My research areas include computational soft matter and biophysics.


My research is primarily focused on using computational modeling to understand the molecular mechanism behind various bulk and interfacial phenomena in soft matter. A complementary focus of my research is to develop coarse-grained (CG) models and characterization tools, and to extend generic theoretical frameworks to problem-specific context. Some of these problems are elaborated below.


Lipid membrane order and preferential protein partitioning

We explore the molecular origin of dynamic heterogeneity in lipid membranes exhibiting coexisting fluid phases by formalizing the seemingly trivial connection between membrane local order and lipid packing. Toward this, we characterize membrane order in terms of the local nonaffine content of the deformation, which captures the distinct nature of the spatio-temporal evolution of lipids in their environment.  Additionally, we developed an efficient algorithm to analyze lipid packing defects in three dimensions.  Using these, we explore the mechanistic principle behind the functionality of membrane heterogeneity, such as preferential protein partitioning and membrane permeation.

Related Publications:

Iyer, Tripathy et al. (2018) Biophysical Journal 

Tripathy et al. (2018) Advances in Biomembranes and Lipid Self-Assembly 

Tripathy et al.  (2020) Journal of Chemical Theory and Computation 

Tripathy and Srivastava (2023) Biophysical Journal 


Solvation shell thermodynamics of hydrophobic solutes

We characterize density and energy fluctuations within the hydration/solvation shell of a model extended hydrophobic solute in pure water and water-urea/methanol mixtures to investigate the role of solute length scales and the effect of cosolutes. Toward this, we extend the small system method (SSM) to characterize the thermodynamic properties of solute solvation shells.

Related Publications:

Tripathy et al. (2020) Nanomaterials 

Tripathy et al. (2022) Journal of Chemical Physics 

Dynamical consistency in coarse-grained simulations

We parameterize isotropic, configuration independent, non-Markovian generalized Langevin equation (GLE) based thermostats to achieve dynamic consistency in CG molecular simulations. We employ such models to coarse-grain molecular liquids and their idea/non-ideal mixtures and study the conformational dynamics of model hydrophobic polymers in water and water-cosolute mixtures.

Related Publications:

Klippenstein, Tripathy et al. (2021) Journal of Physical Chemistry B 

Tripathy et al. (2023) Journal of Chemical Physics

Systematic coarse-graining in soft matter simulation

We employed a structure based systematic coarse-graining approach to extract chemical specific CG model for sulfonated poly(ether ether ketone), corresponding to the highest possible CG mapping. The CG potentials were used to study molecular structuring and water percolation in the membrane at various hydration levels toward understanding its efficiency as a proton exchange membrane in fuel cells.


A force-matching approach was followed to coarse-grain a set of  small poly-aromatic hydrocarbons toward developing a minimal CG mapping scheme involving uniaxial Gay-Berne potential (in collaboration with Shell Technology Center, Bangalore, India).

Related Publications:

Tripathy et al. (2016) Macromolecular Theory and Simulations 

Tripathy et al. (2017) Journal of Physical Chemistry B

Tripathy et al. (2019) Macromolecular Theory and Simulations