Ayman A. Salem

Strain hardening of titanium: role of deformation twinning

Abstract The purpose of this study is to investigate the role of deformation twinning in the strain-hardening behavior of high purity, polycrystalline α-titanium in a number of different deformation modes. Constant strain rate tests were conducted on this material in simple compression, plane-strain compression and simple shear, and the true stress (σ)-true strain (e) responses were documented. From the measured data, the strain hardening rates were numerically computed, normalized by the shear modulus (G), and plotted against both normalized stress and e. These normalized strain hardening plots exhibited three distinct stages of strain hardening that were similar to those observed in previous studies on low stacking fault energy fcc metals (e.g. 70/30 brass) in which deformation twinning has been known to play an important role. Optical microscopy and Orientation imaging microscopy were conducted on samples deformed to different strain levels in the various deformation paths. It was found that the onset of deformation twinning correlated with a sudden increase in strain hardening rate in compression tests. The falling strain hardening rate correlated with saturation in the twin volume fraction. In shear testing a much lower rate of strain hardening was found, at all strains, and this correlated with a lower density of deformation twinning.

Strain hardening regimes and microstructure evolution during large strain compression of high purity titanium

Abstract The sudden increase of strain hardening rates seen after small strains in titanium, was shown to correlate with the onset of deformation twinning. This result appears to match quantitatively with Hall–Petch grain size strengthening. The new twin boundaries appear to reduce the effective grain size.

Variant Selection During Cooling after Beta Annealing of Ti-6Al-4V Ingot Material

The selection of alpha variants during the cooling of Ti-6Al-4V from the beta-phase field was investigated. For this purpose, samples with a coarse, columnar beta-grain structure with a 〈100〉 fiber texture were extracted from an as-cast production-scale ingot. The alpha variants in the as-cast samples as well as those produced during several successive beta-annealing treatments were determined using electron backscatter diffraction (EBSD). The EBSD results indicated that a subset of the 12 possible variants was developed within each grain; the specific variants were a function of the cooling rate after beta heat treatment. Moreover, the generation of similar variants during successive heat treatments involving an identical cooling rate suggested a noticeable memory effect. The variant selection process was rationalized based on calculations of the strain associated with the beta-to-alpha transformation. These calculations revealed that the overall aggregate strain approached zero in both the as-cast condition as well as after beta heat treatment, suggesting the occurrence of a long-range self-accommodation mechanism.

Workflow for integrating mesoscale heterogeneities in materials structure with process simulation of titanium alloys

In this paper, a generalized workflow is outlined for the necessary integration of multimodal measurements and multiphysics models at multiple hierarchical length scales demanded by an Integrated Computational Materials Engineering (ICME) approach to accelerated materials development. Recognizing that multiple choices or techniques are typically available in each of the main steps, several exemplary analyses are detailed utilizing mainly the alpha/beta titanium alloys as an illustrative case. It is anticipated that the use and further refinement of these workflows will promote transparency and engender intimate collaborations between materials experts and manufacturing/design specialists by providing an understanding of the various mesoscale heterogeneities that develop naturally in the workpiece as a direct consequence of the inherent heterogeneity imposed by the manufacturing history (i.e., different thermomechanical histories at different locations in the sample). More specifically, this article focuses on three main areas: (i) data science protocols for efficient analysis of large microstructure datasets (e.g., cluster analysis), (ii) protocols for extracting reduced descriptions of salient microstructure features for insertion into simulations (e.g., regions of homogeneity), and (iii) protocols for direct and efficient linking of materials models/databases into process/performance simulation codes (e.g., crystal plasticity finite element method).

Microstructure-Informed Cloud Computing for Interoperability of Materials Databases and Computational Models: Microtextured Regions in Ti Alloys

With the fast global adoption of the Materials Genome Initiative (MGI), scientists and engineers are faced with the need to conduct sophisticated data analytics on large datasets to extract knowledge that can be used in modeling the behavior of materials. This raises a new problem for materials scientists: how to create and foster interoperability and share developed software tools and generated datasets. A microstructure-informed cloud-based platform (MiCloud™) has been developed that addresses this need, enabling users to easily access and insert microstructure informatics into computational tools that predict performance of engineering products by accounting for microstructural dependencies on manufacturing provenance. The platform extracts information from microstructure data by employing algorithms including signal processing, machine learning, pattern recognition, computer vision, predictive analytics, uncertainty quantification, and data visualization. The interoperability capabilities of MiCloud and its various web-based applications are demonstrated in this case study by analyzing Ti6AlV4 microstructure data via automatic identification of various features of interest and quantifying its characteristics that are used in extracting correlations and causations for the associated mechanical behavior (e.g., yield strength, cold-dwell debit, etc.). The data were recorded by two methods: (1) backscattered electron (BSE) imaging for extracting spatial and morphological information about alpha and beta phases and (2) electron backscatter diffraction (EBSD) for extracting spatial, crystallographic, and morphological information about microtextured regions (MTRs) of the alpha phase. Extracting reliable knowledge from generated information requires data analytics of a large amount of multiscale microstructure data which necessitates the development of efficient algorithms (and the associated software tools) for data recording, analysis, and visualization. The interoperability of these tools and superior effectiveness of the cloud computing approach are validated by featuring several examples of its use in alpha/beta titanium alloys and Ni-based superalloys, reflecting the anticipated computational cost and time savings via the use of web-based applications in implementations of microstructure-informed integrated computational materials engineering (ICME).

Effects of Post-processing on Microstructure and Mechanical Properties of SLM-Processed IN-718

Nickel-based superalloys have been developed extensively and have proven attractive for various industrial applications over the past four decades, due to excellent mechanical properties that are maintained at high temperature. This study investigates selective laser melting (SLM) of the nickel-based superalloy IN-718 and documents the effects of post-processing treatments on the resulting microstructure and mechanical properties. Comprehensive microstructural characterization was performed on both as-deposited and post-processed materials using various techniques (e.g. EBSD, OM, BSE, CT). The as-deposited alloy exhibited fine and elongated grains that contribute to the mechanical anisotropy presented in a companion paper while post-processing produced a more equiaxed microstructure and reduced the mechanical anisotropy. Tensile, fracture toughness, and fatigue crack growth tests conducted at room temperature are reported in this work while elevated temperature properties are reported elsewhere. This work revealed the changes of the microstructure (γ morphology, γ crystallography, and precipitate distributions) and hence the mechanical behavior due HIP+HT which resulted in mechanical properties that approach wrought alloys after comparable heat treatment. The results are discussed in this light and focus on the differences in microstructure resulting from the AM process.