Abstract: Due to a beneficial balance of computational cost and accuracy, real-time time-dependent density-functional theory has emerged as a promising first-principles framework to describe electron real-time dynamics. Here we discuss recent implementations around this approach, in particular in the context of complex, extended systems. Results include an analysis of the computational cost associated with numerical propagation and when using absorbing boundary conditions. We extensively explore the shortcomings for describing electron–electron scattering in real time and compare to many-body perturbation theory. Modern improvements of the description of exchange and correlation are reviewed. In this work, we specifically focus on the Qb@ll code, which we have mainly used for these types of simulations over the last years, and we conclude by pointing to further progress needed going forward. Graphical abstract: [Figure not available: see fulltext.].
The effect of crystallography on transgranular chloride-induced stress corrosion cracking (TGCISCC) of arc welded 304L austenitic stainless steel is studied on >300 grains along crack paths. Schmid and Taylor factor mismatches across grain boundaries (GBs) reveal that cracks propagate either from a hard to soft grain, which can be explained merely by mechanical arguments, or soft to hard grain. In the latter case, finite element analysis reveals that TGCISCC will arrest at GBs without sufficient mechanical stress, favorable crystallographic orientations, or crack tip corrosion. GB type does not play a significant role in determining TGCISCC cracking behavior nor susceptibility. TGCISCC crack behaviors at GBs are discussed in the context of the competition between mechanical, crystallographic, and corrosion factors.
Shuttling ions at high speed and with low motional excitation is essential for realizing fast and high-fidelity algorithms in many trapped-ion-based quantum computing architectures. Achieving such performance is challenging due to the sensitivity of an ion to electric fields and the unknown and imperfect environmental and control variables that create them. Here we implement a closed-loop optimization of the voltage waveforms that control the trajectory and axial frequency of an ion during transport in order to minimize the final motional excitation. The resulting waveforms realize fast round-trip transport of a trapped ion across multiple electrodes at speeds of 0.5 electrodes per microsecond (35 m·s−1 for a one-way transport of 210 μm in 6 μs) with a maximum of 0.36 ± 0.08 mean quanta gain. This sub-quanta gain is independent of the phase of the secular motion at the distal location, obviating the need for an electric field impulse or time delay to eliminate the coherent motion.
Migration of seismic events to deeper depths along basement faults over time has been observed in the wastewater injection sites, which can be correlated spatially and temporally to the propagation or retardation of pressure fronts and corresponding poroelastic response to given operation history. The seismicity rate model has been suggested as a physical indicator for the potential of earthquake nucleation along faults by quantifying poroelastic response to multiple well operations. Our field-scale model indicates that migrating patterns of 2015–2018 seismicity observed near Venus, TX are likely attributed to spatio-temporal evolution of Coulomb stressing rate constrained by the fault permeability. Even after reducing injection volumes since 2015, pore pressure continues to diffuse and steady transfer of elastic energy to the deep fault zone increases stressing rate consistently that can induce more frequent earthquakes at large distance scales. Sensitivity tests with variation in fault permeability show that (1) slow diffusion along a low-permeability fault limits earthquake nucleation near the injection interval or (2) rapid relaxation of pressure buildup within a high-permeability fault, caused by reducing injection volumes, may mitigate the seismic potential promptly.
Soil organic carbon (SOC) changes under future climate warming are difficult to quantify in situ. Here we apply an innovative approach combining space-for-time substitution with meta-analysis to SOC measurements in 113,013 soil profiles across the globe to estimate the effect of future climate warming on steady-state SOC stocks. We find that SOC stock will reduce by 6.0 ± 1.6% (mean±95% confidence interval), 4.8 ± 2.3% and 1.3 ± 4.0% at 0–0.3, 0.3–1 and 1–2 m soil depths, respectively, under 1 °C air warming, with additional 4.2%, 2.2% and 1.4% losses per every additional 1 °C warming, respectively. The largest proportional SOC losses occur in boreal forests. Existing SOC level is the predominant determinant of the spatial variability of SOC changes with higher percentage losses in SOC-rich soils. Our work demonstrates that warming induces more proportional SOC losses in topsoil than in subsoil, particularly from high-latitudinal SOC-rich systems.
Heavy metals released from kerogen to produced water during oil/gas extraction have caused major enviromental concerns. To curtail water usage and production in an operation and to use the same process for carbon sequestration, supercritical CO2 (scCO2) has been suggested as a fracking fluid or an oil/gas recovery agent. It has been shown previously that injection of scCO2 into a reservoir may cause several chemical and physical changes to the reservoir properties including pore surface wettability, gas sorption capacity, and transport properties. Using molecular dynamics simulations, we here demonstrate that injection of scCO2 might lead to desorption of physically adsorbed metals from kerogen structures. This process on one hand may impact the quality of produced water. On the other hand, it may enhance metal recovery if this process is used for in-situ extraction of critical metals from shale or other organic carbon-rich formations such as coal.
Hydrogen produced through low-temperature water electrolysis using anion exchange membranes (AEM) combines the benefits of liquid-electrolyte alkaline electrolysis and solid-polymer proton exchange membrane electrolysis. The anion conductive ionomers in the oxygen-producing anode and hydrogen-producing cathode are a critical part of the three-dimensional electrodes. The ionomer in the hydrogen-producing cathode facilitates hydroxide ion conduction from the cathode catalyst to the anode catalyst, and water transport from the anode to the cathode catalyst through the AEM. This ionomer also binds the catalyst particles to the porous transport layer. In this study, the cathode durability was improved by use of a self-adhesive cathode ionomer to chemically bond the cathode catalyst particles to the porous transport layer. It was found that the cathode ionomers with high ion exchange capacity (IEC) were more effective than low IEC ionomers because of the need to transport water to the cathode catalyst and transport hydroxide away from the cathode. The cathode durability was improved by using ionomers which were soluble in the spray-coated cathode ink. Optimization of the catalyst and ionomer content within the cathode led to electrolysis cells which were both mechanically durable and operated at low voltage.
The interaction of an intense laser with a solid foil target can drive ∼ TV/m electric fields, accelerating ions to MeV energies. In this study, we experimentally observe that structured targets can dramatically enhance proton acceleration in the target normal sheath acceleration regime. At the Texas Petawatt Laser facility, we compared proton acceleration from a 1μm flat Ag foil, to a fixed microtube structure 3D printed on the front side of the same foil type. A pulse length (140–450 fs) and intensity ((4–10) × 10 20 W/cm2) study found an optimum laser configuration (140 fs, 4 × 10 20 W/cm2), in which microtube targets increase the proton cutoff energy by 50% and the yield of highly energetic protons (> 10 MeV) by a factor of 8×. When the laser intensity reaches 10 21 W/cm2, the prepulse shutters the microtubes with an overcritical plasma, damping their performance. 2D particle-in-cell simulations are performed, with and without the preplasma profile imported, to better understand the coupling of laser energy to the microtube targets. The simulations are in qualitative agreement with the experimental results, and show that the prepulse is necessary to account for when the laser intensity is sufficiently high.
Zandanel, Amber; Sauer, Kirsten B.; Rock, Marlena; Caporuscio, Florie A.; Telfeyan, Katherine; Matteo, Edward N.
Direct disposal of dual-purpose canisters (DPC) has been proposed to streamline the disposal of spent nuclear fuel. However, there are scenarios where direct disposal of DPCs may result in temperatures in excess of the specified upper temperature limits for some engineered barrier system (EBS) materials, which may cause alteration within EBS materials dependent on local conditions such as host rock composition, chemistry of the saturating groundwaters, and interactions between barrier materials themselves. Here we report the results of hydrothermal experiments reacting EBS materials—bentonite buffer and steel—with an analogue crystalline host rock and groundwater at 250 °C. Experiment series explored the effect of reaction time on the final products and the effects of the mineral and fluid reactants on different steel types. Post-mortem X-ray diffraction, electron microprobe, and scanning electron microscopy analyses showed characteristic alteration of both bentonite and steel, including the formation of secondary zeolite and calcium silicate hydrate minerals within the bentonite matrix and the formation of iron-bearing clays and metal oxides at the steel surfaces. Swelling clays in the bentonite matrix were not quantitatively altered to non-swelling clay species by the hydrothermal conditions. The combined results of the solution chemistry over time and post-mortem mineralogy suggest that EBS alteration is more sensitive to initial groundwater chemistry than the presence of host rock, where limited potassium concentration in the solution prohibits conversion of the smectite minerals in the bentonite matrix to non-swelling clay species.
Hydrogen is an attractive option for energy storage because it can be produced from renewable sources and produces environmentally benign byproducts. However, the volumetric energy density of molecular hydrogen at ambient conditions is low compared to other storage methods like batteries, so it must be compressed to attain a viable energy density for applications such as transportation. Nanoporous materials have attracted significant interest for gas storage because they can attain high storage density at lower pressure than conventional compression. In this work, we examine how to improve the cryogenic hydrogen storage capacity of a series of porous aromatic frameworks (PAFs) by controlling the pore size and increasing the surface area by adding functional groups. We also explore tradeoffs in gravimetric and volumetric measures of the hydrogen storage capacity and the effects of temperature swings using grand canonical Monte Carlo simulations. We also consider the effects of adding functional groups to the metal–organic framework NU-1000 to improve its hydrogen storage capacity. We find that highly flexible alkane chains do not improve the hydrogen storage capacity in NU-1000 because they do not extend into the pores; however, rigid chains containing alkyne groups do increase the surface area and hydrogen storage capacity. Finally, we demonstrate that the deliverable capacity of hydrogen in NU-1000 can be increased from 40.0 to 45.3 g/L (at storage conditions of 100 bar and 77 K and desorption conditions of 5 bar and 160 K) by adding long, rigid alkyne chains into the pores.
Understanding the adsorption of isolated metal cations from water on to mineral surfaces is critical for toxic waste retention and cleanup in the environment. Heterogeneous nucleation of metal oxyhydroxides and other minerals on material surfaces is key to crystal growth and dissolution. The link connecting these two areas, namely cation dimerization and polymerization, is far less understood. In this work we apply ab initio molecular dynamics calculations to examine the coordination structure of hydroxide-bridged Cu(II) dimers, and the free energy changes associated with Cu(II) dimerization on silica surfaces. The dimer dissociation pathway involves sequential breaking of two Cu2+-OH− bonds, yielding three local minima in the free energy profiles associated with 0-2 OH− bridges between the metal cations, and requires the design of a (to our knowledge) novel reaction coordinate for the simulations. Cu(II) adsorbed on silica surfaces are found to exhibit stronger tendency towards dimerization than when residing in water. Cluster-plus-implicit-solvent methods yield incorrect trends if OH− hydration is not correctly depicted. The predicted free energy landscapes are consistent with fast equilibrium times (seconds) among adsorbed structures, and favor Cu2+ dimer formation on silica surfaces over monomer adsorption.
Although gold remains a preferred surface finish for components used in high-reliability electronics, rapid developments in this area have left a gap in the fundamental understanding of solder joint gold (Au) embrittlement. Furthermore, as electronic designs scale down in size, the effect of Au content is not well understood on increasingly smaller solder interconnections. As a result, previous findings may have limited applicability. The current study focused on addressing these gaps by investigating the interfacial microstructure that evolves in 63Sn-37Pb solder joints as a function of Au layer thickness. Those findings were correlated to the mechanical performance of the solder joints. Increasing the initial Au concentration decreased the mechanical strength of a joint, but only to a limited degree. Kirkendall voids were the primary contributor to low-strength joints, while brittle fracture within the intermetallic compounds (IMC) layers is less of a factor. The Au embrittlement mechanism appears to be self-limiting, but only once mechanical integrity is degraded. Sufficient void evolution prevents continued diffusion from the remaining Au.
Rock, concrete, and other engineered materials are often composed of several minerals that change volumetrically in response to variations in the moisture content of the local environment. Such differential shrinkage is caused by varying shrinkage rates between mineral compositions during dehydration. Using both 3D X-ray imaging of geo-architected samples and peridynamic (PD) numerical simulations, we show that the spatial distribution of the clay affects the crack network geometry with distributed clay particles yielding the most complex crack networks and percent damage (99.56%), along with a 60% reduction in material strength. We also demonstrate that crack formation, growth, coalescence, and distribution during dehydration, are controlled by the differential shrinkage rates between a highly shrinkable clay and a homogeneous mortar matrix. Sensitivity tests performed with the PD models show a clay shrinkage parameter of 0.4 yields considerable damage, and reductions in the parameter can result in a significant reduction in fracturing and an increase in material strength. Additionally, isolated clay inclusions induced localized fracturing predominantly due to debonding between the clay and matrix. These insights indicate differential shrinkage is a source of potential failure in natural and engineered barriers used to sequester anthropogenic waste.
This report provides recommendations to improve the assessment method of the Federal Radiological Monitoring and Assessment Center (FRMAC) for the ingestion of crops contaminated with radionuclides. The current FRMAC method of calculating investigation levels (ILs) and crop derived response levels (DRLs) is detailed. Recommended modifications to these calculations are presented based on the following aspects: handling radionuclide mixtures, no immediate equilibrium, washing of contaminated crops, and updated dietary intake rates.
The Waste Isolation Pilot Plant (WIPP) is an underground facility designed to safely dispose of radioactive waste. The WIPP uses many heavy vehicles to transport materials and equipment underground. Most of these vehicles are powered by traditional internal combustion engines (ICE) with diesel fuel. Recently, electric vehicles (EVs) powered with batteries have been used at the WIPP. EVs have very low operational and maintenance costs, not considering battery replacements, and they have zero emissions during operation. This absence of emissions makes them ideal for underground facilities with limited ventilation. Even if a facility has robust ventilation normally, ventilation systems can break down leading to restrictions in ICE powered operations. Figure 1 shows a rendering of the WIPP.
The FY22 Proxy App Suite Release milestone includes the following activities: Curate a collection of proxy applications that represents the breadth of ECP applications, including application domains, programming models, supporting libraries, numerical methods, etc. Identify gaps in coverage and work with application teams to commission or develop proxies to cover gaps. From within this collection, designate the ”ECP Proxy Application Suite” of 10–15 proxies that balance breadth of coverage with ease of use and quality of implementation. Also designate approximately 6–10 proxies to form the “ECP Machine Learning Proxy Suite”. The ML suite will represent algorithms, use cases, and programming methods typically used by ECP science workloads to incorporate machine learning into their workflows.
The Strategic Petroleum Reserve (SPR) is the world's largest supply of emergency crude oil. The reserve consists of four sites in Louisiana and Texas. Each site stores crude in deep, underground salt caverns. It is the mission of the SPR's Enhanced Monitoring Program to examine all available data to inform our understanding of each site. This report discusses the monitoring data, processes, and results for each of the four sites for fiscal year 2022.
Picuris Pueblo is a small tribal community in Northern New Mexico consisting of about 306 members and 86 homes. Picuris Pueblo has made advances with renewable energy implementation, including the installation of a 1 megawatt photovoltaic (PV) array. This array has provided the tribe with economic and other benefits that contribute toward the tribe's goal of tribal sovereignty. The tribe is seeking to implement more PV generation as well as battery energy storage systems. Picuris Pueblo is considering different implementation methods, including the formation of a microgrid system. This report studies the potential implementation of a PV and battery storage microgrid system and the associated benefits and challenges. The benefits of a microgrid system include cost savings, increased resiliency, and increased tribal sovereignty and align with the tribe's goals of becoming energy independent and lowering the cost of electricity.
The leading edge erosion of wind turbine blades is a common issue that can have a range of implications for the operation and maintenance of the turbine. A variety of methods have attempted to determine the severity of erosion damage, applied in different academic, testing and in-situ settings. This paper describes the current state of the art in categorization, and the individual drivers in assessment. From this foundation, the IEA Wind Task 46 WP3 group collated key considerations from the process of categorizing erosion damage and a proposed erosion classification system was put forward. Trial assessments were performed using the initial system, which led to adjustments to the original proposition. The refined system defines discrete severity levels that concern the wind turbine blade: (1) Visual Condition (concerning blades with/without leading edge protection); (2) Mass Loss; (3) Aerodynamic Performance; and (4) Structural Integrity. The classification system presented is not intended to be a fixed entity. The Task 46 group has already identified specific challenges and opportunities that are applicable to individual use and the overall wind energy industry. The intention is for the system to evolve as improvements are identified, technology improves, and work progresses through other Task 46 activities. Several considerations and recommendations are discussed that could be applicable for future implementation of the system.
Mobile sources is a term most commonly used to describe radioactive sources that are used in applications requiring frequent transportation. Such radioactive sources are in common use world-wide where typical applications include radiographic non-destructive evaluation (NDE) and oil and gas well logging, among others requiring lesser amounts of radioactivity. This report provides a general overview of mobile sources used for well logging and industrial radiography applications including radionuclides used, equipment, and alternative technologies. Information presented here has been extracted from a larger study on common mobile radiation sources and their use.
This report updates the Regional Disruption Economic Impact Model (RDEIM) GDP-based model described in Bixler et al. (2020) used in the MACCS accident consequence analysis code. MACCS is the U.S. Nuclear Regulatory Commission (NRC) used to perform probabilistic health and economic consequence assessments for atmospheric releases of radionuclides. It is also used by international organizations, both reactor owners and regulators. It is intended and most commonly used for hypothetical accidents that could potentially occur in the future rather than to evaluate past accidents or to provide emergency response during an ongoing accident. It is designed to support probabilistic risk and consequence analyses and is used by the NRC, U.S. nuclear licensees, the Department of Energy, and international vendors, licensees, and regulators. The update of the RDEIM model in version 4.2 expresses the national recovery calculation explicitly, rather than implicitly as in the previous version. The calculation of the total national GDP losses remains unchanged. However, anticipated gains from recovery are now allocated across all the GDP loss types – direct, indirect, and induced – whereas in version 4.1, all recovery gains were accounted for in the indirect loss type. To achieve this, we’ve introduced new methodology to streamline and simplify the calculation of all types of losses and recovery. In addition, RDEIM includes other kinds of losses, including tangible wealth. This includes loss of tangible assets (e.g., depreciation) and accident expenditures (e.g., decontamination). This document describes the updated RDEIM economic model and provides examples of loss and recovery calculation, results analysis, and presentation. Changes to the tangible cost calculation and accident expenditures are described in section 2.2. The updates to the RDEIM input-output (I-O) model are not expected to affect the final benchmark results Bixler et al. (2020), as the RDEIM calculation for the total national GDP losses remains unchanged. The reader is referred to the MACCS revision history for other cost modelling changes since version 4.0 that may affect the benchmark. RDEIM has its roots in a code developed by Sandia National Laboratories for the Department of Homeland Security to estimate short-term losses from natural and manmade accidents, called the Regional Economic Accounting analysis tool (REAcct). This model was adapted and modified for MACCS. It is based on I-O theory, which is widely used in economic modeling. It accounts for direct losses to a disrupted region affected by an accident, indirect losses to the national economy due to disruption of the supply chain, and induced losses from reduced spending by displaced workers. RDEIM differs from REAcct in in its treatment and estimation of indirect loss multipliers, elimination of double-counting associated with inter-industry trade in the affected area, and that it is intended to be used for extended periods that can occur from a major nuclear reactor accident, such as the one that occurred at the Fukushima Daiichi site in Japan. Most input-output models do not account for economic adaptation and recovery, and in this regard RDEIM differs from its parent, REAcct, because it allows for a user-definable national recovery period. Implementation of a recovery period was one of several recommendations made by an independent peer review panel to ensure that RDEIM is state-of-practice. For this and several other reasons, RDEIM differs from REAcct.
In support of the DOE Office of Science, Sandia National Labs is one of nine national laboratories which oversees the Atmospheric Radiation Measurement (ARM) Program. The Sandia ARM team has an obligation to fulfill its mission to provide the nation with data to improve the understanding of climate processes and the representation of those processes in climate models. Sandia’s ARM team’s ability to provide detailed and accurate descriptions of the Earth’s atmosphere in diverse climate regimes assists the DOE in development of sustainable solutions to the nation’s energy and environmental challenges. Sandia Labs manages ARM atmospheric facilities along the North Slope of Alaska (NSA) at Utqiagvik as well as the Tethered Balloon System (TBS). Activities conducted at NSA and with the TBS aide in data collection for the ARM data archive. An overview of these activities for the month of December follows.
This white paper describes the program vision, objectives, and R&D targets in 5 to 10 years for the Department of Energy (DOE) Office of Electricity (OE) Microgrid R&D Program. The vision is to facilitate the nation’s transitions to (1) a more resilient and reliable, (2) more decarbonized electricity infrastructure, in which (3) microgrids have a reduced cost to implement. This strategy is developed in the context that the United States’ electricity delivery system is becoming more distributed in nature. The electricity generation capacity in 10 years may be 30-50% distributed energy assets.
As part of the project “Designing Resilient Communities (DRC): A Consequence-Based Approach for Grid Investment,” funded by the United States (US) Department of Energy’s (DOE) Grid Modernization Laboratory Consortium (GMLC), Sandia National Laboratories (Sandia) is partnering with a variety of government, industry, and university participants to develop and test a framework for community resilience planning focused on modernization of the electric grid. This report provides a summary of the section of the project focused on hardware demonstration of “resilience nodes” concept.
The ECP Proxy Application Project has an annual milestone to assess the state of ECP proxy applications. Our FY21 milestone (ADCD-504-11) proposed to: Assess the performance and fidelity of proxy applications, including those in the ECP Proxy App Suite, relative to the ECP Application workload on heterogeneous platforms. Use proxy applications and selected ECP applications to assess the utility of critical elements of the Exascale toolchain, especially tools used to collect performance data. Identify gaps in coverage and/or common situations in which proxies may fail to adequately represent ECP applications.
Zyvex Labs has created several p-n junction devices with a variety of gaps between the boron and phosphorus electrodes, from 0-7.7 nm, which are now being measured. We have developed a different contacting process based on palladium disilicide rather than aluminium to improve the reliability of the device contacts. Preliminary measurements indicate that these new contacts are successfully contacting the buried dopant layers, which are intact after the overgrowth process. Modelling of the p-n junction properties has made good progress, with the model matching previous published data, and modelling of n-p-n junction devices has begun. This now awaits experimental validation.
In July 2022, Sandia National Laboratories hosted a workshop in Washington, D.C., bringing together representatives from eleven Federal Government agencies, responsible for public health, environmental security, and biodefense, as well as six Department of Energy (DOE) National Laboratories, to discuss how to work together to address climate-driven zoonotic disease risk. The primary goal of this workshop was to provide a forum for Federal and DOE National Lab attendees to share their missions, programs, and capabilities relevant to zoonotic disease emergence, to discuss how to best leverage these collective resources, identify key gaps, and to determine an effective path forward.
The Arroyo Seco Improvement Program (ASIP) is intended to provide active channel improvements and stream zone management activities that will reduce current flood and erosion risk while providing additional and improved habitat for critical species that may use the Arroyo Seco at the Sandia National Laboratories, California (SNL/CA). SNL/CA facility is operated by the National Technology and Engineering Solutions of Sandia, LLC (NTESS) under a contract with the U.S. Department of Energy/National Nuclear Security Administration (DOE/NNSA). The DOE/ NNSA’s Sandia Field Office (SFO) oversees the operations of the site.
Unmanned aircraft systems (UAS/drones) are rapidly evolving and are considered an emerging threat by nuclear facilities throughout the world. Due to the wide range of UAS capabilities, members of the workforce and security/response force personnel need to be prepared for a variety of drone incursion situations. Tabletop exercises are helpful, but actual live exercises are often needed to evaluate the quick chain of events that might ensue during a real drone fly-in and the essential kinds of information that will help identify the type of drone and pilot. Even with drone detection equipment, the type of UAS used for incursion drills can have a major impact on detection altitude and finding the UAS in the sky. Using a variety of UAS, the U.S. National Nuclear Security Administration (NNSA) Office of International Nuclear Security (INS) would like to offer partners the capability of adding actual UAS into workforce and response exercises to improve overall UAS awareness as well as the procedures that capture critical steps in dealing with intruding drones.
We present Q Framework: a verification framework used at Sandia National Laboratories. Q is a collection of tools used to verify safety and correctness properties of high-consequence embedded systems and captures the structure and compositionality of system specifications written with state machines in order to prove system-level properties about their implementations. Q consists of two main workflows: 1) compilation of temporal properties and state machine models (such as those made with Stateflow) into SMV models and 2) generation of ACSL specifications for the C code implementation of the state machine models. These together prove a refinement relation between the state machine model and its C code implementation, with proofs of properties checked by NuSMV (for SMV models) and Frama-C (for ACSL specifications).
This report represents completion of milestone deliverable M2SF-23SN010309082 Annual Status Update for OWL due on November 30, 2022. It provides the status of fiscal year 2022 (FY2022) updates for the Online Waste Library (OWL).
Commercial vendors, trying to tap into the physical protection of critical infrastructure, are offering nuclear facilities the opportunity to borrow detection counter-unmanned aircraft systems (CUAS) equipment to survey the airspace over and around the facility. However, using one vendor or method of detection (e.g., radio frequency [RF], radar, acoustic, visual) will not necessarily provide a complete airspace profile since no single method can detect all UAS threats. Using several detection technologies, the unmanned aircraft systems (UAS) Team, who supports the U.S. National Nuclear Security Administration (NNSA) Office of International Nuclear Security (INS), would like to offer partners a comprehensive airspace profile of the types and frequency of UAS that fly within and around critical infrastructure. Improved UAS awareness will aid in the risk assessment process.
Metal-assisted chemical etching (MACE) is a flexible technique for texturing the surface of semiconductors. In this work, we study the spatial variation of the etch profile, the effect of angular orientation relative to the crystallographic planes, and the effect of doping type. We employ gold in direct contact with germanium as the metal catalyst, and dilute hydrogen peroxide solution as the chemical etchant. With this catalyst-etchant combination, we observe inverse-MACE, where the area directly under gold is not etched, but the neighboring, exposed germanium experiences enhanced etching. This enhancement in etching decays exponentially with the lateral distance from the gold structure. An empirical formula for the gold-enhanced etching depth as a function of lateral distance from the edge of the gold film is extracted from the experimentally measured etch profiles. The lateral range of enhanced etching is approximately 10–20 µm and is independent of etchant concentration. At length scales beyond a few microns, the etching enhancement is independent of the orientation with respect to the germanium crystallographic planes. The etch rate as a function of etchant concentration follows a power law with exponent smaller than 1. The observed etch rates and profiles are independent of whether the germanium substrate is n-type, p-type, or nearly intrinsic.
As machine learning (ML) models are deployed into an ever-diversifying set of application spaces, ranging from self-driving cars to cybersecurity to climate modeling, the need to carefully evaluate model credibility becomes increasingly important. Uncertainty quantification (UQ) provides important information about the ability of a learned model to make sound predictions, often with respect to individual test cases. However, most UQ methods for ML are themselves data-driven and therefore susceptible to the same knowledge gaps as the models themselves. Specifically, UQ helps to identify points near decision boundaries where the models fit the data poorly, yet predictions can score as certain for points that are under-represented by the training data and thus out-of-distribution (OOD). One method for evaluating the quality of both ML models and their associated uncertainty estimates is out-of-distribution detection (OODD). We combine OODD with UQ to provide insights into the reliability of the individual predictions made by an ML model.
Recently, the study of topological structures in photonics has garnered significant interest, as these systems can realize robust, nonreciprocal chiral edge states and cavity-like confined states that have applications in both linear and nonlinear devices. However, current band theoretic approaches to understanding topology in photonic systems yield fundamental limitations on the classes of structures that can be studied. Here, we develop a theoretical framework for assessing a photonic structure’s topology directly from its effective Hamiltonian and position operators, as expressed in real space, and without the need to calculate the system’s Bloch eigenstates or band structure. Using this framework, we show that nontrivial topology, and associated boundary-localized chiral resonances, can manifest in photonic crystals with broken time-reversal symmetry that lack a complete band gap, a result that may have implications for new topological laser designs. Finally, we use our operator-based framework to develop a novel class of invariants for topology stemming from a system’s crystalline symmetries, which allows for the prediction of robust localized states for creating waveguides and cavities.
The dynamics of the gold–silicon eutectic reaction in limited dimensions were studied using in situ transmission electron microscopy and scanning transmission electron microscopy heating experiments. The phase transformation, viewed in both plan-view and cross-section of the film, occurs through a complex combination of dislocation and grain boundary motion and diffusion of silicon along gold grain boundaries, which results in a dramatic change in the microstructure of the film. The conversion observed in cross-section shows that the eutectic mixture forms at the Au–Si interface and proceeds into the Au film at a discontinuous growth rate. This complex process can lead to a variety of microstructures depending on sample geometry, heating temperature, and the ratio of gold to silicon which was found to have the largest impact on the eutectic microstructure. The eutectic morphology varied from dendrites to hollow rectangular structures to Au–Si eutectic agglomerates with increasing silicon to gold ratio. Graphical abstract: [Figure not available: see fulltext.]
Dr. Fitzgerald, a postdoc at Sandia National Laboratories, works in a materials of mechanics group characterizing material properties of ductile materials. Her presentation focuses specifically on increasing throughput of coefficient of thermal expansion (CTE) measurements with the use of optical strain measurements, called digital image correlation (DIC). Currently, the coefficient of thermal expansion is found through a time intensive process called dilatometry. There are multiple types of dilatometers. One type, a double push rod mechanical dilatometer, uses and LVDT to measure the expansion of a specimen in one direction. It uses a reference material with known properties to determine the CTE of the specimen in question. Testing about 500 samples using the double push rod mechanical dilatometer would take about 2 years if testing Monday through Friday, because the reference material needs to be at a constant temperature and heating must done slowly to ensure no thermal gradients across the rod. A second type, scissors type dilatometer, pinches a sample using a “scissor-like” appendage that also uses a LVDT to measure thermal expansion as the sample is heated. Finally, laser dilatometry, was created to provide a non-contact means to measure thermal expansion. This process greatly reduces the time required to setup a measurement but is still only able to measure one sample at a time. The time required to test 500 samples gets reduced to 3.5 weeks. Additionally, to measure expansion in different directions, multiple lasers must be used. Dr. Fitzgerald solved this conundrum by using an optical measurement technique called digital image correlation to create strain maps in multiple orientations as well as measuring multiple samples at once. Using this technique, Dr. Fitzgerald can test 500 samples, conservatively, in 2 days.
We have demonstrated focused ion implantation for fabrication of single atom devices and nanofabrication. This is a viable solution for prototyping - fast and easy! There is on-going work in diamond, SiN, SiC, hBN, GaN, AlGan, etc. A new liquid metal alloy ion source development is on-going. There is a pathway towards deterministic defect centers in wide bandgap materials using FIB implantation.
On July 11, 2022, Sandia National Laboratories in California (SNL/CA) submitted a Response to Regional Water Quality Control Board Comments on Soil Sampling Results for Closure of a Portion of SWMU #16 in response to the February 16,2022 San Francisco Bay Regional Water Quality Control Board’s (SFRWQCB) letter requesting supporting information for the recommended closure of 7,700 linear feet of abandoned sewer lines. On August 18, 2022, SFRWQCB further requested a Sampling and Analysis Plan (SAP) for additional “step-out” sampling to delineate the potential presence of benzidine near borehole BH-056, which is located near the former sewer line. SNL/CA is in the process of contracting Weiss Associates (Weiss) to perform and oversee the boring, sampling, analysis, and report development to determine the potential presence and extent of benzidine. This document outlines the work that is anticipated, including the development of the SAP, to complete the investigation and submit a final report to the SFRWQCB. The work proposed by Weiss provides an estimated schedule for completing the investigation and developing the addendum Part II SAP for the project. In addition, Weiss provided a preliminary estimate of the sample locations (see Attachment A) which serve as addendum Part I of the SAP requested by the SFRWQCB. The contractor will submit the addendum Part II SAP, to satisfy the SFRWQCB requirement, before proceeding with any work.
This report describes research and development (R&D) activities conducted during Fiscal Year 2022 (FY22) specifically related to the Engineered Barrier System (EBS) R&D Work Package in the Spent Fuel Waste Science and Technology (SFWST) Campaign supported by the United States (U.S.) Department of Energy (DOE). The R&D activities focus on understanding EBS component evolution and interactions within the EBS, as well as interactions between the host media and the EBS. The R&D team represented in this report consists of individuals from Sandia National Laboratories, Lawrence Berkeley National Laboratory (LBNL), Los Alamos National Laboratory (LANL), and Vanderbilt University. EBS R&D work also leverages international collaborations to ensure that the DOE program is active and abreast of the latest advances in nuclear waste disposal.
Perez, Christopher; Jog, Atharv; Kwon, Heungdong; Gall, Daniel; Asheghi, Mehdi; Kumar, Suhas; Park, Woosung; Goodson, Kenneth E.
High aspect ratio metal nanostructures are commonly found in a broad range of applications such as electronic compute structures and sensing. The self-heating and elevated temperatures in these structures, however, pose a significant bottleneck to both the reliability and clock frequencies of modern electronic devices. Any notable progress in energy efficiency and speed requires fundamental and tunable thermal transport mechanisms in nanostructured metals. In this work, time-domain thermoreflectance is used to expose cross-plane quasi-ballistic transport in epitaxially grown metallic Ir(001) interposed between Al and MgO(001). Thermal conductivities ranges from roughly 65 (96 in-plane) to 119 (122 in-plane) W m−1 K−1 for 25.5–133.0 nm films, respectively. Further, low defects afforded by epitaxial growth are suspected to allow the observation of electron–phonon coupling effects in sub-20 nm metals with traditionally electron-mediated thermal transport. Via combined electro-thermal measurements and phenomenological modeling, the transition is revealed between three modes of cross-plane heat conduction across different thicknesses and an interplay among them: electron dominant, phonon dominant, and electron–phonon energy conversion dominant. The results substantiate unexplored modes of heat transport in nanostructured metals, the insights of which can be used to develop electro-thermal solutions for a host of modern microelectronic devices and sensing structures.
This report represents the 1st shot (in a series of 8) conducted on September 15, 2022. One 10 lb C4 charge (along with ~200g of Potassium Bromide (KBr)) was detonated inside 9920 North Pad Boom Box. Noise sampling was performed at several points on Site 9920 to characterize the noise mitigation provided by the block structure. This data will help inform safe locations for Members of the Workforce (MOWs) to be located during future testing with similar net explosive weights. During the test, all MOW/site visitors were bunkered inside Building 9926/Mobile Firing Control Point (MFCP) to prevent personnel exposure to any hazards associated with the testing
The purpose of this sampling event was to determine if the observation point (inside the MFCP) could be relocated from 74 feet away to 21 feet from ground zero and to determine how much attenuation is provided by the MFCP. The MFCP provides noise attenuation to ensure Members of the Workforce (MOW) exposure to impact noise is below the Occupational Exposure Limit (OEL) of 140 dBC. The MFCP will be used for future tests under similar configurations. Please note that during each test shot, MOW was located inside MFCP that was 74 feet from ground zero and donned hearing protection (e.g., ear plugs with a minimum noise reduction rating of 23).
Elastomeric rubbers serve a vital role as sealing materials in the hydrogen storage and transport infrastructure. With applications including O-rings and hose-liners, these components are exposed to pressurized hydrogen at a range of temperatures, cycling rates, and pressure extremes. Cyclic (de)pressurization is known to degrade these materials through the process of cavitation. This readily visible failure mode occurs as a fracture or rupture of the material and is due to the oversaturated gas localizing to form gas bubbles. Computational modeling in the Hydrogen Materials Compatibility Program (H-Mat), co-led by Sandia National Laboratories and Pacific Northwest National Laboratory, employs multi-scale simulation efforts to build a predictive understanding of hydrogen-induced damage in materials. Modeling efforts within the project aim to provide insight into how to formulate materials that are less sensitive to high-pressure hydrogen-induced failure. In this document, we summarize results from atomistic molecular dynamics simulations, which make predictive assessments of the effects of compositional variations in the commonly used elastomer, ethylene propylene diene monomer (EPDM).
Mishra, Umakant; Yeo, Kyongmin; Adhikari, Kabindra; Riley, William J.; Hoffman, Forrest M.; Hudson, Corey
Accurate representation of environmental controllers of soil organic carbon (SOC) stocks in Earth System Model (ESM) land models could reduce uncertainties in future carbon–climate feedback projections. Using empirical relationships between environmental factors and SOC stocks to evaluate land models can help modelers understand prediction biases beyond what can be achieved with the observed SOC stocks alone. In this study, we used 31 observed environmental factors, field SOC observations (n = 6,213) from the continental United States, and two machine learning approaches (random forest [RF] and generalized additive modeling [GAM]) to (a) select important environmental predictors of SOC stocks, (b) derive empirical relationships between environmental factors and SOC stocks, and (c) use the derived relationships to predict SOC stocks and compare the prediction accuracy of simpler model developed with the machine learning predictions. Out of the 31 environmental factors we investigated, 12 were identified as important predictors of SOC stocks by the RF approach. In contrast, the GAM approach identified six (of those 12) environmental factors as important controllers of SOC stocks: potential evapotranspiration, normalized difference vegetation index, soil drainage condition, precipitation, elevation, and net primary productivity. The GAM approach showed minimal SOC predictive importance of the remaining six environmental factors identified by the RF approach. Our derived empirical relations produced comparable prediction accuracy to the GAM and RF approach using only a subset of environmental factors. The empirical relationships we derived using the GAM approach can serve as important benchmarks to evaluate environmental control representations of SOC stocks in ESMs, which could reduce uncertainty in predicting future carbon–climate feedbacks.
This document is a reference guide to the Xyce™ Parallel Electronic Simulator, and is a companion document to the Xyce™ Users' Guide. The focus of this document is (to the extent possible) exhaustively list device parameters, solver options, parser options, and other usage details of Xyce™. This document is not intended to be a tutorial. Users who are new to circuit simulation are better served by the Xyce™ Users' Guide.
Cyber security has been difficult to quantify from the perspective of defenders. The effort to develop a cyber-attack with some ability, function, or consequence has not been rigorously investigated in Operational Technologies. This specification defines a testing structure that allows conformal and repeatable cyber testing on equipment. The purpose of the ETE is to provide data necessary to analyze and reconstruct cyber-attack timelines, effects, and observables for training and development of Cyber Security Operation Centers. Standardizing the manner in which cyber security on equipment is investigated will allow a greater understanding of the progression of cyber attacks and potential mitigation and detection strategies in a scientifically rigorous fashion.
Grid operating security studies are typically employed to establish operating boundaries, ensuring secure and stable operation for a range of operation under NERC guidelines. However, if these boundaries are severely violated, existing system security margins will be largely unknown, as would be a secure incremental dispatch path to higher security margins while continuing to serve load. As an alternative to the use of complex optimizations over dynamic conditions, this work employs the use of machine learning to identify a sequence of secure state transitions which place the grid in a higher degree of operating security with greater static and dynamic stability margins. Several reinforcement learning solution methods were developed using deep learning neural networks, including Deep Q-learning, Mu-Zero, and the continuous algorithms Proximal Reinforcement Learning, and Advantage Actor Critic Learning. The work is demonstrated on a power grid with three control dimensions but can be scaled in size and dimensionality, which is the subject of ongoing research.
Niobium doped lead-tin-zirconate-titanate ceramics near the PZT 95/5 orthorhombic AFE – rhombohedral FE morphotropic phase boundary Pb1-0.5y(Zr0.865-xTixSn0.135)1-yNbyO3 were prepared according to a 22+1 factorial design with x = 0.05, 0.07 and y = 0.0155, 0.0195. The ceramics were prepared by a traditional solid-state synthesis route and sintered to near full density at 1250°C for 6 h. All compositions were ∼98% dense with no detectable secondary phases by X-ray diffraction. The ceramics exhibited equiaxed grains with intergranular porosity, and grain size was ∼5 µm, decreasing with niobium substitution. Compositions exhibited remnant polarization values of ∼32 µC/cm2, increasing with Ti substitution. Depolarization by the hydrostatic pressure induced FE-AFE phase transition was drastically affected by variation of the Ti and Nb substitution, increasing at a rate of 113 MPa /1% Ti and 21 MPa/1% Nb. Total depolarization output was insensitive to the change in Ti and Nb substitution, ∼32.8 µC/cm2 for the PSZT ceramics. The R3c-R3m and R3m-Pm3m phase transition temperatures on heating ranged from 90 to 105°C and 183 to 191°C, respectively. Ti substitution stabilized the R3c and R3m phases to higher temperatures, while Nb substitution stabilized the Pm3m phase to lower temperatures. Thermal hysteresis of the phase transitions was also observed in the ceramics, with transition temperature on cooling being as much as 10°C lower.
This manual describes the use of the Xyce™ Parallel Electronic Simulator. Xyce™ has been designed as a SPICE-compatible, high-performance analog circuit simulator, and has been written to support the simulation needs of the Sandia National Laboratories electrical designers. This development has focused on improving capability over the current state-of-the-art in the following areas: (1) Capability to solve extremely large circuit problems by supporting large-scale parallel computing platforms (up to thousands of processors). This includes support for most popular parallel and serial computers. (2) A differential-algebraic-equation (DAE) formulation, which better isolates the device model package from solver algorithms. This allows one to develop new types of analysis without requiring the implementation of analysis-specific device models. (3) Device models that are specifically tailored to meet Sandia's needs, including some radiation-aware devices (for Sandia users only). (4) Object-oriented code design and implementation using modern coding practices. Xyce™ is a parallel code in the most general sense of the phrase—a message passing parallel implementation—which allows it to run efficiently a wide range of computing platforms. These include serial, shared-memory and distributed-memory parallel platforms. Attention has been paid to the specific nature of circuit-simulation problems to ensure that optimal parallel eficiency is achieved as the number of processors grows.
Photovoltaic (PV) performance is affected by reversible and irreversible losses. These can typically be mitigated through responsive and proactive operations and maintenance (O&M) activities. However, to generate profit, the cost of O&M must be lower than the value of the recovered electricity. This value depends both on the amount of recovered energy and on the electricity prices, which can vary significantly over time in spot markets. The present work investigates the impact of the electricity price variability on the PV profitability and on the related O&M activities in Italy, Portugal, and Spain. It is found that the PV revenues varied by 1.6 × to 1.8 × within the investigated countries in the last 5 years. Moreover, forecasts predict higher average prices in the current decade compared to the previous one. These will increase the future PV revenues by up to 60% by 2030 compared to their 2015–2020 mean values. These higher revenues will make more funds available for better maintenance and for higher quality components, potentially leading to even higher energy yield and profits. Linearly growing or constant price assumptions cannot fully reproduce these expected price trends. Furthermore, significant price fluctuations can lead to unexpected scenarios and alter the predictions.
This manual describes the installation and use of the Xyce™ XDM Netlist Translator. XDM simplifies the translation of netlists generated by commercial circuit simulator tools into Xyce-compatible netlists. XDM currently supports translation from PSpice, HSPICE, and Spectre netlists into Xyce™ netlists.