Papers

We use replica-exchange molecular dynamics (REMD) to map the conformational free-energy landscape of the macrocyclic drug lorlatinib in explicit water and chloroform. In water a single dominant basin is recovered; in chloroform two conformational states are resolved. We use these conformers as the starting point to calculate proton chemical shifts from first principles and a continuum solvent model. The resulting population-weighted spectrum is compared directly to the experimental CDCl$_3$ spectrum, benchmarking the computational approach against measured NMR data.

We test whether the maximum penetration depth of a circular intruder into a two-dimensional granular bed can be predicted from its early trajectory using machine learning, without giving the intruder density. From 100 DEM simulations with varying density, we extract kinematic features from the first 50 ms. Ridge and Random Forest predict the maximum penetration. A single feature (the intruder height at 50 ms) concentrates almost all predictive power, showing that density information is already encoded in the early impact response.

Young's law on a rigid solid and the Neumann balance at a three-fluid junction describe different admissible motions. We connect them through an ordered continuum construction. An affine viscoelastic third phase first acquires permanent deformation memory in the no-relaxation limit at fixed modulus. Independently specified material-surface laws distinguish surface free energy from mechanical surface stress. On the deformable support, displacement of solid material and migration of the wet-dry partition give separate equilibrium conditions. Stiffening an anchored support suppresses displacement at a fixed macroscopic observation distance but leaves reversible migration possible. The surviving variation gives Young's law; the constrained mechanics remains as a reaction carrying normal and, in general, tangential capillary loads. Two complementary results substantiate this reduction. A clamped finite-strain model with circular liquid interfaces yields uniform convergence of reduced energies and recovery of the spatial Young angle for global almost minimisers. A separate quadratic half-space model gives convergence of stationary migration derivatives and a nonzero limiting traction distribution. The results explain how a local Neumann-like ridge can coexist with a Young angle measured against the distant wall, while distinguishing geometric convergence from the control of migration and reaction forces.

Posture control in slender bodies such as snakes and eels arises from the interplay between passive deformation, active internal actuation, and task-level constraints. We formulate a general framework for the selection of stable postures in active elastic filaments subject to distributed forcing from gravity and fluid drag, by combining the constraints of mechanical equilibrium with optimal control theory. Our theory leads to a minimal description in terms of parameters governing the competition between hydrodynamic and gravitational loading, elasticity, and activity. We show that posture selection reflects a trade-off between control cost, function and dynamical stability, leading to the coexistence of distinct solution branches and abrupt transitions between them. Applying the theory to sessile eels in flow, we recover the experimentally observed transition from upright to reclining postures and predict scaling laws for body shape and exposed length. More generally, our results provide a unified perspective on how active filaments can regulate geometry to maintain function in external fields, with implications for biological and artificial systems.

Dielectric interfaces are ubiquitous in manufactured and natural systems, such as iontronic devices, supercapacitors, and living cells. These, often rough, dielectric surfaces host ionic charge distributions that depend on the surface geometry and the electric fields present. In this work, we study the effect of electric fields on such ionic charge distributions. We demonstrate, by molecular dynamics (MD) and perturbative analytic calculations, that the pattern of alternating regions of ionic charge density created by a sinusoidal interface can be modified and reversed by applying an electric field. We determine the strength of the critical electric field required to cancel the effect of dielectric interface-driven modulation in ion density and develop an analytic expression for that field for small amplitude sinusoidal variations in surface height. We show that ion concentrations near a surface with height given by a sum of Fourier modes can be found by adding the contributions from the concentration modulation due to each mode, allowing the possibility to predict ion distributions near rough surfaces. We updated and validated a LAMMPS package for MD simulation of polarizable surfaces, the DIELECTRIC package, by implementing a new version that achieves a 2.4-24 times speed increase by GPU parallelization on our test system and adds the capability to simulate an applied electric field on simple and complex electrolytes near dielectric interfaces with arbitrary roughness.

Micron-sized particles moving through a fluid are subject to viscous resistance and thermal fluctuations. Beyond steady Stokes friction, colloids also exhibit hydrodynamic memory effects arising from conservation laws of the surrounding fluid. Although fluid-flow problems in complex geometries and confinements are often highly involved, numerical or approximate solutions can be obtained; translating these solutions into closed-form equations of motion for individual colloids, however, is rarely possible. Here, we develop a theoretical framework that provides both underdamped and overdamped colloidal dynamics from the solution of an arbitrary flow problem: (i) Using the Lorentz reciprocal theorem, we express the colloidal equation of motion in terms of the geometry's Green's function and the fluid-flow profile. This formulation yields both the corresponding Stokes drag as well as a Basset-like hydrodynamic memory contribution. (ii) As colloid inertia is often negligible, we furthermore derive the corresponding overdamped (colloid-inertia-less) limit, which inherits the Stokes and Basset-like resistances and additionally gives rise to a spurious drift. We propose applications of this framework to passive and active particles subject to involved confinements and problem geometries.

Micron-sized colloid particles diffusing through a fluid experience hydrodynamic inertial and memory effects, the latter causing velocity autocorrelation to decay as a power law. At the same time, many theoretical descriptions treat colloidal diffusion in a fluid using overdamped Langevin dynamics for its convenience, eliminating velocity, omitting inertia, but also ignoring the power-law memory. In this Letter, we show that hydrodynamic memory survives in the overdamped (colloid-inertialess) limit. By identifying the dimensionless parameter controlling the crossover between early- and late-time dynamics, we derive in closed form the overdamped Langevin equation in the presence of hydrodynamic memory. This provides a theoretical framework for realistically describing colloidal dynamics in a fluid, and establishes a rigorous basis for the positional memory observed in high-resolution experiments. Our theory predicts that hydrodynamic memory becomes increasingly pronounced for smaller particles and under stronger external forcing, and offers experimental probes for the crossover from conventional exponential relaxation to memory-dominated power-law dynamics.

The area compressibility modulus is a key descriptor of lipid membrane mechanics, but the molecular interactions that determine this elasticity are not evident from the total modulus alone. Here, molecular dynamics simulations of a POPC bilayer described by the coarse-grained Martini 3 force field were combined with virial stress analysis to decompose the area compressibility modulus into contributions from molecular groups and their interactions. Partial lateral tensions were evaluated as functions of membrane area strain, and their derivatives at the equilibrium state were used to obtain the corresponding contributions to the area compressibility modulus. Hydrocarbon chains provided the dominant positive contribution, accounting for approximately 70% of the total modulus, whereas water-lipid interactions contributed approximately 30%, predominantly through water-headgroup interactions. Within the bilayer, the headgroup and headgroup-chain contributions were of similar magnitude but opposite in sign and nearly canceled. Direct intermonolayer interactions contributed only about 3% of the bilayer-only modulus, indicating an almost additive elastic response of the two monolayers. The hierarchy of elastic contributions differed markedly from that of equilibrium partial tensions, showing that interactions responsible for static stress balance are not necessarily those governing membrane stiffness. This decomposition provides a microscopic interpretation of lipid bilayer area elasticity.

The mechanical response of a moving probe in an active bath reflects both the dynamics of the bath and how the probe couples to it. For a probe moving at velocity $\mathbf V$ and interacting weakly with an ideal active bath, we show that the trajectory statistics of a free bath particle determine a density response from which the bath force on the probe follows. The probe-particle interaction determines how this response is weighted over wave vector $\mathbf q$, while the probe motion selects frequencies $\omega_{\mathbf q}=\mathbf q\cdot \mathbf V$. This trajectory-response relation separates the bath dynamics from the wave-vector weighting, so neither the stationary state nor force correlations need to be recalculated for each probe interaction and velocity. Applying this relation to active-particle models, we prove that positive power transfer is excluded for active Ornstein–Uhlenbeck particles in all dimensions and for complete-reset run-and-tumble particles in $d\geq2$, while one-dimensional run-and-tumble particles and two-dimensional active Brownian particles possess modes that can transfer positive mechanical power. For a given probe, this response predicts drag reversal, spontaneous probe motion, and motion-induced density distortions, all in quantitative agreement with simulations. Varying the probe geometry changes how the same bath response is weighted, thereby selecting different moving states. Beyond the leading weak-probe, ideal-bath limit, higher orders in probe strength involve multi-interval trajectory statistics, while finite-density corrections involve interacting-particle dynamics. Our results connect the trajectory statistics of active bath particles to the mechanical response of a passive probe, providing a route to predict probe response from single-particle trajectory statistics measured in the absence of the probe.

Odd slip at solid-liquid interfaces, characterized by a velocity component perpendicular to the applied shear stress, introduces a novel class of odd transport phenomena with transverse momentum transfer at boundaries, distinct from odd viscosity, odd elasticity, or odd diffusivity. This effect arises on chiral active surfaces with persistent energy input and defined handedness, such as carpets of rotating biological or synthetic cilia with flexible anchoring. Although odd slip itself is dissipationless, its maintenance comes at an energetic cost, which we estimate from the microscopic model. With respect to its orientation dependence, odd slip can be classified as pseudo-scalar or pseudo-vectorial. We use a perturbative expansion to determine the resistance tensors of problems with different levels of broken symmetries. They reveal how the surface chirality and body asymmetry together violate the Onsager symmetry, but uphold the Onsager-Casimir reciprocity. Strikingly, suspensions of particles with odd slip embedded in a conventional Newtonian bulk fluid exhibit odd viscosity, providing a new minimal mechanism for its emergence beyond current microscopic models.

Active microrheology infers rheological properties from the motion of a force-driven probe. In small samples, however, the probe is often close to walls or other probes, and the resulting hydrodynamic interactions bias the inferred parameters. We present a Bayesian framework in which these interactions are built into simplified analytical models for Newtonian and linear viscoelastic fluids and test it on noisy synthetic data from finite-element simulations of Newtonian and Oldroyd-B fluids. Accounting for the interactions substantially improves the accuracy of the inferred parameters. Near a wall, oblique forcing allows the material parameters and the wall distance to be identified jointly from a single experiment. In the nonlinear viscoelastic regime, posterior predictive checks over multiple force levels reveal the inadequacy of the linear model. Finally, when the probe size is comparable to the heterogeneity length scale, the framework distinguishes spatial variations in the modulus from measurement noise.

This work considers the Enskog kinetic theory for moderately dense confined granular mixtures within the framework of the $\Delta$-model, an effective collisional model that accounts for the transfer of energy from the vertical to the horizontal degrees of freedom of grains through an additional velocity increment during collisions. The main objective is to complete the Navier–Stokes hydrodynamic description of dense binary granular mixtures by explicitly determining the heat-flux transport coefficients, namely the Dufour and thermal conductivity coefficients, together with the first-order contributions to the partial temperatures and the cooling rate. These quantities are determined in the steady state from the Enskog kinetic equation by means of the Chapman–Enskog method and are expressed in terms of the masses and diameters of the particles, mixture composition, density, and coefficients of restitution. The results show that finite-density effects have a significant influence on transport, leading to behaviors that differ markedly from those observed in the dilute regime. The complete set of transport coefficients is considered further to study two different problems. First, we perform a linear stability analysis of the homogeneous steady state (HSS). The analysis demonstrates that no unstable transverse or longitudinal hydrodynamic modes are found over the parameter space explored, indicating that the HSS is linearly stable even at moderate densities. As a second problem, the violation of the Onsager reciprocal relations for a confined dense granular mixture is quantified in terms of the parameter space of the problem.

Phase separation in network-forming materials couples mass transport to mechanical relaxation, yet how adsorbing boundaries reshape this coupling remains unclear. We compare fluid-particle-dynamics simulations resolving solvent hydrodynamics with free-draining Brownian dynamics for attractive colloids confined between parallel walls. Adsorbing boundaries do not slow coarsening uniformly but stratify the network into spatially distinct kinetic regimes. With hydrodynamics, the self-similar central network exhibits growth consistent with poroelastic relaxation, Lb~t^(1/2), whereas the adsorbed region follows an effective Lw~t^(1/3) law. In free-draining dynamics, central coarsening approaches t^(1/3), while the boundary exponent remains time dependent over the accessible times. Direction-resolved displacements reveal suppressed wall-normal motion and reduced lateral mobility near the walls. Increasing wall attraction connects adsorbed islands into an extended layer while leaving local dense-phase packing nearly unchanged. For island-like domains, we propose a testable encounter-controlled scaling framework linking boundary growth to domain geometry, size-dependent mobility, and evolving adsorbed mass. Locally self-similar central coarsening thus coexists with distinct or nonstationary boundary kinetics, precluding a common dynamic-scaling length for the central and adsorbed regions over the accessible times; in both regions, the growth law depends on whether solvent hydrodynamics is resolved.

We develop a two-dimensional inviscid model for extensible membranes with continuous vortex shedding from both edges, coupled to a weak spectral Galerkin discretization of the membrane equation that permits direct computation at zero bending rigidity. Viewing the pressure jump as a flux for bound vorticity explains how membranes respond to concentrated fluid loading. For fixed-fixed membranes, compliance draws the body toward the leading-edge vortex, delaying its detachment and enhancing lift primarily during start-up; after periodic shedding develops, compliance mainly amplifies the force oscillations rather than mean lift. Vortex detachment can unload heavy membranes into compression, producing bending-regularized wrinkles. For $R_2>0$, the membrane equation remains well-posed independently of the sign of the tension, provided the membrane remains an immersion. Releasing the trailing edge creates an intrinsic degeneracy: the tension vanishes at the free endpoint, making the $R_2=0$ problem formally underdetermined, while the weak formulation selects its bounded-energy branch. This vanishing-tension endpoint traps pressure disturbances and drives rapid tip-snapping; the dominant frequency and effective wave number approach their zero-rigidity limits with an inverse-logarithmic correction arising from a singular Bessel branch. Finally, decreasing the stretching modulus destabilizes periodic flutter, and the repeated fluid-driven departure and elastic return suggest a homoclinic tangle underlying the transition from periodic to chaotic flutter.

We explore the heat-rectification properties of a two-phase fluid confined in a nano-chamber with one wall coated with end-grafted polymers using molecular-dynamics simulations. We find a significant thermal diode effect for a wide range of chamber fillings for both very stiff and fully flexible polymers. A stationary heat flux is imposed on the system by fixing the walls at two different temperatures, computing the heat flow as a function of the filling density. The fluid presents a liquid phase, located close to the cold wall, and, for many fillings, a vapor phase in contact with the hot wall. A vapor-liquid interface is also present and located at different distances from the walls, depending on the fluid filling. We study the system by comparing two operational modes: a direct mode, in which the polymers are grafted on the hot wall and exposed to the vapor phase. In the inverse mode, the wall temperatures are swapped and the fluid rearranges to adapt to the interchanged temperature gradient. We calculate the mean heat flow, number density and temperature profiles for the stationary state in both modes. From them, we computed the density and temperature profiles, heat rectification coefficient, and resistivity profiles, for the two studied extreme cases of polymer bending rigidity. We found that, the nano-chamber presents a significant degree of heat rectification with different characteristics and filling density ranges. We describe the conditions to be met to obtain high thermal rectification as regards fluid filling, polymer properties and fluid-polymer affinity. They can be fine-tuned according to the application or material availability. In the direction parallel to the walls the system is easily scalable towards macroscopic sizes, without affecting the thermal rectification. This makes the soft-diode mechanism very versatile in geometry, size and materials choice.

Upstream swimming drives bacterial spreading and surface colonization. Many pathogens encounter fluid flows as they infect the intestines, lungs, and urinary tract, so how bacteria use their flagella to counter these flows matters for disease and treatment. Yet how morphology and flagellar arrangement govern motility against flow remains unknown. Here, we investigate the biophysical determinants of rheotaxis by combining microfluidics, directed evolution, genetics, holography, and hydrodynamics simulations. Using upstream swimming competitions, we find that peritrichous E. coli and S. enterica rapidly outcompete monotrichous P. aeruginosa and V. cholerae, accumulating upstream at densities up to five orders of magnitude higher, even though Vibrio swims three times as fast. Motility selection experiments show that rheotaxis increases with flagellar number and length, confirmed by overexpressing the master regulator flhD/C. Three-dimensional holography and single-cell tracking reveal that multiflagellarity stabilizes surface residence and promotes the weathervane effect that reorients cells upstream, a mechanism further supported by simulations that fully resolve flagellar arrangement and fluid-structure interactions. These results establish multiflagellarity as a key facilitator of upstream navigation, governed by near-wall residence and shear-driven reorientation rather than by swimming speed.

Snap-through is a sudden and large mechanical deformation that is usually triggered by driving a control parameter beyond a bifurcation threshold. Here, we study a buckled strip that undergoes a saddle-node bifurcation as one of its clamps is rotated. We show experimentally, theoretically, and numerically that the effective snapping threshold can be markedly lowered by speeding up the rotation. For actuation times that are short but nevertheless longer than the fundamental flexural period, the strip is observed to remain close to the instantaneous quasi-static equilibrium for most of the loading process. This allows us to derive an energetic criterion that accurately estimates a dynamic instability threshold well below the saddle-node bifurcation point. On the other hand, very near the bifurcation point, the evolution of the quasi-static equilibrium undergoes a geometric boost, which entrains the general motion of the beam. As a result, a slower actuation of the clamp than predicted by the energy argument suffices to produce snap-through. A distinct scaling is derived in that limit, based on the aforementioned boost and critical slowing down of the least stable vibration mode of the beam. More broadly, our results show how finite-rate forcing can trigger snap-through before the quasi-static instability threshold is reached

The last decade has seen the development of powerful methods for learning complex structure from high-dimensional data. These advances have brought to the foreground fundamental connections between subdisciplines of physics, applied mathematics, and machine learning. In this review, we bring together some of these ideas, often expressed in different languages, to highlight a conceptual thread that links five distinct fields: control theory, optimal transport, probabilistic inference, non-equilibrium thermodynamics, and machine learning. A common theme is the optimization of free-energy-like functionals under dynamical or statistical constraints. We offer a guided tour through this thread and present selected applications in reinforcement learning, variational inference, and generative modeling. The review does not assume prior familiarity with these topics, and begins with principles originating from physics.

We consider a minimal model of active agents which collectively learn to reach a target macroscopic state via a decentralized adaptation process. Agents are modeled as active Brownian particles which randomly reorient to a given direction through tumbling events. An average target state is encoded into a reward function evaluated by each agent. Agents can tune one of the parameters of their microscopic dynamics, called `policy' (e.g., speed or reorientation direction), to optimize their reward function thanks to information exchange with neighboring agents. We describe the evolution of the policy distribution across the agent population with a kinetic theory, under the assumption that the adaptation process is slow with respect to the physical dynamics. The adaptation process is illustrated on several learning protocols with either fixed or time-dependent target velocities. A characteristic learning time $\tau$ combining teaching and mutations emerges from the dynamics. For time-oscillating targets at angular frequency $\omega$, the collective dynamics oscillates in time, with an oscillation amplitude and phase shift determined by the product $\omega \tau$. An unlocking transition to a non-adaptable state is also observed for a rotating target velocity.

Liquid water is unusually stable, remaining liquid across a wide range of temperatures and even when confined to spaces only a few molecules wide. Yet it eventually fails in both settings: boiling at the critical temperature or drying in narrow pores, phenomena normally studied separately. Water's hydrogen-bond network is thought to underlie this stability, but tracking bond survival has not resolved the puzzle. Extending a concept we recently introduced for wetting (J. Am. Chem. Soc. 148, 21572 (2026)), we show that these stability limits can be accurately derived from a previously overlooked network property: resilience, the capacity to locally repair a broken bond. Only interactions too weak to be repaired constitute genuine defects, a far smaller population than conventional definitions suggest. While intact bonds remain abundant up to failure and conventionally broken bonds already percolate well before it, instability coincides with the percolation of these genuine defects. Comparing local interaction energies with a single intrinsic scale (identified a priori) predicts the wetting-hydrophobicity crossover, nanoconfinement cavitation, and bulk criticality. These phenomena are thus unified through a common molecular framework whose energetic scale also matches a long-unexplained spectroscopic feature of water. A single, parameter-free molecular criterion rooted in network resilience suffices.

We study the velocity and stress distribution for a planar granular flow in a wedge-shaped hopper using Discrete Element Method simulations. Periodic boundary conditions are used in the direction normal to the plane of the flow to simulate a layer system. A parametric study is carried out varying system parameters (orifice width, wedge angle, wall friction and hopper height) and particle properties (particle diameter and particle friction). Scaling relations are obtained for the velocity and stress ratios. The data indicate that the stresses are not dependent on the shear rate, as in the Mohr-Coulomb rheology, however, the friction coefficient varies spatially, and the coaxiality condition is violated in some regions of the flow. A theory based on the scaling relations is presented, which gives good predictions for all the cases studied. Based on the theory, an expression for the mass flow rate, incorporating the effect of system parameters and particle properties is derived, which gives a close match with the computed mass flow rates for all the cases.

We study an ordered polar active flock on a torus and show that topological sound persists on a compact curved surface without topological defects or physical boundaries. Using the covariant Toner Tu theory, we derive an effective nonHermitian Dirac operator whose curvature-induced mass changes sign across the outer and inner equators, producing two Jackiw Rebbi domain walls. These support co-propagating but distinct chiral edge excitations: a density mode localized on the positively curved outer equator and a Goldstone mode localized on the negatively curved inner equator. The bulk bands possess opposite half-integer Chern numbers whose jumps across the domain walls are determined by the sign of the Gaussian curvature. We further show that the localised modes are protected by a one-dimensional Callias index theorem, while the sum of the local indices obeys the Poincare Hopf theorem on the compact surface. Our results establish that curvature alone, independent of defects and boundaries, is sufficient to generate and protect topological sound in active matter, providing a unified connection between non-Hermitian topology, differential geometry, and hydrodynamic theory of collective motion.

Active matter is liable to invent protocols that evade the constraints of equilibrium thermodynamics. We put forward active pistons that extract work by periodic compression alone without changing any bulk property of the system. Such pistons necessarily couple the perturbation imposed by an external operator with some degrees of freedom internal to active components. We illustrate this design principle with elastic networks composed of self-aligning motile particles. For slow protocols, self-alignment always overwhelms mechanical friction when the internal activity exceeds a specific threshold controlled by fluctuations. We identify the key response coefficient that helps delineate regimes of work extraction, and reveal that the corresponding phase diagram follows a master curve with re-entrance in terms of noise amplitude. Overall, our active pistons embody a novel design principle with broad implications for building innovative engines far from equilibrium.

Dense suspensions can undergo a dramatic increase in viscosity at a critical value of the shear stress. This phenomenon, termed discontinuous shear thickening (DST), has been attributed to an increase in the fraction of particle interactions becoming frictional with increasing shear stress, and a successful mean-field theory has been developed to explain various accompanying rheological properties. On a microscopic scale, however, conventional structural analysis measures such as the grain-position pair correlation function show no significant changes with the onset of DST, though recent work has shown that similar analysis in the dual space of contact forces does lead to marked changes at this transition. Furthermore, experimental results have suggested the existence of higher-order microscopic correlations and the importance of incorporating fluctuations away from a mean-field description. To this end, we use a higher-order cluster analysis tool to study the force networks obtained from simulations of dense suspensions to construct an effective interaction potential in force space. We show that there are significant changes occurring in this potential as a function of density and stress close to DST. We discuss the implications of these observations on an emergent field theory of the DST transition.

One of the defining results in the study of active matter is the spontaneous flow instability, through which a homogeneous, uniformly aligned state breaks translational symmetry along a single direction and develops sustained flow. The vortex state that emerges at higher activity has instead been attributed to nonlinear dynamics. Using a Floquet-type linear stability analysis, we show that no such mechanism is required: the flowing state undergoes a secondary, zigzag instability that breaks the remaining translational symmetry and produces the vortex state. We further identify a regime in which the flowing state ceases to exist and vortices emerge directly from the uniformly aligned state. Under channel confinement, the instability selects a length scale that differs from the establishedactivelengthscale, andsetsthenumberofvorticesthatappear, leadingtoaconfinement- selected pattern reminiscent of a vortex lattice, opening a route toward direct experimental tests of this instability. Full nonlinear simulations reproduce the predicted onset activities and the selected vortex number.

Droplet-laden cloud dynamics emerge from coupled phase transitions and turbulent mixing. Combining experiments and mean-field theory, we establish scaling laws for steam-injected clouds in unsaturated air seeded with condensation nuclei. Depending on whether the cloud is confined to the initial momentum-dominated zone of the jet or extends into the buoyancy-dominated plume, two asymptotic regimes arise. In the momentum regime, cloud dimensions scale with the injector radius. In the buoyancy regime, size follows a \(\dot{m}^{2/5}\) scaling, where \(\dot{m}\) is the injected steam mass flow rate. Assuming inter-droplet air remains humidity-saturated, our mean-field analysis predicts cloud persistence governed by enthalpy and humidity mixing. These findings bridge microphysical processes and macroscale dynamics, offering a quantitative framework for atmospheric cloud evolution.

We investigate and compare a range of indicators for glassiness in monodisperse magnetic and non-magnetic soft-sphere fluids at low temperatures with a view to exploring the effect of the magnetic moment. We perform extensive molecular dynamics simulations using the Stockmayer model for magnetic fluids and a pure Lennard-Jones interaction for the non-magnetic case. Our investigations involve quenching experiments, in which both systems are rapidly cooled deep below their freezing temperatures. Although the Lennard-Jones fluid forms compact aggregates, the inclusion of dipolar interactions promotes the development of branched and open morphologies. After characterizing the static properties of the frozen structures, we focus on their dynamics. A key observable is the self-part of the van Hove function, which measures the probability that a particle is displaced by a distance $\Delta$ over time $t$. In both fluids, this function exhibits non-Gaussian behavior — thereby providing a signature of dynamic heterogeneity and glassiness. This behavior stems from a separation of time scales between two distinct processes: mobile particles that escape their environments and immobile particles that vibrate within cages. In particular, we find a heavier tail in the van Hove function for the Stockmayer fluid, which is a consequence of the strongly correlated motion in chain-like structures found there. These findings shed light on core relaxation mechanisms in magnetic fluids, advancing our understanding of magnetically responsive colloidal systems.

Nanoparticles can dramatically reinforce elastomers while paradoxically causing cavitation at lower strains. Despite decades of research, the microscopic origin of this behavior has remained unsettled. Here, molecular dynamics simulations reveal that cavitation and failure arise from the nanoparticulate reinforcement mechanism itself. Initial jamming of the nanoparticulate network leads to a buildup of negative pressure in the elastomer matrix, reinforcing it and simultaneously driving it towards a cavitation limit. This crisis is initially averted by yield of the particle network. However, an anisotropic rejamming event of the nanoparticles ultimately drives a runaway negative pressure buildup that leads to cavitation and failure. These results identify nanoparticle-network-induced thermodynamic cavitation as the origin of void formation in elastomeric nanocomposites, and they establish collective filler dynamics as a potential point of control of ultimate failure.

Pressure is a critical thermodynamic parameter that profoundly influences the physical properties of glasses. Pressure-induced densification and structural transformation endow glasses manufactured under such conditions with exceptional mechanical and optical properties. Although pressure-treated glasses have been characterized by ensemble-averaged methods such as X-ray diffraction and Raman spectroscopy, their microscopic dynamics have rarely been addressed, limiting our understanding of the coupling among structure, dynamics, and mechanics. Here, using a binary hard-sphere colloidal glass confined in cylindrical capillary tubes, we impose a constant pressure on the particles through the tangential component of gravity. This approach enables the first investigation of pressure effects on colloidal glasses. We find that the dynamics are substantially frozen, whereas the structural change remains comparatively mild. At low pressure, spatial correlations among structural, dynamical, and local elastic heterogeneities are observed. Remarkably, dynamical anisotropy emerges in response to pressure, characterized by faster motion parallel to the pressure direction than perpendicular to it. This anisotropy is attributed to an instability induced by the strong pressure force. Concurrently, structural and dynamical heterogeneities are strongly suppressed under pressure. Our experiments characterize the microscopic dynamics of colloidal glasses under pressure and offer design principles for the manufacturing protocol of glass materials.

Slowly sheared granular materials generally store mechanical energy and dilate between abrupt failures that release energy and compact the material. Here, simultaneous measurements of torque, layer thickness, acoustic emission, and photoelastic force networks reveal all four combinations of energy release or storage with contraction or dilation in a compressed granular fault. Most strikingly, some avalanches both dilate the layer and increase the elastic energy transmitted to the resisting boundary. These events reorganize force chains beyond the shear band and produce a distinct acoustic response. The results show that an avalanche need not relax a driven disordered material; it can instead redistribute stress into a more highly loaded configuration, a mechanism with potential relevance to the physics of both laboratory and natural faults.