Aerosol deposition (AD) is a solid-state deposition technology that has been developed to fabricate ceramic coatings nominally at room temperature. Sub-micron ceramic particles accelerated by pressurized gas impact, deform, and consolidate on substrates under vacuum. Ceramic particle consolidation in AD coatings is highly dependent on particle deformation and bonding; these behaviors are not well understood. In this work, atomistic simulations and in situ micro-compressions in the scanning electron microscope, and the transmission electron microscope (TEM) were utilized to investigate fundamental mechanisms responsible for plastic deformation/fracture of particles under applied compression. Results showed that highly defective micron-sized alumina particles, initially containing numerous dislocations or a grain boundary, exhibited no observable shape change before fracture/fragmentation. Simulations and experimental results indicated that particles containing a grain boundary only accommodate low strain energy per unit volume before crack nucleation and propagation. In contrast, nearly defect-free, sub-micron, single crystal alumina particles exhibited plastic deformation and fracture without fragmentation. Dislocation nucleation/motion, significant plastic deformation, and shape change were observed. Simulation and TEM in situ micro-compression results indicated that nearly defect-free particles accommodate high strain energy per unit volume associated with dislocation plasticity before fracture. The identified deformation mechanisms provide insight into feedstock design for AD.
In this study, ductile failure of structural metals is a pervasive issue for applications such as automotive manufacturing, transportation infrastructures, munitions and armor, and energy generation. Experimental investigation of all relevant failure scenarios is intractable, requiring reliance on computation models. Our confidence in model predictions rests on unbiased assessments of the entire predictive capability, including the mathematical formulation, numerical implementation, calibration, and execution.
In this report, we present a multi-scale computational model to simulate plastic deformation of tantalum and validating experiments. In atomistic/ dislocation level, dislocation kink- pair theory is used to formulate temperature and strain rate dependent constitutive equations. The kink-pair theory is calibrated to available data from single crystal experiments to produce accurate and convenient constitutive laws. The model is then implemented into a BCC crystal plasticity finite element method (CP-FEM) model to predict temperature and strain rate dependent yield stresses of single and polycrystalline tantalum and compared with existing experimental data from the literature. Furthermore, classical continuum constitutive models describing temperature and strain rate dependent flow behaviors are fit to the yield stresses obtained from the CP-FEM polycrystal predictions. The model is then used to conduct hydro- dynamic simulations of Taylor cylinder impact test and compared with experiments. In order to validate the proposed tantalum CP-FEM model with experiments, we introduce a method for quantitative comparison of CP-FEM models with various experimental techniques. To mitigate the effects of unknown subsurface microstructure, tantalum tensile specimens with a pseudo-two-dimensional grain structure and grain sizes on the order of millimeters are used. A technique combining an electron back scatter diffraction (EBSD) and high resolution digital image correlation (HR-DIC) is used to measure the texture and sub-grain strain fields upon uniaxial tensile loading at various applied strains. Deformed specimens are also analyzed with optical profilometry measurements to obtain out-of- plane strain fields. These high resolution measurements are directly compared with large-scale CP-FEM predictions. This computational method directly links fundamental dislocation physics to plastic deformations in the grain-scale and to the engineering-scale applications. Furthermore, direct and quantitative comparisons between experimental measurements and simulation show that the proposed model accurately captures plasticity in deformation of polycrystalline tantalum.
Previous experiments have shown a link between oxidation and strength changes in single crystal silicon nanostructures but provided no clues as to the mechanisms leading to this relationship. Using atomic force microscope-based fracture strength experiments, molecular dynamics modeling, and measurement of oxide development with angle resolved x-ray spectroscopy we study the evolution of strength of silicon (111) surfaces as they oxidize and with fully developed oxide layers. We find that strength drops with partial oxidation but recovers when a fully developed oxide is formed and that surfaces intentionally oxidized from the start maintain their high initial strengths. MD simulations show that strength decreases with the height of atomic layer steps on the surface. These results are corroborated by a completely separate line of testing using micro-scale, polysilicon devices, and the slack chain method in which strength recovers over a long period of exposure to the atmosphere. Combining our results with insights from prior experiments we conclude that previously described strength decrease is a result of oxidation induced roughening of an initially flat silicon (1 1 1) surface and that this effect is transient, a result consistent with the observation that surfaces flatten upon full oxidation.
Bimodal grain structures are common in many alloys, arising from a number of different causes including incomplete recrystallization and abnormal grain growth. These bimodal grain structures have important technological implications, such as the well-known Goss texture which is now a cornerstone for electrical steels. Yet our ability to detect bimodal grain distributions is largely confined to brute force cross-sectional metallography. The present study presents a new method for rapid detection of unusually large grains embedded in a sea of much finer grains. Traditional X-ray diffraction-based grain size measurement techniques such as Scherrer, Williamson–Hall, or Warren–Averbach rely on peak breadth and shape to extract information regarding the average crystallite size. However, these line broadening techniques are not well suited to identify a very small fraction of abnormally large grains. The present method utilizes statistically anomalous intensity spikes in the Bragg peak to identify regions where abnormally large grains are contributing to diffraction. This needle-in-a-haystack technique is demonstrated on a nanocrystalline Ni–Fe alloy which has undergone fatigue-induced abnormal grain growth. In this demonstration, the technique readily identifies a few large grains that occupy <0.00001 % of the interrogation volume. Finally, while the technique is demonstrated in the current study on nanocrystalline metal, it would likely apply to any bimodal polycrystal including ultrafine grained and fine microcrystalline materials with sufficiently distinct bimodal grain statistics.
