Papers

Biological membranes are highly deformable structures that undergo shape transformations during numerous cellular processes. These transformations are often driven by active agents, including molecular motors, cytoskeletal machinery, and motile microorganisms, which consume energy and maintain biological systems far from equilibrium. Here, we investigate how a single active particle confined within a lipid vesicle drives membrane deformation. Using a lipid-resolved coarse-grained model, we examine how the activity and shape of an encapsulated self-propelled particle influence vesicle dynamics and morphology. Active particles generate persistent propulsion that exerts mechanical stresses on the enclosing membrane, thereby driving its deformation. Using particles of different shapes but identical surface area, we systematically investigate membrane morphologies as functions of activity and bending rigidity. We quantify membrane deformation through asphericity and excess bending energy relative to the equilibrium spherical state. Both measures exhibit a non-monotonic dependence on activity, peaking at intermediate activity. At sufficiently high activity, membrane rupture occurs before significant large-scale deformation can develop, limiting further remodeling. We further demonstrate that membrane surface tension plays a significant role in regulating activity-induced deformation dynamics.

Bubbles frequently emerge in dense chiral active fluids, yet it remains unclear whether they result from an instability of the homogeneous state or from rare nucleation events within a metastable phase. Here we develop a nucleation theory for chiral bubble formation by reducing the hydrodynamic equations to a single collective coordinate, the bubble radius. This reduction yields an effective nonlinear potential that captures the radial dynamics and predicts distinct stable, metastable, and unstable regimes of the homogeneous state. In the metastable regime, the theory identifies a critical bubble radius and an associated effective mechanical-work barrier, while its large-radius behavior determines whether bubble growth saturates at a finite size or becomes unbounded. We further analyze the stability of circular bubbles against noncircular perturbations, finding growing modes that can lead to elongation and breakup. The theoretical predictions are tested against event-driven molecular-dynamics simulations of chiral hard disks, which reproduce the predicted trends in the critical radius, nucleation barrier, and selected bubble size. Our results establish a unified framework for stability and nucleation in chiral active fluids and suggest routes to control bubble formation in experiments with spinning colloids and chiral spinners.

Traditional theories of electrolyte and polyelectrolyte solutions overlook ion and polymer hydration, yielding an overly idealized perspective of the thermodynamic and dynamic properties of these solutions. In particular, the propensity of certain ions to increase or decrease the water diffusion coefficient at low solution concentrations, is poorly understood, a phenomenon that correlates strongly with the Hofmeister series describing the influence of salts on the solubility and self-assembly of synthetic and biomacromolecules as well as colloidal particles. These ion-specific effects have profound ramifications in diverse biological, medical science and technological applications. We address the general problem of understanding ion and uncharged water-soluble polymer hydration through molecular dynamics (MD) simulations of representative water-soluble polymers, polyacrylamide (PAM) and polyethylene oxide (PEO), in aqueous salt solutions. Careful attention is given to the capacity of our model to reproduce observed trends of added monovalent salts on the diffusion coefficient of water. Reproducing these ion-specific trends in the mobility of water has been a recurrent challenge in prior MD simulations of aqueous solutions based on a physically realistic model of water. Our work on salt solutions represents an important advance on which we build our modeling of aqueous polymer solutions with added salts. Simulations of our model polymers reveal an extended nanoscale dynamic hydration layer having a scale on the order of one nanometer (nm) in which the mobility is perturbed from its bulk value, and the mobility gradient in this layer appears to obey a near universal functional form.

The competitive interactions arising from the proximity of positive and negatively charged groups in the monomers in polyzwitterions (PZ) makes these polymers have properties similar in some ways to intrinsically disordered proteins. To gain qualitative insights into this important class of water-soluble polymers, we performed molecular dynamics (MD) simulations of a model PZ chain with an explicit solvent to understand the conformational state in the absence and presence of added salt. We find that isolated PZ chains under salt-free conditions adopt a self-associated state having a weak dependence on temperature. The addition of an appreciable amount of NaCl leads to a weakening of the intrachain associations, resulting in chain expansion, a transition reminiscent of the denaturation of globular proteins. In particular, the hydrodynamic penetration function, the ratio of hydrodynamic radius to the radius of gyration, of the PZ chains under salt free conditions, is found to be more consistent with a randomly branched polymer or single chain nanoparticle than a random coil polymer where the physical cross-links within the chain arise from the dipoles within the chain. The chain conformation not only tends to become larger with the addition of salt but also acquires a more appreciable temperature dependence of its average size with temperature. This swelling trend of PZ molecules with added salt, sometimes referred to as the anti-polyelectrolyte effect, is distinct from the normal trend polyelectrolytes, which typically become more contracted with the addition of salt. We also examined the spatial extent of the dynamic hydration layer the PZ chain, both with and without added salt, and the effect of temperature and salt concentration on the water mobility within this layer, and PZ side-chain mobility, whose dynamics is apparently strongly coupled to the surrounding water molecules.

We investigate experimentally the dynamic phase transition from compressed to buckled phases for thin sheets of rubber. We find that the rubber strips enter a highly compressed, metastable state when compression speed is high. During the compressed phase, higher modes grow, followed by mode coarsening. Mode growth is accompanied by an expansion of length while the system is still being compressed. We measure the forces and length of the sheet to confirm this, and we develop a mechanism for how modes grow and coarsen during dynamical buckling. The influence of crucial control parameters in the experiments, such as the material cross section and compression speed, on the buckling dynamics, are explained theoretically.

Self-propelled particles that only repel one another can still separate into a dense and a dilute phase, a process known as motility-induced phase separation (MIPS). In a clean system the domains coarsen like any conserved mixture: domains grow as $\ell(t)\sim t^{1/3}$. Living and synthetic swimmers, however, move through rough, porous, or patterned surroundings. Using large-scale simulations of active Brownian particles, we ask how frozen heterogeneity changes MIPS coarsening. We introduce disorder in two ways, as a quenched random force field acting on particle positions and as a quenched random torque field acting on their orientations. Both destroy Lifshitz-Slyozov growth. A transient power law with a disorder-dependent exponent gives way to activated dynamics in which the effective dynamic exponent grows without bound and domains grow at most logarithmically. The crossover obeys the scaling form known from the random-field Ising model, and the domain morphology depends on disorder strength, so superuniversality fails. The two kinds of disorder act through different mechanisms. Random forces trap particles in the sinks of a random drift field once the drift beats self-propulsion. Random torques act as a sign-random, quenched chirality that erodes persistence and lowers the local Péclet number toward its critical value. Our results show that quenched disorder is a relevant perturbation for the kinetics of active phase separation and connect MIPS coarsening to the physics of pinned interfaces in disordered magnets.

We examine the dc driven transport of particles with Yukawa interactions through an assembly of chiral active particles undergoing circular motion. The driven particles exhibit a jammed phase, a nonlinear disordered or plastic regime where there is a finite Hall effect produced by interactions with the active chiral particles, and a high drive linear regime where the driven and nondriven particles phase separate and the Hall effect nearly disappears. The chiral particles experience strong drag and Hall effects from the driven particles, and these effects vary monotonically with changing thermal fluctuations or chiral motion parameters. The different dynamical phases are correlated with features in the longitudinal and transverse transport curves, and we map out the phases as a function of active orbit size, thermal fluctuations, and particle density.

Predicting the relationship between surface charge density and electrostatic potential for spherical particles remains a fundamental challenge in colloid science. Because the governing non-linear Poisson–Boltzmann equation lacks a general exact analytical solution, researchers typically rely on numerical calculations or various semi-empirical approximations. In this paper, we overcome these limitations by developing a dual-asymptotic framework that provides explicit, closed-form expressions for this surface charge–potential relationship across the entire spectrum of particle curvature. For weakly curved systems, where the Debye length $\lambda_D$ is much smaller than the particle radius $R$ ($\lambda_D/R \ll 1$), a formal mathematical derivation rigorously establishes the Ohshima–Healy–White formula as an exact regular perturbation expansion. Conversely, for highly curved spheres ($R/\lambda_D \ll 1$), we employ singular perturbation analysis using the scaled particle radius as the small parameter. This approach provides a first-principles mathematical justification for the spherical Debye–Hückel theory, proving that its leading-order expansion remains asymptotically exact within the full non-linear Poisson–Boltzmann framework due to the geometric deactivation of non-linearity. Crucially, we map the exact limits of this geometric regulation, demonstrating how non-linear screening re-emerges as the particle radius increases, with the breakdown threshold governed by the interplay between curvature and surface charge density.

During embryonic development and cancer progression, clusters of cells migrate collectively following external cues. Such migrating cell clusters have been modeled as active droplets wetting a substrate. So far, this active wetting model assumed the cluster to take the symmetric shape of a spherical cap. Here, in contrast, we experimentally show that migrating clusters of frog neural crest cells have asymmetric height profiles, with a lower contact angle at the front than at the rear. We then extend the active wetting model by deriving an equation for the cluster shape, which becomes part of the solution rather than an assumption. Our model shows that shape asymmetry can arise from the asymmetric tractions that drive cluster migration: They generate a pressure gradient across the tissue which, via the Young-Laplace equation, leads to a curvature gradient on the cluster's upper surface. Finally, by fitting the theoretical predictions to the measured height profile, we estimate the tissue viscosity. Overall, our results provide a general mechanism for the emergence of asymmetric shapes in migrating cell clusters, understood as active droplets on a wettability gradient.

We investigate the performance characteristics of an active magneto gyrator that consists of an inertial charged active particle confined in a two-dimensional asymmetric parabolic potential coupled to two thermal baths maintained at two different temperatures and in the presence of a magnetic field applied perpendicular to the plane of motion. In contrast to the passive Brownian gyrator, where the power-efficiency trade-off imposes strict operational limits, the active magneto gyrator exhibits striking violations of this rule, allowing regimes in which both output power and efficiency increase simultaneously with load strength. Moreover, while the Thermodynamic Uncertainty Relation (TUR) predicts that highly efficient engines necessarily produce strongly fluctuating power, rendering the Brownian gyrator unusable as the efficiency approaches the Carnot bound, the active magneto gyrator circumvents this constraint. Specifically, it achieves high efficiency with minimal power fluctuations, thus defying the TUR. Remarkably, efficiency can even surpass the Carnot limit and approach 100%, without compromising stability. This condition cannot be achieved in the absence of either activity or a magnetic field. These results highlight the active magneto gyrator as a promising setup for designing stochastic heat engines that can transcend Carnot efficiency.

The cell cortex and cell adhesion contribute to the mechanics of epithelial cells and hence tissues. Vertex models of epithelia represent the cell cortex and cell adhesion, but these models mostly ignore the other subcellular structures that compose the cytoplasm surrounded by the cortex. Here, we reveal the mechanical consequences of these structures in a minimal vertex model of an epithelial monolayer, in which the single-cell energy includes a cytoplasmic contribution that represents, e.g., the cost of confinement of cytosolic polymers. Strikingly, our simulations show that the buckling transition of the monolayer under compression becomes discontinuous in an intermediate range of values of the associated cytoplasmic modulus. By asymptotic solution of this buckling problem in the continuum limit of the model, we explain this reentrant behaviour in terms of the tricritical points of a sixth-order Landau theory. Our results thus underline how cell-scale mechanics beyond the cortex and cell adhesion can change emergent, tissue-scale behaviour even qualitatively.

We identify an entropy-mediated mechanism underlying the spatiotemporal organization of the chromosome in the bacterial cell Caulobacter crescentus. Effective entropic interactions between replicating DNA segments emerge from their topological modifications of daughter DNA polymers caused by transient ParA-ParB binding. Enthalpic contributions arising from the ParABS system further influence their dynamics. In C. crescentus, chromosome replication and segregation occur concurrently before cell division. The origin of replication oriC of the mother chromosome of C. crescentus is tethered to the old cell pole. Replication generates two daughter oriCs, one of which remains anchored at the old pole. The other oriC is actively transported toward the new pole by the ParABS system of proteins even as replication of the rest of the chain is in progress. How ParABS generates a directed force to transport a daughter oriC to the opposite pole during chromosome replication remains unclear. Furthermore, the two daughter chromosomes get neatly segregated into two halves of the cell. In a bead-spring polymer model of the replicating C. crescentus chromosome, we model transient ParA-ParB contacts that generate DNA loops and an effective entropic repulsion. This repulsion drives chromosome segregation and produces oriC trajectories consistent with experiments, aided by the ParA concentration gradient near the new pole. This minimal framework, incorporating the physics of topologically modified (ToMo) polymers, allows us to quantitatively reproduce the time-dependent spatial organization of different tagged loci and replisomes observed in multiple experiments. Incorporating a minimal model of extrusion also allows us to recover the linear arrangement of the chromosome arms, as is inferred from the characteristic diagonals of Hi-C maps.

Universal rheological properties of unentangled polymer melts are investigated through the stretch-orientation decomposition of polymer dynamics. By externalizing stretch from the explicit state of each Rouse mode, we construct a constitutive model with orientational kinetics that preserves the Rouse relaxation spectrum. The resulting model yields the observed steady-shear scalings of the shear viscosity and first normal-stress coefficient, predicts a finite second normal-stress coefficient, and approximately reproduces the Cox-Merz and Gleissle-Osaki rules. The derived steady-oscillatory shear correspondence further identifies an elastic contribution, associated with the first normal stress difference, that is absent from the conventional Cox-Merz rule.

We study an equilibrium system, where linear molecules with a rigid charge distribution interact via the mean-field generated by the Coulomb coupling. We focus on the nonlinear regime, which is valid close to external charges immersed in the system. The finite molecular size in this regime leads to a nonlocal response at short distances. First, we show that the mean-field potential is non-monotonic, i.e., like charges can attract each other. Second, we show that the polarization induced by an external charge (and hence its solvation structure) depends on the sign of this charge, violating the effective C-symmetry of the macroscopic electrodynamics. We identify several scenarios of this effect, characterize it with the free energy and entropy differences, and compare it with analogous effects in asymmetric electrolytes described by nonlinear Poisson-Boltzmann equations.

A highly coarse-grained model for the lipid monolayer is formulated by considering a two-dimensional system of spherical particles with distinct types of S, U, and C, corresponding to the saturated, unsaturated, and cholesterol molecules. Their interactions are defined as modified Lennard-Jones type with distinct interaction strengths. The phase behavior of the system is studied for various cholesterol compositions, $x$ ranging from 0.1 to 0.6. From the simulation results, we observe that the S- and C-type particles segregate together to form ordered microdomains, with U-type particles at their outer leaflet; consistent with observations in literature. An order parameter $\Phi$ is defined to quantify the extent of phase separation among the constituents. The time averaged value of $\Phi$ is found increasing with the $x$ value. Radial distribution function calculations indicate the structural ordering within the phase separated domains.

Many physical and biological systems -foams, membranes, elastic shells, or tissue sheets- can be mathematically described as 2D surfaces. These surfaces can host complex dynamics, like reaction-diffusion systems, and undergo drastic deformations. Here, we present triangulax, an open-source Python library for simulations and geometry processing that discretizes surfaces using triangular meshes available at https://github.com/nikolas-claussen/triangulax. It combines two features. First, discrete differential geometry provides coordinate-free discretization, which allows simulating strongly deforming surfaces. Second, the library is built on the machine-learning framework JAX, so mesh-based energies and entire simulations can be differentiated automatically (including simulations with stochastic forces or topological modifications). This simplifies multi-physics simulations by computing forces automatically and allows fitting model parameters to experimental data or design objectives. We implement an algorithm to preserve mesh quality in strongly deforming surfaces and apply it to a model of membrane mechanics coupled to an on-membrane concentration field. We validate our approach against exact solutions and existing software, and demonstrate triangulax across a range of problems, including membrane mechanics, vertex models, and inverse design of a shape-morphing elastomer sheet.

We recently proposed a framework for the steady mass flux of particles through circular apertures [R.~S.~Sharma et al., Phys. Rev. Lett. 136, 068204 (2026)]. Here, we combine experiments and discrete-element simulations of spherical particles discharging through triangular and rectangular apertures to test this framework beyond circular openings. Despite changes in aperture shape, we observe a similar free-fall flux, with a modified relevant transport length. Deviations due to confinement reflect packing modifications, which are explained by geometry. A boundary layer dilation imposed by the aperture edge is shown to be a mechanism for the decrease of flux across various aperture shapes. By integrating the local packing deficit over the opening, we identify a hydraulic diameter $D_h=4A/P$, where $A$ and $P$ are the aperture area and perimeter, respectively, as the leading confinement length. This length also provides a reference scale, $\sqrt{gD_h}$, for the mean outlet velocity when the aperture is much larger than an individual particle. The same local packing model predicts the field in a lens-shaped aperture without further fitting, while the normalized discharge rates follow a common trend across the tested shapes.

Hard Magnetic Soft Materials, i.e., elastomers seeded with hard magnetic particles, convert magnetic energy into complex motion and have become central to the design of untethered soft robots, biomedical devices, and, in general, for enabling fast, wireless actuation. Their behavior depends critically on how the surrounding soft matrix deforms and transmits torque to each magnetized inclusion, yet there is no consensus on the correct mapping between macroscopic strain and microscopic motion. Competing models predict conflicting particle rotations and magnetic responses under identical loads. Here, we construct counterexamples that show the key shortcomings in these models, and then establish a first-principles framework that leads to an optimal deformation mapping. The resulting closed-form law unifies conflicting models and shows that they are, in fact, simply different limits of our general approach. Our work permits the rational design of magnetically actuated soft devices and a unified view of deformation in magnetic soft matter, and broadly, in similar architectured materials.

Shear transformations are the elementary events of plasticity in glasses and underpin many mesoscopic models of plastic flow, yet their atomic origin and energetics remain difficult to establish. Here we use a machine-learned interatomic potential to show that, in amorphous carbon as a representative network glass, a shear transformation corresponds to the breaking or formation of a single covalent bond. The simplicity of the associated reaction coordinate, the bond length, enables us to extract energy landscapes and barriers. Despite the intrinsic structural disorder, we find that all energy landscapes collapse onto a universal barrier shape. What remains bond-specific is a single scale, the bond-jump distance, which fixes the barrier height through a cubic law. Combined with the activation statistics of shear transformations, this yields a model that predicts the plastic flow stress from independently determined bond-level quantities. Our results provide microscopic support for phenomenological models of plastic flow in glasses and suggest a route towards a quantitative description of amorphous plasticity.

Selective advantage leads to the proliferation of a species into an ecosystem. On the other hand, self-propulsion can lead to dynamic clustering of individuals. To analyze the intricate effects produced by such competing processes, we introduce a minimal model for a proliferating active population, where run-and-tumble migration is combined with a stochastic birth-death process. Beginning with the microscopic dynamics of the particles, we derive the corresponding hydrodynamic equations and validate them through numerical simulations. We demonstrate that the inclusion of activity leads to the emergence of novel morphological patterns, which are sensitive to the specific rules governing migration. Furthermore, we show that activity significantly alters the characteristics of invasion waves, increasing their propagation speed. However, beyond a threshold, excessive activity disrupts the wave-like nature of the invasion process. We also extend our study to two dimensions and analyze the instabilities that lead to pattern formation in such systems.

Density waves in gravity-driven granular pipe flow reduce transport efficiency and produce large fluctuations in the local solid fraction. Helical wall textures suppress these instabilities but at the expense of reduced throughput. Using discrete element simulations (DEM), \RefA{we find that this homogenization is associated with} spiral particle motion induced by the helical wall texture. Quantifying this motion by the mean angular velocity reveals a strong correlation between spiral motion, flow homogenization, and transport performance. Motivated by this insight, we introduce a helical pipe whose centerline follows a helical path while maintaining a constant circular cross section. This design generates stronger spiral motion than conventional helical wall textures. For suitable design parameters, the helical pipe simultaneously enhances flow homogeneity and increases the mean flow velocity beyond that of a plain straight pipe. These results support spiral motion as a useful diagnostic and design variable for simultaneously improving flow homogeneity and transport efficiency within the investigated parameter range.

We show that a two-dimensional chiral fluid supports an antisymmetric contribution to the pressure, and determine its microscopic expression. Its origin lies outside the standard kinetic and collisional channels of the normal pressure tensor, stemming instead from the average of a parity-breaking pseudo-scalar. This chiral pressure is set by the rotational (vortex) viscosity of micropolar hydrodynamics, whose kinetic value for rough disks we compute here, to Gaussian order. Crucially, both the chiral pressure and the rotational viscosity survive at zeroth order in the gradients, meaning they persist even in the fully homogeneous fluid – which we show is not only well defined but steady (the Quiescent Chiral State, QCS). Since this averaged pseudo-scalar does not vanish in a chiral fluid, any expansion of its distribution function must contain terms in this pseudo-scalar variable.

Pneumatic conveying at moderate gas velocities can result in strongly heterogeneous particle transport, with slow particles accumulating near the bottom of the pipe while faster particles are transported above. Here, we investigate helical pipes as a passive means of homogenizing particle transport without increasing the gas velocity. CFD-DEM simulations show that the helical pipe induces swirling motion of the gas and particles, continuously redistributing particles across the pipe cross-section. This transforms the heterogeneous transport observed in a straight pipe into a more homogeneous state with a narrower particle-velocity distribution. The results demonstrate that helical pipes can maintain efficient pneumatic conveying at moderate gas velocities while reducing excessive particle velocities.

Many microgravity experiments require centimeter-sized spherical liquid drops. In drop-tower experiments, only a few seconds of microgravity are available, so the drops must be generated and reach a nearly relaxed state within a very short time. We investigate capillary auto-ejection (puddle jumping) as a passive mechanism for producing free-floating drops and investigate how the supporting cavity can be shaped to minimize the relaxation time after ejection. For cavities with a parabolic cross-section filled with a fixed liquid volume, minimization of the initial liquid surface area yields a unique shape, and smoothed particle hydrodynamics simulations show that this shape also gives the shortest relaxation time within the parabolic family. Introducing a shallow central depression into the cavity reduces the relaxation time further, despite producing a larger initial liquid surface area. These results provide design principles for capillary-driven drop generators that enable the rapid production of relaxed centimeter-sized drops during the short microgravity intervals available in drop towers.

The active Brownian particle (ABP) model is one of the most widely used particle-based models in studies of scalar active fluids. A collection of interacting ABPs is known to exhibit intriguing phenomena that are absent in equilibrium counterparts. A prominent example is spontaneous phase separation, known as motility-induced phase separation (MIPS), which occurs even in the absence of explicit attractive interactions. In parallel, the large-scale behavior of scalar active fluids is often modeled using continuum descriptions, namely, scalar field theories. Such scalar active field theories are usually formulated in a top-down manner, and establishing their connections to particle-based models remains challenging, with these connections not yet fully understood. To advance the microscopic derivation of scalar active field theories, we revisit the connection between ABPs interacting via a two-body potential in two dimensions and scalar field theories that include all possible terms up to fourth order in spatial gradients. Our approach is based on a pressure expansion and the renormalization group (RG) method in the context of singular perturbation theory. The RG method provides a systematic way to eliminate fast variables and identify the dynamics on the slow invariant manifold. Within this framework, scalar field theories can be obtained as RG flow equations. We also apply this method to a chiral variant of the ABP model, the chiral ABP (cABP) model, in which a constant torque biases particle rotation to the left or right. We show that the scalar field theory corresponding to the cABP model contains two “odd” terms in addition to those present in the scalar field theory for ABPs. The method developed here may also be useful for deriving hydrodynamic descriptions of other types of active matter systems.

Dense melts of nonconcatenated ring polymers exhibit anomalous dynamics and nonlinear rheology, in some cases linked to long-lived inter-ring threading entanglement. Detecting these geometric constraints remains computationally demanding, with different methods being based on different geometric features tuned to specific models. Here, we introduce a machine-learning framework that detects threading directly from the writhe of ring conformations and we demonstrate its broad generalisability. Trained on simulations of isolated, distance-constrained pairs of short rings, a one-dimensional convolutional neural network (CNN1D) operating on the writhe profile classifies threading states with over 98% accuracy on held-out ring pairs. Remarkably, this model generalises without retraining to equilibrium dense melts spanning a wide range of densities and chain lengths (N = 100 to 1600), maintaining true-positive rates above 91% with false-positive rates near zero. Misclassified conformations are limited to physically ambiguous, shallow threading events which are arguably not impacting the dynamics of the rings. Effectively, writhe captures the interaction between the two rings, allowing writhe-based classifiers to improve the topological analysis of large ring-polymer systems with a 3-fold speed-up over the state-of-the-art minimal-surface detection. These results establish the writhe-trained neural networks as an accurate, scalable tool for characterising entanglement in ring polymer melts.

Phyllosilicate clays are widely used in polymer nanocomposites owing to their high anisotropy and tunable surface polarity. Their distribution and interface localization in polymer blends can be used to tune the properties of polymer-clay nanocomposites (PCNCs). A coarse-grained (CG) force field for clays can aid molecular simulations in PCNC development. Here, we developed MARTINI-3 parameters, a CG force field with high chemical specificity, for phyllosilicate clays with diverse surface polarities. Initial interactions for the clay functional groups were determined from hydration free energies, obtained by applying the Lifshitz theory to experimental surface tension data. These were fine-tuned using the structural, thermodynamic, and dynamic properties of thermoplastic starch (TPS)-clay composites from all-atom (AA) molecular dynamics (MD) simulations. The radial distribution function and two-body excess entropy of TPS components, not used in CG parameterization, were accurately estimated, establishing the robustness of the parameters. We investigated the effect of clay surface polarity on polymer segmental dynamics and structure-property relationships. The CG parameters were then used to study the effect of dodecyltrimethylammonium (C12TAB)-modified montmorillonite (MMT), an organically-modified MMT, on TPS-polyethylene (PE) blend morphology using large time- and length-scale MD simulations. We observed compatibilization of the TPS-PE interphase by the amphiphilic clay particle, reducing the TPS-PE interfacial tension from 45 mN/m to 13.06 mN/m. We found good agreement between MARTINI-3 estimates for properties of model MMT-based PCNCs and those from AA simulations and experimental data, establishing grounds for the transferability of the parameters to other systems.

Peptide sequence governs both the structures formed through supramolecular assembly and the dynamics by which they emerge, but predicting either requires resolving slow collective processes among many interacting molecules. Molecular dynamics (MD) provides microscopic insight into these processes, yet the long timescales of assembly and the vast peptide sequence space make systematic exploration computationally demanding. We introduce SupraTITO, a transferable generative molecular dynamics (GenMD) framework for supramolecular systems, demonstrated through peptide self-assembly. SupraTITO learns transferable implicit transfer operators (TITO) conditioned on peptide sequence, molecular topology, and periodic geometry, allowing configurations to be propagated over physical intervals much longer than an MD integration step. On a comprehensive dipeptide benchmark, SupraTITO generalizes to held-out sequences and reproduces sequence-dependent structures and dynamics while maintaining molecular integrity over long rollouts. Compared with direct ensemble prediction trained on the same trajectory data, SupraTITO more accurately reproduces assembly structures while also resolving their temporal evolution. The learned dynamics generalize across peptide concentrations, including dilute conditions not represented during training. These results extend transferable GenMD to collective dynamics in periodic supramolecular systems and provide a foundation for modeling related processes beyond peptide assembly.

Extending a fundamental concept of thermodynamics to the nonequilibrium realm of active matter, we derive an ideal gas law for a suspension of noninteracting active particles confined to a finite rectangular box. The law is exact for run-and-tumble particles (RTPs) in one dimension and established by a systematic analytical expansion of the steady-state probability density for active Ornstein-Uhlenbeck particles in any dimension. It also agrees well with numerical results for active Brownian particles and RTPs in higher dimensions and recovers previously known relations for the limit of large system sizes. Together, these results demonstrate the applicability of the ideal active gas law to the three most widely studied theoretical models of colloidal active matter. As an application, we analyze thermodynamic processes involving active matter on a macroscopic level, without recourse to microscopic particle trajectories or self-propulsion fluctuations.

Bacterial swarming is the collective expansion of dense populations of motile cells across hydrated soft surfaces, yet gravity is usually treated as a fixed background condition in standard horizontal assays. We used surface inclination to examine how agar-surface orientation relative to gravity affects the expansion of Enterobacter sp. SM3 swarms. Colony expansion depended non-monotonically on inclination, with the strongest spreading at intermediate inclinations and weaker expansion under shallow or near-inverted conditions. Paired up-facing acute and down-facing obtuse configurations with the same tilt magnitude showed different expansion responses, suggesting that swarm expansion depended on both tilt magnitude and which side of the agar surface faced upward relative to gravity. Inclination also produced downhill-biased colony morphologies. PIV analysis showed generally lower mean activity under inclination than in the flat references, with a non-monotonic angular response and inward increases in speed and spatial velocity-correlation length. The downhill tip showed slower motion, shorter spatial correlations and smaller vortex cores than the upper region. To interpret the macroscopic trends, we extended a two-phase thin-film model by introducing an effective gravity coupling projected normal and tangential to the agar surface. Simulations suggest that the surface-tangential component mainly drives lateral redistribution, whereas the surface-normal component modifies film pressure and thereby pressure-dependent water replenishment, helping distinguish up-facing from down-facing configurations.