Single Crystal Plasticity Modeling of Ni-Based Alloys with First-Principles Calculations of Ideal Shear Strength
John Shimanek, The Pennsylvania State University
The macroscopic deformation behavior of a crystalline material can be resolved onto its slip systems to allow for the consideration of microscopic physical mechanisms. In the crystal plasticity method, constitutive hardening models describe the evolution of slip system strength, which can be phenomenological or based on theories describing the collective motion of dislocations, the primary carriers of plasticity in metals under moderate to low strain rates. Hardening models of both types are often parameterized by fitting to experimental stress-strain curves, limiting their predictive power and their use in alloy design for applications requiring large plastic strains. The present work examines how information from lower length scale calculations, including first-principles calculations based on density functional theory, can be incorporated into a phenomenological hardening model within a crystal plasticity finite element method framework. The ideal shear strength of pure Ni is first incorporated into an analytical model of dislocation population evolution, and the resulting parameterized hardening model is used to predict stress-strain behavior of single crystal Ni of multiple crystallographic orientations, comparing well to experimental results in the literature. A similar methodology is used to calculate the ideal shear strengths of binary Ni-based alloys of the composition Ni11X, where X is one of 26 different alloying elements. Methods of feature selection and correlational analysis on the calculated strengths and a database containing atomic features of each alloying element reveal associations between alloy strength and atomic size and electronic properties, highlighting possible strategies in the construction of descriptors for data-driven deformation applications.
Abstract Author(s): John D. Shimanek, Shun-Li Shang, Allison M. Beese, and Zi-Kui Liu