This work aimed to apply Sandia’s expertise in metallurgy and modeling to enable the use of hybrid laser arc welding for building nuclear reactor containment structures, via a collaboration with Holtec International. Experimental observations were coupled with finite element analysis to resolve microstructure development, mechanical properties, distortion, and residual stress in welds relevant to the production of the Holtec SMR-160. High residual stresses were observed in welds that were not subjected to preheat. Meanwhile, the microstructure of the welds generally exhibited a narrow heat affected zone relative to conventional arc welds. FEA appeared to be effective in simulating the thermal/mechanical conditions that occur during hybrid laser arc welding of simplified and instrumented test welds. Subsequently, FEA was used to perform sensitivity analyses for various weld geometries that would be prohibitively costly to assess with physical experiments. Insights from the study were used to inform Holtec’s welding process, and successful production welds were performed in 2025.
In response to gradual nanoindentation, the surface of muscovite mica deforms by sudden stochastic nanometer-scale displacement bursts. Here, the statistics of these displacement events are interpreted using a statistical model previously used to model earthquakes to understand how chemically reactive environments alter the surface properties of this material. We show that the statistics of nanoindentation displacement bursts in muscovite mica are tuned by chemomechanical weakening in a manner similar to how the statistics of model events are tuned by a mechanical weakening parameter that describes how easily system-spanning cracks can be nucleated. Because the predictions of this model are independent of any surface defects or structural details, these results suggest this simple model can be universally used to describe chemomechanical weakening in many systems prone to slip avalanches on a wide range of spatio-temporal scales.
The performance and reliability of many structures and components depend on the integrity of interfaces between dissimilar materials. Interfacial toughness Γ is the key material parameter that characterizes resistance to interfacial crack growth, and Γ is known to depend on many factors including temperature. For example, previous work showed that the toughness of an epoxy/aluminum interface decreased 40 % as the test temperature was increased from −60 °C to room temperature (RT). Interfacial integrity at elevated temperatures is of considerable practical importance. Recent measurements show that instead of continuing to decrease with increasing temperature, Γ increases when test temperature is above RT. Cohesive zone finite element calculations of an adhesively bonded, asymmetric double cantilever beam specimen of the type used to measure Γ suggest that this increase in toughness may be a result of R-curve behavior generated by plasticity-enhanced toughening during stable subcritical crack growth with interfacial toughness defined as the critical steady-state limit value. In these calculations, which used an elastic-perfectly plastic epoxy model with a temperature-dependent yield strength, the plasticity-enhanced increase in Γ above its intrinsic value Γo depended on the ratio of interfacial strength σ* to the yield strength σyb of the bond material. There is a nonlinear relationship between Γ/Γo and σ*/σyb with the value Γ/Γo increasing rapidly above a threshold value of σ*/σyb. The predicted increase in toughness can be significant. For example, there is nearly a factor of two predicted increase in Γ/Γo during micrometer-scale crack-growth when σ*/σyb = 2 (a reasonable choice for σ*/σyb). Furthermore, contrary to other reported results, plasticity-enhanced toughening can occur prior to crack advance as the cohesive zone forms and the peak stress at the tip of the original crack tip translates to the tip of the fully formed cohesive zone. These results suggest that plasticity-enhanced toughening should be considered when modeling interfaces at elevated temperatures.
Corrosion challenges persist throughout SNL’s mission areas. The primary difficulty lies in the fact that corrosion typically manifests as isolated, rare events, making preemptive identification exceedingly difficult. Our current strategy for addressing corrosion issues, such as anomalies and SFIs, is similarly isolated and reactive. This method is costly, time-consuming, heavily dependent on a limited number of experts, and offers minimal understanding of the overall damage distribution within the stockpile. This technical challenge is not unique to corrosion but is also prevalent in other material aging phenomena, such as tin-whisker growth in lead-free solder and fatigue failure of springs.
BeyondFingerprinting was a 2021-2024 Sandia Grand Challenge LDRD exploring the potential to develop new resilient materials and manufacturing processes by taking an artificial-intelligence (AI)-guided approach that integrates human-subject-matter expertise with algorithms enriched with physics-based constraints to unearth process-structure-property correlations. Such algorithms, trained on high-throughput experiments and simulations, are shown to serve as surrogate models that efficiently detect key “fingerprints” in materials data, prognose material performance, and guide effective process improvements. To accelerate broader adoption across mission areas, this AI-guided approach was demonstrated with three complex process-centric exemplars: electroplating, physical vapor deposition, and laser powder bed fusion. Together, these exemplars impact nearly every hardware component relevant to DOE and NNSA national security missions.
In this letter, we present interfacial fracture toughness data for a polymer-metal interface where tests were conducted at various test temperatures T and loading rates δ˙. An adhesively bonded asymmetric double cantilever beam (ADCB) specimen was utilized to measure toughness. ADCB specimens were created by bonding a thinner, upper adherend to a thicker, lower adherend (both 6061 T6 aluminum) using a thin layer of epoxy adhesive, such that the crack propagated along the interface between the thinner adherend and the epoxy layer. The specimens were tested at T from 25 to 65 °C and δ˙ from 0.002 to 0.2 mm/s. The measured interfacial toughness Γ increased as both T and δ˙ increased. For an ADCB specimen loaded at a constant δ˙, the energy release rate G increases as the crack length a increases. For this reason, we defined rate effects in terms of the rate of change in the energy release rate G˙. Although not rigorously correct, a formal application of time–temperature superposition (TTS) analysis to the Γ data provided useful insights on the observed dependencies. In the TTS-shifted data, Γ decreased and then increased for monotonically increasing G˙. Thus, the TTS analysis suggests that there is a minimum value of Γ. This minimum value could be used to define a lower bound in Γ when designing critical engineering applications that are subjected to T and δ˙ excursions.
Sputter-deposited Pt-Au thin films have been reported to develop a hard, stable, nanocrystalline structure, yet little is known about how these characteristics vary with PtxAu1-x composition and process conditions. Toward this end, this document describes an extensive, combinatorial Pt-Au thin film library including characterized film compositions, structure, and properties. Complemented by kinematic Monte Carlo simulations of codeposition, a broad range of PtxAu1-x compositions (from x ~ 0.02 to 0.93) was first established by sputtering with varied magnetron powers and gun tilt angles. Further, the produced films were subsequently interrogated using automated nanoindentation, x-ray reflectivity, x-ray diffraction, atomic force microscopy, surface profilometry, four-point probe sheet resistance techniques, and wavelength dispersive spectroscopy in order to determine how hardness, modulus, density, surface roughness, structure, and resistivity vary with film stoichiometry and process parameters. Combinatorial films displayed an assortment of properties with the hardness of some films exceeding values reported previously for this material system. High hardness, high modulus, and low resistivity were generally attained when using increased deposition energy and reduced angle-of-incidence processes. Overall, the research identified promising, new PtxAu1-x compositions for future study and pinpointed strategies for improved deposition.
The additive manufacture of compositionally graded Al/Cu parts by laser engineered net shaping (LENS) is demonstrated. The use of a blue light build laser enabled deposition on a Cu substrate. The thermal gradient and rapid solidification inherent to selective laser melting enabled mass transport of Cu up to 4 mm from a Cu substrate through a pure Al deposition, providing a means of producing gradients with finer step sizes than the printed layer thicknesses. Divorcing gradient continuity from layer or particle size makes LENS a potentially enabling technology for the manufacture of graded density impactors for ramp compression experiments. Printing graded structures with pure Al, however, was prevented by the growth of Al2Cu3 dendrites and acicular grains amid a matrix of Al2Cu. A combination of adding TiB2 grain refining powder and actively varying print layer composition suppressed the dendritic growth mode and produced an equiaxed microstructure in a compositionally graded part. Material phase was characterized for crystal structure and nanoindentation hardness to enable a discussion of phase evolution in the rapidly solidifying melt pool of a LENS print.
The rotating bending fatigue (RBF) behavior (fully reversed, R = −1) of additively manufactured (AM) Ti–6Al–4V alloy produced via laser powder bed fusion (PBF-L) was investigated with respect to different microstructures achieved through novel heat treatments. The investigation herein seeks to elucidate the effect of microstructure by controlling variables that can affect fatigue behavior in Ti–6Al–4V, such as chemistry, porosity, and surface roughness. In order to control these variables, different hot isostatic pressing (HIP) treatments at 800 °C, 920 °C, and 1050 °C with a 920 °C temper were applied to three sets of Ti–6Al–4V cylinders that originated from the same PBF-L build, such that there were 30 tests per condition. After HIP treatment, the specimens were machined and tested. The highest runout stress was achieved after sub-β transus HIP at 800 °C for 2 h at 200 MPa of pressure. A significant drop in fatigue strength was attributed to large prior-β grains and grain boundary α resulting from super-β transus HIP treated specimens. For the sub-β transus HIP specimens, differences in fatigue strength were attributed to α lath thickness, relative dislocation density, and dislocation boundary strengthening.
Density-functional theory (DFT) is used to identify phase-equilibria in multi-principal-element and high-entropy alloys (MPEAs/HEAs), including duplex-phase and eutectic microstructures. A combination of composition-dependent formation energy and electronic-structure-based ordering parameters were used to identify a transition from FCC to BCC favoring mixtures, and these predictions experimentally validated in the Al-Co-Cr-Cu-Fe-Ni system. A sharp crossover in lattice structure and dual-phase stability as a function of composition were predicted via DFT and validated experimentally. The impact of solidification kinetics and thermodynamic stability was explored experimentally using a range of techniques, from slow (castings) to rapid (laser remelting), which showed a decoupling of phase fraction from thermal history, i.e., phase fraction was found to be solidification rate-independent, enabling tuning of a multi-modal cell and grain size ranging from nanoscale through macroscale. Strength and ductility tradeoffs for select processing parameters were investigated via uniaxial tension and small-punch testing on specimens manufactured via powder-based additive manufacturing (directed-energy deposition). This work establishes a pathway for design and optimization of next-generation multiphase superalloys via tailoring of structural and chemical ordering in concentrated solid solutions.
Due to its tunable bandgap, anisotropic behavior, and superior thermoelectric properties, device applications using layered tellurene (Te) are becoming more attractive. Here, we report a thinning technique for exfoliated tellurene nanosheets using thermal annealing in an oxygen environment. We characterize different thinning parameters, including temperature and annealing time. Based on our measurements, we show that controlled layer thinning occurs in the narrow temperature range of 325-350 °C. We also show a reliable method to form β-tellurene oxide (β-TeO2), which is an emerging wide bandgap semiconductor with promising electronic and optoelectronic properties. This wide bandgap semiconductor exhibits a broad photoluminescence (PL) spectrum with multiple peaks covering the range of 1.76-2.08 eV. This PL emission, coupled with Raman spectra, is strong evidence of the formation of 2D β-TeO2. We discuss the results obtained and the mechanisms of Te thinning and β-TeO2 formation at different temperature regimes. We also discuss the optical bandgap of β-TeO2 and show the existence of pronounced excitonic effects evident by the large exciton binding energy in this 2D β-TeO2 system that reach 1.54-1.62 eV for bulk and monolayer, respectively. Our work can be utilized to have better control over the Te nanosheet thickness. It also sheds light on the formation of well-controlled β-TeO2 layered semiconductors for electronic and optoelectronic applications.
As the field of low-dimensional materials (1D or 2D) grows and more complex and intriguing structures are continuing to be found, there is an emerging need for techniques to characterize the nanoscale mechanical properties of all kinds of 1D/2D materials, in particular in their most practical state: sitting on an underlying substrate. While traditional nanoindentation techniques cannot accurately determine the transverse Young's modulus at the necessary scale without large indentations depths and effects to and from the substrate, herein an atomic-force-microscopy-based modulated nanomechanical measurement technique with Angstrom-level resolution (MoNI/ÅI) is presented. This technique enables non-destructive measurements of the out-of-plane elasticity of ultra-thin materials with resolution sufficient to eliminate any contributions from the substrate. This method is used to elucidate the multi-layer stiffness dependence of graphene deposited via chemical vapor deposition and discover a peak transverse modulus in two-layer graphene. While MoNI/ÅI has been used toward great findings in the recent past, here all aspects of the implementation of the technique as well as the unique challenges in performing measurements at such small resolutions are encompassed.
Future machine learning strategies for materials process optimization will likely replace human capital-intensive artisan research with autonomous and/or accelerated approaches. Such automation enables accelerated multimodal characterization that simultaneously minimizes human errors, lowers costs, enhances statistical sampling, and allows scientists to allocate their time to critical thinking instead of repetitive manual tasks. Previous acceleration efforts to synthesize and evaluate materials have often employed elaborate robotic self-driving laboratories or used specialized strategies that are difficult to generalize. Herein we describe an implemented workflow for accelerating the multimodal characterization of a combinatorial set of 915 electroplated Ni and Ni–Fe thin films resulting in a data cube with over 160,000 individual data files. Our acceleration strategies do not require manufacturing-scale resources and are thus amenable to typical materials research facilities in academic, government, or commercial laboratories. The workflow demonstrated the acceleration of six characterization modalities: optical microscopy, laser profilometry, X-ray diffraction, X-ray fluorescence, nanoindentation, and tribological (friction and wear) testing, each with speedup factors ranging from 13–46x. In addition, automated data upload to a repository using FAIR data principles was accelerated by 64x.
The development of additively-manufactured (AM) 316L stainless steel (SS) using laser powder bed fusion (LPBF) has enabled near net shape components from a corrosion-resistant structural material. In this article, we present a multiscale study on the effects of processing parameters on the corrosion behavior of as-printed surfaces of AM 316L SS formed via LPBF. Laser power and scan speed of the LPBF process were varied across the instrument range known to produce parts with >99 % density, and the macroscale corrosion trends were interpreted via microscale and nanoscale measurements of porosity, roughness, microstructure, and chemistry. Porosity and roughness data showed that porosity φ decreased as volumetric energy density Ev increased due to a shift in the pore formation mechanism and that roughness Sq was due to melt track morphology and partially fused powder features. Cross-sectional and plan-view maps of chemistry and work function ϕs revealed an amorphous Mn-silicate phase enriched with Cr and Al that varied in both thickness and density depending on Ev. Finally, the macroscale potentiodynamic polarization experiments under full immersion in quiescent 0.6 M NaCl showed significant differences in breakdown potential Eb and metastable pitting. In general, samples with smaller φ and Sq values and larger ϕs values and homogeneity in the Mn-silicate exhibited larger Eb. The porosity and roughness effects stemmed from an increase to the overall number of initiation sites for pitting, and the oxide phase contributed to passive film breakdown by acting as a crevice former or creating a galvanic couple with the SS.
Human activities involving subsurface reservoirs—resource extraction, carbon and nuclear waste storage—alter thermal, mechanical, and chemical steady-state conditions in these systems. Because these systems exist at lithostatic pressures, even minor chemical changes can cause chemically assisted deformation. Therefore, understanding how chemical effects control geomechanical properties is critical to optimizing engineering activities. The grand challenge in predicting the effect of chemical processes on mechanical properties lays in the fact that these phenomena take place at molecular scales, while they manifest all the way to reservoir scales. To address this fundamental challenge, we investigated chemical effects on deformation in model and real systems spanning molecular- to centimeter scales. We used theory, experiment, molecular dynamics simulation, and statistical analysis to (1) identify the effect of simple reactions, such as hydrolysis, on molecular structures in interfacial regions of stressed geomaterials; (2) quantify chemical effects on the bulk mechanical properties, fracture and displacement for granular rocks and single crystals; (3) develop initial understanding of universal scaling for individual displacement events in layered geomaterials; and (4) develop analytic approximations for the single-chain mechanical response utilizing asymptotically correct statistical thermodynamic theory. Taken together, these findings advance the challenging field of chemo-mechanics.
Multimodal datasets of materials are rich sources of information which can be leveraged for expedited discovery of process–structure–property relationships and for designing materials with targeted structures and/or properties. For this data descriptor article, we provide a multimodal dataset of magnetron sputter-deposited molybdenum (Mo) thin films, which are used in a variety of industries including high temperature coatings, photovoltaics, and microelectronics. In this dataset we explored a process space consisting of 27 unique combinations of sputter power and Ar deposition pressure. Here, the phase, structure, surface morphology, and composition of the Mo thin films were characterized by x-ray diffraction, scanning electron microscopy, atomic force microscopy, and Rutherford backscattering spectrometry. Physical properties—namely, thickness, film stress and sheet resistance—were also measured to provide additional film characteristics and behaviors. Additionally, nanoindentation was utilized to obtain mechanical load-displacement data. The entire dataset consists of 2072 measurements including scalar values (e.g., film stress values), 2D linescans (e.g., x-ray diffractograms), and 3D imagery (e.g., atomic force microscopy images). An additional 1889 quantities, including film hardness, modulus, electrical resistivity, density, and surface roughness, were derived from the experimental datasets using traditional methods. Minimal analysis and discussion of the results are provided in this data descriptor article to limit the authors’ preconceived interpretations of the data. Overall, the data modalities are consistent with previous reports of refractory metal thin films, ensuring that a high-quality dataset was generated. The entirety of this data is committed to a public repository in the Materials Data Facility.
