arXiv subjects

Aparna Baskaran

Publications and source records attributed to Aparna Baskaran.

At least 19 recordsLinked to original sources

arXiv2026

Controlling Turbulent Flows in Compressible Active Nematics

Motivated by experiments on light-patterned, quasi-2D active suspensions that exhibit large density variations, we develop a continuum theory of compressible active nematics--suspensions of apolar rods whose orientation is invariant under pi rotations. Under spatially patterned activity, the extensile isotropic active pressure expels material from high-activity regions and accumulates it in low-activity ones; an exactly solvable 1D reduction shows that the resulting density contrast is governed by a single dimensionless parameter, linear in the compressibility. Using compressibility as a tuning knob, we then steer active turbulence from high- to low-activity regions and, at sharp activity interfaces, stabilize an analytically tractable dynamical steady state: a one-dimensional chain of vortices held by soft, activity-induced confinement. Our results establish compressibility as a control parameter for density variations and turbulent flow in active nematic suspensions.

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arXiv2025

Segregation dynamics in active-passive mixtures of semiflexible filaments

We study the segregation of motile semiflexible filaments from a background of similar but non-motile filaments. Our Langevin dynamics simulations reveal a wide range of emergent structures governed by filament flexibility and activity, i.e., self-propulsion strength. The system segregates at low activities, while at high activities it undergoes remixing which is a characteristic feature of semi-flexible active filaments. We show that collision-induced softening of single filaments is the dominant mode for this remixing. We provide a scaling argument for the lowering of the active polymer stiffness and show that it agrees well with the lowering of the segregation order parameter. We expect that our studies will shed light on the spatial organization of biofilaments within the cell, on the plasma-membrane, and beyond, and help in the design of novel biomaterials whose structure can be tuned via the properties of the active or the passive filaments.

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arXiv2025

Coarsening of biomimetic condensates in a self-stirring active fluid

Coarsening, the process where larger structures grow at the expense of smaller ones, is a fundamental aspect of multiphase systems. The cell cytoplasm exemplifies an out-of-equilibrium multiphase system, where phase-separated condensates nucleate and expand within an active fluid made of biopolymers and energy-dependent enzymes. In this study, we explore how condensates grow in a self-stirring active fluid by examining the coarsening of biomimetic condensates embedded in a 3D reconstituted cytoskeleton composed of microtubules and molecular motors. The strong agreement among experiments, an active hydrodynamic model, and computer simulations offers a comprehensive framework that explains why self-similarity is absent in active coarsening and identifies the origins of the continuously changing coarsening exponents for both active and passive condensates. The dynamics of coarsening are primarily determined by the statistics of binary droplet collisions, which depend on their size-dependent motility, regardless of whether they are active or passive. These results reveal a unifying control parameter for the coarsening process and size distribution of active condensates, broadening our understanding of phase separation in out-of-equilibrium systems and potentially impacting materials science and biology.

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arXiv2025

The mechanics of disclination emergence in 3D active nematics

The spontaneous creation of disclinations is a defining characteristic of active nematics, which is rarely observed in equilibrium systems or other active matter systems. Thus, understanding the mechanics of disclinations is crucial for developing reliable continuum theories and practical applications. In this work, we explore this intrinsic mechanics by performing large-scale 3D simulations of a particle-based model of active semiflexible filaments. We investigate the effects of filament stiffness and activity on the collective behavior of active nematics. Analysis of the steady state and the topological properties of initial disclination loops reveals that the system is governed by a single parameter, an activity-dependent effective stiffness. Then, we develop a method to visualize director field orientations in a physically transparent manner during the formation of disclination loops. Based on this, we establish a unified theory for the mechanics of disclination emergence, across the range of bend and twist. This disclination analysis framework can also be applied to diverse other 3D liquid crystal systems.

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arXiv2024

Active noise-induced dynamic clustering of passive colloids

Active fluids generate spontaneous, often chaotic mesoscale flows. Harnessing these flows to drive embedded soft materials into structures with controlled length scales and lifetimes is a key challenge at the interface between the fields of active matter and nonequilibrium self-assembly. Here, we present a simple and efficient computational approach to model soft materials advected by active fluids, by simulating particles moving in a spatiotemporally correlated noise field. To illustrate our approach, we simulate the dynamical self-organization of repulsive colloids within such an active noise field in two and three dimensions. The colloids form structures whose sizes and dynamics can be tuned by the correlation time and length of the active fluid, and range from small rotating droplets to clusters with internal flows and system-spanning sizes that vastly exceed the active correlation length. Our results elucidate how the interplay between active fluid time/length scales and emergent driven assembly can be used to rationally design functional assemblies. More broadly, our approach can be used to efficiently simulate diverse active fluids and other systems with spatiotemporally correlated noise.

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arXiv2024

Achieving designed texture and flows in bulk active nematics using optimal control theory

Being intrinsically nonequilibrium, active materials can potentially perform functions that would be thermodynamically forbidden in passive materials. However, active systems have diverse local attractors that correspond to distinct dynamical states, many of which exhibit chaotic turbulent-like dynamics and thus cannot perform work or useful functions. Designing such a system to choose a specific dynamical state is a formidable challenge. Motivated by recent advances enabling opto-genetic control of experimental active materials, we describe an optimal control theory framework that identifies a spatiotemporal sequence of light-generated activity that drives an active nematic system toward a prescribed dynamical steady-state. Active nematics are unstable to spontaneous defect proliferation and chaotic streaming dynamics in the absence of control. We demonstrate that optimal control theory can compute activity fields that redirect the dynamics into a variety of alternative dynamical programs and functions. This includes dynamically reconfiguring between states, and selecting and stabilizing emergent behaviors that do not correspond to attractors, and are hence unstable in the uncontrolled system. Our results provide a roadmap to leverage optical control methods to rationally design structure, dynamics, and function in a wide variety of active materials.

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arXiv2024

Spatiotemporal control of structure and dynamics in a polar active fluid

We apply optimal control theory to a model of a polar active fluid (the Toner-Tu model), with the objective of driving the system into particular emergent dynamical behaviors or programming switching between states on demand. We use the effective self-propulsion speed as the control parameter (i.e. the means of external actuation). We identify control protocols that achieve outcomes such as relocating asters to targeted positions, forcing propagating solitary waves to reorient to a particular direction, and switching between stationary asters and propagating fronts. We analyze the solutions to identify generic principles for controlling polar active fluids. Our findings have implications for achieving spatiotemporal control of active polar systems in experiments, particularly in vitro cytoskeletal systems. Additionally, this research paves the way for leveraging optimal control methods to engineer the structure and dynamics of active fluids more broadly.

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arXiv2024

Deep-learning Optical Flow Outperforms PIV in Obtaining Velocity Fields from Active Nematics

Deep learning-based optical flow (DLOF) extracts features in adjacent video frames with deep convolutional neural networks. It uses those features to estimate the inter-frame motions of objects at the pixel level. In this article, we evaluate the ability of optical flow to quantify the spontaneous flows of MT-based active nematics under different labeling conditions. We compare DLOF against the commonly used technique, particle imaging velocimetry (PIV). We obtain flow velocity ground truths either by performing semi-automated particle tracking on samples with sparsely labeled filaments, or from passive tracer beads. We find that DLOF produces significantly more accurate velocity fields than PIV for densely labeled samples. We show that the breakdown of PIV arises because the algorithm cannot reliably distinguish contrast variations at high densities, particularly in directions parallel to the nematic director. DLOF overcomes this limitation. For sparsely labeled samples, DLOF and PIV produce results with similar accuracy, but DLOF gives higher-resolution fields. Our work establishes DLOF as a versatile tool for measuring fluid flows in a broad class of active, soft, and biophysical systems.

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arXiv2023

A Machine Learning Approach to Robustly Determine Director Fields and Analyze Defects in Active Nematics

Active nematics are dense systems of rodlike particles that consume energy to drive motion at the level of the individual particles. They exist in natural systems like biological tissues and artificial materials such as suspensions of self-propelled colloidal particles or synthetic microswimmers. Active nematics have attracted significant attention in recent years due to their spectacular nonequilibrium collective spatiotemporal dynamics, which may enable applications in fields such as robotics, drug delivery, and materials science. The director field, which measures the direction and degree of alignment of the local nematic orientation, is a crucial characteristic of active nematic and is essential for studying topological defects. However, determining the director field is a significant challenge in many experimental systems. Although director fields can be derived from images of active nematics using traditional imaging processing methods, the accuracy of such methods are highly sensitive to the settings of the algorithms. These settings must be tuned from image-to-image due to experimental noise, intrinsic noise of the imaging technology, and perturbations caused by changes in experimental conditions. This sensitivity currently limits automatic analysis of active nematics. To address this, we developed a machine learning model for extracting reliable director fields from raw experimental images, which enables accurate analysis of topological defects. Application of the algorithm to experimental data demonstrates that the approach is robust and highly generalizable to experimental settings that are different from those in the training data. It could be a promising tool for investigating active nematics and may be generalized to other active matter systems.

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arXiv2023

Flow states of two dimensional active gels driven by external shear

Using a minimal hydrodynamic model, we theoretically and computationally study active gels in straight and annular two-dimensional channels subject to an externally imposed shear. The gels are isotropic in the absence of externally- or activity-driven shear, but have nematic order that increases with shear rate. Using the finite element method, we determine the possible flow states for a range of activities and shear rates. Linear stability analysis of an unconfined gel in a straight channel shows that an externally imposed shear flow can stabilize an extensile fluid that would be unstable to spontaneous flow in the absence of the shear flow, and destabilize a contractile fluid that would be stable against spontaneous flow in the absence of shear flow. These results are in rough agreement with the stability boundaries between the base shear flow state and the nonlinear flow states that we find numerically for a confined active gel. For extensile fluids, we find three kinds of nonlinear flow states in the range of parameters we study: unidirectional flows, oscillatory flows, and dancing flows. To highlight the activity-driven spontaneous component of the nonlinear flows, we characterize these states by the average volumetric flow rate and the wall stress. For contractile fluids, we only find the linear shear flow and a nonlinear unidirectional flow in the range of parameters that we studied. For large magnitudes of the activity, the unidirectional contractile flow develops a boundary layer. Our analysis of annular channels shows how curvature of the streamlines in the base flow affects the transitions among flow states.

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arXiv2023

From Disks to Channels: Dynamics of Active Nematics Confined to an Annulus

Confinement can be used to systematically tame turbulent dynamics occurring in active fluids. Although periodic channels are the simplest geometries to study confinement numerically, the corresponding experimental realizations require closed racetracks. Here, we computationally study 2D active nematics confined to such a geometry -- an annulus. By systematically varying the annulus inner radius and channel width, we bridge the behaviors observed in the previously studied asymptotic limits of the annulus geometry: a disk and an infinite channel. We identify new steady-state behaviors, which reveal the influence of boundary curvature and its interplay with confinement. We also show that, below a threshold inner radius, the dynamics are insensitive to topological constraints imposed by boundary conditions. We explain this insensitivity through a simple scaling analysis. Our work sheds further light on design principles for using confinement to control the dynamics of active nematics.

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arXiv2023

Design principles for transporting vesicles with enclosed active particles

We use coarse-grained molecular dynamics simulations to study the motility of a 2D vesicle containing self-propelled rods, as a function of the vesicle bending rigidity and the number density, length, and activity of the enclosed rods. Above a threshold value of the rod length, distinct dynamical regimes emerge, including a dramatic enhancement of vesicle motility characterized by a highly persistent random walk. These regimes are determined by clustering of the rods within the vesicle; the maximum motility state arises when there is one long-lived polar cluster. We develop a scaling theory that predicts the dynamical regimes as a function of control parameters, and shows that feedback between activity and passive membrane forces govern the rod organization. These findings yield design principles for building self-propelled superstructures using independent active agents under deformable confinement.

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arXiv2022

Data-driven discovery of active nematic hydrodynamics

Two-dimensional active nematics are often modeled using phenomenological continuum theories that describe the dynamics of the nematic director and fluid velocity through partial differential equations (PDEs). While these models provide a statistically accurate description of the experiments, the identification of the relevant terms in the PDEs and their parameters is usually indirect. Here, we adapt a recently developed method to automatically identify optimal continuum models for active nematics directly from the spatio-temporal director and velocity data, via sparse fitting of the coarse-grained fields onto generic low order PDEs. We test the method extensively on computational models, and then apply it to data from experiments on microtubule-based active nematics. Thereby, we identify the optimal models for microtubule-based active nematics, along with the relevant phenomenological parameters. We find that the dynamics of the orientation field are largely governed by its coupling to the underlying flow, with free-energy gradients playing a negligible role. Furthermore, by fitting the flow equation to experimental data, we estimate a key parameter quantifying the `activity' of the nematic.

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arXiv2021

Dual antagonistic role of motor proteins in fluidizing active networks

Cells accomplish diverse functions using the same molecular building blocks, from setting up cytoplasmic flows to generating mechanical forces. In particular, transitions between these non-equilibrium states are triggered by regulating the expression and activity of cytoskeletal proteins. However, how these proteins set the large-scale mechanics of the cytoskeleton and drive such non-equilibrium phase transitions remain poorly understood. Here, we show that a minimal network of biopolymers, molecular motors, and crosslinkers exhibits two distinct emergent behaviors depending on its composition, spontaneously flowing like an active fluid, or buckling like an active solid. Molecular motors play a dual antagonistic role, fluidizing or stiffening the network depending on the ATP concentration. By combining experiments, continuum theory, and chemical kinetics, we identify how to assemble materials with targeted activity and elasticity by setting the concentrations of each component. Active and elastic stresses can be further manipulated in situ by light-induced pulses of motor activity, controlling the solid-to-fluid transition. These results highlight how cytoskeletal stresses regulate the self-organization of living matter and set the foundations for the rational design and control of active materials.

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arXiv2021

Steady states of active Brownian particles interacting with boundaries

An active Brownian particle is a minimal model for a self-propelled colloid in a dissipative environment. Experiments and simulations show that, in the presence of boundaries and obstacles, active Brownian particle systems approach nontrivial nonequilibrium steady states with intriguing phenomenology, such as accumulation at boundaries, ratchet effects, and long-range depletion interactions. Nevertheless, theoretical analysis of these phenomena has proven difficult. Here we address this theoretical challenge in the context of non-interacting particles in two dimensions, basing our analysis on the steady-state Smoluchowski equation for the 1-particle distribution function. Our primary result is an approximation strategy that explicitly connects asymptotic solutions of the Smoluchowski equation to boundary conditions. We test this approximation against the exact analytic solution in a 2d planar geometry as well as numerical solutions in circular and elliptic geometries. We find good agreement so long as the boundary conditions do not vary too rapidly with respect to the persistence length of particle trajectories. Our results are relevant for characterizing long-range flows and depletion interactions in such systems. In particular, our framework shows how such behaviors are connected to the breaking of detailed balance at the boundaries.

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arXiv2021

Confinement-induced Self-Pumping in 3D Active Fluids

Two dimensional active fluids display a transition from turbulent to coherent flow upon decreasing the size of the confining geometry. A recent experiment suggests that the behavior in three dimensions is remarkably different; emergent flows transition from turbulence to coherence upon \emph{increasing} the confinement height to match the width. Using a simple hydrodynamic model of a suspension of extensile rod-like units, we provide the theoretical explanation for this puzzling behavior. Furthermore, using extensive numerical simulations supported by theoretical arguments, we map out the conditions that lead to coherent flows and elucidate the critical role played by the aspect ratio of the confining channel. The mechanism that we identify applies to a large class of symmetries and propulsion mechanisms, leading to a unified set of design principles for self-pumping 3D active fluids.

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arXiv2021

Vesicle shape transformations driven by confined active filaments

In active matter systems, deformable boundaries provide a mechanism to organize internal active stresses and perform work on the external environment. To study a minimal model of such a system, we perform particle-based simulations of an elastic vesicle containing a collection of polar active filaments. The interplay between the active stress organization due to interparticle interactions and that due to the deformability of the confinement leads to a variety of filament spatiotemporal organizations that have not been observed in bulk systems or under rigid confinement, including highly-aligned rings and caps. In turn, these filament assemblies drive dramatic and tunable transformations of the vesicle shape and its dynamics. We present simple scaling models that reveal the mechanisms underlying these emergent behaviors and yield design principles for engineering active materials with targeted shape dynamics.

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arXiv2020

Nonreciprocity as a generic route to traveling states

We examine a non-reciprocally coupled dynamical model of a mixture of two diffusing species. We demonstrate that nonreciprocity, which is encoded in the model via antagonistic cross diffusivities, provides a generic mechanism for the emergence of traveling patterns in purely diffusive systems with conservative dynamics. In the absence of non-reciprocity, the binary fluid mixture undergoes a phase transition from a homogeneous mixed state to a demixed state with spatially separated regions rich in one of the two components. Above a critical value of the parameter tuning non-reciprocity, the static demixed pattern acquires a finite velocity, resulting in a state that breaks both spatial and time translational symmetry, as well as the reflection parity of the static pattern. We elucidate the generic nature of the transition to traveling patterns using a minimal model that can be studied analytically. Our work has direct relevance to nonequilibrium assembly in mixtures of chemically interacting colloids that are known to exhibit non-reciprocal effective interactions, as well as to mixtures of active and passive agents where traveling states of the type predicted here have been observed in simulations. It also provides insight on transitions to traveling and oscillatory states seen in a broad range of nonreciprocal systems with non-conservative dynamics, from reaction-diffusion and prey-predators models to multispecies mixtures of microorganisms with antagonistic interactions.

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