Anupam Gupta

We study spatiotemporal chaos in two-dimensional dense active suspensions using a generalized hydrodynamic model. Increasing activity induces a structural transition marked by the formation of intense vortices and giant number fluctuations at the mesoscale. The flow self-organizes into locally polar-ordered regions coexisting with chaotic domains, producing a bimodal velocity distribution and enhanced correlations. This mixed-state morphology underlies the universal statistical behavior observed beyond a critical activity threshold. Reducing the instability timescale yields similar transitions, showing that both activity and instability act as control parameters for pattern formation. An energy-based order parameter derived from the system's budget quantifies and unifies these structural transitions across the phase space of activity and instability timescales.

We simulate active Brownian particles (ABPs) with soft-repulsive interactions subjected to a four-roll-mill flow. In the absence of flow, this system exhibits motility-induced phase separation (MIPS). To investigate the interplay between MIPS and flow-induced mixing, we introduce dimensionless parameters: a scaled time, τ, and a scaled speed, V, characterizing the ratio of ABP to fluid time and speed scales, respectively. The parameter space defined by τ and V reveals three distinct ABP distribution regimes. At low speeds, V ≪ 1, flow dominates, leading to a homogeneous mixture. Conversely, at high speeds, V ≫ 1, motility prevails, resulting in MIPS. In the intermediate regime (V ∼ 1), the system's behavior depends on τ. For τ < 1, a moderately mixed homogeneous phase emerges, while for τ > 1, a novel phenomenon, termed flow-induced phase separation (FIPS), arises due to the combined effects of flow topology and ABP motility and size. To characterize these phases, we analyze drift velocity, diffusivity, mean-squared displacement, giant number fluctuations, radial distribution function, and cluster-size distribution.

Aurora kinase B, Ipl1 inSaccharomyces cerevisiae, is a master regulator of cell division, required for checkpoint regulation, spindle assembly and disassembly, chromosome segregation, and cytokinesis. Decades of research employed ensemble averaging methods to understand its dynamics and function; however, the dynamic information was lost because of population-based averaging. Here, we use single-molecule imaging and tracking (SMIT) to quantify the recruitment dynamics of Ipl1 at the kinetochores and spindles in live cells. Our data suggest that Ipl1 is recruited to these locations with different dynamics. We have demonstrated how the recruitment dynamics of Ipl1 at the kinetochores during metaphase changes in the presence and absence of tension across the kinetochores, in the absence of protein phosphatase 1 (Glc7), and in the absence of its known recruiters (Ctf19 and Bub1). The SMIT of other chromosome passenger complex members (Bir1, Nbl1, Sli15) suggests their hierarchical assembly at the kinetochore. Hence, SMIT provides a dynamic view of the Ipl1 trafficking at the kinetochores and spindles.

Simulations of elastic turbulence, the chaotic flow of highly elastic and inertialess polymer solutions, are plagued by numerical difficulties: the chaotically advected polymer conformation tensor develops extremely large gradients and can lose its positive-definiteness, which triggers numerical instabilities. While efforts to tackle these issues have produced a plethora of specialized techniques – tensor decompositions, artificial diffusion, and shock-capturing advection schemes – we still lack an unambiguous route to accurate and efficient simulations. In this work, we show that even when a simulation is numerically stable, maintaining positive-definiteness and displaying the expected chaotic fluctuations, it can still suffer from errors significant enough to distort the large-scale dynamics and flow structures. We focus on two-dimensional simulations of the Oldroyd-B and FENE-P equations, driven by a large-scale cellular body forcing. We first compare two positivity-preserving decompositions of the conformation tensor: symmetric square root (SSR) and Cholesky with a logarithmic transformation (Cholesky-log). While both simulations yield chaotic flows, only the latter preserves the pattern of the forcing, i.e. its fluctuating vortical cells remain ordered in a lattice. In contrast, the SSR simulation exhibits distorted vortical cells that shrink, expand and reorient constantly. To identify the accurate simulation, we appeal to a hitherto overlooked mathematical bound on the determinant of the conformation tensor, which unequivocally rejects the SSR simulation. Importantly, the accuracy of the Cholesky-log simulation is shown to arise from the logarithmic transformation. We also consider local artificial diffusion, a potential low-cost alternative to high-order advection schemes. Unfortunately, the artificially enhanced diffusive smearing of polymer stress in regions of intense stretching substantially modifies the global dynamics. We then show how the spurious large-scale motions, identified here, contaminate predictions of scalar mixing. Finally, we discuss the effects of spatial resolution, which controls the steepness of gradients in a non-diffusive simulation.

Viscoelastic fluids flowing through porous media have been shown to provide improvements in oil displacement efficiency resulting from a favorable mobility ratio. In this study, we demonstrate the existence of an additional mechanism sourced from the buildup of elastic stresses near critical fluid–solid contact regions, which is capable of further displacing trapped oil droplets in porous media. Applying a hybrid lattice Boltzmann multiphase model, the viscoelastic mechanism is numerically explored inside a model porous medium, which involves displacing a trapped nonwetting Newtonian droplet with a surrounding viscoelastic fluid. When compared to the purely Newtonian displacing fluid, the additional viscoelastic response provides a considerable mobility enhancement across a range of competing capillary, wettability, and elastic conditions. It is revealed that the source of mobility improvement in the viscoelastic fluid is attributed to the growth of polymer stresses near the fluid–solid contact regions, which contributes to an additional forcing contribution that generates a “pinch-off” mechanism. Ultimately, this additional contribution is found to depend strongly on the elastic properties of the viscoelastic fluid, rather than its viscous properties. This suggests that the use of viscoelastic fluids has the potential to enhance oil recovery efforts in porous media by providing an additional method beyond a favorable mobility ratio.

Viscoelastic instabilities are notoriously sensitive to their geometrical environment. Consequently, understanding the onset and general behavior of viscoelastic instabilities in geometrically complex applications where viscoelastic fluids naturally occur, such as porous media, is far from a trivial task. To this aim, this study numerically investigates the geometrical dependence of viscoelastic instabilities through confined one-dimensional (1-D) channel arrays of circular pore contractions of ideal (i.e., symmetrical) and non-ideal (i.e., asymmetrical) pore configurations. At low elasticity, we demonstrate that the viscoelastic instability behavior in all geometries is the same as it was previously reported in ideal pore geometries, which can be characterized by a gradual loss of the well-defined symmetry in the velocity streamline plots, as well as the build-up of secondary vortices. However, at higher elasticity, we observe the transition into strong transient behavior, whereby the flow in all pore geometries experiences the multistability phenomenon reported by Kumar et al., Phys. Rev. Fluids 6, 033304 (2021). Interestingly, it is shown that the viscoelastic instability response is the strongest for the most non-ideal pore geometry, which not only has the fastest transition time but also produces the most chaotic flow fluctuations, characterized by a broadband spectrum. Ultimately, we demonstrate that the viscoelastic instability response in each pore geometry adheres to the Pakdel-McKinley criterion for elastic instability, specifically, the streamline curvature and elastic stress anisotropy.

We investigate the effect of cooperative interactions in an ensemble of microorganisms, modeled as self-propelled disklike and rodlike particles, in a three-dimensional turbulent flow and show flocking and nematic ordering as an emergent phenomenon. Building on the work by Choudhary et al. [ Europhys. Lett. 112, 24005 (2015)] for two-dimensional systems, and combining ideas from active matter and turbulent transport, we show that nontrivial correlations between the flow and individual dynamics are essential for the microorganisms to flock in, for example, a turbulent three-dimensional marine environment. Our results may have implications especially in the modeling of artificial microswimmers in a hostile environment.

We investigate the effect of cooperative interactions in an ensemble of microorganisms, modelled as self-propelled disk-like and rod-like particles, in a three-dimensional turbulent flow to show flocking as an emergent phenomenon. Building on the work by Choudhary, et al. [Europhys. Lett. 112, 24005 (2015)] for two-dimensional systems, and combining ideas from active matter and turbulent transport, we show that non-trivial correlations between the flow and individual dynamics are essential for the microorganisms to flock in, for example, a turbulent three-dimensional, marine environment. Our results may have implications especially in the modelling of artificial microswimmers in a hostile environment.

We study the rotational dynamics of inertial disks and rods in three-dimensional, homogeneous, isotropic turbulence. In particular, we show how the alignment and the decorrelation timescales of such spheroids depend, critically, on both the level of inertia and the aspect ratio of these particles. These results illustrate the effect of inertia—which leads to a preferential sampling of the local flow geometry—on the statistics of both disks and rods in a turbulent flow. Our results are important for a variety of natural and industrial settings where the turbulent transport of asymmetric, spheroidal inertial particles is ubiquitous.