Existing models for most materials do not describe phase transformations and associated lattice dy- namics (kinetics) under extreme conditions of pressure and temperature. Dynamic x-ray diffraction (DXRD) allows material investigations in situ on an atomic scale due to the correlation between solid-state structures and their associated diffraction patterns. In this LDRD project we have devel- oped a nanosecond laser-compression and picosecond-to-nanosecond x-ray diffraction platform for dynamically-compressed material studies. A new target chamber in the Target Bay in building 983 was commissioned for the ns, kJ Z-Beamlet laser (ZBL) and the 0.1 ns, 250 J Z-Petawatt (ZPW) laser systems, which were used to create 8-16 keV plasma x-ray sources from thin metal foils. The 5 ns, 15 J Chaco laser system was converted to a high-energy laser shock driver to load material samples to GPa stresses. Since laser-to-x-ray energy conversion efficiency above 10 keV is low, we employed polycapillary x-ray lenses for a 100-fold fluence increase compared to a conventional pinhole aperture while simultaneously reducing the background significantly. Polycapillary lenses enabled diffraction measurements up to 16 keV with ZBL as well as diffraction experiments with ZPW. This x-ray diffraction platform supports experiments that are complementary to gas guns and the Z facility due to different strain rates. Ultimately, there is now a foundation to evaluate DXRD techniques and detectors in-house before transferring the technology to Z. This page intentionally left blank.
The Vanguard program informally began in January 2017 with the submission of a white paper entitled "Sandia's Vision for a 2019 Arm Testbed" to NNSA headquarters. The program proceeded in earnest in May 2017 with an announcement by Doug Wade (Director, Office of Advanced Simulation and Computing and Institutional R&D at NNSA) that Sandia National Laboratories (Sandia) would host the first Advanced Architecture Prototype platform based on the Arm architecture. In August 2017, Sandia formed a Tri-lab team chartered to develop a robust HPC software stack for Astra to support the Vanguard program goal of demonstrating the viability of Arm in supporting ASC production computing workloads.
The 2018 NRC HEAF tests were conducted in Chalfont Pennsylvania at KEMA High Power Laboratory during the week of September 10th. These scoping tests were executed to determine the most effective measurement methodologies for future tests. The goal of Sandia’s Photometrics group was to provide high-speed quantitative and qualitative imaging of the arcing fault tests for the Nuclear Regulatory Commission. The measurement methods included visible high-speed imaging, high-speed high-dynamic range visible imaging, thermal imaging, and quantitative flow imaging. In addition, data fusion products were generated to visualize instrumentation data and imaging measurements. All imaging has been time synchronized to the start of the arcing event.
Cheap and efficient ion conducting separators are needed to improve efficiency and lifetime in fuel cells, batteries, and electrolyzers. Current state-of-the-art polymeric separators are made from Nafion, which is too expensive to be competitive with other technologies. Sandia has developed unique polymer separators that have lower cost and equivalent or superior ion transport compared to Nafion. These membranes consist of sulfonated Diels-Alder poly(phenylene) (SDAPP), a completely hydrocarbon polymer that conducts protons when hydrated. SDAPP membranes are thermally and chemically robust, with conductivities rivaling those of Nafion at high sulfonation levels. However, rational design of new separators requires molecular-level knowledge, currently unknown, of how polymer morphology affects transport. Here we describe the use of multiple computational and experimental techniques to understand the nanoscale morphology and water/proton transport properties in a series of sulfonated SDAPP membranes over a wide range of temperature, hydration, and sulfonation conditions.
Placing a crystal under extreme pressure can sometimes change its structure from one form, or phase, to another. Determining exactly how crystals change phase under compression is an important area of materials physics research. The availability of x-ray diffraction at synchrotron facilities has allowed scientists to observe compression-driven phase changes in unprecedented detail. Most of the research in this field has focused on pressure-induced phase changes using slow (static) compression on the minute timescale. Now, utilizing x-ray diffraction at the APS, a multi-institution research team led by scientists at Sandia National Laboratories has observed, over nanosecond timescales, microstructural phase changes within a two-element (calcium fluoride) crystal subjected to extreme pressures. The high pressures were achieved both through high-velocity instantaneous shock compression and by statically squeezing the samples. The researchers expect that their real-time observations of phase transitions within calcium fluoride will provide a template for the phase transitions of similarly-structured compounds. More generally, it is anticipated that the experimental methods and results of this study will lead to improved modeling of phase transitions over nanosecond timescales, within a wide range of complex materials.
A new race is emerging among nuclear powers: the hypersonic weapon. Hypersonics are flight vehicles that travel at Mach 5 (five times the speed of sound) or faster. They can cruise in the atmosphere, unlike traditional exo-atmospheric ballistic missiles, allowing stealth and maneuverability during midflight. Faster, lower, and stealthier means the missiles can better evade adversary defense systems. The U.S. has experimented with hypersonics for years, but current investments by Russia and China into their own offensive hypersonic systems may render U.S. missile defense systems ineffective. For the U.S. to avoid obsolescence in this strategically significant technology arena, hypersonics—combined with autonomy—needs to be a force multiplier. Achieving an autonomous hypersonic missile, however, that can intelligently navigate, guide, and control itself and home-in on targets ranging from traditional stationary systems to targets that are themselves hypersonic vehicles—with all the maneuverability that this entails—may sound far-fetched. But to Sandia's Autonomy for Hypersonics (A4H) team, this dream is one step closer to reality.
Lipid-coated mesoporous silica nanoparticles (LC-MSNs) have recently emerged as a next-generation cargo delivery nanosystem combining the unique attributes of both the organic and inorganic components. The high surface area biodegradable inorganic mesoporous silica core can accommodate multiple classes of bio-relevant cargos in large amounts, while the supported lipid bilayer coating retains the cargo and increases the stability of the nanocarrier in bio-relevant media which should promote greater bio-accumulation of LC-MSNs in cancer sites. In this paper, we report on the optimization of various sol–gel synthesis (pH, stirring speed) and post-synthesis (hydrothermal treatment) procedures to enlarge the MSN pore size and tune the surface chemistry so as to enable loading and delivery of large biomolecules. Finally, the proof of concept of the dual cargo-loaded nanocarrier has been demonstrated in immortalized cervical cancer HeLa cells using MSNs of various fine-tuned pore sizes.
High-performance computing (HPC) systems are critically important to the objectives of universities, national laboratories, and commercial companies. Because of the cost of deploying and maintaining these systems ensuring their efficient use is imperative. Job scheduling and resource management are critically important to the efficient use of HPC systems. As a result, significant research has been conducted on how to effectively schedule user jobs on HPC systems. Developing and evaluating job scheduling algorithms, however, requires a detailed understanding of how users request resources on HPC systems. In this paper, we examine a corpus of job data that was collected on Trinity, a leadership-class supercomputer. During the stabilization period of its Intel Xeon Phi (Knights Landing) partition, it was made available to users outside of a classified environment for the Trinity Open Science Phase 2 campaign. We collected information from the resource manager about each user job that was run during this Open Science period. In this paper, we examine the jobs contained in this dataset. Our analysis reveals several important characteristics of the jobs submitted during the Open Science period and provides critical insight into the use of one of the most powerful supercomputers in existence. Specifically, these data provide important guidance for the design, development, and evaluation of job scheduling and resource management algorithms.
Large-scale HPC systems increasingly incorporate sophisticated power management control mechanisms. While these mechanisms are potentially useful for performing energy and/or power-aware job scheduling and resource management (EPA JSRM), greater understanding of their operation and performance impact on real-world applications is required before they can be applied effectively in practice. In this paper, we compare static p-state control to static node-level power cap control on a Cray XC system. Empirical experiments are performed to evaluate node-to-node performance and power usage variability for the two mechanisms. We find that static p-state control produces more predictable and higher performance characteristics than static node-level power cap control at a given power level. However, this performance benefit is at the cost of less predictable power usage. Static node-level power cap control produces predictable power usage but with more variable performance characteristics. Our results are not intended to show that one mechanism is better than the other. Rather, our results demonstrate that the mechanisms are complementary to one another and highlight their potential for combined use in achieving effective EPA JSRM solutions.
