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There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
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~~THE SCHOOL OF MATERIALS SCIENCE AND ENGINEERING
GEORGIA INSTITUTE OF TECHNOLOGY
Under the provisions of the regulations for the degree
DOCTOR OF PHILOSOPHY
on Friday, November 11, 2016
1:00 - 3:00 PM EST
(10:00 AM – Noon PST)
in Love 295
will be held the
DISSERTATION DEFENSE
for
Soo Kyung Kim
"Hybrid Computational Modeling of Thermomagnetic Material Systems"
Committee Members:
Prof. Hamid Garmestini, Advisor, MSE
Prof. Seung Soon Jang, MSE
Prof. Richard Fujimoto, CSE
Prof. Chaitanya S. Deo, ME
Dr. Lorin Benedict, LLNL
Dr. Mohammad A. Khaleel, ORNL
Abstract:
Current knowledge of computational material modeling for engineering demands accurate prediction of thermo-magnetic properties of material. Different of computational modeling approaches should be considered and selected in a way that fit the best to the specific material systems. In general, thermo-magnetic properties of material should benefit from ab-initio Density Functional Theory (DFT) calculation in some degree. However, DFT alone has the limitation in fully modeling finite temperature properties in that the concept of statistical physics such as magnetic excitation and magnetic spin interaction are not considered in DFT. The nature of atomic scale simulation also made it difficult to extend to meso-scale simulation. Therefore, a promising route toward this goal is a combination of DFT with concepts of statistical physics, which was shown to yield accurate predictions for a wide range of magnetic and nonmagnetic materials.
There are two aims for this work. Firstly, a review and comparison of various computational modeling techniques currently available for predicting thermo-magnetic properties of materials is presented. Specifically, different approaches for those computational modeling methods are presented for different material systems.
Secondly, new computational modeling frameworks based on currently available methodologies is developed and proposed for particular material systems for engineering task purposes. (1) For rare-earth replacement permanent magnets, the new program combining DFT based Korringa–Kohn–Rostoker (KKR) calculation and Heisenberg Monte Carlo has been developed and applied to (Fe1-xCox)2B. (2) For stainless steel, the new quantum-mechanically driven computational material discovery framework is proposed. (3) For meso-scale simulation of strong ferromagnetic material, GPU based parallel computing technique has been applied for Ising Monte-Carlo simulation and applied to Fe. The results from the proposed modeling routines show that we can achieve our exact aim to understand better the theoretical origin of thermo-magnetic properties of different material systems.
