Application of ASTAR/precession electron diffraction technique to quantitatively study defects in nanocrystalline metallic materials

Nanocrystalline metallic materials have the potential to exhibit outstanding performance which leads to their usage in challenging applications such as coatings and biomedical implant devices. To optimize the performance of nanocrystalline metallic materials according to the desired applications, it is important to have a decent understanding of the structure, processing and properties of these materials. Various efforts have been made to correlate microstructure and properties of nanocrystalline metallic materials. Based on these research activities, it is noticed that microstructure and defects (e.g., dislocations and grain boundaries) play a key role in the behavior of these materials. Therefore, it is of great importance to establish methods to quantitatively study microstructures, defects and their interactions in nanocrystalline metallic materials. Since the mechanisms controlling the properties of nanocrystalline metallic materials occur at a very small length scale, it is fairly difficult to study them. Unfortunately, most of the characterization techniques used to explore these materials do not have the high enough spatial resolution required for the characterization of these materials. For instance, by applying complex profile-fitting algorithms to X-ray diffraction patterns, it is possible to get an estimation of the average grain size and the average dislocation density within a relatively large area. However, these average values are not enough for developing meticulous phenomenological models which are able to correlate microstructure and properties of nanocrystalline metallic materials. As another example, electron backscatter diffraction technique also cannot be used widely in the characterization of these materials due to problems such as relative poor spatial resolution (which is ~90 nm) and the degradation of Kikuchi diffraction patterns in severely deformed nano-size grain metallic materials. In this study, ASTAR/precession electron diffraction is introduced as a relatively new orientation microscopy technique to characterize defects (e.g., geometrically necessary dislocations and grain boundaries) in challenging nanocrystalline metallic materials. The capability of this characterization technique to quantitatively determine the dislocation density distributions of geometrically necessary dislocations in severely deformed metallic materials is assessed. Based on the developed method, it is possible to determine the distributions and accumulations of dislocations with respect to the nearest grain boundaries and triple junctions. Also, the competency of this technique to study the grain boundary character distributions of nanocrystalline metallic materials is presented

An Integrated Approach to Determine Phenomenological Equations in Metallic Systems

It is highly desirable to be able to make predictions of properties in metallic materials based upon the composition of the material and the microstructure. Unfortunately, the complexity of real, multi-component, multi-phase engineering alloys makes the provision of constituent-based (i.e., composition or microstructure) phenomenological equations extremely difficult. Due to these difficulties, qualitative predictions are frequently used to study the influence of microstructure or composition on the properties. Neural networks were used as a tool to get a quantitative model from a database. However, the developed model is not a phenomenological model. In this study, a new method based upon the integration of three separate modeling approaches, specifically artificial neural networks, genetic algorithms, and monte carlo was proposed. These three methods, when coupled in the manner described in this study, allows for the extraction of phenomenological equations with a concurrent analysis of uncertainty. This approach has been applied to a multi-component, multi-phase microstructure exhibiting phases with varying spatial and morphological distributions. Specifically, this approach has been applied to derive a phenomenological equation for the prediction of yield strength in a+b processed Ti-6-4. The equation is consistent with not only the current dataset but also, where available, the limited information regarding certain parameters such as intrinsic yield strength of pure hexagonal close-packed alpha titanium

Determination of the five parameter grain boundary character distribution of nanocrystalline alpha-zirconium thin films using transmission electron microscopy

Grain boundary engineering and other fundamental materials science problems (e.g., phase transformations and physical properties) require an improvement in the understanding of the type and population of grain boundaries in a given system – yet, databases are limited in number and spare in detail, including for hcp crystals such as zirconium. One way to rapidly obtain databases to analyze is to use small-grained materials and high spatial resolution orientation microscopy techniques, such as ASTAR™/precession electron diffraction. To demonstrate this, a study of grain boundary character distributions was conducted for α-zirconium deposited at room temperature on fused silica substrates using physical vapor deposition. The orientation maps of the nanocrystalline thin films were acquired by the ASTAR™/precession electron diffraction technique, a new transmission electron microscope based orientation microscopy method. The reconstructed grain boundaries were classified as pure tilt, pure twist, 180°-twist and 180°-tilt grain boundaries based on the distribution of grain boundary planes with respect to the angle/axis of misorientation associated with grain boundaries. The results of the current study were compared to the results of a similar study on α-titanium and the molecular dynamics results of grain boundary energy for α-titanium

A Constitutive Equation Relating Composition and Microstructure to Properties in Ti-6Al-4V: As Derived Using a Novel Integrated Computational Approach

While it is useful to predict properties in metallic materials based upon the composition and microstructure, the complexity of real, multi-component, and multi-phase engineering alloys presents difficulties when attempting to determine constituent-based phenomenological equations. This paper applies an approach based upon the integration of three separate modeling approaches, specifically artificial neural networks, genetic algorithms, and Monte Carlo simulations to determine a mechanism-based equation for the yield strength of α+βprocessed Ti-6Al-4V (all compositions in weight percent) which consists of a complex multi-phase microstructure with varying spatial and morphological distributions of the key microstructural features. Notably, this is an industrially important alloy yet an alloy for which such an equation does not exist in the published literature. The equation ultimately derived in this work not only can accurately describe the properties of the current dataset but also is consistent with the limited and dissociated information available in the literature regarding certain parameters such as intrinsic yield strength of pure hexagonal close-packed alpha titanium. In addition, this equation suggests new interesting opportunities for controlling yield strength by controlling the relative intrinsic strengths of the two phases through solid solution strengthening

A new combinatorial approach to assess the influence of alloy composition on the oxidation behavior and concurrent oxygen-induced phase transformations for binary Ti–xCr alloys at 650°C

AbstractPoor oxidation performance of Ti-based alloys is an important life-limiting factor for high temperature applications. In this paper, a combinatorial approach is used to investigate systematically the influence of composition and time on the oxidation of Ti–Cr system. A compositionally graded Ti–xCr specimen (0⩽x⩽40wt%) was prepared and oxidized at 650°C. The structure and composition of the oxide and near-surface region were studied and a critical composition of ∼20wt% Cr was identified above which the oxidation resistance is enhanced. Below the critical composition transition to a rapid breakaway oxidation was observed for extended exposure times

Systematic Assessment of the Influence of Mo Concentration on the Oxygen Ingress in Ti–Mo System During High Temperature Oxidation

To understand the role of composition in the oxidation behavior of Ti–Mo system and to evaluate the extent of oxygen ingress into the metal substrate during high temperature exposure, a compositionally graded Ti–xMo specimen (0 ≤ x ≤ 12 wt% Mo) was prepared using an additive manufacturing technique, solutionized and then subjected to oxidation tests at 650 °C for different exposure times. The depth of oxygen diffusion, across the composition range, was assessed via change in the local hardness and the results were coupled with quantitative measurement of the oxygen concentration. The concentration of O in the α phase was reduced by 90 % after a short distance of 16 μm from the metal/oxide interface while it remained more or less the same in β phase. The solubility of Mo in α phase also approached zero near the surface as O changed the partition coefficient of this element between α and β phases. It was shown that the addition of Mo reduces the solubility of O in the metal substrate which in turn retards the transition point from parabolic to the linear oxidation stage

Microscale phase field modeling of the martensitic transformation during cyclic loading of NiTi single crystal

A microscale phase field model developed in Levitas et al. (2004) and Idesman et al. (2005) is slightly advanced for different and anisotropic elastic moduli of phases and is employed for the study of the stress-induced cubic-monoclinic phase transition in NiTi single crystal involving all 12 martensitic variants. The model is scale-independent, without the gradient term, and it is applicable for any scale greater than 100 nm. This model includes strain softening and the corresponding transformation strain localization, and it reproduces a discrete martensitic microstructure. The model only tracks finite-width interfaces between austenite and the mixture of martensitic variants, and does not consider the interfaces between martensitic variants. The model is implemented as a UMAT subroutine in a commercial finite element (FE) package, ABAQUS. Multiple problems for a uniaxial cyclic loading are solved to study the effect of mesh, strain rate, crystal orientation, different numbers of pre-existing nuclei, and the magnitude of the athermal threshold on the stress-strain responses as well as the microstructure evolution. The obtained results exhibit that the microstructure and global stress-strain responses are practically independent of mesh discretization and the applied strain rate for relatively small strain rates. While the presence of the initial nuclei in the sample decreases the nucleation stress, it slightly increases the total energy dissipation. The observed microstructure, the sudden drop in the stress-strain curve after initiation of the martensitic transformation, and the absence of a similar jump for the reverse phase transformation are in qualitative agreement with known experiments. Changing the crystallographic orientation of the sample varies the entire behavior, namely, the variants which are involved in the phase transformation, the morphology of the associated microstructure, the stress-strain curve, and the total dissipation. Athermal threshold, in addition to the expected increase in the magnitude of hysteresis, leads to some strain hardening for the direct phase transformation

Characterizing the nano-structure and defect structure of nano-scaled non-ferrous structural alloys

The presence and interaction of nanotwins, geometrically necessary dislocations, and grain boundaries play a key role in the mechanical properties of nanostructured crystalline materials. Therefore, it is vital to determine the orientation, width and distance of nanotwins, the angle and axis of grain boundary misorientations as well as the type and the distributions of dislocations in an automatic and statistically meaningful fashion in a relatively large area. In this paper, such details are provided using a transmission electron microscope-based orientation microscopy technique called ASTAR™/precession electron diffraction. The remarkable spatial resolution of this technique (~ 2 nm) enables highly detailed characterization of nanotwins, grain boundaries and the configuration of dislocations. This orientation microscopy technique provides the raw data required for the determination of these parameters. The procedures to post-process the ASTAR™/PED datasets in order to obtain the important (and currently largely hidden) details of nanotwins as well as quantifications of dislocation density distributions are described in this study

Developing a phenomenological equation to predict yield strength from composition and microstructure in β processed Ti-6Al-4V

A constituent-based phenomenological equation to predict yield strength values from quantified measurements of the microstructure and composition of β processed Ti-6Al-4V alloy was developed via the integration of artificial neural networks and genetic algorithms. It is shown that the solid solution strengthening contributes the most to the yield strength (~80% of the value), while the intrinsic yield strength of the two phases and microstructure have lower effects (~10% for both terms). Similarities and differences between the proposed equation and the previously established phenomenological equation for the yield strength prediction of the α+β processed Ti-6Al-4V alloys are discussed. While the two equations are very similar in terms of the intrinsic yield strength of the two constituent phases, the solid solution strengthening terms and the ‘Hall-Petch’-like effect from the alpha lath, there is a pronounced difference in the role of the basketweave factor in strengthening. Finally, Monte Carlo simulations were applied to the proposed phenomenological equation to determine the effect of measurement uncertainties on the estimated yield strength values

On the role of composition and processing parameters on the microstructure evolution of Ti-xMo alloys

Abstract Laser Engineered Net Shaping (LENS™) was used to produce a compositionally graded Ti-xMo (0 ≤ x ≤ 12 wt %) specimen and nine Ti-15Mo (fixed composition) specimens at different energy densities to understand the composition–processing–microstructure relationships operating using additive manufacturing. The gradient was used to evaluate the effect of composition on the prior-beta grain size. The specimens deposited using different energy densities were used to assess the processing parameters influence the microstructure evolutions. The gradient specimen did not show beta grain size reduction with the Mo content. The analysis from the perspective of the two grain refinement mechanisms based on a model known as the Easton & St. John, which was originally developed for aluminum and magnesium alloys shows the lower bound in prior-beta grain refinement with the Ti–Mo system. The low growth restriction factor for the Ti-Mo system of Q = 6,5C0 explains the unsuccessful refinement from the solute-based mechanism. The energy density and the grain size are proportional according to the results of the nine fixed composition specimens at different energy densities. More energy absorption from the material represents bigger molten pools, which in turn relates to lower cooling rates.https://deepblue.lib.umich.edu/bitstream/2027.42/147465/1/13065_2019_Article_529.pd