It is well know that the addition of substitutional elements changes the mechanical behavior of metals, a effect referred to solid solution hardening. For body-centered-cubic (BCC) metals, screw dislocation play a key role in the mechanical properties. Here the detailed modification of the Peierls barrier for screw dislocation motion in Ta with W substitutional atoms is computing using density functional theory (DFT). A reduced order model (ROM) of the influence of W substitution on the Peierls barrier is developed. The mean field change in the Peierls barrier for a Ta10W alloy is determined and shown to be larger than anticipated based on simple elasticity considerations. The ROM could be used in future calculations to determine the local variability of the Peierls barrier and the resultant influence on the motion of screw dislocation in this alloy.
Under the direction of the James W. Todd, Assistant Manager for Engineering within the National Nuclear Security Administration Sandia Field Office, the team listed above has performed the attached study to evaluate the vibration sensitivity of the Center for Integrated Nanotechnolog ies and propose possible mitigation strategies .
Power systems in rural Alaska villages face a unique combination of challenges that can increase the cost of energy and lowers energy supply reliability. In the case of the remote village of Shungnak, diesel and heating fuel is either shipped in by barge or flown in by aircraft. This report presents a technical analysis of several energy infrastructure upgrade and modification options to reduce the amount of fuel consumed by the community of Shungnak. Reducing fuel usage saves money and makes the village more resilient to disruptions in fuel supply. The analysis considers demand side options, such as energy efficiency, alongside the installation of wind and solar power generation options. Some novel approaches are also considered including battery energy storage and the use of electrical home heating stoves powered by renewable generation that would otherwise be spilled and wasted. This report concludes with specific recommendations for Shungnak based on economic factors, and fuel price sensitivity. General conclusions are also included to support future work analyzing similar energy challenges in remote arctic regions.
The formulation of carrier transport through heterojunctions by tunneling and thermionic emission is derived from first principles. The treatment of tunneling is discussed at three levels of approximation: numerical solution of the one-band envelope equation for an arbitrarily specified potential profile; the WKB approximation for an arbitrary potential; and, an analytic formulation assuming constant internal field. The effects of spatially varying carrier chemical potentials over tunneling distances are included. Illustrative computational results are presented. The described approach is used in exploratory physics models of irradiated heterojunction bipolar transistors within Sandia's QASPR program.
Recent advances in information technology have led to an expansion of crowdsourcing activities that utilize the “power of the people” harnessed via online games, communities of interest, and other platforms to collect, analyze, verify, and provide technological solutions for challenges from a multitude of domains. To related this surge in popularity, the research team developed a taxonomy of crowdsourcing activities as they relate to international nuclear safeguards, evaluated the potential legal and ethical issues surrounding the use of crowdsourcing to support safeguards, and proposed experimental designs to test the capabilities and prospect for the use of crowdsourcing to support nuclear safeguards verification.
The XVis project brings together the key elements of research to enable scientific discovery at extreme scale. Scientific computing will no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/O limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. This project provides the necessary research and infrastructure for scientific discovery in this new computational ecosystem by addressing four interlocking challenges: emerging processor technology, in situ integration, usability, and proxy analysis.
Following the conclusion of the first phase of the crosswalk analysis, one of the key unanswered questions was whether or not the deviations found would persist during a partially recovered accident scenario, similar to the one that occurred in TMI - 2. In particular this analysis aims to compare the impact of core degradation morphology on quenching models inherent within the two codes and the coolability of debris during partially recovered accidents. A primary motivation for this study is the development of insights into how uncertainties in core damage progression models impact the ability to assess the potential for recovery of a degraded core. These quench and core recovery models are of the most interest when there is a significant amount of core damage, but intact and degraded fuel still remain in the cor e region or the lower plenum. Accordingly this analysis presents a spectrum of partially recovered accident scenarios by varying both water injection timing and rate to highlight the impact of core degradation phenomena on recovered accident scenarios. This analysis uses the newly released MELCOR 2.2 rev. 966 5 and MAAP5, Version 5.04. These code versions, which incorporate a significant number of modifications that have been driven by analyses and forensic evidence obtained from the Fukushima - Daiichi reactor site.
Measure the total quantity of tritium in the sample by heating to high temperatures for protracted periods of time. This increases the mean migration distance of a triton (at 700 °C held for 90 minutes) to be larger than the thickness of the sample.
This report characterizes communications network latency under various network topologies and qualities of service (QoS). The characterizations are probabilistic in nature, allowing deeper analysis of stability for Internet Protocol (IP) based feedback control systems used in grid applications. The work involves the use of Raspberry Pi computers as a proxy for a controlled resource, and an ns-3 network simulator on a Linux server to create an experimental platform (testbed) that can be used to model wide-area grid control network communications in smart grid. Modbus protocol is used for information transport, and Routing Information Protocol is used for dynamic route selection within the simulated network.
Transient simulation in circuit simulation tools, such as SPICE and Xyce, depend on scalable and robust sparse LU factorizations for efficient numerical simulation of circuits and power grids. As the need for simulations of very large circuits grow, the prevalence of multicore architectures enable us to use shared memory parallel algorithms for such simulations. A parallel factorization is a critical component of such shared memory parallel simulations. We develop a parallel sparse factorization algorithm that can solve problems from circuit simulations efficiently, and map well to architectural features. This new factorization algorithm exposes hierarchical parallelism to accommodate irregular structure that arise in our target problems. It also uses a hierarchical two-dimensional data layout which reduces synchronization costs and maps to memory hierarchy found in multicore processors. We present an OpenMP based implementation of the parallel algorithm in a new multithreaded solver called Basker in the Trilinos framework. We present performance evaluations of Basker on the Intel SandyBridge and Xeon Phi platforms using circuit and power grid matrices taken from the University of Florida sparse matrix collection and from Xyce circuit simulation. Basker achieves a geometric mean speedup of 5.91× on CPU (16 cores) and 7.4× on Xeon Phi (32 cores) relative to state-of-the-art solver KLU. Basker outperforms Intel MKL Pardiso solver (PMKL) by as much as 30× on CPU (16 cores) and 7.5× on Xeon Phi (32 cores) for low fill-in circuit matrices. Furthermore, Basker provides 5.4× speedup on a challenging matrix sequence taken from an actual Xyce simulation.
Saeedi, Ali; Delle Piane, Claudio; Esteban, Lionel; Brady, Patrick V.
The South West Hub project is one of the Australian Flagship Carbon Capture and Storage projects located in the south-west of Western Australia. To evaluate the injectivity potential during the forthcoming full-scale CO2 injection, we conducted three core-flooding experiments using reservoir core plugs from the well Harvey-1. We aimed to investigate whether the injection of CO2 leads to fines migration and permeability reduction due to the relatively high kaolinite content (up to 13%) in the injection interval of the target formation (i.e. the Wonnerup Member of the Lesueur Formation). We imaged the core samples before flooding to verify the presence of kaolinite at the pore-scale using scanning electron microscopy (SEM). We also examined the pore network of the core plugs before and after the core-flooding experiments using Nuclear Magnetic Resonance (NMR). Moreover, to gain a better understanding of any kaolinite fines migration, we delineated surface force using two models based on Derjaguin−Landau−Verwey−Overbeek (denoted by DLVO) theory coupled hydrodynamic force: (1) sphere/flat model representing interaction between kaolinite/quartz, and (2) flat/flat model representing interaction between kaolinite/kaolinite. Our core-flooding experimental results showed that CO2/brine injection triggered moderate to significant reduction in the permeability of the core samples with a negligible porosity change. NMR measurements supported the core-flooding results, suggesting that the relatively large pores disappeared in favour of a higher proportion of the medium to small pores after flooding. The DLVO calculations showed that some kaolinite particles probably lifted off and detached from neighbouring kaolinite particles rather than quartz grains. Moreover, the modelling results showed that the kaolinite fines migration would not occur under normal reservoir multiphase flow conditions. This is not because of the low hydrodynamic force. It is rather because the geometries of the particles dominate their interplay. Overall, both of the experimental and analytical modelling results point to the fines migration to be the most likely cause of the permeability impairment observed during core-flooding experiments.
The cost of data movement has always been an important concern in high performance computing (HPC) systems. It has now become the dominant factor in terms of both energy consumption and performance. Support for expression of data locality has been explored in the past, but those efforts have had only modest success in being adopted in HPC applications for various reasons. them However, with the increasing complexity of the memory hierarchy and higher parallelism in emerging HPC systems, locality management has acquired a new urgency. Developers can no longer limit themselves to low-level solutions and ignore the potential for productivity and performance portability obtained by using locality abstractions. Fortunately, the trend emerging in recent literature on the topic alleviates many of the concerns that got in the way of their adoption by application developers. Data locality abstractions are available in the forms of libraries, data structures, languages and runtime systems; a common theme is increasing productivity without sacrificing performance. This paper examines these trends and identifies commonalities that can combine various locality concepts to develop a comprehensive approach to expressing and managing data locality on future large-scale high-performance computing systems.
Obtaining multi-process hard failure resilience at the application level is a key challenge that must be overcome before the promise of exascale can be fully realized. Previous work has shown that online global recovery can dramatically reduce the overhead of failures when compared to the more traditional approach of terminating the job and restarting it from the last stored checkpoint. If online recovery is performed in a local manner further scalability is enabled, not only due to the intrinsic lower costs of recovering locally, but also due to derived effects when using some application types. In this paper we model one such effect, namely multiple failure masking, that manifests when running Stencil parallel computations on an environment when failures are recovered locally. First, the delay propagation shape of one or multiple failures recovered locally is modeled to enable several analyses of the probability of different levels of failure masking under certain Stencil application behaviors. Our results indicate that failure masking is an extremely desirable effect at scale which manifestation is more evident and beneficial as the machine size or the failure rate increase.
Frequency combs based on quantum cascade lasers (QCLs) are finding promising applications in high-speed broadband spectroscopy in the terahertz regime, where many molecules have their “fingerprints.” To form stable combs in QCLs, an effective control of group velocity dispersion plays a critical role. The dispersion of the QCL cavity has two main parts: a static part from the material and a dynamic part from the intersubband transitions. Unlike the gain, which is clamped to a fixed value above the lasing threshold, dispersion associated with the intersubband transitions changes with bias, even above the threshold, and this reduces the dynamic range of comb formation. Here, by incorporating tunability into the dispersion compensator, we demonstrate a QCL device exhibiting comb operation from Ith to Imax, which greatly expands the operation range of the frequency combs.
The purpose of this project was to gain a fundamental understanding of molecular diffusion in nanogap electrodes and the diffusive behavior of single molecules undergoing electron transfer. Electrochemical methods for single molecule detection have remained elusive due to the vanishingly small currents involved in single molecule electron transfer. Electrochemical detection of single molecules undergoing redox cycling would enable detection of single enzymes, proteins, and DNA strands resulting in new and improved ultrasensitive sensing devices impacting Detection At The Limits research challenge (DATL), supporting needs in DHS and DoD. We attempted to integrate orthogonal validation techniques, Total Internal Reflection Fluorescence Microscopy (TIRF), and molecular simulation to clarify (1) the mechanism leading to current build up due to redox cycling and (2) diffusion and adsorption of single molecules undergoing redox reactions. While creation of nanogap electrodes with transparent windows was ultimately successful in this project (along with TIRF demonstration of single molecule imaging), time and methods constraints did not allow final electrochemical measurements to be coupled for simultaneous interrogation.
For a three-degree-of-freedom wave energy converter (heave, pitch, and surge), the equations of motion could be coupled depending on the buoy shape. This paper presents a multiresonant feedback control, in a general framework, for this type of a wave energy converter that is modeled by linear time invariant dynamic systems. The proposed control strategy finds the optimal control in the sense that it computes the control based on the complex conjugate criteria. This control strategy is relatively easy to implement since it is a feedback control in the time domain that requires only measurements of the buoy motion. Numerical tests are presented for two different buoy shapes: a sphere and a cylinder. Regular, Bretschnieder, and Ochi-Hubble waves are tested. Simulation results show that the proposed controller harvests energy in the pitch-surge-heave modes that is about three times the energy that can be harvested using a heave-only device. This multiresonant control can also be used to shift the energy harvesting between the coupled modes, which can be exploited to eliminate one of the actuators while maintaining about the same level of energy harvesting.
Many experiments on Sandia National Laboratories' Z Pulsed Power Facility - a 30 MA, 100 ns rise-time, pulsed-power driver - use a monochromatic quartz crystal backlighter system at 1.865 keV (Si Heα) or 6.151 keV (Mn Heα) x-ray energy to radiograph an imploding liner (cylindrical tube) or wire array z-pinch. The x-ray source is generated by the Z-Beamlet laser, which provides two 527-nm, 1 kJ, 1-ns laser pulses. Radiographs of imploding, thick-walled beryllium liners at convergence ratios CR above 15 [CR=ri(0)/ri(t)] using the 6.151-keV backlighter system were too opaque to identify the inner radius ri of the liner with high confidence, demonstrating the need for a higher-energy x-ray radiography system. Here, we present a 7.242 keV backlighter system using a Ge(335) spherical crystal with the Co Heα resonance line. This system operates at a similar Bragg angle as the existing 1.865 keV and 6.151 keV backlighters, enhancing our capabilities for two-color, two-frame radiography without modifying the system integration at Z. The first data taken at Z include 6.2-keV and 7.2-keV two-color radiographs as well as radiographs of low-convergence (CR about 4-5), high-areal-density liner implosions.
Hyperspectral imaging polarimetry enables both the spectrum and its spectrally resolved state of polarization to be measured. This information is important for identifying material properties for various applications in remote sensing and agricultural monitoring. We describe the design and performance of a ruggedized, field deployable hyperspectral imaging polarimeter, designed for wavelengths spanning the visible to near-infrared (450 to 800 nm). An entrance slit was used to sample the scene in a pushbroom scanning mode across a 30 deg vertical by 110 deg horizontal field-of-view. Furthermore, athermalized achromatic retarders were implemented in a channel spectrum generator to measure the linear Stokes parameters. The mechanical and optical layout of the system and its peripherals, in addition to the results of the sensor's spectral and polarimetric calibration, are provided. Finally, field measurements are also provided and an error analysis is conducted. With its present calibration, the sensor has an absolute polarimetric error of 2.5% RMS and a relative spectral error of 2.3% RMS.
Results of axisymmetric compression tests on weak, porous Castlegate Sandstone (Cretaceous, Utah, USA), covering a range of dilational and compactional behaviors, are examined for localization behavior. Assuming isotropy, bulk and shear moduli evolve as increasing functions of mean stress and Mises equivalent shear stress respectively, and as decreasing functions of work-conjugate plastic strains. Acoustic emissions events located during testing show onset of localization and permit calculation of observed shear and low-angle compaction localization zones, or bands, as localization commences. Total strain measured experimentally partitions into: A) elastic strain with constant moduli, B) elastic strain due to stress dependence of moduli, C) elastic strain due to moduli degradation with increasing plastic strain, and D) plastic strain. The third term is the elastic-plastic coupling strain, and though often ignored, contributes significantly to pre-failure total strain for brittle and transitional tests. Constitutive parameters and localization predictions derived from experiments are compared to theoretical predictions. In the brittle regime, predictions of band angles (angle between band normal and maximum compression) demonstrate good agreement with observed shear band angles. Compaction localization was observed in the transitional regime in between shear localization and spatially pervasive compaction, over a small range of mean stresses. In contrast with predictions, detailed acoustic emissions analyses in this regime show low angle, compaction-dominated but shear-enhanced, localization.
The FY17Q4 milestone of the ECP/VTK-m project includes the completion of a key-reduce scheduling mechanism, a spatial division algorithm, an algorithm for basic particle advection, and the computation of smoothed surface normals. With the completion of this milestone, we are able to, respectively, more easily group like elements (a common visualization algorithm operation), provide the fundamentals for geometric search structures, provide the fundamentals for many flow visualization algorithms, and provide more realistic rendering of surfaces approximated with facets.
Thermomechanical stability and high thermal conductivity are important for nuclear cladding material performance and reliability, which degrade over time under irradiation. The literature suggests nanocrystalline materials as radiation tolerant, but little or no evidence is present from thermal transport perspective. In this study, we irradiated 10 nm grain size zirconium thin films with 800 keV Zr+ beam from a 6 MV HVE Tandem accelerator to achieve various doses of 3 × 1010 to 3.26 × 1014 ions/cm2, corresponding to displacement per atom (dpa) of 2.1 × 10− 4 to 2.28. Transmission electron microscopy showed significant grain growth, texture evolution and oxidation in addition to the creation of displacement defects due to the irradiation. The specimens were co-fabricated with micro-heaters to establish thermal gradients that were mapped using infrared thermometry. An energy balance approach was used to estimate the thermal conductivity of the specimens, as function of irradiation dosage. Up to 32% reduction of thermal conductivity was measured for the sample exposed to a dose of 2.1 dpa (3 × 1014 ions/cm2).
This research and development project is focused on the advancement of a technology that produces hydrogen at a cost that is competitive with fossil-based fuels for transportation. A twostep, solar-driven WS thermochemical cycle is theoretically capable of achieving an STH conversion ratio that exceeds the DOE target of 26% at a scale large enough to support an industrialized economy [1]. The challenge is to transition this technology from the laboratory to the marketplace and produce hydrogen at a cost that meets or exceeds DOE targets.
In this paper we develop a fully-retarded, dipole approximation model to estimate the effective polarizabilities of a dimer made of dielectric resonators. They are computed from the polarizabilities of the two resonators composing the dimer. We analyze the situation of full-cubes as well as split-cubes, which have been shown to exhibit overlapping electric and magnetic resonances. We compare the effective dimer polarizabilities to ones retrieved via full-wave simulations as well as ones computed via a quasi-static, dipole approximation. We observe good agreement between the fully-retarded solution and the full-wave results, whereas the quasi-static approximation is less accurate for the problem at hand. The developed model can be used to predict the electric and magnetic resonances of a dimer under parallel or orthogonal (to the dimer axis) excitation. This is particularly helpful when interested in locating frequencies at which the dimer will emit directional radiation.
Materials designed for nuclear reactors undergo microstructural changes resulting from a combination of several environmental factors, including neutron irradiation damage, gas accumulation and elevated temperatures. Typical ion beam irradiation experiments designed for simulating a neutron irradiation environment involve irradiating the sample with a single ion beam and subsequent characterization of the resulting microstructure, often by transmission electron microscopy (TEM). This method does not allow for examination of microstructural effects due to simultaneous gas accumulation and displacement cascade damage, which occurs in a reactor. Sandia's in situ ion irradiation TEM (I3TEM) offers the unique ability to observe microstructural changes due to irradiation damage caused by concurrent multi-beam ion irradiation in real time. This allows for time-dependent microstructure analysis. A plethora of additional in situ stages can be coupled with these experiments, e.g.; for more accurately simulating defect kinetics at elevated reactor temperatures. This work outlines experiments showing synergistic effects in Au using in situion irradiation with various combinations of helium, deuterium and Au ions, as well as some initial work on materials utilized in tritium-producing burnable absorber rods (TPBARs): zirconium alloys and LiAlO2.
The former Nalu interior heterogeneous algorithm design, which was originally designed to manage matrix assembly operations over all elemental topology types, has been modified to operate over homogeneous collections of mesh entities. This newly templated kernel design allows for removal of workset variable resize operations that were formerly required at each loop over a Sierra ToolKit (STK) bucket (nominally, 512 entities in size). Extensive usage of the Standard Template Library (STL) std::vector has been removed in favor of intrinsic Kokkos memory views. In this milestone effort, the transition to Kokkos as the underlying infrastructure to support performance and portability on many-core architectures has been deployed for key matrix algorithmic kernels. A unit-test driven design effort has developed a homogeneous entity algorithm that employs a team-based thread parallelism construct. The STK Single Instruction Multiple Data (SIMD) infrastructure is used to interleave data for improved vectorization. The collective algorithm design, which allows for concurrent threading and SIMD management, has been deployed for the core low-Mach element- based algorithm. Several tests to ascertain SIMD performance on Intel KNL and Haswell architectures have been carried out. The performance test matrix includes evaluation of both low- and higher-order methods. The higher-order low-Mach methodology builds on polynomial promotion of the core low-order control volume nite element method (CVFEM). Performance testing of the Kokkos-view/SIMD design indicates low-order matrix assembly kernel speed-up ranging between two and four times depending on mesh loading and node count. Better speedups are observed for higher-order meshes (currently only P=2 has been tested) especially on KNL. The increased workload per element on higher-order meshes bene ts from the wide SIMD width on KNL machines. Combining multiple threads with SIMD on KNL achieves a 4.6x speedup over the baseline, with assembly timings faster than that observed on Haswell architecture. The computational workload of higher-order meshes, therefore, seems ideally suited for the many-core architecture and justi es further exploration of higher-order on NGP platforms. A Trilinos/Tpetra-based multi-threaded GMRES preconditioned by symmetric Gauss Seidel (SGS) represents the core solver infrastructure for the low-Mach advection/diffusion implicit solves. The threaded solver stack has been tested on small problems on NREL's Peregrine system using the newly developed and deployed Kokkos-view/SIMD kernels. fforts are underway to deploy the Tpetra-based solver stack on NERSC Cori system to benchmark its performance at scale on KNL machines.
Randomized benchmarking (RB) is widely used to measure an error rate of a set of quantum gates, by performing random circuits that would do nothing if the gates were perfect. In the limit of no finite-sampling error, the exponential decay rate of the observable survival probabilities, versus circuit length, yields a single error metric r. For Clifford gates with arbitrary small errors described by process matrices, r was believed to reliably correspond to the mean, over all Clifford gates, of the average gate infidelity between the imperfect gates and their ideal counterparts. We show that this quantity is not a well-defined property of a physical gate set. It depends on the representations used for the imperfect and ideal gates, and the variant typically computed in the literature can differ from r by orders of magnitude. We present new theories of the RB decay that are accurate for all small errors describable by process matrices, and show that the RB decay curve is a simple exponential for all such errors. These theories allow explicit computation of the error rate that RB measures (r), but as far as we can tell it does not correspond to the infidelity of a physically allowed (completely positive) representation of the imperfect gates.
The following discussion contains a high-level description of methods used to implement software for data processing. It describes the required directory structures and file handling required to use Excel's Visual Basic for Applications programming language and how to identify shot, test and capture types to appropriately process data. It also describes how to interface with the software.
Calibration of terrestrial ecosystem models is important but challenging. Bayesian inference implemented by Markov chain Monte Carlo (MCMC) sampling provides a comprehensive framework to estimate model parameters and associated uncertainties using their posterior distributions. The effectiveness and efficiency of the method strongly depend on the MCMC algorithm used. In this work, a differential evolution adaptive Metropolis (DREAM) algorithm is used to estimate posterior distributions of 21 parameters for the data assimilation linked ecosystem carbon (DALEC) model using 14 years of daily net ecosystem exchange data collected at the Harvard Forest Environmental Measurement Site eddy-flux tower. The calibration of DREAM results in a better model fit and predictive performance compared to the popular adaptive Metropolis (AM) scheme. Moreover, DREAM indicates that two parameters controlling autumn phenology have multiple modes in their posterior distributions while AM only identifies one mode. The application suggests that DREAM is very suitable to calibrate complex terrestrial ecosystem models, where the uncertain parameter size is usually large and existence of local optima is always a concern. In addition, this effort justifies the assumptions of the error model used in Bayesian calibration according to the residual analysis. The result indicates that a heteroscedastic, correlated, Gaussian error model is appropriate for the problem, and the consequent constructed likelihood function can alleviate the underestimation of parameter uncertainty that is usually caused by using uncorrelated error models.
Reducing defects in InGaN films deposited on GaN substrates has been critical to fill the “green” gap for solid-state lighting applications. To enable researchers to use molecular dynamics vapor deposition simulations to explores ways to reduce defects in InGaN films, we have developed and characterized a Stillinger-Weber potential for InGaN. We show that this potential reproduces the experimental atomic volume, cohesive energy, and bulk modulus of the equilibrium wurtzite / zinc-blende phases of both InN and GaN. Most importantly, the potential captures the stability of the correct phase of InGaN compounds against a variety of other elemental, alloy, and compound configurations. Lastly, this is validated by the potential’s ability to predict crystalline growth of stoichiometric wurtzite and zinc-blende InxGa1-xN compounds during vapor deposition simulations where adatoms are randomly injected to the growth surface.
Using a high-electron-mobility cadmium oxide perfect absorber and intraband optical pumping, we experimentally demonstrate a reflective polarizer with a polarization extinction ratio of 91 that can be switched on and off within 800 fs.
We have demonstrated a scalable dual-band tunable infrared filter based on gating of a continuous graphene layer. The measured and modeled response of the device are in good agreement.
Aryal, Dipak; Agrawal, Anupriya; Perahia, Dvora; Grest, Gary S.
Structure and dynamics of melts of copolymers with an ABCBA topology, where C is an ionizable block, have been studied by fully atomistic molecular dynamics (MD) simulations. Introducing an ionizable block for functionality adds a significant element to the coupled set of interactions that determine the structure and dynamics of the macromolecule. The polymer consists of a randomly sulfonated polystyrene C block tethered to a flexible poly(ethylene-r-propylene) bridge B and end-capped with poly(tert-butylstyrene) A. The chemical structure and topology of these polymers constitute a model for incorporation of ionic blocks within a framework that provides tactility and mechanical stability. Here we resolve the structure and dynamics of a structured polymer on the nanoscale constrained by ionic clusters. We find that the melts form intertwined networks of the A and C blocks independent of the degree of sulfonation of the C block with no long-range order. The cluster cohesiveness and morphology affect both macroscopic translational motion and segmental dynamics of all the blocks.
SNL has a combination of experimental facilities, nuclear engineering, nuclear security, severe nuclear accidents, and nuclear safeguards expertise that can enable significant progress towards molten salts and fuels for Molten Salt Reactors (MSRs). The following areas and opportunities are discussed in more detail in this white paper.
Liu, Henan; Zhang, Yong; Steenbergen, Elizabeth H.; Liu, Shi; Lin, Zhiyuan; Zhang, Yong-Hang; Kim, Jeomoh; Ji, Mi-Hee; Detchprohm, Theeradetch; Dupuis, Russell D.; Kim, Jin K.; Hawkins, Samuel D.; Klem, John F.
The InAs/InAs1-x Sbx superlattice system distinctly differs from two well-studied superlattice systems GaAs/AlAs and InAs/GaSb in terms of electronic band alignment, common elements at the interface, and phonon spectrum overlapping of the constituents. This fact leads to the unique electronic and vibrational properties of the InAs/InAs1-xSbx system when compared to the other two systems. Here in this work, we report a polarized Raman study of the vibrational properties of the InAs/InAs1-x Sbx superlattices (SLs) as well as selected InAs1-xSbx alloys, all grown on GaSb substrates by either MBE or metalorganic chemical vapor deposition (MOCVD) from both the growth surface and cleaved edge. In the SL, from the (001) backscattering geometry, an InAs-like longitudinal optical (LO) mode is observed as the primary feature, and its intensity is found to increase with increasing Sb composition. From the (110) cleaved-edge backscattering geometry, an InAs-like transverse optical (TO) mode is observed as the main feature in two cross-polarization configurations, but an additional InAs-like “forbidden” LO mode is observed in two parallel-polarization configurations. The InAs1-xSbx alloys lattice matched to the substrate ( xSb ~ 0.09) grown by MBE are also found to exhibit the forbidden LO mode, implying the existence of some unexpected [001] modulation. However, the strained samples (xSb~ 0.35) grown by MOCVD are found to behave like a disordered alloy. The primary conclusions are (1) the InAs-like LO or TO mode can be either a confined or quasiconfined mode in the InAs layers of the SL or extended mode of the whole structure depending on the Sb composition. (2) InAs/InAs1-xSbx and InAs/GaSb SLs exhibit significantly different behaviors in the cleaved-edge geometry but qualitatively similar in the (001) geometry. (3) The appearance of the forbidden LO-like mode is a universal signature for SLs and bulk systems resulting from the mixing of phonon modes due to structural modulation or symmetry reduction.
With the increased scale expected on future leadership-class systems, detailed information about the resource usage and performance of MPI message matching provides important insights into how to maintain application performance on next-generation systems. However, obtaining MPI message matching performance data is often not possible without significant effort. A common approach is to instrument an MPI implementation to collect relevant statistics. While this approach can provide important data, collecting matching data at runtime perturbs the application’s execution, including its matching performance, and is highly dependent on the MPI library’s matchlist implementation. In this paper, we introduce a trace-based simulation approach to obtain detailed MPI message matching performance data for MPI applications without perturbing their execution. Using a number of key parallel workloads, we demonstrate that this simulator approach can rapidly and accurately characterize matching behavior. Specifically, we use our simulator to collect several important statistics about the operation of the MPI posted and unexpected queues. For example, we present data about search lengths and the duration that messages spend in the queues waiting to be matched. Data gathered using this simulation-based approach have significant potential to aid hardware designers in determining resource allocation for MPI matching functions and provide application and middleware developers with insight into the scalability issues associated with MPI message matching.
Here, we present a low resistance, straightforward planar ohmic contact for Al0.45Ga0.55N/Al0.3Ga0.7N high electron mobility transistors. Five metal stacks (a/Al/b/Au; a = Ti, Zr, V, Nb/Ti; b = Ni, Mo, V) were evaluated at three individual annealing temperatures (850, 900, and 950°C). The Ti/Al/Ni/Au achieved the lowest specific contact resistance at a 900°C anneal temperature. Transmission electron microscopy analysis revealed a metal-semiconductor interface of Ti-Al-Au for an ohmic (900°C anneal) and a Schottky (850°C anneal) Ti/Al/Ni/Au stack. HEMTs were fabricated using the optimized recipe with resulting contacts that had room-temperature specific contact resistances of ρc = 2.5 × 10-5 Ω cm², sheet resistances of RSH = 3.9 kΩ/$\blacksquare$, and maximum current densities of 75 mA/mm (at VGATE of 2 V). Electrical measurements from -50 to 200°C had decreasing specific contact resistance and increasing sheet resistance, with increasing temperature. These contacts enabled state-of-the-art performance of Al0.45Ga0.55N/Al0.3Ga0.7N HEMTs.
The Spent Fuel and Waste Science and Technology (SFWST) Campaign of the U.S. Department of Energy (DOE) Office of Nuclear Energy (NE), Office of Fuel Cycle Technology (OFCT) is conducting research and development (R&D) on geologic disposal of spent nuclear fuel (SNF) and high level nuclear waste (HLW). Two high priorities for SFWST disposal R&D are design concept development and disposal system modeling (DOE 2011, Table 6). These priorities are directly addressed in the SFWST Generic Disposal Systems Analysis (GDSA) work package, which is charged with developing a disposal system modeling and analysis capability for evaluating disposal system performance for nuclear waste in geologic media (e.g., salt, granite, shale, and deep borehole disposal).
Aggregating millions of hardware components to construct an exascale computing platform will pose significant resilience challenges. In addition to slowdowns associated with detected errors, silent errors are likely to further degrade application performance. Moreover, silent data corruption (SDC) has the potential to undermine the integrity of the results produced by important scientific applications.In this paper, we propose an application-independent mechanism to efficiently detect and correct SDC in read-mostly memory, where SDC may be most likely to occur. We use memory protection mechanisms to maintain compressed backups of application memory. We detect SDC by identifying changes in memory contents that occur without explicit write operations. We demonstrate that, for several applications, our approach can potentially protect a significant fraction of application memory pages from SDC with modest overheads. Moreover, our proposed technique can be straightforwardly combined with many other approaches to provide a significant bulwark against SDC.
While large-scale simulations have been the hallmark of the High Performance Computing (HPC) community for decades, Large Scale Data Analytics (LSDA) workloads are gaining attention within the scientific community not only as a processing component to large HPC simulations, but also as standalone scientific tools for knowledge discovery. With the path towards Exascale, new HPC runtime systems are also emerging in a way that differs from classical distributed computing models. However, system software for such capabilities on the latest extreme-scale DOE supercomputing needs to be enhanced to more appropriately support these types of emerging software ecosystems.In this paper, we propose the use of Virtual Clusters on advanced supercomputing resources to enable systems to support not only HPC workloads, but also emerging big data stacks. Specifically, we have deployed the KVM hypervisor within Cray's Compute Node Linux on a XC-series supercomputer testbed. We also use libvirt and QEMU to manage and provision VMs directly on compute nodes, leveraging Ethernet-over-Aries network emulation. To our knowledge, this is the first known use of KVM on a true MPP supercomputer. We investigate the overhead our solution using HPC benchmarks, both evaluating single-node performance as well as weak scaling of a 32-node virtual cluster. Overall, we find single node performance of our solution using KVM on a Cray is very efficient with near-native performance. However overhead increases by up to 20% as virtual cluster size increases, due to limitations of the Ethernet-over-Aries bridged network. Furthermore, we deploy Apache Spark with large data analysis workloads in a Virtual Cluster, effectively demonstrating how diverse software ecosystems can be supported by High Performance Virtual Clusters.
Proceedings - IEEE International Conference on Cluster Computing, ICCC
Jha, Saurabh; Brandt, James M.; Gentile, Ann C.; Kalbarczyk, Zbigniew; Bauer, Greg; Enos, Jeremy; Showerman, Michael; Kaplan, Larry; Bode, Brett; Greiner, Annette; Bonnie, Amanda; Mason, Mike; Iyer, Ravishankar K.; Kramer, William
In high-performance computing systems, application performance and throughput are dependent on a complex interplay of hardware and software subsystems and variable workloads with competing resource demands. Data-driven insights into the potentially widespread scope and propagationof impact of events, such as faults and contention for shared resources, can be used to drive more effective use of resources, for improved root cause diagnosis, and for predicting performance impacts. We present work developing integrated capabilities for holistic monitoring and analysis to understand and characterize propagation of performance-degrading events. These characterizations can be used to determine and invoke mitigating responses by system administrators, applications, and system software.
Optimal design of a gas detection systems is challenging because of the numerous sources of uncertainty, including weather and environmental conditions, leak location and characteristics, and process conditions. Rigorous CFD simulations of dispersion scenarios combined with stochastic programming techniques have been successfully applied to the problem of optimal gas detector placement; however, rigorous treatment of sensor failure and nonuniform unavailability has received less attention. To improve reliability of the design, this paper proposes a problem formulation that explicitly considers nonuniform unavailabilities and all backup detection levels. The resulting sensor placement problem is a large-scale mixed-integer nonlinear programming (MINLP) problem that requires a tailored solution approach for efficient solution. We have developed a multitree method which depends on iteratively solving a sequence of upper-bounding master problems and lower-bounding subproblems. The tailored global solution strategy is tested on a real data problem and the encouraging numerical results indicate that our solution framework is promising in solving sensor placement problems. This study was selected for the special issue in JLPPI from the 2016 International Symposium of the MKO Process Safety Center.
Effective passivation of lithium metal surfaces, and prevention of battery-shorting lithium dendrite growth, are critical for implementing lithium metal anodes for batteries with increased power densities. Nanoscale surface heterogeneities can be "hot spots" where anode passivation breaks down. Motivated by the observation of lithium dendrites in pores and grain boundaries in all-solid batteries, we examine lithium metal surfaces covered with Li2O and/or LiF thin films with grain boundaries in them. Electronic structure calculations show that at >0.25 V computed equilibrium overpotential Li2O grain boundaries with sufficiently large pores can accommodate Li0 atoms which aid e- leakage and passivation breakdown. Strain often accompanies Li insertion; applying an ∼1.7% strain already lowers the computed overpotential to 0.1 V. Lithium metal nanostructures as thin as 12 Å are thermodynamically favored inside cracks in Li2O films, becoming "incipient lithium filaments". LiF films are more resistant to lithium metal growth. The models used herein should in turn inform passivating strategies in all-solid-state batteries.
The recent discovery of excellent thermoelectric properties and topological surface states in SnTe-based compounds has attracted extensive attention in various research areas. Indium doped SnTe is of particular interest because, depending on the doping level, it can either generate resonant states in the bulk valence band leading to enhanced thermoelectric properties, or induce superconductivity that coexists with topological states. Here we report on the vapor deposition of In-doped SnTe nanowires and the study of their surface oxidation and thermoelectric properties. The nanowire growth is assisted by Au catalysts, and their morphologies vary as a function of substrate position and temperature. Transmission electron microscopy characterization reveals the formation of an amorphous surface in single crystalline nanowires. X-ray photoelectron spectroscopy studies suggest that the nanowire surface is composed of In2O3, SnO2, Te and TeO2 which can be readily removed by argon ion sputtering. Exposure of the cleaned nanowires to atmosphere leads to rapid oxidation of the surface within only one minute. Characterization of electrical conductivity σ, thermopower S, and thermal conductivity κ was performed on the same In-doped nanowire which shows suppressed σ and κ but enhanced S yielding an improved thermoelectric figure of merit ZT compared to the undoped SnTe.
This document describes the theoretical foundation of thermal analysis in Sierra Mechanics. The SIERRA Multimechanics Module: Aria, henceforth referred to as Aria for brevity, was developed at Sandia National Laboratories under the ASC program, and approximates linear and nonlinear continuum models of heat transfer. Aria uses the SIERRA Framework, which provides data management services commonly required by computational mechanics software, and facilitates the development of coupled, multi-mechanics applications for massively parallel computers. The mathematical models in Aria are based heavily on those of COYOTE, a well-established thermal analysis program that was also developed at Sandia and its ASC code predecessor, Calore. Aria, Calore and COYOTE share a significant body of numerical methods, which are described in detail by Reddy and Gartling. Throughout this document, the terms software and implementation are synonymous with the Aria thermal-fluid analysis computer program.
The SNL Sierra Mechanics code suite is designed to enable simulation of complex multiphysics scenarios. The code suite is composed of several specialized applications which can operate either in standalone mode or coupled with each other. Arpeggio is a supported utility that enables loose coupling of the various Sierra Mechanics applications by providing access to Framework services that facilitate the coupling. More importantly Arpeggio orchestrates the execution of applications that participate in the coupling. This document describes the various components of Arpeggio and their operability. The intent of the document is to provide a fast path for analysts interested in coupled applications via simple examples of its usage.
Cache has long been used to minimize the latency of main memory accesses by storing frequently used data near the processor. Processor performance depends on the underlying cache performance. Therefore, significant research has been done to identify the most crucial metrics of cache performance. Although the majority of research focuses on measuring cache hit rates and data movement as the primary cache performance metrics, cache utilization is significantly important. We investigate the application’s locality using cache utilization metrics. In addition, we present cache utilization and traditional cache performance metrics as the program progresses providing detailed insights into the dynamic application behavior on parallel applications from four benchmark suites running on multiple cores. We explore cache utilization for APEX, Mantevo, NAS, and PARSEC, mostly scientific benchmark suites. Our results indicate that 40% of the data bytes in a cache line are accessed at least once before line eviction. Also, on average a byte is accessed two times before the cache line is evicted for these applications. Moreover, we present runtime cache utilization, as well as, conventional performance metrics that illustrate a holistic understanding of cache behavior. To facilitate this research, we build a memory simulator incorporated into the Structural Simulation Toolkit (Rodrigues et al. in SIGMETRICS Perform Eval Rev 38(4):37–42, 2011). Finally, our results suggest that variable cache line size can result in better performance and can also conserve power.
We demonstrate a new route toward the integration and deterministic placement of quantum dots (QDs) within prepatterned nanostructures. Using standard electron-beam lithography (EBL) and inductively coupled plasma reactive-ion etching (ICP-RIE), we fabricate arrays of nanowires on a III-nitride platform. Next, we integrate QDs of controlled size within the prepatterned nanowires using a bandgap-selective, wet-etching technique: quantum-size-controlled photoelectrochemical (QSC-PEC) etching. Low-Temperature microphotoluminescence (μ-PL) measurements of individual nanowires reveal sharp spectral signatures, indicative of QD formation. Further, internal quantum efficiency (IQE) measurements reveal a near order of magnitude improvement in emitter efficiency following QSC-PEC etching. Finally, second-order cross-correlation (g(2)(0)) measurements of individual QDs directly confirm nonclassical, antibunching behavior. Our results illustrate an exciting approach toward the top-down integration of nonclassical light sources within nanophotonic platforms.
This report provides an update to Sassani et al. (2016) and includes: (1) an updated set of inputs (Sections 2.3) on various additional waste forms (WF) covering both DOE-managed spent nuclear fuel (SNF) and DOE-managed (as) high-level waste (HLW) for use in the inventory represented in the geologic disposal safety analyses (GDSA); (2) summaries of evaluations initiated to refine specific characteristics of particular WF for future use (Section 2.4); (3) updated development status of the Online Waste Library (OWL) database (Section 3.1.2) and an updated user guide to OWL (Section 3.1.3); and (4) status updates (Section 3.2) for the OWL inventory content, data entry checking process, and external OWL BETA testing initiated in fiscal year 2017.
Construction of a test problem that quantitatively tests the effectiveness and robustness of the many features and capabilities that a comprehensive E2E UQ framework should have is very challenging. Accordingly, this report illustrates many of the considerations and numerical investigations that went into the construction of the Sandia Cantilever Beam End-to-End UQ test problem.
We present a study of an electrically modulated nonlinear metamaterial consisting of an array of split-ring resonators fabricated on n-type gallium arsenide. The resonant metamaterial nonlinearity appears as an intensity-dependent transmission minimum at terahertz frequencies and arises from the interaction between local electric fields in the split-ring resonator (SRR) capacitive gaps and charge carriers in the n-type substrate. We investigate the active tuning range of the metamaterial device as the incident terahertz field intensity is increased and conversely the effect of an applied DC bias on the terahertz field-induced nonlinear modulation of the metamaterial response. Applying a DC bias to the metamaterial sample alters the nonlinear response and reduces the net nonlinear modulation. Similarly, increasing the incident terahertz field intensity decreases the net modulation induced by an applied DC bias. We interpret these results in terms of DC and terahertz-field-assisted carrier acceleration, scattering, and multiplication processes, highlighting the unique nature of this DC-field modulated terahertz nonlinearity.
A new method is proposed for a fast evaluation of high-dimensional integrals of potential energy surfaces (PES) that arise in many areas of quantum dynamics. It decomposes a PES into a canonical low-rank tensor format, reducing its integral into a relatively short sum of products of low-dimensional integrals. The decomposition is achieved by the alternating least squares (ALS) algorithm, requiring only a small number of single-point energy evaluations. Therefore, it eradicates a force-constant evaluation as the hotspot of many quantum dynamics simulations and also possibly lifts the curse of dimensionality. This general method is applied to the anharmonic vibrational zero-point and transition energy calculations of molecules using the second-order diagrammatic vibrational many-body Green's function (XVH2) theory with a harmonic-approximation reference. In this application, high dimensional PES and Green's functions are both subjected to a low-rank decomposition. Evaluating the molecular integrals over a low-rank PES and Green's functions as sums of low-dimensional integrals using the Gauss–Hermite quadrature, this canonical-tensor-decomposition-based XVH2 (CT-XVH2) achieves an accuracy of 0.1 cm−1 or higher and nearly an order of magnitude speedup as compared with the original algorithm using force constants for water and formaldehyde.
Gautier et al. (2014) recently published their determination of hydromagnesite solubility constant and hydromagnesite growth kinetics. Although their raw data appear to be of high quality, there is an oversight in their calculations of the hydromagnesite solubility constants given the solution compositions in their experiments. The oversight lies in the fact that they did not consider the constraint of simultaneous equilibrium with brucite. This oversight causes their newly calculated equilibrium constant for hydromagnesite to be discordant with the literature values (Königsberger et al., 1992; Xiong, 2011).
The EPRI/DOE High-Burnup Confirmatory Data Project (herein called the “Demo”) is a multi-year, multi-entity test with the purpose of providing quantitative and qualitative data to show if high-burnup fuel mechanical properties change in dry storage over a ten-year period. The Demo involves obtaining 32 assemblies of high-burnup PWR fuel of common cladding alloys from the North Anna Nuclear Power Plant, loading them in an NRC-licensed TN-32B cask, drying them according to standard plant procedures, and then storing them on the North Anna dry storage pad for ten years. After the ten-year storage time, the cask will be opened and the mechanical properties of the rods will be tested and analyzed.
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.
Chemical thermodynamic data remain a keystone for geochemical modeling and reactive transport simulation as applied to an increasing number of applications in the earth sciences, as well as applications in other areas including metallurgy, material science, and industrial process design. The last century has seen the development of a large body of thermodynamic data and a number of major compilations. The past several decades have seen the development of thermodynamic databases in digital form designed to support computer calculations. However, problems with thermodynamic data appear to be persistent. One problem pertains to the use of inconsistent primary key reference data. Such data pertain to elemental reference forms and key, stoichiometrically simple chemical species including metal oxides, CO2, water, and aqueous species such as Na+ and Cl−. A consistent set of primary key data (standard Gibbs energies, standard enthalpies, and standard entropies for key chemical species) for 298.15 K and 1 bar pressure is essential. Thermochemical convention is to define the standard Gibbs energy and the standard enthalpy of an individual chemical species in terms of formation from reference forms of the constituent chemical elements. We propose a formal concept of “links” to the elemental reference forms. This concept involves a documented understanding of all reactions and calculations leading to values for a formation property (standard Gibbs energy or enthalpy). A valid link consists of two parts: (a) the path of reactions and corrections and (b) the associated data, which are key data. Such a link differs from a bare “key” or “reference” datum in that it requires additional information. Some or all of its associated data may also be key data. In evaluating a reported thermodynamic datum, one should identify the links to the chemical elements, a process which can be time-consuming and which may lead to a dead end (an incomplete link). The use of two or more inconsistent links to the same elemental reference form in a thermodynamic database will result in an inconsistency in the database. Thus, in constructing a database, it is important to establish a set of reliable links (generally resulting in a set of primary reference data) and then correct all data adopted subsequently for consistency with that set. Recommended values of key data have not been constant through history. We review some of this history through the lens of major compilations and other influential reports, and note a number of problem areas. Finally, we illustrate the concepts developed in this paper by applying them to some key species of geochemical interest, including liquid water; quartz and aqueous silica; and gibbsite, corundum, and the aqueous aluminum ion.
The coherent elastic scattering of neutrinos off nuclei has eluded detection for four decades, even though its predicted cross section is by far the largest of all low-energy neutrino couplings. This mode of interaction offers new opportunities to study neutrino properties and leads to a miniaturization of detector size, with potential technological applications. We observed this process at a 6.7s confidence level, using a low-background, 14.6-kilogram CsI[Na] scintillator exposed to the neutrino emissions from the Spallation Neutron Source at Oak Ridge National Laboratory. Characteristic signatures in energy and time, predicted by the standard model for this process, were observed in high signal-to-background conditions. Improved constraints on nonstandard neutrino interactions with quarks are derived from this initial data set.
Jove Colon, Carlos F.; Wang, Yifeng; Hadgu, Teklu H.; Zheng, Liange; Rutqvist, Jonny; Xu, Hao; Kim, Kunhwi; Voltolini, Marco; Cao, Xiaoyuan; Fox, Patricia; Nico, Peter S.; Caporuscio, Florie A.; Norskog, Katherine E.; Zavarin, Mavrik; Wolery, Thomas J.; Atkins-Duffin, Cindy; Jerden, James; Gattu, Vineeth K.; Ebert, William; Buck, Edgar C.; Wittman, Richard S.
The DOE R&D program under the Spent Fuel Waste Science Technology (SFWST) campaign has made key advances in experimental and modeling aspects of chemical and physical phenomena towards the long-term safety assessment of nuclear waste disposition in deep clay/shale/argillaceous rock. Experimental activities on clay barrier interactions with fluids and radionuclides provide the much needed knowledge to evaluate engineered barrier system (EBS) performance. Thermal-Hydrological-Mechanical-Chemical (THMC) model development of clay provides a rigorous simulation platform to assess the complex dynamic behavior of engineered and natural barrier materials in response to coupled process phenomena induced by heat-generating nuclear waste. This report describes the ongoing disposal R&D efforts on the advancement and refinement of coupled THMC process models, hydrothermal experiments and geochemical modeling of on barrier material (clay/metal) interactions, spent fuel and canister material degradation, radiolytic phenomena and UO2 degradation, and thermodynamic database development. These play an important role to the evaluation of sacrificial zones as part of the EBS exposure to thermally-driven chemical and transport processes. Clay-zeolite phase equilibria play a key role in the mineralogical transformations of clay barrier conducive to loss in swelling properties but also in controlling H20 uptake/release through hydration/dehydration reactions. The result is volume changes can affect the interface / bulk phase porosities, transport, and the mechanical (stress) state of the bentonite barrier. Characterization studies on barrier samples (bentonite/cement) from controlled tests at underground research laboratories (URLs) provide key insights into barrier materials interactions at EBS interfaces. Spent fuel degradation modeling coupled with canister and cladding corrosion effects demonstrate the strong influence of H2 generation on the source term.
This milestone 1) exercised a broad set of performance profiling and analysis tools, including tools whose development has been promoted by the ASC program; 2) exercised the tools on two different SNL ASC codes, one Sierra code (Sierra/Aria, a C++ codebase) and one RAMSES code (ITS, a Fortran codebase); and 3) exercised the tools on multiple platforms, including the CTS-1 (e.g., Serrano) and ATS-1 Trinity (e.g., Mutrino) platforms. The milestone generated a plethora of strong and weak scaling, trend and profile data for multiple versions and problem cases for each of the two codes. A wealth of experience was gained with the various tools that included identification of problems, an improved understanding of feature sets, enhanced usage documentation, and insights for future tool-development. Results are provided from a large number and variety of performance analysis runs with the target codes, together with instructions for how to make use of the tools with the codes.
A rigorous treatment of the uncertainty in the underlying nuclear data on silicon displacement damage metrics is presented. The uncertainty in the cross sections and recoil atom spectra are propagated into the energy-dependent uncertainty contribution in the silicon displacement kerma and damage energy using a Total Monte Carlo treatment. An energy-dependent covariance matrix is used to characterize the resulting uncertainty. A strong correlation between different reaction channels is observed in the high energy neutron contributions to the displacement damage metrics which supports the necessity of using a Monte Carlo based method to address the nonlinear nature of the uncertainty propagation.
The atomic force microscope (AFM) offers a rich observation window on the nanoscale, yet many dynamic phenomena are too fast and too weak for direct AFM detection. Integrated cavity-optomechanics is revolutionizing micromechanical sensing; however, it has not yet impacted AFM. Here, we make a groundbreaking advance by fabricating picogram-scale probes integrated with photonic resonators to realize functional AFM detection that achieve high temporal resolution (<10 ns) and picometer vertical displacement uncertainty simultaneously. The ability to capture fast events with high precision is leveraged to measure the thermal conductivity (η), for the first time, concurrently with chemical composition at the nanoscale in photothermal induced resonance experiments. The intrinsic η of metal-organic-framework individual microcrystals, not measurable by macroscale techniques, is obtained with a small measurement uncertainty (8%). The improved sensitivity (50×) increases the measurement throughput 2500-fold and enables chemical composition measurement of molecular monolayer-thin samples. Our paradigm-shifting photonic readout for small probes breaks the common trade-off between AFM measurement precision and ability to capture transient events, thus transforming the ability to observe nanoscale dynamics in materials.
The mechanisms that limit the temperature performance of diagonal GaAs/Al0.15GaAs0.85-based terahertz quantum cascade lasers (THz-QCLs) have been identified as thermally activated leakage of charge carriers through excited states into the continuum. THz-QCLs with energetically higher-laying excited states supported by sufficiently high barriers aim to eliminate these leakage mechanisms and lead to improved temperature performance. Although suppression of thermally activated carrier leakage was realized in a three-well THz-QCL based on a resonant-phonon scheme, no improvement in the temperature performance was reported thus far. Here, we report a major improvement in the temperature performance of a two-quantum-well direct-phonon THz-QCL structure. We show that the improved laser performance is due to the suppression of the thermally activated carrier leakage into the continuum with the increase in the injection barrier height. Moreover, we demonstrate that high-barrier two-well structures can support a clean three-level laser system at elevated temperatures, which opens the opportunity to achieve temperature performance beyond the state-of-the-art.
Over the past 20 years, many strategies utilizing sol-gel chemistry to integrate biological cells into silica-based materials have been reported. One such strategy, Sol-Generating Chemical Vapor into Liquid (SG-CViL) deposition, shows promise as an efficient encapsulation technique due to the ability to vary the silica encapsulation morphology obtained by this process through variation of SG-CViL reaction conditions. In this report, we develop SG-CViL as a tunable, multi-purpose silica encapsulation strategy by investigating the mechanisms governing both silica particle generation and subsequent interaction with phospholipid assemblies (liposomes and living cells). Using Dynamic Light Scattering (DLS) measurements, linear and exponential silica particle growth dynamics were observed which were dependent on deposition buffer ion constituents and ion concentration. Silica particle growth followed a cluster-cluster growth mechanism at acidic pH, and a monomer-cluster growth mechanism at neutral to basic pH. Increasing silica sol aging temperature resulted in higher rates of particle growth and larger particles. DLS measurements employing PEG-coated liposomes and cationic liposomes, serving as model phospholipid assemblies, revealed that electrostatic interactions promote more stable liposome-silica interactions than hydrogen bonding and facilitate silica coating on suspension cells. However, continued silica reactivity leads to aggregation of silica-coated suspension cells, revealing the need for cell isolation to tune deposited silica thickness. Utilizing these mechanistic study insights, silica was deposited onto adherent HeLa cells under biocompatible conditions with micrometer-scale control over silica thickness, minimal cell manipulation steps, and retained cell viability over several days.