Current Research - High Fidelity Force Field Development for Water
High Fidelity Force Field Development for Water
I am currently working on developing new highly accurate coarse grained force fields for water using complex potential functions. The model is aimed at reproducing high temperature thermodynamics of water with minimum computational expense and with long range interactions.
To study the nanochannel evaporation and microchannel evaporation, I developed coarse grained water model named as Morse-D. Parameters are optimized using a variety of optimization techniques including Genetic Algorithm, Nelder-Mead, Particle Swarm Optimization, and Strength Pareto Evolutionary Algorithm. Morse-D is computationally faster and can perform large scale nano/micro evaporation studies which were not possible before. The figure on the top shows nanopore evaporation using Morse-D water model. Visit my google scholar profile for latest publications on my research!
Research Grants ( $33,000 Funded)
Past Research (Completed)
1. Multiscale Modeling of Thrombosis
Understanding the mechanics behind the formation of thrombo-embolisms can improve the existing thrombolytic therapies and can be helpful in treating patients with deep vein thrombosis and hyper-coagulable blood. Our objective was 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.
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. We developed 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.
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.
2014 - 2023 Member of American Society of Mechanical Engineers (ASME)
2021 - 2023 Member of Society for Mathematical Biology (SMB)
Prof. Xianqiao Wang (Univ. of Georgia, USA)