We work in the following areas.
Flagellar propulsion & steering in sperm
Understanding how sperm swim to find an egg and fertilize it is crucial to designing artificial reproduction technologies that have a high chance of success and reliably select the best quality sperm to create offspring free of serious genetic defects. Sperm cells swim by “beating” flexible tails called flagella. These flexible propellers are driven by an incredibly complex nanoengine, called the axoneme. Thousands of protein nanomotors, called dyneins, act in a concerted manner within this engine to drive complex beating patterns in the flagellum. How do all these motors manage to coordinate themselves in a highly noisy nanoscale environment to produce beating patterns to propel and steer the swimming cell towards an egg? We are developing mathematical models that account for the interplay between the action of the motors, the elastic resistance of the flexible body, and the fluid forces inside and outside the cell. Using these simulations, we aim to connect the internal and external physical parameters that govern this system to the experimentally observable beating patterns that arise under different physical conditions. We hope to diagnose the internal health of a sperm cell from its beat signature. This will enable the design of microfluidic strategies to select cells of high genetic quality for in vitro fertilization.
Key outcomes
- Image analysis of long-duration high-speed, high-resolution videos of single tethered sperm to measure flagellar energetics: This was achieved trhough a three-year collaboration with an experimental group led by Moira O’Bryan, Reza Nosrati and Julio Soria [Nandagiri et al., eLife, 2021].
- Image-analysis of flagellar beating patterns in single sperm demonstrating that a set of proteins called CRISPs boost flagellar propulsion [Gaikwad et al., Frontiers in Cell and Developmental Biology, 2021].
- Measurements of 3D-ness of flagellar beating patterns of individual sperm cells close to a wall [Powar et al., Small Methods, 2022].
Positions Open
PhD projects in this research area provide training for a career in modeling and simulations of fluid-structure interactions at low Reynolds numbers. There are several projects available:
- Image-analysis of experimentally obtained videos of flagellar beating in cells
- Modeling of fluid-structure interactions in internally-driven microfilaments
- Computational methods for fluid-structure interactions accounting for walls, internal and external viscoelasticity, biochemical signalling, etc.
- Predicting beating patterns and swimming trajectories under different conditions e.g. in the presence of walls
Complex flows of viscoelastic polymer solutions
Polymers are ubiquitous in nature (e.g. DNA, cellulose) or as plastics. When dissolved, flexible polymer molecules can behave as nanosprings and make the fluid viscoelastic. Even a small amount of polymeric additives can dramatically change the flow behaviour of their Newtonian solvents. These additives can also reduce turbulent friction by as much as 40%. They can suppress micro-droplet (or mist) formation in pesticide spraying. On the other hand, if they are not chosen correctly, they can cause toxic mist formation in roll-coating of paper and other products. The connections between polymer size, chemistry and concentration, and the behaviour of their solutions in complex flow situations such as turbulent pipe flows, jets and free surface flows, etc. are, however, not yet well understood. We develop advanced microstructure-based rheolgical models and computational fluid dynamics (CFD) simulations that connect the nanoscale fluid mechanics of polymer molecules with the macroscale flow behaviour of their solutions. The goal is the design of polymer solutions for use in flow applications such as spraying, surface-coatings, ink-jet printing, turbulence control, etc.
Key outcomes
- Correct prediction of the non-trivial concentration dependence of hysteretic behaviour of polymer solutions using a new microstructure-based rheological model [Prabhakar et al., Physical Review Fluids, 2017].
- A new microstructure-based model that correctly predicts complex self-concentrating/self-diluting behaviour of unentangled polymer solutions in strongly stretching flows: This was a collaboration with Tam Sridhar and Ravi Prakash Jagadeeshan. Model predictions were successfully tested against experiments (Sridhar) and mesoscale Brownian Dynamics simulations (Jagadeeshan) [Prabhakar et al.,Journal of Rheology, 2016].
- Development of the Acousticall-Driven Microfluidic Extensional Rheometer (ADMiER): This device was developed in collaboration with Leslie Yeo and James Friend. It measures the extensional viscosities of microlitre-sized drops of complex fluids [Bhattacharjee et al., New Journal of Physics, 2011; McDonnell et al., Soft Matter, 2015].
Positions Open
PhD projects in this research area provide training for careers in microtructure-based computational rheology and CFD of viscoelastic fluids. The following projects available:
- CFD of free-surface flows (slender filaments, jets, etc.) of polymer solutions
- CFD of unstable 2D & 3D flows of polymer solutions
- Constructing new models for viscoelastic stresses in polymer solutions
- New mesoscale computational methods for simulations of macromomecluar hydrodynamics
Complex flows of Active Matter
Interesting things happen when highly-mobile individuals get together! Complex motion patterns emerge in bird flocks, wildebeest herds, human crowds, fish shoals, ants, etc. This is also true of
of suspensions of swimming cells or of synthetic nanomotors. The behaviour of such active matter is rich and diverse. Living matter — organelles, cells, tissues, organs, organisms, species — is active matter perfected for specific functions by billions of years of evolution. Our goal is to develop models and techniques to connect the properties and behaviour of active matter to with the motility and other interactions of the mobile particles that make up such materials.
Key outcomes
- Correct prediction of intricate furrow networks created by motile cells moving through soft media: These networks were originally observed in experiments with Pseudomonas aeruginosa biofilms, performed by Cynthia Whitchurch and Michelle Gee, and quantified using measures developed in our group [Gloag et al., PNAS, 2013]. Simulations peformed in collaboration with Mandar Inamdar and Raghunath Chelakkot demonstrated that the network patterns are caused by the phenomenon of motility-induced clustering [Imaran et al., Soft Matter, 2021].
- Simulations of pattern-formation in epithelial monolayers consisting of a “foam” consisting of tightly-packed polygon-shaped motile cells: in collaboration with Mandar Inamdar and Raghunath Chelakkot [Bajpai et al., Journal of the Royal Society Interface, 2021].
- Correct prediction of the changes in suspension extensional viscosity induced by propulsive forces exerted by swimming bacteria, algae and sperm: This was a collaboration with Leslie Yeo and James Friend who performed the experiments. A new microstructure-based model for the extensional viscosity of suspensions of rod-shaped microswimmers captured the concentration-dependence observed in motility-induced changes in extensional viscosity [McDonnell et al., Soft Matter, 2015].
Positions Open
PhD projects in this research area provide training in modeling and simulations of dense suspensions and collectives of particles interacting with ordinary soft matter. The following projects are available:
- Developing mesoscale simulations of suspensions of self-propelled colloids, chains and sheets
- Developing mirostructure-based rheological models for active suspensions
- Developing a framework for the thermodynamics of active matter
Computational Mechanics of Soft Matter 