In this project, we demonstrated stable nanoscale fracture in single-crystal silicon using an in-situ wedge-loaded double cantilever beam (DCB) specimen. The fracture toughness KIC was calculated directly from instrumented measurement of force and displacement via finite element analysis with frictional corrections. Measurements on multiple test specimens were used to show KIC = 0.72 ± 0.07 MPa m1/2 on {111} planes and observe the crack-growth resistance curve in <500 nm increments. The exquisite stability of crack growth, instrumented measurement of material response, and direct visual access to observe nanoscale fracture processes in an ideally brittle material differentiate this approach from prior DCB methods.
Process parameter selection in laser powder bed fusion (LPBF) controls the as-printed dimensional tolerances, pore formation, surface quality and microstructure of printed metallic structures. Measuring the stochastic mechanical performance for a wide range of process parameters is cumbersome both in time and cost. In this study, we overcome these hurdles by using high-throughput tensile (HTT) testing of over 250 dogbone samples to examine process-driven performance of strut-like small features, ~1 mm2 in austenitic stainless steel (316 L). The output mechanical properties, porosity, surface roughness and dimensional accuracy were mapped across the printable range of laser powers and scan speeds using a continuous wave laser LPBF machine. Tradeoffs between ductility and strength are shown across the process space and their implications are discussed. While volumetric energy density deposited onto a substrate to create a melt-pool can be a useful metric for determining bulk properties, it was not found to directly correlate with output small feature performance.
The microstructural-scale mechanisms that produce cracks in metals during deformation at elevated temperatures are relevant to applications that involve thermal exposure. Prior studies of cavitation during high-temperature deformation, for example, creep, suffered from an inability to directly observe the microstructural evolution that occurs during deformation and leads to void nucleation. The current study takes advantage of modern high-speed electron backscatter diffraction (EBSD) detectors to observe cavitation in oxygen-free, high-conductivity copper in situ during deformation at 300°C. Most voids formed at the triple junction between a twin boundary and a high-angle grain boundary (HAGB). This finding does not contradict previous studies that suggested that twins are resistant to cracking—it reveals that cracks in HAGBs originate at twin/HAGB triple junctions and that cracks preferentially grow along HAGBs rather than the accompanying twins. Atomistic simulations explored the origins of this observation and suggest that twin/HAGB triple junctions are microstructural weak points.
Metals subjected to irradiation environments undergo microstructural evolution and concomitant degradation, yet the nanoscale mechanisms for such evolution remain elusive. Here, we combine in situ heavy ion irradiation, atomic resolution microscopy, and atomistic simulation to elucidate how radiation damage and interfacial defects interplay to control grain boundary (GB) motion. While classical notions of boundary evolution under irradiation rest on simple ideas of curvature-driven motion, the reality is far more complex. Focusing on an ion-irradiated Pt Σ3 GB, we show how this boundary evolves by the motion of 120° facet junctions separating nanoscale {112} facets. Our analysis considers the short- and mid-range ion interactions, which roughen the facets and induce local motion, and longer-range interactions associated with interfacial disconnections, which accommodate the intergranular misorientation. We suggest how climb of these disconnections could drive coordinated facet junction motion. These findings emphasize that both local and longer-range, collective interactions are important to understanding irradiation-induced interfacial evolution.
Digital twins are emerging as powerful tools for supporting innovation as well as optimizing the in-service performance of a broad range of complex physical machines, devices, and components. A digital twin is generally designed to provide accurate in-silico representation of the form (i.e., appearance) and the functional response of a specified (unique) physical twin. This paper offers a new perspective on how the emerging concept of digital twins could be applied to accelerate materials innovation efforts. Specifically, it is argued that the material itself can be considered as a highly complex multiscale physical system whose form (i.e., details of the material structure over a hierarchy of material length) and function (i.e., response to external stimuli typically characterized through suitably defined material properties) can be captured suitably in a digital twin. Accordingly, the digital twin can represent the evolution of structure, process, and performance of the material over time, with regard to both process history and in-service environment. This paper establishes the foundational concepts and frameworks needed to formulate and continuously update both the form and function of the digital twin of a selected material physical twin. The form of the proposed material digital twin can be captured effectively using the broadly applicable framework of n-point spatial correlations, while its function at the different length scales can be captured using homogenization and localization process-structure-property surrogate models calibrated to collections of available experimental and physics-based simulation data.
With the proliferation of additive manufacturing and 3D printing technologies, a broader palette of material properties can be elicited from cellular solids, also known as metamaterials, architected foams, programmable materials, or lattice structures. Metamaterials are designed and optimized under the assumption of perfect geometry and a homogeneous underlying base material. Yet in practice real lattices contain thousands or even millions of complex features, each with imperfections in shape and material constituency. While the role of these defects on the mean properties of metamaterials has been well studied, little attention has been paid to the stochastic properties of metamaterials, a crucial next step for high reliability aerospace or biomedical applications. In this work we show that it is precisely the large quantity of features that serves to homogenize the heterogeneities of the individual features, thereby reducing the variability of the collective structure and achieving effective properties that can be even more consistent than the monolithic base material. In this first statistical study of additive lattice variability, a total of 239 strut-based lattices were mechanically tested for two pedagogical lattice topologies (body centered cubic and face centered cubic) at three different relative densities. The variability in yield strength and modulus was observed to exponentially decrease with feature count (to the power −0.5), a scaling trend that we show can be predicted using an analytic model or a finite element beam model. The latter provides an efficient pathway to extend the current concepts to arbitrary/complex geometries and loading scenarios. These results not only illustrate the homogenizing benefit of lattices, but also provide governing design principles that can be used to mitigate manufacturing inconsistencies via topological design.
With the rapid proliferation of additive manufacturing and 3D printing technologies, architected cellular solids including truss-like 3D lattice topologies offer the opportunity to program the effective material response through topological design at the mesoscale. The present report summarizes several of the key findings from a 3-year Laboratory Directed Research and Development Program. The program set out to explore novel lattice topologies that can be designed to control, redirect, or dissipate energy from one or multiple insult environments relevant to Sandia missions, including crush, shock/impact, vibration, thermal, etc. In the first 4 sections, we document four novel lattice topologies stemming from this study: coulombic lattices, multi-morphology lattices, interpenetrating lattices, and pore-modified gyroid cellular solids, each with unique properties that had not been achieved by existing cellular/lattice metamaterials. The fifth section explores how unintentional lattice imperfections stemming from the manufacturing process, primarily sur face roughness in the case of laser powder bed fusion, serve to cause stochastic response but that in some cases such as elastic response the stochastic behavior is homogenized through the adoption of lattices. In the sixth section we explore a novel neural network screening process that allows such stocastic variability to be predicted. In the last three sections, we explore considerations of computational design of lattices. Specifically, in section 7 using a novel generative optimization scheme to design novel pareto-optimal lattices for multi-objective environments. In section 8, we use computational design to optimize a metallic lattice structure to absorb impact energy for a 1000 ft/s impact. And in section 9, we develop a modified micromorphic continuum model to solve wave propagation problems in lattices efficiently.
The advanced materials team investigated the use of additively manufactured metallic lattice structures for mitigating impact response in a Davis gun earth penetrator impact experiment. High-fidelity finite element models were developed and validated with quasistatic experiments. These models were then used to simulate the response of such lattices when subjected to the acceleration loads expected in the Davis gun experiment. Results reveal how the impact mitigation performance of lattices can change drastically at a certain relative density. Based on these observations, an experiment deck was designed to probe the response of lattices with different relative densities during the Davis gun phase 2 shots. The expected performance of these lattices is predicted before testing based on simulation results. The results of the Davis gun phase 2 shots are expected to provide data which will be used to assess the predictive capability of the finite element simulations in such a complex impact environment.
Lithium-metal anodes can theoretically enable 10x higher gravimetric capacity than conventional graphite anodes. However, Li-metal anode cycling has proven difficult due to porous and dendritic morphologies, extensive parasitic solid electrolyte interphase reactions, and formation of dead Li. We systematically investigate the effects of applied interfacial pressure on Li-metal anode cycling performance and morphology in the recently developed and highly efficient 4 M lithium bis(fluorosulfonyl)imide in 1,2-dimethoxyethane electrolyte. We present cycling, morphology, and impedance data at a current density of 0.5 mA/cm2 and a capacity of 2 mAh/cm2 at applied interfacial pressures of 0, 0.01, 0.1, 1, and 10 MPa. Cryo-focused ion beam milling and cryo-scanning electron microscopy imaging in cross section reveal that increasing the applied pressure during Li deposition from 0 to 10 MPa leads to greater than a fivefold reduction in thickness (and therefore volume) of the deposited Li. This suggests that pressure during cycling can have a profound impact on the practical volumetric energy density for Li-metal anodes. A “goldilocks zone” of cell performance is observed at intermediate pressures of 0.1–1 MPa. Increasing pressure from 0 to 1 MPa generally improves cell-to-cell reproducibility, cycling stability, and Coulombic efficiency. However, the highest pressure (10 MPa) results in high cell overpotential and evidence of soft short circuits, which likely result from transport limitations associated with increased pressure causing local pore closure in the separator. All cells exhibit at least some signs of cycling instability after 50 cycles when cycled to 2 mAh/cm2 with thin 50 μm Li counter electrodes, though instability decreases with increasing pressure. In contrast, cells cycled to only 1 mAh/cm2 perform well for 50 cycles, indicating that capacity plays an important role in cycling stability.
Metamaterials, otherwise known as architected or programmable materials, enable designers to tailor mesoscale topology and shape to achieve unique material properties that are not present in nature. Additionally, with the recent proliferation of additive manufacturing tools across industrial sectors, the ability to readily fabricate geometrically complex metamaterials is now possible. However, in many high-performance applications involving complex multi-physics interactions, design of novel lattice metamaterials is still difficult. Design is primarily guided by human intuition or gradient optimization for simple problems. In this work, we show how machine learning guides discovery of new unit cells that are Pareto optimal for multiple competing objectives; specifically, maximizing elastic stiffness during static loading and minimizing wave speed through the metamaterial during an impact event. Additionally, we show that our artificial intelligence approach works with relatively few (3500) simulation calls.
Zarnas, Patrick D.; Boyce, Brad B.; Qu, Jianmin; Dingreville, Rémi
The accumulation of point defects and defect clusters in materials, as seen in irradiated metals for example, can lead to the formation and growth of voids. Void nucleation is derived from the condensation of supersaturated vacancies and depends strongly on the stress state. It is usually assumed that such stress states can be produced by microstructural defects such dislocations, grain boundaries or triple junctions, however, much less attention has been brought to the formation of voids near microcracks. Here, we investigate the coupling between point-defect diffusion/recombination and concentrated stress fields near mode-I crack tips via a spatially-resolved rate theory approach. A modified chemical potential enables point-defect diffusion to be partially driven by the mechanical fields in the vicinity of the crack tip. Simulations are carried out for microcracks using the Griffith model with increasing stress intensity factor KI. Our results show that below a threshold for the stress intensity factor, the microcrack acts purely as a microstructural sink, absorbing point defects. Above this threshold, vacancies accumulate at the crack tip. These results suggest that, even in the absence of plastic deformation, voids can form in the vicinity of a microcrack for a given load when the crack's characteristic length is above a critical length. While in ductile metals, irradiation damage generally causes hardening and corresponding quasi-brittle cleavage, our results show that irradiation conditions can favor void formation near microstructural stressors such as crack tips leading to lower resistance to crack propagation as predicted by traditional failure analysis.
Nanocrystalline (NC) metals suffer from an intrinsic thermal instability; their crystalline grains undergo rapid coarsening during processing treatments or under service conditions. Grain boundary (GB) solute segregation has been proposed to mitigate grain growth and thermally stabilize the grain structures of NC metals. However, the role of GB character in solute segregation and thermal stability of NC metals remains poorly understood. Herein, we employ high resolution microscopy techniques, atomistic simulations, and theoretical analysis to investigate and characterize the impact of GB character on segregation behavior and thermal stability in a model NC Pt-Au alloy. High resolution electron microscopy along with X-ray energy dispersive spectroscopy and automated crystallographic orientation mapping is used to obtain spatially correlated Pt crystal orientation, GB misorientation, and Au solute concentration data. Atomistic simulations of polycrystalline Pt-Au systems are used to reveal the plethora of GB segregation profiles as a function of GB misorientation and the corresponding impact on grain growth processes. With the aid of theoretical models of interface segregation, the experimental data for GB concentration profiles are used to extract GB segregation energies, which are then used to elucidate the impact of GB character on solute drag effects. Our results highlight the paramount role of GB character in solute segregation behavior. In broad terms, our approach provides future avenues to employ GB segregation as a microstructure design strategy to develop NC metallic alloys with tailored microstructures. This journal is
Metamaterials derive their unusual properties from their architected structure, which generally consists of a repeating unit cell designed to perform a particular function. However, existing metamaterials are, with few exceptions, physically continuous throughout their volume, and thus cannot take advantage of multi-body behavior or contact interactions. Here we introduce the concept of multi-body interpenetrating lattices, where two or more lattices interlace through the same volume without any direct connection to each other. This new design freedom allows us to create architected interpenetrating structures where energy transfer is controlled by surface interactions. As a result, multifunctional or composite-like responses can be achieved even with only a single print material. While the geometry defining interpenetrating lattices has been studied since the days of Euclid, additive manufacturing allows us to turn these mathematical concepts into physical objects with programmable interface-dominated properties. In this first study on interpenetrating lattices, we reveal remarkable mechanical properties including improved toughness, multi-stable/negative stiffness behavior, and electromechanical coupling.
In-situ transmission electron microscopy (TEM) provides an avenue to explore time-dependent nanoscale material changes induced by a wide range of environmental conditions that govern material performance and degradation. The In-situ Ion Irradiation TEM (I3TEM) at Sandia National Laboratories is a JEOL 2100 microscope that has been highly modified with an array of hardware and software that makes it particularly well suited to explore fundamental mechanisms that arise from coupled extreme conditions. Here, examples pertaining to multibeam ion irradiation, rapid thermal cycling, and nanomechanical testing on the I3TEM are highlighted, along with prospective advancements in the field of in-situ microscopy.
The failure forces and fracture strengths of polysilicon microelectromechanical system (MEMS) components in the form of stepped tensile bars with shoulder fillets were measured using a sequential failure chain methodology. Approximately 150 specimens for each of four fillet geometries with different stress concentration factors were tested. The resulting failure force and strength distributions of the four geometries were related by a common sidewall flaw population existing within different effective stressed lengths. The failure forces, strengths, and flaw population were well described by a weakest-link based analytical framework. Finite element analysis was used to verify body-force based expressions for the stress concentration factors and to provide insight into the variation of specimen effective length with fillet geometry. Monte Carlo simulations of flaw size and location, based on the strength measurements, were also used to provide insight into fillet shape and size effects. The successful description of the shoulder fillet specimen strengths provides further empirical support for application of the strength and flaw framework in MEMS fabrication and design optimization.
Advances in printed electronics are predicated on the integration of sophisticated printing technologies with functional materials. Although scalable manufacturing methods, such as letterpress and flexographic printing, have significant history in graphic arts printing, functional applications require sophisticated control and understanding of nanoscale transfer of fluid inks. Herein, a versatile platform is introduced to study and engineer printing forms, exploiting a microscale additive manufacturing process to design micro-architected materials with controllable porosity and deformation. Building on this technology, controlled ink transfer for submicron functional films is demonstrated. The design freedom and high-resolution 3D control afforded by this method provide a rich framework for studying mechanics of fluid transfer for advanced manufacturing processes.
Product designs from a wide range of industries such as aerospace, automotive, biomedical, and others can benefit from new metamaterials for mechanical energy dissipation. In this study, we explore a novel new class of metamaterials with unit cells that absorb energy via sliding Coulombic friction. Remarkably, even materials such as metals and ceramics, which typically have no intrinsic reversible energy dissipation, can be architected to provide dissipation akin to elastomers. The concept is demonstrated at different scales (centimeter to micrometer), with different materials (metal and polymer), and in different operating environments (high and low temperatures), all showing substantial dissipative improvements over conventional non-contacting lattice unit cells. Further, as with other ‘programmable’ metamaterials, the degree of Coulombic absorption can be tailored for a given application. An analytic expression is derived to allow rapid first-order optimization. This new class of Coulombic friction energy absorbers can apply broadly to many industrial sectors such as transportation (e.g. monolithic shock absorbers), biomedical (e.g. prosthetics), athletic equipment (e.g. skis, bicycles, etc.), defense (e.g. vibration tolerant structures), and energy (e.g. survivable electrical grid components).
Additively manufactured metamaterials such as lattices offer unique physical properties such as high specific strengths and stiffnesses. However, additively manufactured parts, including lattices, exhibit a higher variability in their mechanical properties than wrought materials, placing more stringent demands on inspection, part quality verification, and product qualification. Previous research on anomaly detection has primarily focused on using in-situ monitoring of the additive manufacturing process or post-process (ex-situ) x-ray computed tomography. In this work, we show that convolutional neural networks (CNN), a machine learning algorithm, can directly predict the energy required to compressively deform gyroid and octet truss metamaterials using only optical images. Using the tiled nature of engineered lattices, the relatively small data set (43 to 48 lattices) can be augmented by systematically subdividing the original image into many smaller sub-images. During testing of the CNN, the prediction from these sub-images can be combined using an ensemble-like technique to predict the deformation work of the entire lattice. This approach provides a fast and inexpensive screening tool for predicting properties of 3D printed lattices. Importantly, this artificial intelligence strategy goes beyond ‘inspection’, since it accurately estimates product performance metrics, not just the existence of defects.
Residual strain in electrodeposited Li films may affect safety and performance in Li metal battery anodes, so it is important to understand how to detect residual strain in electrodeposited Li and the conditions under which it arises. To explore this Li films, electrodeposited onto Cu metal substrates, were prepared under an applied pressure of either 10 or 1000 kPa and subsequently tested for the presence or absence of residual strain via sin(ψ) analysis. X-ray diffraction (XRD) analysis of Li films required preparation and examination within an inert environment; hence, a Be-dome sample holder was employed during XRD characterization. Results show that the Li film grown under 1000 kPa displayed a detectable presence of in-plane compressive strain (-0.066%), whereas the Li film grown under 10 kPa displayed no detectable in-plane strain. The underlying Cu substrate revealed an in-plane residual strain near zero. Texture analysis via pole figure determination was also performed for both Li and Cu and revealed a mild fiber texture for Li metal and a strong bi-axial texture of the Cu substrate. Experimental details concerning sample preparation, alignment, and analysis of the particularly air-sensitive Li films have also been detailed. This work shows that Li metal exhibits residual strain when electrodeposited under compressive stress and that XRD can be used to quantify that strain.
The high-cycle fatigue life of nanocrystalline and ultrafine-grained Ni-Fe was examined for five distinct grain sizes ranging from approximately 50–600 nm. The fatigue properties were strongly dependent on grain size, with the endurance limit changing by a factor of 4 over this narrow range of grain size. The dataset suggests a breakdown in fatigue improvement for the smallest grain sizes <100 nm, likely associated with a transition to grain coarsening as a dominant rate-limiting mechanism. The dataset also is used to explore fatigue prediction from monotonic tensile properties, suggesting that a characteristic flow strength is more meaningful than the widely-utilized ultimate tensile strength.
Nanocrystalline metals are promising radiation tolerant materials due to their large interfacial volume fraction, but irradiation-induced grain growth can eventually degrade any improvement in radiation tolerance. Therefore, methods to limit grain growth and simultaneously improve the radiation tolerance of nanocrystalline metals are needed. Amorphous intergranular films are unique grain boundary structures that are predicted to have improved sink efficiencies due to their increased thickness and amorphous structure, while also improving grain size stability. In this study, ball milled nanocrystalline Cu-Zr alloys are heat treated to either have only ordered grain boundaries or to contain amorphous intergranular films distributed within the grain boundary network, and are then subjected to in situ transmission electron microscopy irradiation and ex situ irradiation. Differences in defect density and grain growth due to grain boundary complexion type are then investigated. When amorphous intergranular films are incorporated within the material, fewer and smaller defect clusters are observed while grain growth is also limited, leading to nanocrystalline alloys with improved radiation tolerance.
Recent work in metal additive manufacturing (AM) suggests that mechanical properties may vary with feature size; however, these studies do not provide a statistically robust description of this phenomenon, nor do they provide a clear causal mechanism. Because of the huge design freedom afforded by 3D printing, AM parts typically contain a range of feature sizes, with particular interest in smaller features, so the size effect must be well understood in order to make informed design decisions. This work investigates the effect of feature size on the stochastic mechanical performance of laser powder bed fusion tensile specimens. A high-throughput tensile testing method was used to characterize the effect of specimen size on strength, elastic modulus and elongation in a statistically meaningful way. The effective yield strength, ultimate tensile strength and modulus decreased strongly with decreasing specimen size: all three properties were reduced by nearly a factor of two as feature dimensions were scaled down from 6.25 mm to 0.4 mm. Hardness and microstructural observations indicate that this size dependence was not due to an intrinsic change in material properties, but instead the effects of surface roughness on the geometry of the specimens. Finite element analysis using explicit representations of surface topography shows the critical role surface features play in creating stress concentrations that trigger deformation and subsequent fracture. The experimental and finite element results provide the tools needed to make corrections in the design process to more accurately predict the performance of AM components.
Ductile rupture or tearing usually involves structural degradation from the nucleation and growth of voids and their coalescence into cracks. Although some materials contain preexisting pores, the first step in failure is often the formation of voids. Because this step can govern both the failure strain and the fracture mechanism, it is critical to understand the mechanisms of void nucleation and the enabling microstructural configurations which give rise to nucleation. To understand the role of dislocations during void nucleation, the present study presents ex-situ cross-sectional observations of interrupted deformation experiments revealing incipient, subsurface voids in a copper material containing copper oxide inclusions. The local microstructural state was evaluated using electron backscatter diffraction (EBSD), electron channeling contrast (ECC), transmission electron microscopy (TEM), and transmission kikuchi diffraction (TKD). Surprisingly, before substantial growth and coalescence had occurred, the deformation process had resulted in the nucleation of a high density of nanoscale (≈50 nm) voids in the deeply deformed neck region where strains were on the order of 1.5. Such a proliferation of nucleation sites immediately suggests that the rupture process is limited by void growth, not nucleation. With regard to void growth, analysis of more than 20 microscale voids suggests that dislocation boundaries facilitate the growth process. The present observations call into question prior assumptions on the role of dislocation pile-ups and provide new context for the formulation of revised ductile rupture models. While the focus of this study is on damage accumulation in a highly ductile metal containing small, well-dispersed particles, these results are also applicable to understanding void nucleation in engineering alloys.
The mechanical properties of additively manufactured metals tend to show high variability, due largely to the stochastic nature of defect formation during the printing process. This study seeks to understand how automated high throughput testing can be utilized to understand the variable nature of additively manufactured metals at different print conditions, and to allow for statistically meaningful analysis. This is demonstrated by analyzing how different processing parameters, including laser power, scan velocity, and scan pattern, influence the tensile behavior of additively manufactured stainless steel 316L utilizing a newly developed automated test methodology. Microstructural characterization through computed tomography and electron backscatter diffraction is used to understand some of the observed trends in mechanical behavior. Specifically, grain size and morphology are shown to depend on processing parameters and influence the observed mechanical behavior. In the current study, laser-powder bed fusion, also known as selective laser melting or direct metal laser sintering, is shown to produce 316L over a wide processing range without substantial detrimental effect on the tensile properties. Ultimate tensile strengths above 600 MPa, which are greater than that for typical wrought annealed 316L with similar grain sizes, and elongations to failure greater than 40% were observed. It is demonstrated that this process has little sensitivity to minor intentional or unintentional variations in laser velocity and power.
Knowing when, why, and how materials evolve, degrade, or fail in radiation environments is pivotal to a wide range of fields from semiconductor processing to advanced nuclear reactor design. A variety of methods, including optical and electron microscopy, mechanical testing, and thermal techniques, have been used in the past to successfully monitor the microstructural and property evolution of materials exposed to extreme radiation environments.Acoustic techniques have also been used in the past for this purpose, although most methodologies have not achieved widespread adoption. However, with an increasing desire to understand microstructure and property evolution in situ, acoustic methods provide a promising pathway to uncover information not accessible to more traditional characterization techniques. This work highlights how two different classes of acoustic techniques may be used to monitor material evolution during in situ ion beam irradiation. The passive listening technique of acoustic emission is demonstrated on two model systems, quartz and palladium, and shown to be a useful tool in identifying the onset of damage events such as microcracking.An active acoustic technique in the form of transient grating spectroscopy is used to indirectly monitor the formation of small defect clusters in copper irradiated with self-ions at high temperature through the evolution of surface acoustic wave speeds.These studies together demonstrate the large potential for using acoustic techniques as in situ diagnostics. Such tools could be used to optimize ion beam processing techniques or identify modes and kinetics of materials degradation in extreme radiation environments.
Since the landmark development of the Scherrer method a century ago, multiple generations of width methods for X-ray diffraction originated to non-invasively and rapidly characterize the property-controlling sizes of nanoparticles, nanowires, and nanocrystalline materials. However, the predictive power of this approach suffers from inconsistencies among numerous methods and from misinterpretations of the results. Therefore, we systematically evaluated twenty-two width methods on a representative nanomaterial subjected to thermal and mechanical loads. To bypass experimental complications and enable a 1:1 comparison between ground truths and the results of width methods, we produced virtual X-ray diffractograms from atomistic simulations. These simulations realistically captured the trends that we observed in experimental synchrotron diffraction. To comprehensively survey the width methods and to guide future investigations, we introduced a consistent, descriptive nomenclature. Alarmingly, our results demonstrated that popular width methods, especially the Williamson-Hall methods, can produce dramatically incorrect trends. We also showed that the simple Scherrer methods and the rare Energy methods can well characterize unloaded and loaded states, respectively. Overall, this work improved the utility of X-ray diffraction in experimentally evaluating a variety of nanomaterials by guiding the selection and interpretation of width methods.
The competition between ductile rupture mechanisms in high-purity Cu and other metals is sensitive to the material composition and loading conditions, and subtle changes in the metal purity can lead to failure either by void coalescence or Orowan Alternating Slip (OAS). In situ X-ray computed tomography tensile tests on 99.999% purity Cu wires have revealed that the rupture process involves a sequence of damage events including shear localization; growth of micron-sized voids; and coalescence of microvoids into a central cavity prior to the catastrophic enlargement of the coalesced void via OAS. This analysis has shown that failure occurs in a collaborative rather than strictly competitive manner. In particular, strain localization along the shear band enhanced void nucleation and drove the primary coalescence event, and the size of the resulting cavity and consumption of voids ensured a transition to the OAS mechanism rather than continued void coalescence. Additionally, the tomograms identified examples of void coalescence and OAS growth of individual voids at all stages of the failure process, suggesting that the transition between the different mechanisms was sensitive to local damage features, and could be swayed by collaboration with other damage mechanisms. The competition between the different damage mechanisms is discussed in context of the material composition, the local damage history, and collaboration between the mechanisms.
The populations of flaws in individual layers of microelectromechanical systems (MEMS) structures are determined and verified using a combination of specialized specimen geometry, recent probabilistic analysis, and topographic mapping. Strength distributions of notched and tensile bar specimens are analyzed assuming a single flaw population set by fabrication and common to both specimen geometries. Both the average spatial density of flaws and the flaw size distribution are determined and used to generate quantitative visualizations of specimens. Scanning probe-based topographic measurements are used to verify the flaw spacings determined from strength tests and support the idea that grain boundary grooves on sidewalls control MEMS failure. The findings here suggest that strength controlling features in MEMS devices increase in separation, i.e., become less spatially dense, and decrease in size, i.e., become less potent flaws, as processing proceeds up through the layer stack. The method demonstrated for flaw population determination is directly applicable to strength prediction for MEMS reliability and design.
This project has developed models of variability of performance to enable robust design and certification. Material variability originating from microstructure has significant effects on component behavior and creates uncertainty in material response. The outcomes of this project are uncertainty quantification (UQ) enabled analysis of material variability effects on performance and methods to evaluate the consequences of microstructural variability on material response in general. Material variability originating from heterogeneous microstructural features, such as grain and pore morphologies, has significant effects on component behavior and creates uncertainty around performance. Current engineering material models typically do not incorporate microstructural variability explicitly, rather functional forms are chosen based on intuition and parameters are selected to reflect mean behavior. Conversely, mesoscale models that capture the microstructural physics, and inherent variability, are impractical to utilize at the engineering scale. Therefore, current efforts ignore physical characteristics of systems that may be the predominant factors for quantifying system reliability. To address this gap we have developed explicit connections between models of microstructural variability and component/system performance. Our focus on variability of mechanical response due to grain and pore distributions enabled us to fully probe these influences on performance and develop a methodology to propagate input variability to output performance. This project is at the forefront of data-science and material modeling. We adapted and innovated from progressive techniques in machine learning and uncertainty quantification to develop a new, physically-based methodology to address the core issues of the Engineering Materials Reliability (EMR) research challenge in modeling constitutive response of materials with significant inherent variability and length-scales.
Architected structural metamaterials, also known as lattice, truss, or acoustic materials, provide opportunities to produce tailored effective properties that are not achievable in bulk monolithic materials. These topologies are typically designed under the assumption of uniform, isotropic base material properties taken from reference databases and without consideration for sub-optimal as-printed properties or off-nominal dimensional heterogeneities. However, manufacturing imperfections such as surface roughness are present throughout the lattices and their constituent struts create significant variability in mechanical properties and part performance. This study utilized a customized tensile bar with a gauge section consisting of five parallel struts loaded in a stretch (tensile) orientation to examine the impact of manufacturing heterogeneities on quasi-static deformation of the struts, with a focus on ultimate tensile strength and ductility. The customized tensile specimen was designed to prevent damage during handling, despite the sub-millimeter thickness of each strut, and to enable efficient, high-throughput mechanical testing. The strut tensile specimens and reference monolithic tensile bars were manufactured using a direct metal laser sintering (also known as laser powder bed fusion or selective laser melting) process in a precipitation hardened stainless steel alloy, 17-4PH, with minimum feature sizes ranging from 0.5-0.82 mm, comparable to minimum allowable dimensions for the process. Over 70 tensile stress-strain tests were performed revealing that the effective mechanical properties of the struts were highly stochastic, considerably inferior to the properties of larger as-printed reference tensile bars, and well below the minimum allowable values for the alloy. Pre- and post-test non-destructive analyses revealed that the primary source of the reduced properties and increased variability was attributable to heterogeneous surface topography with stress-concentrating contours and commensurate reduction in effective load-bearing area.
Nanocrystalline metals typically have high fatigue strengths but low resistance to crack propagation. Amorphous intergranular films are disordered grain boundary complexions that have been shown to delay crack nucleation and slow crack propagation during monotonic loading by diffusing grain boundary strain concentrations, which suggests they may also be beneficial for fatigue properties. To probe this hypothesis, in situ transmission electron microscopy fatigue cycling is performed on Cu-1 at.% Zr thin films thermally treated to have either only ordered grain boundaries or amorphous intergranular films. The sample with only ordered grain boundaries experienced grain coarsening at crack initiation followed by unsteady crack propagation and extensive nanocracking, whereas the sample containing amorphous intergranular films had no grain coarsening at crack initiation followed by steady crack propagation and distributed plastic activity. Microstructural design for control of these behaviors through simple thermal treatments can allow for the improvement of nanocrystalline metal fatigue toughness.
Molecular dynamics simulations were employed to simulate the mechanical response and grain evolution in a Ni nanowire for both static and cyclic loading conditions at both 300 and 500 K for periods of 40 ns. The loading conditions included thermal annealing with no deformation, constant 1% extension (creep loading) and cyclic loading with strain amplitudes of 0.5% and 1% for 200 cycles. Under cyclic loading, the stress-strain response showed permanent deformation and cyclic hardening behavior. At 300 K, modest grain evolution was observed at all conditions within the 40 ns simulations. At 500 K, substantial grain growth is observed in all cases, but is most pronounced under cyclic loading. This may result mechanistically from a net motion of the boundaries associated with boundary ratcheting. There is a striking qualitative consistency between the present simulation results and the experimental observation of abnormal grain growth in nanocrystalline metals as a precursor to fatigue crack initiation.
The Sandia Fracture Challenges provide the mechanics community a forum for assessing its ability to predict ductile fracture through a blind, round-robin format where computationalists are asked to predict the deformation and failure of an arbitrary geometry given experimental calibration data. This presentation will cover the three Sandia Fracture Challenges, with emphasis on the third. The third Challenge, issued in 2017, consisted of an additively manufactured 316L stainless steel tensile bar with through holes and internal cavities that could not have been conventionally machined. The volunteer prediction teams were provided extensive materials data from tensile tests of specimens printed on the same build tray to electron backscatter diffraction microstructural maps and micro-computed tomography scans of the Challenge geometry. The teams were asked a variety of questions, including predictions of variability in the resulting fracture response, as the basis for assessment of their predictive capabilities. This presentation will describe the Challenges and compare the experimental results to the predictions, identifying gaps in capabilities, both experimentally and computationally, to inform future investments. The Sandia Fracture Challenge has evolved into the Structural Reliability Partnership, where researchers will create several blind challenges covering a wider variety of topics in structural reliability. This presentation will also describe this new venture.
Zhang, Xin; Wang, Q.J.; Harrison, Katharine L.; Jungjohann, Katherine; Boyce, Brad B.; Roberts, Scott A.; Attia, Peter M.; Harris, Stephen J.
We offer an explanation for how dendrite growth can be inhibited when Li metal pouch cells are subjected to external loads, even for cells using soft, thin separators. We develop a contact mechanics model for tracking Li surface and sub-surface stresses where electrodes have realistically (micron-scale) rough surfaces. Existing models examine a single, micron-scale Li metal protrusion under a fixed local current density that presses more or less conformally against a separator or stiff electrolyte. At the larger, sub-mm scales studied here, contact between the Li metal and the separator is heterogeneous and far from conformal for surfaces with realistic roughness: the load is carried at just the tallest asperities, where stresses reach tens of MPa, while most of the Li surface feels no force at all. Yet, dendrite growth is suppressed over the entire Li surface. To explain this dendrite suppression, our electrochemical/mechanics model suggests that Li avoids plating at the tips of growing Li dendrites if there is sufficient local stress; that local contact stresses there may be high enough to close separator pores so that incremental Li+ ions plate elsewhere; and that creep ensures that Li protrusions are gradually flattened. These mechanisms cannot be captured by single-dendrite-scale analyses.
Nanocrystalline metals offer significant improvements in structural performance over conventional alloys. However, their performance is limited by grain boundary instability and limited ductility. Solute segregation has been proposed as a stabilization mechanism, however the solute atoms can embrittle grain boundaries and further degrade the toughness. In the present study, we confirm the embrittling effect of solute segregation in Pt-Au alloys. However, more importantly, we show that inhomogeneous chemical segregation to the grain boundary can lead to a new toughening mechanism termed compositional crack arrest. Energy dissipation is facilitated by the formation of nanocrack networks formed when cracks arrested at regions of the grain boundaries that were starved in the embrittling element. This mechanism, in concert with triple junction crack arrest, provides pathways to optimize both thermal stability and energy dissipation. A combination of in situ tensile deformation experiments and molecular dynamics simulations elucidate both the embrittling and toughening processes that can occur as a function of solute content.
This SAND report fulfills the final report requirement for the Born Qualified Grand Challenge LDRD. Born Qualified was funded from FY16-FY18 with a total budget of ~$13M over the 3 years of funding. Overall 70+ staff, Post Docs, and students supported this project over its lifetime. The driver for Born Qualified was using Additive Manufacturing (AM) to change the qualification paradigm for low volume, high value, high consequence, complex parts that are common in high-risk industries such as ND, defense, energy, aerospace, and medical. AM offers the opportunity to transform design, manufacturing, and qualification with its unique capabilities. AM is a disruptive technology, allowing the capability to simultaneously create part and material while tightly controlling and monitoring the manufacturing process at the voxel level, with the inherent flexibility and agility in printing layer-by-layer. AM enables the possibility of measuring critical material and part parameters during manufacturing, thus changing the way we collect data, assess performance, and accept or qualify parts. It provides an opportunity to shift from the current iterative design-build-test qualification paradigm using traditional manufacturing processes to design-by-predictivity where requirements are addressed concurrently and rapidly. The new qualification paradigm driven by AM provides the opportunity to predict performance probabilistically, to optimally control the manufacturing process, and to implement accelerated cycles of learning. Exploiting these capabilities to realize a new uncertainty quantification-driven qualification that is rapid, flexible, and practical is the focus of this effort.
Recent work suggests that thermally stable nanocrystallinity in metals is achievable in several binary alloys by modifying grain boundary energies via solute segregation. The remarkable thermal stability of these alloys has been demonstrated in recent reports, with many alloys exhibiting negligible grain growth during prolonged exposure to near-melting temperatures. Pt–Au, a proposed stable alloy consisting of two noble metals, is shown to exhibit extraordinary resistance to wear. Ultralow wear rates, less than a monolayer of material removed per sliding pass, are measured for Pt–Au thin films at a maximum Hertz contact stress of up to 1.1 GPa. This is the first instance of an all-metallic material exhibiting a specific wear rate on the order of 10−9 mm3 N−1 m−1, comparable to diamond-like carbon (DLC) and sapphire. Remarkably, the wear rate of sapphire and silicon nitride probes used in wear experiments are either higher or comparable to that of the Pt–Au alloy, despite the substantially higher hardness of the ceramic probe materials. High-resolution microscopy shows negligible surface microstructural evolution in the wear tracks after 100k sliding passes. Mitigation of fatigue-driven delamination enables a transition to wear by atomic attrition, a regime previously limited to highly wear-resistant materials such as DLC.
Prior studies on the high-cycle fatigue behavior of nanocrystalline metals have shown that fatigue fracture is associated with abnormal grain growth (AGG). However, those previous studies have been unable to determine if AGG precedes fatigue crack initiation, or vice-versa. The present study shows that AGG indeed occurs prior to crack formation in nanocrystalline Ni-Fe by using a recently developed synchrotron X-ray diffraction modality that has been adapted for in-situ analysis. The technique allows fatigue tests to be interrupted at the initial signs of the AGG process, and subsequent microscopy reveals the precursor damage state preceding crack initiation.
In the absence of pre-existing failure-critical defects, the fracture or tearing process in deformable metals loaded in tension begins with the nucleation of internal cavities or voids in regions of elevated triaxial stress. While ductile rupture processes initiate at inclusions or precipitates in many alloys, nucleation in pure metals is often assumed to be associated with grain boundaries or triple junctions. This study presents ex situ observations of incipient, subsurface void nucleation in pure tantalum during interrupted uniaxial tensile tests using electron channeling contrast (ECC) imaging, electron backscatter diffraction (EBSD), transmission Kikuchi diffraction (TKD) and transmission electron microscopy (TEM). Instead of forming at grain boundaries, voids initiated at and grew along dislocation cell and cell block boundaries created by plastic deformation. Most of the voids were associated with extended, lamellar deformation-induced boundaries that run along the traces of the {110} or {112} planes, though a few voids initiated at low-angle dislocation subgrain boundaries. In general, a high density of deformation-induced boundaries was observed near the voids. TEM and TKD demonstrate that voids initiate at and grow along cell block boundaries. Two mechanisms for void nucleation in pure metals, vacancy condensation and stored energy dissipation, are discussed in light of these results. The observations of the present investigation suggest that voids in pure materials nucleate by vacancy condensation and subsequently grow by consuming dislocations.
The Structural Reliability Partnership Workshop was held in Albuquerque, NM on August 29-30, 2017 and was hosted by Sandia National Laboratories. Attendees were present from academia, industry and several other national laboratories. The workshop kicked off with an introduction to the SRP to familiarize potential members with what the purpose, structure and benefits would be to their organization. Technical overviews were given on several topics by attendees from each sector – national labs, universities and industry – to provide a snapshot of the type of work that is currently being conducted on structural reliability. Attendees were then given the opportunity to suggest and discuss potential Challenge Scenario topics. Three were ultimately decided upon as being the most important: Additive Manufacturing, Hydrogen Pipeline Steels, and Bolted Joined Structures. These were then analyzed using Quad Charts to determine What, How, Who, and Why these areas would be further investigated. Rather than restricting future research to only one area, the option was left open to investigate both the top two, depending on interest and cost associated with hosting such an event. More informal collaboration may be undertaken for the third topic if members have time and interest. Other items discussed pertained to the organization, structure and policies of the Partnership. Topics including Data Management, IP, and mechanisms of partnering/information sharing were touched upon but final decisions were not made. Further action is needed before this can be done. Action items were outlined and assigned, where possible. The next workshop is to be held in early August 2018 in Boulder, CO and is to be hosted by NIST. In the interim, quarterly updates are to take place via WebEx to maintain a line of communication and to ensure progress on both the administrative and technical tasks.
Additive manufacturing enables the rapid, cost effective production of customized structural components. To fully capitalize on the agility of additive manufacturing, it is necessary to develop complementary high-throughput materials evaluation techniques. In this study, over 1000 nominally identical tensile tests are used to explore the effect of process variability on the mechanical property distributions of a precipitation hardened stainless steel produced by a laser powder bed fusion process, also known as direct metal laser sintering or selective laser melting. With this large dataset, rare defects are revealed that affect only ≈2% of the population, stemming from a single build lot of material. The rare defects cause a substantial loss in ductility and are associated with an interconnected network of porosity. The adoption of streamlined test methods will be paramount to diagnosing and mitigating such dangerous anomalies in future structural components.
Additive manufacturing offers unprecedented opportunities to design complex structures optimized for performance envelopes inaccessible under conventional manufacturing constraints. Additive processes also promote realization of engineered materials with microstructures and properties that are impossible via traditional synthesis techniques. Enthused by these capabilities, optimization design tools have experienced a recent revival. The current capabilities of additive processes and optimization tools are summarized briefly, while an emerging opportunity is discussed to achieve a holistic design paradigm whereby computational tools are integrated with stochastic process and material awareness to enable the concurrent optimization of design topologies, material constructs and fabrication processes.
An adage within the Additive Manufacturing (AM) community is that “complexity is free”. Complicated geometric features that normally drive manufacturing cost and limit design options are not typically problematic in AM. While geometric complexity is usually viewed from the perspective of part design, this advantage of AM also opens up new options in rapid, efficient material property evaluation and qualification. In the current work, an array of 100 miniature tensile bars are produced and tested for a comparable cost and in comparable time to a few conventional tensile bars. With this technique, it is possible to evaluate the stochastic nature of mechanical behavior. The current study focuses on stochastic yield strength, ultimate strength, and ductility as measured by strain at failure (elongation). However, this method can be used to capture the statistical nature of many mechanical properties including the full stress-strain constitutive response, elastic modulus, work hardening, and fracture toughness. Moreover, the technique could extend to strain-rate and temperature dependent behavior. As a proof of concept, the technique is demonstrated on a precipitation hardened stainless steel alloy, commonly known as 17-4PH, produced by two commercial AM vendors using a laser powder bed fusion process, also commonly known as selective laser melting. Using two different commercial powder bed platforms, the vendors produced material that exhibited slightly lower strength and markedly lower ductility compared to wrought sheet. Moreover, the properties were much less repeatable in the AM materials as analyzed in the context of a Weibull distribution, and the properties did not consistently meet minimum allowable requirements for the alloy as established by AMS. The diminished, stochastic properties were examined in the context of major contributing factors such as surface roughness and internal lack-of-fusion porosity. This high-throughput capability is expected to be useful for follow-on extensive parametric studies of factors that affect the statistical reliability of AM components.
Ductile rupture in metals is generally a multi-step process of void nucleation, growth, and coalescence. Particle decohesion and particle fracture are generally invoked as the primary microstructural mechanisms for room-temperature void nucleation. However, because high-purity materials also fail by void nucleation and coalescence, other microstructural features must also act as sites for void nucleation. Early studies of void initiation in high-purity materials, which included post-mortem fracture surface characterization using scanning electron microscopy (SEM) and high-voltage electron microscopy (HVEM) and in-situ HVEM observations of fracture, established the presence of dislocation cell walls as void initiation sites in high-purity materials. Direct experimental evidence for this contention was obtained during in-situ HVEM tensile tests of Be single crystals. Voids between 0.2 and 1 μm long appeared suddenly along dislocation cell walls during tensile straining. However, subsequent attempts to replicate these results in other materials, particularly α -Fe single crystals, were unsuccessful because of the small size of the dislocation cells, and these remain the only published in-situ HVEM observations of void nucleation at dislocation cell walls in the absence of a growing macrocrack. Despite this challenge, other approaches to studying void nucleation in high-purity metals also indicate that dislocation cell walls are nucleation sites for voids.
One of the most common causes of structural failure in metals is fatigue induced by cyclic loading. Historically, microstructure-level analysis of fatigue cracks has primarily been performed post mortem. However, such investigations do not directly reveal the internal structural processes at work near micro- and nanoscale fatigue cracks and thus do not provide direct evidence of active microstructural mechanisms. In this study, the tension-tension fatigue behavior of nanocrystalline Cu was monitored in real time at the nanoscale by utilizing a new capability for quantitative cyclic mechanical loading performed in situ in a transmission electron microscope (TEM). Controllable loads were applied at frequencies from one to several hundred hertz, enabling accumulations of 106 cycles within 1 h. The nanometer-scale spatial resolution of the TEM allows quantitative fatigue crack growth studies at very slow crack growth rates, measured here at ∼10-12 m·cycle-1. This represents an incipient threshold regime that is well below the tensile yield stress and near the minimum conditions for fatigue crack growth. Evidence of localized deformation and grain growth within 150 nm of the crack tip was observed by both standard imaging and precession electron diffraction orientation mapping. These observations begin to reveal with unprecedented detail the local microstructural processes that govern damage accumulation, crack nucleation, and crack propagation during fatigue loading in nanocrystalline Cu.
Boyce, Brad B.; Mohanty, G M.; Wehrs, J.W.; Taylor, A.J.; Hasegawa, M.H.; Philippe, L.P.
In this report, we report a micropillar stress relaxation technique employing a stable displacement-controlled, in-situ scanning electron microscope indenter, and unusually large micropillars to precisely measure stress relaxation in electroplated nanocrystalline Ni thin films. The observed stress relaxation is significant under constant displacement: even well below the 0.2% offset yield strength, the stresses relax by ~4% within a minute; in the work hardening regime, stress relaxes by ~9% in 1 min. A logarithmic fit of the relaxation curves is consistent with an Arrhenius thermal activation of plasticity and suggests an activation volume in the vicinity of ~10 b3. The apparent and effective activation volumes diverge at lower strains, particularly in the “elastic” regime. These measurements are compared to similar measurements performed on free-standing thin film tensile coupons. Both methods yield similar results, thereby validating the applicability of pillar compression to capture time-dependent plasticity. To our knowledge, these are the first micropillar stress relaxation experiments on metals ever reported.
Recent studies have shown the potential for nanocrystalline metals to possess excellent fatigue resistance compared to their coarse-grained counterparts. Although the mechanical properties of nanocrystalline metals are believed to be particularly susceptible to material defects, a systematic study of the effects of geometric discontinuities on their fatigue performance has not yet been performed. In the present work, nanocrystalline Ni-40 wt%Fe containing both intrinsic and extrinsic defects were tested in tension-tension fatigue. The defects were found to dramatically reduce the fatigue resistance, which was attributed to the relatively high notch sensitivity in the nanocrystalline material. Microstructural analysis within the crack-initiation zones underneath the defects revealed cyclically-induced abnormal grain growth (AGG) as a predominant deformation and crack initiation mechanism during high-cycle fatigue. The onset of AGG and the ensuing fracture is likely accelerated by the stress concentrations, resulting in the reduced fatigue resistance compared to the relatively defect-free counterparts.
No industry-wide standards yet exist for minimum properties in additively manufactured (AM) metals. While AM alloys such as 17-4 precipitation hardened stainless steel have been shown to have average properties that can be comparable to wrought or cast product, they suffer from inconsistent performance. Variability in the feedstock powder, feature sizes, thermal history, and laser performance can lead to unpredictable surface finish, chemistry, phase content, and defects. To address this issue, rapid, efficient, high-throughput mechanical testing and data analysis was developed, providing profound statistical insight into the stochastic variability in properties. With this new approach, 1000’s of comprehensive tensile tests can be performed for the cost of 10’s of conventional tests. This new high-throughput approach provides a material qualification pathway that is commensurate with the quick turn-around benefit of AM.
Evermore sophisticated ductile plasticity and failure models demand experimental material characterization of shear behavior; yet, the mechanics community lacks a widely accepted, standard test method for shear-dominated deformation and failure of ductile metals. We investigated the use of the V-notched rail test, borrowed from the ASTM D7078 standard for shear testing of composites, for shear testing of Ti-6Al-4V titanium alloy sheet material, considering sheet rolling direction and quasi-static and transient load rates. In this paper, we discuss practical aspects of testing, modifications to the specimen geometry, and the experimental shear behavior of Ti-6Al-4V. Specimen installation, machine compliance, specimen-grip slip during testing, and specimen V-notched geometry all influenced the measured specimen behavior such that repeatable shear-dominated behavior was initially difficult to obtain. We will discuss the careful experimental procedure and set of measurements necessary to extract meaningful shear information for Ti-6Al-4V. We also evaluate the merits and deficiencies, including practicality of testing for engineering applications and quality of results, of the V-notched rail test for characterization of ductile shear behavior.
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 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.