Most of the materials that make up our daily-life infrastructure (transportation, power generation, etc.) are predominantly polycrystalline and metallic, such as steel, aluminum, magnesium, or copper. Polycrystallinity means that all atoms in the material are arranged on a regular grid and the grid orientation is different in neighboring volumes (which are termed "grains" or "crystallites"). To master the manufacturing steps and predict the in-service performance of such structurally important materials, engineers make use of models that describe the mechanical behavior of these materials. Such models have a fair number of adjustable parameters, which are different for each material and need to be quantified for each of them. This parameter identification is quite involved, particularly for metals that have complicated atomic arrangements, such as, for instance, titanium, magnesium, or tin.
In this research project, the PIs replace the traditional way of parameter identification done by observing the deformation of difficult to obtain samples, by a new method that puts small impressions with a specially shaped needle. Having such a cost-effective means to establish the material model will lead to substantial savings in time, energy, and material cost across the manufacturing chain and improved prediction of final material properties. This program will also have broad benefits by exposing students at multiple levels to science and engineering, including the education and training of both graduate and undergraduate students to contribute to the nation's intellectual infrastructure.
The integration of computational modeling into process development and design continues to accelerate due to the potential shortened development times, cost savings, and enhanced reliability. At the fundamental level, the controlling factors in the mechanical behavior of structural metals are the resistance of dislocations to slip, i.e. the critical resolved shear stress for the motion of dislocations, and the concurrent structural evolution (e.g. work hardening). Thus, in order to accurately describe the deformation, possible damage nucleation, and fracture behavior of the polycrystalline arrays that make up structural components, it is necessary to have a sound model with physical deformation processes involved and accurate values for the adjustable parameters that enter such models. While these constitutive parameters can be readily determined for many cubic metals using well established single crystal methods, they are much more difficult to ascertain in many non-cubic metals. This is because even in cases when suitable single crystals can be obtained, the large differences in activation stress for different slip system types can make it impossible to selectively activate some (set of) slip systems in standard uniaxial tests of single crystals. Multiphase materials pose a further challenge, where historically it has been very difficult to carry out analysis on the individual phases without the influence of neighboring phases. Provided that adjustable parameters of a selected constitutive model are available with confidence, full or mean field crystal plasticity simulations of arbitrary deformation paths (occurring, for instance, in metal forming) can then be used to understand and predict the anisotropic deformation and damage nucleation in non-cubic metals. The proposed research applies a newly developed approach to determine parameters of the constitutive description in a relatively rapid and cost-effective manner to a number of different single and dual phase alloys. In this technique, sphero-conical nano-indentation is used to serially interrogate a sufficiently large number of different crystal orientations at the surface of polycrystalline samples. Atomic force microscopy is then used to measure the topography around these indents, which is a strong function of the crystal orientation and the specific local activity of different slip systems. Crystal plasticity finite element (CPFE) simulation of the indentation process is then carried out with varying constitutive parameters until an optimal match is achieved between the measured and simulated topographies in several different indents on crystals with different orientations/topographies. This method is effective because the axisymmetric sphero-conical indentation geometry causes many different slip systems to operate at different rates and along different strain paths depending on the material location beneath the indent. In the present study this approach will be used to determine the constitutive parameters in a range of titanium-based alloys containing hexagonal and body-centered cubic phases as well as in tetragonal tin of 99% purity. The constitutive parameters identified for the commercially important alloys will have a direct effect on the ability to develop integrated computational materials engineering (ICME) data and models across a variety of length scales. This will lead to substantial savings in time, energy, and material cost. Overall it is very important for materials processing to be able to reliably predict heterogeneous deformation, which is required before prediction of performance or reliability can be made with physically-based confidence.
