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.