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PhD Student, Missouri University of Science and Technology


Computer simulation of realistic experiment of solidification in metals in presence of oxygen.

As we increase the temperature of any metallic materials such as Aluminum, Iron, Steel etc. it melts. In the same way if the melted materials are left out in a lower temperature environment it solidifies. The melting-solidification phenomena changes the physical, chemical, mechanical properties of a material. Melting-solidification have wide range of applications in manufacturing industries (such as steel making, automobiles). The properties of a metal or alloys can be controlled by controlled melting solidification. If each metal or alloy are studied individually by experiments, it will take a large amount of resources (in terms of budget and equipment) and manpower to create a database of these properties in different experimental conditions. Instead of doing each of the different experiment we can run computer simulation and accelerate the process of understanding the behavior of materials during and after the melting-solidification. Computer simulations can give a guideline to the experimentalists how the materials may behave in a certain experimental condition and it will behave after the experiments. This will accelerate the process of running different experiments and also, we can design new materials. We can predict materials with superior properties, which will be lengthy and time consuming process to find it by performing experiments. All materials are consisted of atoms/molecules. When there is any kind of change of properties of a materials, it must start at atomic or molecular level. For an example, when we see a piece of metal or a wood is broken, we see it macroscopically (at a very large scale). If we look closer and try to see it under microscope we will find, the larger crack was originated from much smaller identical cracks. If we keep magnifying it, we will find the crack started at an atomic scale. So, to study the properties of melting-solidification we need to look at atomic scale to understand how material properties evolve by melting or solidification. The method I use for my research is called molecular dynamics. Molecular dynamics based models can simulate a small portion (Few atoms to Billions of atoms) of the materials and it can predict how it will behave a larger scale. Computer simulations act as a bridge between microscopic length and time scales and the macroscopic world of the laboratory. This is the frontiers of new material development.


Probabilistic Analysis and Design of HCP Nanowires: an Efficient Surrogate Based Molecular Dynamics Simulation Approach

Abstract: We investigate the dependency of strain rate, temperature and size on yield strength of hexagonal close packed (HCP) nanowires based on large-scale molecular dynamics (MD) simulation. A variance-based analysis has been proposed to quantify relative sensitivity of the three controlling factors on the yield strength of the material. One of the major drawbacks of conventional MD simulation based studies is that the simulations are computationally very intensive and economically expensive. Large scale molecular dynamics simulation needs supercomputing access and the larger the number of atoms, the longer it takes time and computational resources. For this reason it becomes practically impossible to perform a robust and comprehensive analysis that requires multiple simulations such as sensitivity analysis, uncertainty quantification and optimization. We propose a novel surrogate based molecular dynamics (SBMD) simulation approach that enables us to carry out thousands of virtual simulations for different combinations of the controlling factors in a computationally efficient way by performing only few MD simulations. Following the SBMD simulation approach an efficient optimum design scheme has been developed to predict optimized size of the nanowire to maximize the yield strength. Subsequently the effect of inevitable uncertainty associated with the controlling factors has been quantified using Monte Carlo simulation. Though we have confined our analyses in this article for Magnesium nanowires only, the proposed approach can be extended to other materials for computationally intensive nano-scale investigation involving multiple factors of influence.

Pub.: 17 Nov '16, Pinned: 30 Jun '17

Understanding Homogeneous Nucleation in Solidification of Aluminum by Large Scale Molecular Dynamics Simulations

Abstract: Homogeneous nucleation from aluminum (Al) melt was investigated by million-atom molecular dynamics (MD) simulations utilizing the second nearest neighbor modified embedded atom method (MEAM) potentials. The natural spontaneous homogenous nucleation from the Al melt was produced without any influence of pressure, free surface effects and impurities. Initially isothermal crystal nucleation from undercooled melt was studied at different constant temperatures, and later superheated Al melt was quenched with different cooling rates. The crystal structure of nuclei, critical nucleus size, critical temperature for homogenous nucleation, induction time, and nucleation rate were determined. The quenching simulations clearly revealed three temperature regimes: sub-critical nucleation, super-critical nucleation, and solid-state grain growth regimes. The main crystalline phase was identified as face-centered cubic (fcc), but a hexagonal close-packed (hcp) and an amorphous solid phase were also detected. The hcp phase was created due to the formation of stacking faults during solidification of Al melt. By slowing down the cooling rate, the volume fraction of hcp and amorphous phases decreased. After the box was completely solid, grain growth was simulated and the grain growth exponent was determined for different annealing temperatures.

Pub.: 22 Jun '17, Pinned: 30 Jun '17