Papers

The simulation of viscous fingering in porous media is of direct relevance to displacement processes in petroleum engineering and hydrogeology. Building on recent work proposing a modelling approach for well-defined fingers at very adverse viscosity ratios, we investigate the physical mechanisms behind viscous fingering and the modelling requirements for capturing the finger scales and saturation patterns observed in experiments. We simulate and match a viscous fingering experiment at a viscosity ratio of $\mu_{o}/\mu_{w}{=}2000$, discussing the physical significance of each modelling step. Linear stability analysis is used to characterize the early-stage instability of the displacement. Subsequent numerical simulations show that, for the simulated finger scales to match the experiment, the most unstable wavelength at onset must be several times smaller than the desired finger width—so that, after accounting for shielding and merging in the nonlinear regime, the fingers remain thin. Small-scale channelling effects are also required to disrupt the trailing stable region commonly observed in simulations of viscous fingering in nearly homogeneous media. Finally, we show that including a weakly oil-wet capillary pressure function enables our model to capture the bypassed oil observed in the experiment.

The Light-Heavy (LH) model involves two species of particles (light and heavy) coupled with a fluctuating surface (described by tilts). The dynamics include the inherent diffusion of the particles (or tilts) as well as the drive provided by the tilts (or particles). When the two are of similar magnitude, the system lies in the unscaled (uLH) regime, while a significantly weaker drive leads to the scaled (sLH) regime. In the unscaled limit, the model exhibits an order-disorder transition characterized by the fluctuation-dominated phase ordering (FDPO). In this state, interestingly the dynamics is driven by multiple modes, giving rise to dynamic clusters. Away from the critical regime the disordered phase retains vestiges of FDPO behavior on length scales smaller than the correlation length. We examine this local FDPO-like behavior by using a scaling function that links the off-critical and critical regimes. We next turn to the scaled model and show that the multi-mode dynamics present in the unscaled regime is replaced by dynamics that is effectively controlled by a single dominant mode in the scaled regime. Concurrently, the two-point correlations change from the $\mathcal{O}(1)$ FDPO form to an anomalous long-range form that decays as $1/\sqrt{L}$. Drawing on the analogy with the sABC model, where similar anomalous correlations appear at criticality, we derive an analytical expression for the two-point correlation function using the same approach used for that model.

Structured environments repeatedly redirect active particles, producing transport pathways that cannot be readily inferred from individual trajectories. Here, we show that the large-scale organization of these transport pathways is governed by topological constraints. Hydrodynamic scattering generates nonequilibrium current fields whose defect structure, characterized by integer indices, constrain transport pathways and renders them robust to smooth perturbations. This principle is demonstrated with rotating colloids in obstacle arrays and extended to stokeslet and force-dipole flows, thereby linking microscale transport to the topology of hydrodynamically generated nonequilibrium currents.

We develop an analytical theory for the dense packing of hard spheres in cylinders. Physically, our theory consists of a finite cylindrical masking of a close-packed three-dimensional solid and covers the entire range of cylinder aspect ratios, thus going beyond efforts that are focused on very tall cylinders in a narrow range of widths. We explicitly derive an exact equation for resulting packing fractions, valid for any regular lattice, and it provides a basis to understand the oscillations and scaling of volume fractions that have appeared in previous works. Our analytical relation serves as a rigorous lower bound and to tighten it we derive, and implement, an efficient mathematical procedure to optimize the orientation of the cylinder. Furthermore, we suggest simple techniques to improve on the predicted packings. Overall, we provide a general theoretical foundation for the packing of balls in cylinders, valid for all container sizes.

We use the density of surface-grafted polymers as a geometry-preserving control parameter for tuning the rheology of colloidal depletion gels. Reducing brush density accelerates gelation and produces gels with higher plateau storage modulus and yield stress. This mechanical enhancement is not accompanied by increased local densification; low-brush networks exhibit lower average contact number and reduced spatial heterogeneity while displaying stronger elastic responses than their high-brush counterparts. Our findings demonstrate a reduced coordination threshold to form elastic nodes in the low-brush gel network. In addition, low-brush gels relax more slowly, accumulate less creep deformation, and exhibit lower effective noise temperatures within the Soft Glassy Rheology framework. These results establish surface-brush density as an experimentally accessible control parameter for colloidal depletion gel rheology with coupled changes in effective attraction, network architecture, and contact kinematics.

We apply a modal framework for investigating the effect of density variations on gravity-type driven flows at the nanoscale. Using eigenfunction decomposition of the density and acceleration fields, each shear-pressure mode is separated into a homogeneous contribution and an inhomogeneous contribution determined by the Fourier amplitudes of the density and applied acceleration. This decomposition provides a direct means of identifying how density variations and external forcing couple and govern the flow behavior. We first revisit the Poiseuille flow and show that for channel heights larger than the characteristic intermolecular distance the homogeneous contribution dominates the long wave length (small wave vector) response, consistent with previous simulation results. In contrast, for sinusoidally driven flow, selective excitation of acceleration modes can produce the opposite behavior, with the inhomogeneous contribution dominating the long wave length response. The results show that the effect of the density variations depends on the specific flow; specifically the detailed mode coupling between the acceleration and density fields. The framework presented here provides a direct systematic approach for understanding and predicting the flow depending on the applied acceleration.

We numerically study motility-induced phase separation of active particles in two-dimensional convection rolls. We analyse local packing-fraction distributions, density fluctuations, the corresponding phase diagrams, and diffusivity curves to characterise the interplay between self-propulsion, global packing fraction, and advection strength. In the weak-flow regime, the system exhibits phase separation characterised by bimodal density distributions, slowly decaying density fluctuations, and a sharp reduction in diffusivity. Increasing advection suppresses clustering by enhancing particle transport and reducing trapping, leading to a shift in the critical self-propulsion velocity for motility-induced phase separation and a shrinkage of the spinodal region. Beyond the intuitive suppression of clustering by weak-flow advection, our results reveal several non-trivial phenomena including a reentrant phase behaviour where extremely high self-propulsion hinders motility-induced phase separation by facilitating particle escape from dense regions. We also observe that the density distributions strongly depend on roll periodicity. These findings demonstrate that convection rolls provide an effective means to control non-equilibrium collective behaviour in active matter.

Poroelastic materials, such as polymer tissue scaffolds, porous rocks, and hydrogels, can weaken due to interactions between the solid skeleton and chemical species in the interstitial fluid. We develop a mathematical model for a poroelastic material to provide fundamental mechanistic insight into how weakening the material can affect the time-varying mechanics of the system. Our model couples large-deformation poroelasticity with an advection-diffusion equation for the solute. Furthermore, we introduce a decay equation for the material stiffness, whose rate of decay depends on the solute concentration. In this way, we describe a three-way coupling between poroelastic deformation, weakening of the skeleton and transport of solute through the material. We exploit numerical and analytical techniques to reveal the flow-driven uniaxial compression of a weakening poroelastic material and determine parameter regimes for which weakening the material facilitates pore closure at the downstream boundary. We identify parameter regimes in which (1) a steady state is attained without pore closure, (2) pore closure occurs at a finite time or (3) the pores close instantaneously; we uncover case (2) through the introduction of weakening into the system. We provide insights into the relationship between the differing behaviours and the separation between the timescales of the system. For systems with slow weakening, we derive a leading-order approximation for the time of pore closure, treating the ratio of the timescales of poroelastic relaxation and weakening as a small parameter, and investigate the accuracy of this approximation and the new behaviours that arise when these timescales become comparable.

In crowded environments, active polymers can trap themselves by winding into long-lived conformations. We show that fluctuations of the surrounding confinement can resonantly accelerate escape from these self-generated traps. Brownian dynamics simulations of a driven semiflexible chain in a breathing obstacle lattice reveal intermittent switching between a compact rotating spiral and an extended translating state. Long-time diffusion increases by up to two orders of magnitude when the environmental fluctuation rate becomes comparable to the spiral's intrinsic relaxation rate. The enhancement persists under stochastic fluctuations, showing that coherent periodic forcing is not required. Activity creates a second optimum: it promotes escape once favorable conformations form, yet at strong drive stabilizes the spiral and suppresses their formation. Resonant untrapping thus provides a general mechanism by which fluctuating environments regulate transport through barriers generated by internal conformational dynamics.

Liquid bridges suspended between two parallel horizontal cylinders are studied using experiments, reduced-order mathematical modelling and numerical simulations. Both non-electrified and electrified configurations are considered, with the cylinders acting as electrodes between which a potential difference can be applied. The initial focus is on equilibrium bridge shapes, while the dynamics is examined only in the non-electrified case. In the experiments, transformer-oil bridges are investigated and modelled as perfect dielectrics. The electric field counteracts the gravitational effects and causes the bridges to rise and become flatter, with shapes that are well described by Young–Laplace-type equations containing non-local electric-field contributions evaluated using a boundary-element method. Bifurcation diagrams of these solutions are constructed by pseudo-arclength continuation to characterise the dependence of bridge shapes on liquid volume and electric-field strength. In the absence of an electric field, the transient relaxation to equilibrium is analysed using a reduced-order model developed using Onsager's variational principle, with comparison to direct numerical simulations. The steady states predicted by the reduced-order model agree closely with those of the full formulation over a wide parameter range, and the dynamics is well captured in the overdamped regime.

A body floating atop a supersaturated fluid may accumulate bubbles along its underbelly, which can render the body rotationally unstable. But rotation can strip the surface of these bubbles when they make contact with the air above. To explore this coupling we perform experiments using cylinders floating on carbonated water. The cylinders exhibit an array of distinct dynamics, including constant rolling, periodic and aperiodic oscillation, chaos, and intermittent capsizing, which can be tuned by body size, mass distribution, and gas concentration. A continuum model for the bubble density dynamics, and Galerkin projection, tie the experiment to the generalized Lorenz system and its famed chaotic attractor. Even an extremely small center-of-mass offset can have a qualitative impact on the dynamics, and an offset of as little as a few percent can fully stabilize the system. The experiment represents a highly accessible physical realization of the Lorenz system, which, owing to continuous gas loss from the fluid to the air above, sweeps slowly without intervention across a classical bifurcation diagram in time.

While the bulk structure of vapor-deposited glasses has been extensively studied, structure at buried interfaces has received little attention, despite being important for organic electronic applications. To learn about glass structure at buried interfaces, we study the structure of vapor-deposited glasses of the organic semiconductor DSA-Ph (1,4-di-[4-(N,N-diphenyl)amino]styryl-benzene) as a function of film thickness; structure is probed with grazing incidence X-ray scattering. We deposit on silicon and gold substrates and span a film thickness range of 10-600 nm. Our experiments demonstrate that interfacial molecular packing in vapor-deposited glasses of DSA-Ph is more disordered compared to the bulk. At a deposition temperature near room temperature, we estimate ~ 8 nm near the substrate can have modified molecular packing. Molecular dynamics simulations of a coarse-grained representation of DSA-Ph reveal a similar length scale. In both the simulations and the experiments, deposition temperature controls glass structure beyond this interfacial layer of a few nanometers.

The acceleration of structural relaxation or physical aging by deformation, known as overaging, has been reported in experiments and simulations of polymer and colloid glasses, and correctly accounting for overaging is important for the prediction of the long-term behavior of polymer glasses in engineering applications. Here the effects of cyclic loading/unloading on the segmental dynamics and mechanical properties of PMMA glasses are investigated using a probe reorientation technique and time-aging time superposition of the mechanical response, respectively. Sets of 5000 tensile loading/unloading cycles were performed at temperatures between Tg - 10 K and Tg - 25 K with cycle extension strains ranging from 0.003 to 0.007. After cycling, the segmental dynamics measured with the probe reorientation technique either remained unchanged or were faster relative to an undeformed sample. The relaxation times of cycled glasses recovered with a common time scale on the order of their aging time, indicating that they retain a memory of their original age, as opposed to a full erasure of their thermal and mechanical history. Surprisingly, changes as a result of cycling were more obvious in probe reorientation measurements than in the mechanical properties, suggesting that the probe reorientation technique can sensitively detect nonlinear effects of deformation. No evidence of overaging was observed in the optical or mechanical measurements as a result of these cyclic loading/unloading experiments.

The last decade has seen great progress in manipulating the structure of vapor-deposited glasses of organic semiconductors. By varying the substrate temperature during deposition, glasses with a wide range of density and molecular orientation can be prepared from a given molecule. We review recent studies that show the structure of vapor-deposited glasses can be tuned to significantly improve the external quantum efficiency and lifetime of OLEDs (organic light emitting diodes). We highlight the ability of molecular simulations to reproduce experimentally observed structures, setting the stage for in-silico design of vapor-deposited glasses in the coming decade. Finally, we identify research opportunities for improving the properties of organic semiconductors by controlling the structure of vapor-deposited glasses.

Colloidal gels are frequently modeled as monodisperse particle networks, although practical formulations commonly contain particles with multiple characteristic sizes. Here, we use large-scale, hydrodynamically resolved simulations of colloidal depletion gels to isolate the effects of particle size and local packing in bimodal systems with a small-to-large size ratio of 1:2. Increasing the large-particle fraction introduces new heterotypic angular motifs and substantially increases the fraction of bonds participating in tetrahedral structures, with a maximum at intermediate composition. However, these additional rigid motifs do not reorganize into larger or more highly connected tetrahedral aggregates. The mean coordination and characteristic aggregate size remain nearly composition independent. By contrast, the void and cluster-size distributions coarsen systematically as the large-particle fraction increases. These mesoscale distributions largely collapse when normalized by a composition-dependent particle length scale, indicating that changes in composition primarily rescale gel architecture rather than producing distinct rigid-network topologies. An elastic modulus estimated using Cauchy-Born theory similarly follows this effective length scale more closely than the abundance of local tetrahedral motifs. These results show that, for moderate size disparity, particle size controls the structural scale and predicted mechanical response of bimodal colloidal gels more strongly than enhanced local packing.

We formulate a physics-informed data-driven method for modeling anisotropic pairwise interactions in the presence of long-ranged electrostatics. The method separates the total interaction into a long-ranged electrostatic interaction that is approximated using a multipole expansion truncated at the dipole level and a short-ranged residual interaction that is approximated using multivariate Chebyshev polynomials fit to measurements from a limited number of configurations. We assess the approach on a sequence of aromatic molecules (benzene, benzonitrile, and phenoxide), finding that it produces satisfactory results using a modest cutoff distance for the short-ranged interaction. This method has applications for modeling complex interactions for, and conducting dynamic simulations of, synthetic and biological materials with charge.

We report structural and physical investigations on the biaxial smectic-A phase exhibited by a compound consisting of asymmetric bent-core molecules. Upon cooling from the isotropic phase, the compound exhibits the following phase sequence: Isotropic (403.9 K) $\rightarrow$ biaxial Smectic-A (359.8 K) $\rightarrow$ Crystal. The polarized optical microscopy, X-ray diffraction, and polarization reversal current measurements clearly establish the biaxial nature of the smectic-A phase without any layer polarization. The measured layer spacing in the entire temperature range of the smectic-A phase is close to the molecular length. The schlieren texture in a homeotropically aligned sample shows both $\pm \frac{1}{2}$ and $\pm 1$ defects which indicate the biaxial nature of this smectic-A phase. The dielectric spectroscopy studies on the samples revealed Debye-type relaxation processes with the relaxation time following the Arrhenius equation with temperature. Interestingly, the observed biaxial smectic-A phase exhibits a remarkable electro-optic response for a planar-aligned sample without any reorganization of the smectic layer structure.

Soft materials remember their deformation history, and identifying that memory from experiments is essential for predicting how these materials behave under real-world loading conditions. Chirp rheometry has recently emerged as a way to accelerate this characterization, compressing hours of conventional measurement into seconds and yielding thousands of stress-strain pairs per experiment. That density is then largely discarded: the standard pipeline reduces the record to a handful of frequency-domain estimates before any constitutive model is fitted. We introduce a physics-informed Gaussian process framework that infers the material's constitutive law directly from the raw time-domain record of a single chirp, selecting among candidate memory kernels and parametrizing the selected one without any intermediate signal processing step. Because the framework infers the memory kernel rather than the specific waveform used during training, it predicts the response to deformation histories it never saw, without retraining. The method also resolves material evolution within a single chirp directly in the time domain.

In this work, we adopt a finite strain computational homogenization approach to characterize the response of semi-flexible biopolymer networks modeled as idealized 8- and 14-chain periodic networks. We use the geometrically exact special Cosserat rod theory to model the microscale fibers forming these 8- and 14-chain networks. This allows us to capture arbitrarily large microscale deformations. Both macroscopic strain- and stress-driven homogenization are performed to study the macroscopic uniaxial tension, compression and simple shear responses. Several phenomena unique to biopolymer networks are recovered such as strain-stiffening and volume shrinkage under uniaxial tension, softening under compression and reverse Poynting effect under simple shear. We find that nonlinearity and non-affine deformation at microscale, especially bending and buckling of microscale fibers, plays an important role in these phenomena. We obtain the postbuckled solutions of the homogenization problem using a nonlinear, imperfection-free path following approach and also check for their stability. We further compare our homogenization results with experimental data for uniaxial tension and compression of biofilament networks and find good agreement. When the fibers are replaced by helical rods in the 8-chain unit cell, we are also able to capture the enlarged stretching behaviour as shown in recently fabricated compliant metastructures.

A major challenge in the field of heterogeneous catalysis is selecting an optimal catalyst support structure. Commercially available structures can be easily manufactured at scale, but their stochastic nature makes their chemical and transport properties suboptimal. This is particularly relevant for gas-generation reactions, where non-uniformity of a porous structure leads to bubble trapping. Such trapping impedes the flow of reactants to catalyst sites, leading to conversion inefficiencies. Previous experimental work demonstrated that spinodally-derived architectures, in particular bicontinuous interfacially jammed emulsion gels (bijels), can alleviate these issues and deliver superior performance. However, to the best of our knowledge, numerical studies to optimize the operating conditions for such a morphology have not been performed yet. In this work, we aim to close this gap using color-gradient lattice Boltzmann simulations of reactive flows with a novel central moments collision operator. We develop an analytical model to predict catalyst performance based on our simulation data. Our findings show that this type of morphology can achieve very high conversion efficiencies. Moreover, we demonstrate that its catalyst performance can be optimized using superhydrophilic surface coatings.

We investigate the nonlinear shape dynamics and autonomous propulsion of actively driven quasi-spherical vesicles with locally inextensible membranes at low Reynolds number. Starting from Stokes hydrodynamics, linearized membrane elasticity, and harmonic active forcing, we derive a reduced description in terms of spherical harmonic deformation modes. The global area constraint enforced by local inextensibility is the sole source of dynamic nonlinearity. It confines the dynamics to compact manifolds in the space of possible shapes. Autonomous propulsion arises through nonlinear mode coupling and is determined geometrically by the oriented area swept by the trajectories in shape space. For two active modes, the dynamics reduces to a periodically driven phase equation exhibiting synchronization, phase slips, and mode locking. Introducing a third active mode fundamentally changes the dynamics, giving rise to quasiperiodic invariant tori and resonant periodic cycles. A recurrence diagnostic reveals the resulting resonance structure, while fluctuations of the cycle-averaged propulsion provide an experimentally accessible signature of the underlying shape dynamics. Our results demonstrate that, for actively driven vesicles, a geometric constraint is sufficient to transform an otherwise linear dynamical system into one exhibiting rich nonlinear dynamics.

GEMSS (GEnerator of Multi-Sphere Shapes) converts 3D surface meshes or voxel grids into multi-sphere representations of granular particles using the recently published MSS algorithm. It computes key physical properties required for discrete element method (DEM) and general multibody dynamics simulations, including particle volume, center of mass, and principal moments and axes of inertia. Implemented as a header-only C++ library, GEMSS is easily integrated into DEM and molecular dynamics frameworks. The library has been integrated into MercuryDPM, which enables on-the-fly generation of multi-sphere particles directly within the simulation loop.

The Multi-Sphere Shape Generator (MSS) [1] places spheres according to a feature-enhanced residual field, but the geometric basis of this strategy has remained unknown. We prove that every local maximum of the residual field lies on the medial axis of the target shape, implying that MSS places spheres at the centers of maximal inscribed spheres without explicit skeleton extraction. Numerical tests show that deviations from the exact medial axis are limited to the voxel resolution. This result provides a mathematical explanation for the placement strategy that underlies the accuracy of MSS.

Motile Escherichia coli bacteria can alter salt crystallization patterns during the evaporation of sessile droplets. In dilute bacterial suspensions in deionized water, dried bacteria cells predominantly accumulate at the droplet periphery, consistent with the classic "coffee-ring" effect. At higher cell densities, however, the bacterial distribution becomes more uniform. In the absence of bacteria, pure Phosphate Buffered Saline also forms salt crystals in a coffee-ring pattern. When bacteria are present alongside the salt solute, additional isolated crystals appear near the droplet center, with their abundance increasing with bacterial concentration, while crystals at the periphery adopt dendritic morphologies that extend radially. To investigate these phenomena, we used a Stokes-based analytical model to estimate the evolution of internal flow fields and compare them with bacterial motility. Then a finite volume model is implemented for bacteria and salt transport and adsorption, and a stochastic model for salt nucleation was developed, which successfully explains the crystallization pattern seen in the experiments. Our results show that bacterial motility can overcome evaporation induced flow during early stage, enabling bacteria cells to serve as nucleation sites and thereby altering the final crystalline morphology. This work highlights the potential of motile microorganisms to actively control evaporative crystallization, with implications for porous media flow and microfluidic deposition processes.

Growth is a fundamental process in living systems. Although the stress-deformation response of growing materials is often described as either purely elastic or purely viscous, many biological tissues, from biofilms to tumors, exhibit both elastic and viscous behavior. Here, we show that this viscoelastic response can crucially control the mechanics of proliferating matter when the growth rate becomes comparable to the rate of stress relaxation. Focusing first on the prototypical case of a growing elastic beam, we find that the dynamics are governed by a single dimensionless parameter, $g \tau$, where $g$ is the growth rate and $\tau$ is the viscoelastic relaxation time. While the limits $g \tau \to 0$ and $g \tau \to \infty$ recover purely viscous and purely elastic behavior, respectively, the intermediate regime is not merely a smooth crossover between them. Instead, qualitatively new dynamics emerge at $g \tau \sim 1$, including rapid transitions between metastable states that occur in neither limiting regime. We then develop a general, growth-compatible theoretical framework in which unconstrained growth is intrinsically stress-free, extending the analysis to other prototypical geometries and enabling simulations of more realistic growing biological materials. Within this framework, sharp mechanical transitions arise when stress generated by exponential growth accumulates faster than it can be dissipated by viscoelastic relaxation.

A flexible body placed in a steady flow bends to reduce drag. This self-streamlining is a hallmark of fluid-structure interaction (FSI). Granular-structure interaction is equally ubiquitous in nature. However, it remains poorly understood. Thus, we investigate inertial granular-structure interaction (IGSI). Specifically, ejection induced by a flexible plate sweeping a granular bed is experimentally examined. We find that a faster sweep results in less ejection, particularly for a flexible plate. To understand the underlying physics of this behavior, a dimensionless number Sk is introduced as the ratio of the plate elastic timescale to the sweep timescale. At $\mathrm{Sk} \lesssim 1$, the plate deflection follows the self-streamlining law of FSI and induces substantial ejection. At $\mathrm{Sk} \gtrsim 1$, on the other hand, the plate skims the bed and the mass of ejected grains decreases sharply. Sk organizes IGSI as the granular counterpart of FSI.

We demonstrate optical coherence tomography (OCT) as a measurement technique for dense, optically opaque suspensions. Conventional optical methods cannot access the interior of such suspensions. OCT resolves individual potato-starch particles (${\sim}20~\mathrm{\mu m}$) as distinct scatterers, even though the suspension appears opaque to the eye. By tracking the vertical centroid position of the particle-laden layer $\langle Z \rangle(t)$ and the supernatant boundary $Z_\mathrm{sup}(t)$ in the same OCT image sequence, we obtain the instantaneous settling velocity $V(t)$ and the time-evolving effective volume fraction $\phi_\mathrm{eff}(t)$ simultaneously and continuously in time. To our knowledge, this is the first measurement to combine settling velocity and particle concentration into a single continuous trajectory within one sedimentation run. Conventional batch measurements yield only one velocity value per run. We applied this method to dense potato-starch suspensions, varying the initial volume fraction $\phi_0$ from 0.30 to 0.50 and the solvent density $\rho_\mathrm{L}$ from 1.0 to $1.3{\times}10^3~\mathrm{kg~m^{-3}}$ using aqueous sodium polytungstate solutions. The normalized velocity $V/V_\mathrm{Stokes}$ plotted against $\phi_\mathrm{eff}$ collapses onto a common trend consistent with both the Krieger–Dougherty model and the Richardson–Zaki law over $\phi_\mathrm{eff} \simeq 0.30$–$0.52$, confirming that the method captures physically reasonable hindered-settling behavior. These results establish OCT as a viable tool for probing internal dynamics in dense suspensions that were previously inaccessible to optical measurement.

Mechanical properties of biological tissues, driven by passive and active forces, play a vital role in several processes ranging from development to cancer metastasis. However, the dynamical responses of cells in tissues, subject to mechanical deformations such as shear and the associated rheological properties, are not well characterized. Here, we use three-dimensional agent-based models for normal and cancer tissues to investigate their responses to simple shear as a function of cell stiffness and stochastic active forces. In the normal epithelium, with uniform strength of active force, the yield stress as a function of shear rate follows the Herschel-Bulkley form over a range of cell volume fraction. Strikingly, the shear rate dependence and the elasticity-dependent changes in the yield stress fall on master curves upon suitable scaling. To model cancer-like behavior, a certain fraction ($N_p$) of cells was chosen to have enhanced activity and decreased stiffness. As $N_p$ increases, the extent of collective cell movement decreases, transitioning from affine (collective) to non-affine (individualistic) movement, a finding that is in accord with imaging experiments. Simulations of a model of a stiff solid tumor, with radius $R_s$ embedded in normal tissue, show that as $R_s$ increases, the yield stress increases. Interestingly, the cells migrate collectively as $R_s$ increases. A Gaussian Mixture Model (GMM) and a mean field theory quantitatively account for the simulation as well as experimental results on cancerous, non-cancerous, and a mixture of these two types. The combined theoretical and experimental study establishes that heterogeneity in stiffness and activity determines non-affine movements in normal and cancer tissues.

ESPResSo++ is an open-source software package for molecular dynamics (MD) simulations with a particular emphasis on coarse-grained (CG) models of soft matter systems. Written in C++ with a flexible Python interface, it is designed for high-performance computing (HPC) environments and supports massively parallel simulations through MPI. The package enables simulations of polymers, membranes, colloids and complex fluids with a wide range of interaction models and advanced algorithms.

Mechanical separation of enantiomers is an attractive alternative to synthetic methods for producing enantiopure samples. Shear flow that produces solution vorticity has been shown to be a viable means for separating chiral objects on the micro- to nano-scale due to the tensorial nature of the interactions between chiral objects and the surrounding fluid. A recently-developed theory of molecular pitch characterizes these interactions using the resistance tensor and predicts the shear-induced separation of drug-like molecules from their optimized molecular geometries. We present a molecular dynamics study on the effects of incorporating molecular flexibility into the molecular pitch framework. We also evaluate the potential for enantiomeric separation of two drug molecules: bicalutamide (Casodex) and montelukast sodium (Singulair). Simulations reveal the emergence of flexibility-induced pitch distributions that result from conformational changes occurring in a realistic solvent environment. However, these distributions are weakly influenced by the solvent identity and the shearing process, producing mean scalar pitch values that are close to those from optimized gas phase structures. Despite the opposing effect of translational diffusion at the molecular scale, racemic mixtures of flexible enantiomers show linear rates of separation at the 10 ns timescale, and we predict that cm-scale separation can be achieved within hours. Additionally, we provide estimates for parameters of a Taylor-Couette device for generating laminar shear flow, as well as considerations for future experiments.