Molecular Engineering and Liquid Thermal (MELT) Laboratory
Welcome to the Molecular Engineering and Liquid Thermal (MELT) Laboratory, a hub of computational research focused on exploring molecular dynamics, nanoscale heat transfer, and related areas. At MELT, our goal is to contribute innovative solutions in mechanical and biomedical engineering, aiming to advance technology through our research.
Our work is centered on developing advanced models of water's force fields, enabling us to study evaporation across various scales, from the tiny world of sub-nanometers to the broader scope of micrometers. We utilize a diverse array of techniques, including meta heuristic optimization, machine learning, and molecular dynamics simulations, to address complex questions. These include exploring the limits of liquid cooling's heat flux in electronics and understanding the molecular mechanisms behind venous thromboembolism.
We at MELT believe strongly in the value of student participation. Our lab offers a comprehensive educational experience for both graduate and undergraduate students, providing opportunities for hands-on involvement in forefront research and development. Our commitment to advancing knowledge in heat transfer and biomedical research is reinforced by our focus on collaborative and interdisciplinary methods.
Force Field Development for Water
Morse-D Parameters
Research Grants (Awarded from 2021 to till date)
Sumith Yesudasan (PI), Thomas Filburn, Spring 2024, "University of New Haven/ University of Hartford and Industrial Partners Collaborative Nuclear Fellowship Program Applied Research in Fabrication, Testing and Simulation of Nuclear Power Systems.", Funding Agency: US Nuclear Regulatory Commission ($400k)
Sumith Yesudasan (PI), Fall 2023, "Testing Passive Radiative Cooling for Spacecraft Thermal Protection", Funding Agency: NASA CT Space Grant.
Sumith Yesudasan (PI), Fall 2023, "Incorporating the philosophy of Entrepreneurial-Minded Learning (EML) by emphasizing the concept of learning through failure in Instrumentation Course.", Funding Agency: Office of the Dean, Tagliatela College of Engineering, University of New Haven.
Sumith Yesudasan (PI), Spring 2023, "Experimental Investigation of Cooling Efficiency of Liquid Cooling Computers", Funding Agency: Office of Research and Sponsored Programs, SHSU.
Sumith Yesudasan (PI), Fall 2021, "Interfacing Arduino Microcontroller with Mechatronics Systems", Funding agency: STEM center, SHSU.
Ulan Dakeev (PI), Sumith Yesudasan (Co-PI) and Elizabeth Gross (Co-PI), 2021-22, "Navigation through AR: Development of Augmented Reality Application (ARNavi) to Improve Navigation in Gresham Library", Funding agency: Office of Research and Sponsored Programs, SHSU.
Reg Pecen (PI), Sumith Yesudasan (Co-PI), Faruk Yildiz (Co-PI), Ulan Dakeev (Co-PI), 2021-2022, "Design and Implementation of Senior Design (Capstone) Curriculum for Engineering Technology Majors", Funding agency: Professional & Academic Center for Excellence, SHSU.
Sumith Yesudasan (PI), Spring 2021, "Smart Heating and Ventilation System development for urban Houses", Funding agency: STEM center, SHSU.
Actively contributed to the NSF funded proposal #1454450 as a PhD candidate, "Experimental and Numerical Study of Nanoscale Evaporation Heat Transfer for Passive-Flow Driven High-Heat Flux Devices", 2015 (NSF ID : 000804582) (Status: Funded)
Funding Agencies
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.
Professional Memberships
2014 - 2023 Member of American Society of Mechanical Engineers (ASME)
Life Member of Society for Mathematical Biology (SMB)