Soft-matter systems exhibit nontrivial collective behaviour, e.g. phase transitions and self-assembly. The pervasiveness of soft-matter is impressive with wide ranging applications in industry. However, what makes these systems particularly interesting for physicists is their ubiquity in Biology. For instance, the disordered elastic network shown below is actually found all over in our body. How does this disordered structure impart us mechanical integrity? Surprisingly, even in this system there is a phase transition somewhat analogous to ferromagnetism.
In my group we use the methods of classical statistical mechanics to investigate soft matter, both in and out of equilibrium. This involves the application of computational techniques such as Brownian Dynamics and Monte Carlo simulations and established techniques from liquid-state theory, such as (classical) density functional theory, integral equations, mode-coupling theory etc., as well as the development of new analytic and numerical approaches.
Understanding the fundamental material properties of soft matter:
My research relies extensively on theoretical statistical mechanics; equilibrium and non-equilibrium. The main goal is to provide a theoretical understanding of material properties using microscopic first principles approach.
Biological Soft Matter:
Using tools from the theory of critical phenomenon, elasticity theory and large scale numerical simulations, I have studied linear and nonlinear mechanics of biopolymer networks. Working together with experimentalists, I have investigated how different fields such as bending rigidity, stress, and strain can stabilize an otherwise floppy network. Some of the important results of my research are:
• Nonlinear mechanics are not sensitive to the detailed microstructure of the network
• Motor-activity induced failure of a network exhibits remarkable similarity to percolation transition
• Stress governs the mechanics of collagen networks over a wide range of concentration
Active Brownian Particles:
I investigate the non-equilibrium properties of active systems using a combination of Response theory, Density Functional Theory and Brownian dynamics simulations. Some of the important results of my research are:
• Treating the activity as a non-equilibrioum perturbation, exact expressions can be obtained for key observables, such as average swim speed and average orientation, of active systems.
• One can go beyond the linear response theory by using density functional theory to access observables such as density and pair-correlation function of an active system.