinetic Monte Carlo simulations reveal that the most prominent defects leading to off-target assemblies are a class of disclinations. We derive symmetry-based rules for identifying the optimal (lowest-complexity, highest-symmetry) design that inhibits these disclinations, leading to robust, high-fidelity assembly of targets with arbitrarily large sizes. Optimal complexity varies non-monotonically with target size, with `magic' sizes appearing for high-symmetry designs in which symmetry axes do not intersect vertices of the triangular net. The optimal designs at magic sizes require $12$ times fewer inequivalent interaction-types than the (minimal symmetry) fully addressable construction.

Paints and coatings undergo a variety of physical and chemical changes under environmental exposures. Accurate prediction of these changes is important for the applications of coatings. This work presents a novel approach to modeling accelerated weathering of coating by combining concurrent physical and chemical processes. The model integrates key factors influencing coating degradation and employs a multi-scale framework to capture macro-scale physical changes and micro-level chemical transformations. The chemical component/model simulates photo-degradation reactions using kinetic equations, while the physical component uses Monte Carlo simulations where repeated random events develop surface erosion. The surface topography and chemistry of coating is generated statistically through the physical model. The variations in surface topography and chemistry of coating are correlated with the chemical changes from the chemical model, resulting in estimation of both physical and chemical changes in the coating during real accelerated weathering time. Results demonstrate accurate predictions of chemistry changes, surface degradation profiles, roughness, gloss loss, and relative fracture toughness, which are validated successfully with the experimentally available data. This integrated approach provides insight into coating failure mechanisms, enabling accurate service life prediction, and serve as a tool for formulating durable coatings and optimizing testing protocols.

The driving forces of chiral active particles and deformations of cells are often modeled by spatially inhomogeneous but temporally periodic driving forces. Such inhomogeneous oscillatory driving forces have only recently been proposed in the context of active matter, and their effects on the systems are not yet fully understood. In this work, we theoretically study the impact of spatially inhomogeneous oscillatory driving forces on continuous symmetry breaking. We first analyze the linear model for the soft modes in the ordered phase to derive the lower critical dimension of the model, and then analyze the spherical model to investigate more detailed phase behaviors. Interestingly, our analysis reveals that symmetry breaking occurs even in one and two dimensions, where the Hohenberg--Mermin--Wagner theorem prohibits continuous symmetry breaking in equilibrium. Furthermore, fluctuations of conserved quantities, such as density, are anomalously suppressed in the long-wavelength, {\it i.e.}, show hyperuniformity.

Biomolecules composed of a limited set of chemical building blocks can co-localize into distinct, spatially segregated compartments known as biomolecular condensates. While many condensates are known to form spontaneously via phase separation, it has been unclear how immiscible condensates with precisely controlled molecular compositions assemble from a small number of chemical building blocks. We address this question by establishing a connection between the specificity of biomolecular interactions and the thermodynamic stability of coexisting condensates. By computing the minimum interaction specificity required to assemble condensates with target molecular compositions, we show how to design heteropolymer mixtures that produce compositionally complex condensates using only a small number of monomer types. Our results provide insight into how compositional specificity arises in naturally occurring multicomponent condensates and demonstrate a rational algorithm for engineering complex artificial condensates from simple chemical building blocks.

The brain's remarkable and efficient information processing capability is driving research into brain-inspired (neuromorphic) computing paradigms. Artificial aqueous ion channels are emerging as an exciting platform for neuromorphic computing, representing a departure from conventional solid-state devices by directly mimicking the brain's fluidic ion transport. Supported by a quantitative theoretical model, we present easy to fabricate tapered microchannels that embed a conducting network of fluidic nanochannels between a colloidal structure. Due to transient salt concentration polarisation our devices are volatile memristors (memory resistors) that are remarkably stable. The voltage-driven net salt flux and accumulation, that underpin the concentration polarisation, surprisingly combine into a diffusionlike quadratic dependence of the memory retention time on the channel length, allowing channel design for a specific timescale. We implement our device as a synaptic element for neuromorphic reservoir computing. Individual channels distinguish various time series, that together represent (handwritten) numbers, for subsequent in-silico classification with a simple readout function. Our results represent a significant step towards realising the promise of fluidic ion channels as a platform to emulate the rich aqueous dynamics of the brain.

The emergence of a spatially-organized population distribution depends on the dynamics of the population and mediators of interaction (activators and inhibitors). Two broad classes of models have been used to investigate when and how self-organization is triggered, namely, reaction-diffusion and spatially nonlocal models. Nevertheless, these models implicitly assume smooth propagation scenarios, neglecting that individuals many times interact by exchanging short and abrupt pulses of the mediating substance. A recently proposed framework advances in the direction of properly accounting for these short-scale fluctuations by applying a coarse-graining procedure on the pulse dynamics. In this paper, we generalize the coarse-graining procedure and apply the extended formalism to new scenarios in which mediators influence individuals' reproductive success or their motility. We show that, in the slow- and fast-mediator limits, pulsed interactions recover, respectively, the reaction-diffusion and nonlocal models, providing a mechanistic connection between them. Furthermore, at each limit, the spatial stability condition is qualitatively different, leading to a timescale-induced transition where spatial patterns emerge as mediator dynamics becomes sufficiently fast.

Solid-liquid friction plays a key role in nanofluidic systems. Yet, despite decades of method development to quantify solid-liquid friction using molecular dynamics (MD) simulations, an accurate and widely applicable method is still missing. Here, we propose a method to quantify the solid-liquid friction coefficient (FC) from equilibrium MD simulations of a liquid confined between parallel solid walls. In this method, the FC is evaluated by fitting the Green-Kubo (GK) integral of the S-L shear force autocorrelation for the range of time scales where the GK integral slowly decays with time. The fitting function was derived based on the analytical solution considering the hydrodynamic equations in our previous work [H. Oga et al., Phys. Rev. Research 3, L032019 (2021)], assuming that the timescales related to the friction kernel and to the bulk viscous dissipation can be separated. By comparing the results with those of other equilibrium MD-based methods and those of non-equilibrium MD for a Lennard-Jones liquid between flat crystalline walls with different wettability, we show that the FC is extracted with excellent accuracy by the present method, even in wettability regimes where other methods become innacurate. We then show that the method is also applicable to grooved solid walls, for which the GK integral displays a complex behavior at short times. Overall, the present method extracts efficiently the FC for various systems, with easy implementation and low computational cost.

Nanofluidics shows great promise for energy conversion and desalination applications. The performance of nanofluidic devices is controlled by liquid-solid friction, quantified by the Navier friction coefficient (FC). Despite decades of research, there is no well-established generic framework to determine the frequency dependent Navier FC from atomistic simulations. Here, we have derived analytical expressions to connect the Navier FC to the random force autocorrelation on the confining wall, from the observation that the random force autocorrelation can be related to the hydrodynamic boundary condition, where the Navier FC appears. The analytical framework is generic in the sense that it explicitly includes the system size dependence and also the frequency dependence of the FC, which enabled us to address (i) the long-standing plateau issue in the evaluation of the FC and (ii) the non-Markovian behavior of liquid-solid friction of a Lennard-Jones liquid and of water on various walls and at various temperatures, including the supercooled regime. This new framework opens the way to explore the frequency dependent FC for a wide range of complex liquids.

Volterra's definition of dislocations in crystals distinguishes edge and screw defects geometrically, according to whether the Burgers vector is perpendicular or parallel to the defect. Here, we demonstrate a distinction between screw and edge dislocations that enables a unified, purely topological means of classification. Our construction relies on the construction of real or virtual disclination-line pairs at the core of the dislocation in a smectic and can be generalized to crystals with triply-periodic order. The connection between topology and geometry is exploited.