• Login
    View Item 
    •   SMARTech Home
    • Georgia Tech Theses and Dissertations
    • Georgia Tech Theses and Dissertations
    • View Item
    •   SMARTech Home
    • Georgia Tech Theses and Dissertations
    • Georgia Tech Theses and Dissertations
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Hybrid computational modeling of thermomagnetic material systems

    Thumbnail
    View/Open
    KIM-DISSERTATION-2017.pdf (5.569Mb)
    Date
    2017-03-28
    Author
    Kim, Sookyung Kyung
    Metadata
    Show full item record
    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.
    URI
    http://hdl.handle.net/1853/58213
    Collections
    • Georgia Tech Theses and Dissertations [23877]
    • School of Materials Science and Engineering Theses and Dissertations [986]

    Browse

    All of SMARTechCommunities & CollectionsDatesAuthorsTitlesSubjectsTypesThis CollectionDatesAuthorsTitlesSubjectsTypes

    My SMARTech

    Login

    Statistics

    View Usage StatisticsView Google Analytics Statistics
    facebook instagram twitter youtube
    • My Account
    • Contact us
    • Directory
    • Campus Map
    • Support/Give
    • Library Accessibility
      • About SMARTech
      • SMARTech Terms of Use
    Georgia Tech Library266 4th Street NW, Atlanta, GA 30332
    404.894.4500
    • Emergency Information
    • Legal and Privacy Information
    • Human Trafficking Notice
    • Accessibility
    • Accountability
    • Accreditation
    • Employment
    © 2020 Georgia Institute of Technology