Carnegie Mellon University
Browse
185_DeGeorge_2017_2019.pdf (10.51 MB)

Chemical Partitioning and Resultant Effects on Structure and Electrical Properties in Co-Containing Magnetic Amorphous Nanocomposites for Electric Motors

Download (10.51 MB)
thesis
posted on 2017-04-01, 00:00 authored by Vincent G. DeGeorge

chemical partitioning of Cobalt-containing soft magnetic amorphous and nanocomposite materials has been investigated with particular focus on its consequences on these materials’ nanostructure and electrical resistivity. Theory, models, experiment, and discussion in this regard are presented on this class of materials generally, and are detailed in particular on alloys of composition, (Fe65Co35)79.5+xB13Si2Nb4-xCu1.5, for X={0- 4at%}, and Co-based, Co76+YFe4Mn4-YB14Si2Nb4, for Y={0-4at%}. The context of this work is within the ongoing efforts to integrate soft magnetic metal amorphous and nanocomposite materials into electric motor applications by leveraging material properties with motor topology in order to increase the electrical efficiency and decrease the size, the usage of rare-earth permanent magnets, and the power losses of electric motors. A mass balance model derived from consideration of the partitioning of glass forming elements relates local composition to crystal state in these alloys. The ‘polymorphic burst’ onset mechanism and a Time-Temperature- Transformation diagram for secondary crystallization are also presented in relation to the partitioning of glass forming elements. Further, the intrinsic electrical resistivity of the material is related to the formation of virtual bound states due to dilute amounts of the glass forming elements. And lastly, a multiphase resistivity model for the effective composite resistivity that accounts for the amorphous, crystalline, and glass former-rich amorphous regions, each with distinct intrinsic resistivity, is also presented. The presented models are validated experimentally on the Co-containing alloys by Atom Probe Tomography performed through collaboration with Pacific Northwestern National Laboratory.

History

Date

2017-04-01

Degree Type

  • Dissertation

Department

  • Materials Science and Engineering

Degree Name

  • Doctor of Philosophy (PhD)

Advisor(s)

Michael E. McHenry

Usage metrics

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC