Pulsed-power generators can produce well-controlled continuous ramp compression of condensed matter for high-pressure equation-of-state studies using the magnetic loading technique. X-ray diffraction (XRD) data from dynamically compressed samples provide direct measurements of the elastic compression of the crystal lattice, onset of plastic flow, strength-strain rate dependence, structural phase transitions, and density of crystal defects, such as dislocations. Here, we present a cost-effective, compact, pulsed x-ray source for XRD measurements on pulsed-power-driven ramp-loaded samples. This combination of magnetically driven ramp compression of materials with a single, short-pulse XRD diagnostic will be a powerful capability for the dynamic materials' community to investigate in situ dynamic phase transitions critical to equation of states. We present results using this new diagnostic to evaluate lattice compression in Zr and Al and to capture signatures of phase transitions in CdS.
Pulsed-power generators using the magnetic loading technique are able to produce well-controlled continuous ramp compression of condensed matter for high-pressure equation-of-state studies. X-ray diffraction (XRD) data from dynamically compressed samples provide direct measurements of the elastic compression of the crystal lattice, onset of plastic flow, strength-strain rate dependence, structural phase transitions, and density of crystal defects such as dislocations. Here, we present a cost effective, compact X-ray source for XRD measurements on pulsed-power-driven ramp-loaded samples. This combination of magnetically-driven ramp compression of materials with single, short-pulse XRD diagnostic will be a powerful capability for the dynamic materials community. The success in fielding this new XRD diagnostic dramatically improves our predictive capability and understanding of rate-dependent behavior at or near phase transition. As Sandia plans the next-generation pulse-power driver platform, a key element needed to deliver new state-of-the-art experiments will be having the necessary diagnostic tools to probe new regimes and phenomena. These diagnostics need to be as versatile, compact, and portable as they are powerful. The development of a platform-independent XRD diagnostic gives Sandia researchers a new window to study the microstructure and phase dynamics of materials under load. This project has paved the way for phase transition research in a variety of materials with mission interest.
Ramp-compression experiments have been performed on the “Z” pulsed-power facility to investigate the strengths of Be and lead-antimony alloy. Yield strength and shear stress near peak pressure were obtained from measurements of the sound speed on release and using the Asay self-consistent method. Two S-65 grade Be samples, from batches that showed a significant difference in yield strength at ambient conditions, were found to have near identical yield strengths, which were also in agreement with similar earlier measurements on S-200 grade Be. Yield strength of the Pb4Sb alloy at ∼120 GPa was 1.35 GPa, while a National Ignition Facility experiment by Krygier et al. [Phys. Rev. Lett. 123, 205701 (2020)] found 3.8 GPa at ∼400 GPa pressure. Our result is intermediate between the ambient value and the one by Krygier et al., but the significantly increased strength is probably not associated with the transition to the high-pressure bcc phase of lead.
Magnetic loading was used to shocklessly compress four different metals to extreme pressures. Velocimetry monitored the behavior of the material as it was loaded to a desired peak state and then decompressed back down to lower pressures. Two distinct analysis methods, including a wave profile analysis and a novel Bayesian calibration approach, were employed to estimate quantitative strength metrics associated with the loading reversal. Specifically, we report for the first time on strength estimates for tantalum, gold, platinum, and iridium under shockless compression at strain rates of ∼ 5 × 10 5/s in the pressure range of ∼ 100–400 GPa. The magnitude of the shear stresses supported by the different metals under these extreme conditions are surprisingly similar, representing a dramatic departure from ambient conditions.
Graded density impactors (GDIs) have long been of interest to provide off-Hugoniot loading capabilities for impact systems. We describe a new technique which utilizes sputter deposition to produce an approximately 40 µm-thick film containing alternating layers of Al and Cu. The thicknesses of the respective layers are adjusted to give an effective density gradient through the film. The GDIs were launched into samples of interest with a 2-stage light gas gun, and the resulting shock-ramp-release velocity profiles were measured over timescales of ~10 ns with a new velocimetry probe. Results are shown for the direct impact of the film onto a LiF window, which allows for the dynamic characterization of the GDI, as well as from impact onto a thin (~40 µm) sputtered Ta sample backed by a LiF window. These measurements were coupled into mesoscale numerical simulations to infer the strength of Ta at the high rate (107 s-1), and high pressure (1 MBar) conditions this unique capability provides. Initial results suggest this is a viable strength platform which fills a critical gap and aids in cross-platform comparisons with other high-pressure strength platforms.
We report the atomic- and nanosecond-scale quantification of kinetics of a shock-driven phase transition in Zr metal. We uniquely make use of a multiple shock-and-release loading pathway to shock Zr into the β phase and to create a quasisteady pressure and temperature state shortly after. Coupling shock loading with in situ time-resolved synchrotron x-ray diffraction, we probe the structural transformation of Zr in the steady state. Our results provide a quantified expression of kinetics of formation of β-Zr phase under shock loading: transition incubation time, completion time, and crystallization rate.
In the presence of model discrepancy, the calibration of physics-based models for physical parameter inference is a challenging problem. Lack of identifiability between calibration parameters and model discrepancy requires additional identifiability constraints to be placed on the model discrepancy to obtain unique physical parameter estimates. If these assumptions are violated, the inference for the calibration parameters can be systematically biased. In many applications, such as in dynamic material property experiments, many of the calibration inputs refer to measurement uncertainties. In this setting, we develop a metric for identifying overfitting of these measurement uncertainties, propose a prior capable of reducing this overfitting, and show how this leads to a diagnostic tool for validation of physical parameter inference. The approach is demonstrated for a benchmark example and applied for a material property application to perform inference on the equation of state parameters of tantalum.
This report outlines the fiscal year (FY) 2019 status of an ongoing multi-year effort to develop a general, microstructurally-aware, continuum-level model for representing the dynamic response of material with complex microstructures. This work has focused on accurately representing the response of both conventionally wrought processed and additively manufactured (AM) 304L stainless steel (SS) as a test case. Additive manufacturing, or 3D printing, is an emerging technology capable of enabling shortened design and certification cycles for stockpile components through rapid prototyping. However, there is not an understanding of how the complex and unique microstructures of AM materials affect their mechanical response at high strain rates. To achieve our project goal, an upscaling technique was developed to bridge the gap between the microstructural and continuum scales to represent AM microstructures on a Finite Element (FE) mesh. This process involves the simulations of the additive process using the Sandia developed kinetic Monte Carlo (KMC) code SPPARKS. These SPPARKS microstructures are characterized using clustering algorithms from machine learning and used to populate the quadrature points of a FE mesh. Additionally, a spall kinetic model (SKM) was developed to more accurately represent the dynamic failure of AM materials. Validation experiments were performed using both pulsed power machines and projectile launchers. These experiments have provided equation of state (EOS) and flow strength measurements of both wrought and AM 304L SS to above Mbar pressures. In some experiments, multi-point interferometry was used to quantify the variation is observed material response of the AM 304L SS. Analysis of these experiments is ongoing, but preliminary comparisons of our upscaling technique and SKM to experimental data were performed as a validation exercise. Moving forward, this project will advance and further validate our computational framework, using advanced theory and additional high-fidelity experiments. ACKNOWLEDGEMENTS The authors greatly appreciate the support of Mike Saavedra in machining the experimental samples. The authors would also like to thank the Dynamic Integrated Compression facility (DICE) staff for executing the Thor experiments: Brian Stoltzfus, Randy Hickman, Keith Hodge, Joshua Usher, Lena Pacheco, and Eric Breden. The authors would also like to thank the staff at the Shock Thermodynamics Applied Research (STAR) facility for executing the plate impact experiments: Scott Alexander, Bill Reinhart, Bernardo Farfan, Rocky Palomino, John Martinez, and Rafael Sanchez. Lastly, the authors would like to acknowledge the development support of Jason Sanchez in ALEGRA to incorporate our upscaling method and Michael Powell for helping with post processing scripts for results analysis.