Search Talks

As natural environments are not static, the model parameters in biologically realistic problems are not constant in time, and such situations in population biology are often described in terms of effective parameters that subsume some of the details of the problem; however, it is not always possible to define an effective parameter. I will describe a simple solvable model to address when and why an effective parameter can not be defined, and the implications thereof.

Phase ordering driven by nonequilibrium fluctuations is a hallmark of both living and synthetic active matter. Unlike equilibrium systems, where ordered states arise from the minimisation of free energy, active systems are fueled by the constant injection of energy at the microscopic scale. The emergence of ordered phases in such driven systems challenges our conventional views of domain growth and interfacial structure. In this talk, I will present results on the investigation of coarsening of colloidal clusters in active liquids containing E. coli, highlighting the nature of ordering in systems dominated by strong fluctuations. Our experiments reveal that uniform dispersions of colloids and swimmers are inherently unstable, resulting in spontaneous phase separation characterised by fractal interfaces and unconventional domain growth kinetics.

Fundamental laws of physics are symmetric under time reversal (T) symmetry, hence we are tempted to deduce that the evolution of the world may be T-symmetric. On the other end, there is an important conjecture that a conservative system with many particles becomes randomized. The latter process, called thermalization, is related to the second law of thermodynamics that makes the macroscopic world asymmetric. In addition to these two divergent topics, I will cover additional T-breaking frameworks: multiscale energy transfer, open systems, and asymmetric objects. In driven dissipative nonequilibrium systems, including turbulence, the multiscale energy flux from large scales to small scales helps determine the arrow of time. In addition, open systems are often irreversible due to particle and energy exchanges between the system and the environment.

Concentrated electrolytes have the potential to improve the mechanical stability of rechargeable batteries. Using molecular dynamics simulations, we calculated the ionic conductivity of highly concentrated EC-LiTFSI electrolytes at varying salt concentrations ranging between 0.005 M and 2.5 M and examined the ion transport mechanisms. Ionic conductivity is found to increase at low salt concentrations before declining at higher salt concentrations beyond 0.6 M. Our extensive simulations and analyses suggest a universal relationship between the ionic conductivity and c as σ(c)~c^α e^(-c/c_0 ) The proposed relationship convincingly explains the ionic conductivity over a wide range of c, where the term c^α accounts for the uncorrelated motion of ions and e^(-c/c_0 ) captures the salt-induced changes in shear viscosity. Our simulations suggest vehicular mechanism to be dominant at low c regimes, which transition into a Grotthuss mechanism at high c regime, where structural relaxation is the dominant form of ion transport mechanism.

Two dimensional elastic tethered membranes (ball-and-spring model) with finite bending rigidity and no self-avoidance are known to exist in a flat/crumpled phase for small/large temperatures. The change in phase is mediated by a second order phase transition. Once self-avoidance is introduced, the tethered membranes do not exhibit a crumpled phase and remain flat for all temperatures. By considering the nodes of the membrane as active Brownian particles, we observe that membranes without self-avoidance retain the crumpling transition with activity as the tuning parameter. We find evidence of a crumpled phase with Flory dimensions of 2.4 in spherical self-avoiding active membranes.

We present PIC-VIC, a novel computational framework for simulating collective behavior of self-propelled particles on curved surfaces. Building upon the Particle-in-Cell (PIC) method, widely used in plasma physics, we track individual particles (Lagrangian description) while employing a static Eulerian mesh for interaction calculations. Using mesh with arbitrary geometries we extend the Vicsek model to study flocking dynamics on curved manifolds. Crucially, we incorporate Laplace-Beltrami based vector diffusion to ensure geometrically consistent averaging of particle velocities, effectively implementing parallel transport on the curved surface. This particle-based PIC-VIC method complements continuum active-hydrodynamics approaches and allows for the investigation of curvature-induced fluctuations. We demonstrate the capabilities of PIC-VIC and discuss its potential for uncovering novel collective phenomena, emergent patterns, and geometry-driven interactions in biological, physical, and artificial systems constrained to non-Euclidean spaces.