• Refine Query
  • Source
  • Publication year
  • to
  • Language
  • 1
  • Tagged with
  • 2
  • 2
  • 2
  • 2
  • 2
  • 2
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Laser Additive Manufacturing of Magnetic Materials

Mikler, Calvin V. 08 1900 (has links)
A matrix of variably processed Fe-30at%Ni was deposited with variations in laser travel speeds as well and laser powers. A complete shift in phase stability occurred as a function of varying laser travel speed. At slow travel speeds, the microstructure was dominated by a columnar fcc phase. Intermediate travel speeds yielded a mixed microstructure comprised of both the columnar fcc and a martensite-like bcc phase. At the fastest travel speed, the microstructure was dominated by the bcc phase. This shift in phase stability subsequently affected the magnetic properties, specifically saturation magnetization. Ni-Fe-Mo and Ni-Fe-V permalloys were deposited from an elemental blend of powders as well. Both systems exhibited featureless microstructures dominated by an fcc phase. Magnetic measurements yielded saturation magnetizations on par with conventionally processed permalloys, however coercivities were significantly larger; this difference is attributed to microstructural defects that occur during the additive manufacturing process.
2

HIGH-THROUGHPUT CALCULATIONS AND EXPERIMENTATION FOR THE DISCOVERY OF REFRACTORY COMPLEX CONCENTRATED ALLOYS WITH HIGH HARDNESS

Austin M Hernandez (12468585) 27 April 2022 (has links)
<p>Ni-based superalloys continue to exert themselves as the industry standards in high stress and highly corrosive/oxidizing environments, such as are present in a gas turbine engine, due to their excellent high temperature strengths, thermal and microstructural stabilities, and oxidation and creep resistances. Gas turbine engines are essential components for energy generation and propulsion in the modern age. However, Ni-based superalloys are reaching their limits in the operating conditions of these engines due to their melting onset temperatures, which is approximately 1300 °C. Therefore, a new class of materials must be formulated to surpass the capabilities Ni-based superalloys, as increasing the operating temperature leads to increased efficiency and reductions in fuel consumption and greenhouse gas emissions. One of the proposed classes of materials is termed refractory complex concentrated alloys, or RCCAs, which consist of 4 or more refractory elements (in this study, selected from: Ti, Zr, Hf, V, Nb, Ta, Cr, Mo, and W) in equimolar or near-equimolar proportions. So far, there have been highly promising results with these alloys, including far higher melting points than Ni-based superalloys and outstanding high-temperature strengths in non-oxidizing environments. However, improvements in room temperature ductility and high-temperature oxidation resistance are still needed for RCCAs. Also, given the millions of possible alloy compositions spanning various combinations and concentrations of refractory elements, more efficient methods than just serial experimental trials are needed for identifying RCCAs with desired properties. A coupled computational and experimental approach for exploring a wide range of alloy systems and compositions is crucial for accelerating the discovery of RCCAs that may be capable of replacing Ni-based superalloys. </p> <p>In this thesis, the CALPHAD method was utilized to generate basic thermodynamic properties of approximately 67,000 Al-bearing RCCAs. The alloys were then down-selected on the basis of certain criteria, including solidus temperature, volume percent BCC phase, and aluminum activity. Machine learning models with physics-based descriptors were used to select several BCC-based alloys for fabrication and characterization, and an active learning loop was employed to aid in rapid alloy discovery for high hardness and strength. This method resulted in rapid identification of 15 BCC-based, four component, Al-bearing RCCAs exhibiting room-temperature Vickers hardness from 1% to 35% above previously reported alloys. This work exemplifies the advantages of utilizing Integrated Computational Materials Engineering- and Materials Genome Initiative-driven approaches for the discovery and design of new materials with attractive properties.</p> <p> </p> <p><br></p>

Page generated in 0.0966 seconds