Research Overview

    I am a computational scientist and my primary research interests are the development of highly efficient thermal energy conversion technologies and investigation of the reason behind venous thromboembolism through molecular simulations.


    1) Venous Thromboembolism is one of the leading cause of fatalities related to diabetic patients. My research objective is to develop multi scale models to predict the formation of emboli during a blood clot event.

    2) Ultra fast heat removal with minimum foot print is always a challenge in semiconductor industry. With the advent of solar thermal conversion devices, this will become a very big challenge in the near future. My objective is to investigate the development of highly efficient nano fluids to remove heat from a device, through multi scale theories and simulations.

1. Multiscale Modeling of Thrombosis

    Understanding the mechanics behind the formation of thromboembolisms can improve the existing thrombolytic therapies and can be helpful in treating patients with deep vein thrombosis and hypercoagulable blood. Our objective is to develop models integrating the molecular scales and continuum scales to predict the ablation of the thrombus from the vascular walls and how it is related to the formation of embolisms.


2. Reactive Coarse Grain MD method for Fibrin

    As the first step towards the multiscale model of thrombosis, we created a reactive molecular dynamics method for coarse grain fibrinogen molecules. This customized force field could simulate the fibrin clot formation, its branching and continuous fiber formation etc, which are in qualitative agreement with the experimental results. We also performed confocal microscopy imaging of the fibrin clots (shown in green on the right) which shows the interconnected networks of fibrin  polymer.
3. Molecular Mechanics of Fibrinogen and Hemoglobin

    Mechanical properties play an important role in determining the state of a blood clot, which can embolize or dissolve normally in an event of vascular injury. To understand this, we have characterized the molecular level mechanical properties of the hemoglobin - a major constituent of red blood cells. Our in silico studies show that the hemoglobin which is commonly referred to as a globular protein is in fact having anisotropic properties. We have also found that it can perform well in compression, but has a weak elastic strength. Currently we are extending these findings to develop an accurate coarse grain model for RBCs.
4. Self Assembly and Spontaneous Sickle Fiber Formation

    Sickle cell disease is caused due to the mutation of the hemoglobin. This causes the polymerization of the hemoglobins forming long strands which distorts the shape of the hemoglobin into a sickle. This leads to occlusion of the blood vessels and a high risk related to the cardiac diseases. Our objective is to develop accurate coarse grain models of sickle hemoglobin which can simulate the spontaneous nucleus formation and self assembly of them into long strands and effectively capturing the mechanical deformation or sickling of the red blood cells.    

5. Solid-Liquid Heat Transfer in MD simulations

    Ultra fast heat removal will become a necessity in the industries like solar thermal conversion and integrated chip cooling. To achieve high heat fluxes, one promising technology is the passive cooling methods at nanoscale. With our molecular dynamics studies, we have estimated that ultra high heat fluxes can be removed from very hot surfaces effectively using passive flows. Currently we are developing devices which can work on this principle and can deliver continuous cooling to any system.
6. Fast Local Pressure Estimation for LAMMPS

    Estimating local continuum level thermodynamic properties like pressure, density, surface tension and temperature are essential to couple molecular level simulations with continuum scale simulations. Currently, the AtC package in LAMMPS performs this task at the expense of high computational power in 3d. For systems with 2d inhomogeneity, often we need only 2d pressure. To address this, we have developed a highly efficient 2d local pressure estimation algorithm which can act as a post processing tool for LAMMPS.


    1. Prof. Rodney D. Averett (Univ. of Georgia, USA)

    2. Prof. Xianqiao Wang (Univ. of Georgia, USA)

    3. Prof. Sibi Chacko (Heriot Watt Univ., UK)