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Tuesday, May 18, 2010

Elastic Properties, Shear Energetics, Cleavage Fracture, and the Martensitic Transformation Mechanisms for the Ni-Ti-X (X=Pt, Pd) Ternary Alloys From First Principles

N. B. Hatcher, O. Y. Kontsevoi, A. J. Freeman, Northwestern University, Evanston, IL

To determine the effect of alloying on the martensitic behavior of NiTi, we apply first principles density functional theory calculations using the highly precise full-potential linearized augmented plane wave method (FLAPW) to model Ni-Ti-X (X=Pt, Pd) ternary systems. We compare formation energies of various stoichiometries and the pair energetics between ternary atoms to create a number of model austenite structures and establish solubility of alloying elements in NiTi.   Our findings show that Pt and Pd atoms prefer to decorate the lattice at second and third nearest neighbors from one another, respectively.  We examine the structural stability of each ternary alloy by calculating planar generalized stacking fault energetics of major shear planes, elastic constants, and cleavage energies.  These properties are then used to explain ductility and brittle crack propagation in each alloy.  Additionally, comparisons between ternary and binary alloys are given to explain the effect of alloying on martensitic behavior.  For example, we show that increased Pt content causes a dramatic softening of the austenite C' elastic constant and increased rigidity in the martensite, while low resistance to {011} shear indicates a mechanism to martensitic transformation.  Using this, we map an atomistic martensitic transformation path of binary and ternary systems.Supported by AFOSR (# FA9550-07-1-0174)

Summary: We have performed first principles calculations on the NiTiPt and NiTiPd high temperature shape memory alloys to determine key properties in predicting shape memory behavior. We illustrate the ability of these highly precise calculations to predict elastic properties, total energies, and structural stability without any input parameters. These methods may be used for both novel alloy design and understanding precursory mechanisms governing shape memory behavior.