Spherical nanoindentation combined with electron back-scattered diffraction has been employed to characterize the grain-scale elastic and plastic anisotropy of single crystal alpha-Ti of two different compositions (in two different titanium alloys). Data analyses protocols needed to reliably extract the desired properties of interest are extended and demonstrated in this paper. Specifically, the grain-scale mechanical response is extracted in the form of indentation stressstrain curves for commercially pure (CP-Ti) alpha-Ti and alloyed (Ti-64) titanium from measurements on polycrystalline samples. The results are compared with responses of single crystals and nanoindentation tests (hardness and modulus) from the literature, and the measured indentation moduli are validated using crystal-elastic finite element simulations. The results obtained in this study show that (i) it is possible to characterize reliably the elastic and plastic anisotropy of alpha-Ti (hcp) of varying alloying contents with spherical nanoindentation stressstrain curves, (ii) the indentation modulus of alpha-Ti-64 is 5-10% less than CP-Ti, and (iii) the indentation yield strength of alpha-Ti-64 is 50 to 80% higher than CP-Ti.

Computationally efficient structure-property (S-P) linkages (i.e., reduced order models) are a necessary key ingredient in accelerating the rate of development and deployment of structural materials. This need represents a major challenge for polycrystalline materials, which exhibit rich heterogeneous microstructure at multiple structure/length scales, and exhibit a wide range of properties. In this study, a novel framework is described for extracting S-P linkages in polycrystalline microstructures that are obtained using 2-point spatial correlations (also called 2-point statistics) to quantify the material's microstructure, and principal component analysis (PCA) to represent this information in a reduced dimensional space. Additionally, it is demonstrated that the use of generalized spherical harmonics (GSH) as a Fourier basis for functions defined on the orientation space leads to a compact and computationally efficient representation of the desired S-P linkages. In this study, these novel protocols are developed and demonstrated for elastic stiffness and yield strength predictions for α−Ti microstructures using a dataset produced through microscale finite element simulations.

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