Seminar | October 18 | 4-5 p.m. | 348 Hearst Memorial Mining Building
Dr. Ian Stewart Winter, Postdoc, Materials Science & Engineering, UC Berkeley
The computer-aided discovery of structural alloys is a burgeoning area of research. A primary challenge in the field is to identify computable screening parameters that embody key structural alloy properties, such as strength and ductility. In this talk two parameters are introduced that attempt to deal with these two properties. First, an elastic anisotropy parameter that captures a materials susceptibility to solute solution strengthening is identified. The anisotropy parameter has many applications in the discovery and optimization of structural materials. As a a first example, the parameter is used to identify alloys that might display the super-elasticity, super-strength, and high ductility of the class of Ti-Nb alloys known as Gum Metal. In addition, it is noted that the parameter can be used to screen candidate alloys for shape memory response. In an effort to better predict the intrinsic ductility of alloys a second parameter is presented that is rooted in nonlinear elasticity theory. The intrinsic ductility parameter is shown to correlate well with the measured elongations to failure for elemental body centered cubic and hexagonal close packed metals. Finally, it is demonstrated how these two parameters could potentially aid in the optimization of the mechanical properties of high-entropy alloys.
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