Publications

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Poster presentation at Keystone Symposia on BBB penetrating nanobody project.

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This report documents the development of an arc flash hazard model to calculate the incident energy and zone of influence from high energy arcing faults involving aluminum. The NRC has identified the potential for (HEAFs) involving aluminum to increase the damage zone beyond what is currently postulated in fire probabilistic risk assessment (PRA) methodologies. To estimate the hazard from HEAFs involving aluminum an arc flash model was developed. Differences between the initial model and nuclear power plant (NPP) fire PRA scenarios were identified. Modification of the initial model established from existing literature and test data was used to minimize these differences. The developed model was evaluated against NRC datasets to understand the model prediction and relative uncertainties. Finally, a range of fire PRA zone of influences (ZOI) were developed based on the developed model, target fragility estimates and update HEAF PRA methodology. The results were developed to support an NRC LIC-504 evaluation in tandem with other modeling efforts. The report documents the effort and provides a reference for any future advancements in arc flash modeling.

On May 16-20, 2022, federal mission partners (e.g., DOE Consequence Management, CDC, FDA, FBI, DHS) as well as integrated state, local, tribal, and territorial governments took part in Cobalt Magnet 22 (CM22), a large-scale, week-long radiological incident exercise in Austin, Texas, that linked several important national assets (National Search Program, Radiological Assistance Program, and Consequence Management [CM] personnel) into a single response effort. The exercise had nine (9) overarching Objectives and an additional 162 associated Critical Tasks for all the participating organizations. In total, 13 National Core Capabilities spanning 5 Mission Areas were represented in the final exercise. This exercise enabled a full range of capabilities to be fielded together and examine the operational connection between major assets, discover any resource shortages associated with conducting multiple mission areas simultaneously or in close succession, and identify any challenges related to leadership. This report summarizes nearly 100 successes and observations provided from players and controllers supporting the LA Division, Fly Away Laboratory (FAL) and Gamma Spectroscopist operations. The observations were categorized to align with the FRMAC programmatic functional areas to consider for future improvements: Logistics, CBRN Responder, Laboratory Analysis, Sampling and Monitoring, Health and Safety, Gamma Spectroscopist Operations, Fly Away Laboratory, and the FRMAC Interdivision Interoperability Group (FIIG).

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A natural clinoptilolite sample near the Nevada National Security Site was obtained to study adsorption and retardation on gas transport. Of interest is understanding the competition for adsorption sites that may reduce tracer gas adsorption relative to single-component measurements, which may be affected by the multi-scale pore structure of clinoptilolite. Clinoptilolite has three distinct domains of pore size distributions ranging from nanometers to micrometers: micropores with 0.4–0.7 nm diameters, measured on powders by CO2 adsorption at 273 K, representing the zeolite cages; mesopores with 4–200 nm diameters, observed using liquid nitrogen adsorption at 77 K; and macropores with 300–1000 nm diameters, measured by mercury injection on rock chips (~ 100 mesh), likely representing the microfractures. These pore size distributions are consistent with X-ray computed tomography (CT) and focused ion beam scanning electron microscope (FIB-SEM) images, which are used to construct the three-dimensional (3D) pore network to be used in future gas transport modeling. To quantify tracer gas adsorption in this multi-scale pore structure and multicomponent gas species environment, natural zeolite samples initially in equilibrium in air were exposed to a mixture of tracer gases. As the tracer gases diffuse and adsorb in the sample, the remaining tracer gases outside the sample fractionate. Using a quadrupole mass spectrometer to quantify this fractionation, the degree of adsorption of tracer gases in the multicomponent gas environment and multi-scale pore structure is assessed. The major finding is that Kr reaches equilibrium much faster than Xe in the presence of ambient air, which leads to more Kr uptake than Xe over limited exposure periods. When the clinoptilolite chips were exposed to humid air, the adsorption capability decreases significantly for both Xe and Kr with relative humidity (RH) as low as 3%. Both Xe and Kr reaches equilibrium faster at higher RH. The different, unexpected, adsorption behavior for Xe and Kr is due to their kinetic diameters similar to the micropores in clinoptilolite which makes it harder for Xe to access compared to Kr.

We evaluate neural radiance fields (NeRFs) as a method for reconstructing 3D volumetric scenes from low Earth orbit satellite imagery. We leverage commercial satellite data to reconstruct a scene using existing software tools. In doing so, we identify difficulties in these mapping datasets for NeRF generation. We propose potential applications in geospatial intelligence for context and improved image interpretation.

There are several U.S. government-sponsored programs with significant experience engaging with foreign government and industry partners to support capacity-building in export controls. This work seeks to answer the question: How can the outreach experience of the U.S. government-sponsored export control capacity-building programs (ECCBP) inform best practices for engaging with advanced reactor vendors in the domain of international nuclear safeguards? To answer this question, we interviewed export control subject matter experts with experience working for the U.S. ECCBPs – the Bureau of Industry and Security (BIS), the Export Control and Related Border Security (EXBS) program, and the International Nonproliferation Export Control Program (INECP) – and developed a set of recommendations for industry engagement based on the collective experience of interviewees.

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Earth’s environment can be considered especially harsh due to the cyclic exposure of heat, moisture, oxygen, and ultraviolet (UV) and visible light. Polymer-derived materials subjected to these conditions over time often exhibit symptoms of degradation and deterioration, ultimately leading to accelerated material failure. To combat this, chemical additives known as antioxidants are often used to delay the onset of weathering and oxidative degradation. Phenol-derived antioxidants have been used for decades due to their excellent performance and stability; unfortunately, concerns regarding their toxicity and leaching susceptibility have driven researchers to identify novel solutions to replace phenolic antioxidants. Herein, we report on the antioxidant efficacy of organoborons, which have been known to exhibit antioxidant activity in plants and animals. Four different organoboron molecules were formulated into epoxy materials at various concentrations and subsequently cured into thermoset composites. Their antioxidant performance was subsequently analyzed via thermal, colorimetric, and spectroscopic techniques. Generally, thermal degradation and oxidation studies proved inconclusive and ambiguous. However, aging studies performed under thermal and UV-intensive conditions showed moderate to extreme color changes, suggesting poor antioxidant performance of all organoboron additives. Infrared spectroscopic analysis of the UV aged samples showed evidence of severe material oxidation, while the thermally aged samples showed only slight material oxidation. Solvent extraction experiments showed that even moderately high organoboron concentrations show negligible leaching susceptibility, confirming previously reported results. This finding may have benefits in applications where additive leaching may cause degradation to sensitive materials, such as microelectronics and other materials science related areas.

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Criticality Control Overpack (CCO) containers are being considered for the disposal of defense-related nuclear waste at the Waste Isolation Pilot Plant (WIPP). At WIPP, these containers would be placed in underground disposal rooms, which will naturally close and compact the containers closer to one another over several centuries. This report details simulations to predict the final container configuration as an input to nuclear criticality assessments. Each container was discretely modeled, including the plywood and stainless steel pipe inside the 55-gallon drum, in order to capture its complex mechanical behavior. Although these high-fidelity simulations were computationally intensive, several different material models were considered in an attempt to reasonably bound the horizontal and vertical compaction percentages. When exceptionally strong materials were used for the containers, the horizontal and vertical closure respectively stabilized at 43:9 % and 93:7 %. At the other extreme, when the containers completely degraded and the clay seams between the salt layers were glued, the horizontal and vertical closure reached respective final values of 48:6 % and 100 %.

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Two novel LiCl·DMSO polymer structures were created by combining dry LiCl salt with dimethyl sulfoxide (DMSO), namely, catena-poly[[chlorido­lithium(I)]-μ-(dimethyl sulfoxide)-κ²O:O-[chlorido­lithium(I)]-di-μ-(dimethyl sulfoxide)-κ⁴O:O], [Li₂Cl₂(C₂H₆OS)₃]n, and catena-poly[lithium(I)-μ-chlorido-μ-(dimethyl sulfoxide)-κ₂O:O], [LiCl(C₂H₆OS)]n. The initial synthesized phase had very small block-shaped crystals (<0.08 mm) with monoclinic symmetry and a 2 LiCl: 3 DMSO ratio. As the solution evaporated, a second phase formed with a plate-shaped crystal morphology. After about 20 minutes, large (>0.20 mm) octa­hedron-shaped crystals formed. The plate crystals and the octa­hedron crystals are the same tetra­gonal structure with a 1 LiCl: 1 DMSO ratio. These structures are reported and compared to other known LiCl·solvent compounds.

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This report documents the development of the Blue Canyon Dome (BCD) testbed, including test site selection, development, instrumentation, and logistical considerations. The BCD testbed was designed for small-scale explosive tests (~5 kg TNT equivalence maximum) for the purpose of comparing diagnostic signals from different types of explosives, the assumption being that different chemical explosives would generate different signatures on geophysical and other monitoring tools. The BCD testbed is located at the Energetic Materials Research and Testing Center near Socorro, New Mexico. Instrumentation includes an electrical resistivity tomography array, geophones, distributed acoustic sensing, gas samplers, distributed temperature sensing, pressure transducers, and high-speed cameras. This SAND report is a reference for BCD testbed development that can be cited in future publications.

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This report identifies current best understanding of federal agencies that are responsible for the safe transportation and handling of nuclear materials during various phases of space launch activities and how they interact. It explores the following questions: (1) Which federal agencies have roles, responsibilities, and statutory authorities related to the launch, orbit, and reentry of nuclear materials and components? (2) What relevant current/recent activities are those federal agencies involved in?

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Pursuant to Section 20.6.2.3104 of the New Mexico Administrative Code (NMAC), the U.S. Department of Energy/National Nuclear Security Administration/Sandia Field Office (DOE/NNSA/SFO) as owner and National Technology & Engineering Solutions of Sandia, LLC (NTESS) as operator are submitting this annual monitoring and discharge report for calendar year (CY) 2022 as required in Discharge Permit 530 (DP-530), issued by the New Mexico Environment Department (NMED) for the Pulsed Power Development Facilities Evaporation Lagoons located at Sandia National Laboratories/New Mexico (SNL/NM) Technical Area IV (TA-IV).

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The V31 containment vessel was procured by the US Army Recovered Chemical Materiel Directorate (RCMD) as a third-generation EDS containment vessel. It is the fifth EDS vessel to be fabricated under Code Case 2564 of the 2019 ASME Boiler and Pressure Vessel Code, which provides rules for the design of impulsively loaded vessels. The explosive rating for the vessel, based on the code case, is twenty-four (24) pounds TNT-equivalent for up to 1092 detonations. This report documents the results of explosive tests that were performed on the vessel at Sandia National Laboratories in Albuquerque, New Mexico to qualify the vessel for field operations use. There were three design basis configurations for qualification testing. Qualification test (1) consisted of a simulated M55 rocket motor and warhead assembly of 24lbs of Composition C-4 (30 lb TNT equivalent). This test was considered the maximum load case, based on modeling and simulation methods performed by Sandia prior to the vessel design phase. Qualification test (2) consisted of a regular, right circular cylinder, unitary charge, located central to the vessel interior of 19.2 lb of Composition C-4 (24 lb TNT equivalent). Qualification test (3) consisted of a 12-pack of regular, right circular cylinders of 2 lb each, distributed evenly inside the vessel (totaling 19.2 lb of C-4, or 24 lb TNT equivalent). All vessel acceptance criteria were met.

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Direct air capture (DAC) of CO₂ is a negative emission technology under development to limit the impacts of climate change. The dilute concentration of CO₂ in the atmosphere (~400 ppm) requires new materials for carbon capture with increased CO₂ selectivity that is not met with current carbon capture materials. Porous liquids (PLs) are an emerging candidate for carbon capture and consists of a combination of solvents and porous hosts that creates a liquid with permanent porosity. The fundamental mechanisms of carbon capture in a PL are relatively unknown. To uncover these mechanisms, PLs were synthesized consisting of three different zeolitic-imidazolate framework (ZIF-8, ZIF-67, or ZIF-69) porous host in a water/glycol/2-methylimidazole solvent. The most stable composition was based on ZIF-8 and exhibited carbon capture following exposure to CO₂. Density functional theory identified a three-step carbon capture mechanism based on (i) reaction of OH- with ethylene glycol in the solution followed by (ii) formation of 2-hydroxyethyl carbonate, which (iii) further react with OH- to form a carbonate species. This mechanism was validated with experimental nuclear magnetic resonance spectroscopy (NMR) to identify the dissolved carbonate phases and the decrease in the pH during CO₂ exposure. Deuterated samples of the ZIF-8 PLs were synthesized and analyzed via neutron diffraction at the Spallation Neutron Sources at Oak Ridge National Laboratory. Results identified differences in diffraction for PLs pre- and post-CO₂ exposure that will be combined with ab initio molecular dynamics data of the same PL composition to identify how the presence of a solvent-porous host interfaces results in carbon capture.

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Albany is a parallel C++ finite element library for solving forward and inverse problems involving partial differential equations (PDEs). In this paper we introduce PyAlbany, a newly developed Python interface to the Albany library. PyAlbany can be used to effectively drive Albany enabling fast and easy analysis and post-processing of applications based on PDEs that are pre-implemented in Albany. PyAlbany relies on the library PyBind11 to bind Python with C++ Albany code. Here we detail the implementation of PyAlbany and showcase its capabilities through a number of examples targeting a heat-diffusion problem. In particular we consider the following: (1) the generation of samples for a Monte Carlo application, (2) a scalability study, (3) a study of parameters on the performance of a linear solver, and finally (4) a tool for performing eigenvalue decompositions of matrix-free operators for a Bayesian inference application.

Several studies have proven how ducted fuel injection (DFI) reduces soot emissions for compression-ignition engines. Nevertheless, no comprehensive study has investigated how DFI performs over a load range in combination with low-net-carbon fuels. In this study, optical-engine experiments were performed with four different fuels—conventional diesel and three low-net-carbon fuels—at low and moderate load, to measure emissions levels and performance. The 1.7-liter single-cylinder optical engine was equipped with a high-speed camera to capture natural luminosity images of the combustion event. Conventional diesel and DFI combustion were investigated at four different dilution levels (to simulate exhaust-gas recirculation effects), from 14 to 21 mol% oxygen in the intake. At a given dilution level, with commercial diesel fuel, DFI reduced soot by 82% at medium load, and 75% at low load without increasing NO_x. The results further show how DFI with dilution reduces soot and NO_x without compromising engine performance or other emission types, especially when combined with low-net-carbon fuels. DFI with the oxygenated low-net-carbon blend HEA67 simultaneously reduced soot and NO_x by as much as 93 % and 82 %, respectively, relative to conventional diesel combustion with commercial diesel fuel. These soot and NO_x reductions occurred while lifecycle CO₂ was reduced by at least 70 % when using low-net-carbon fuels instead of conventional diesel. All emissions changes were compared with future emissions regulations for different vehicle sectors to investigate how DFI can be used to facilitate achievement of the regulations. Finally, the results show how the DFI cases fall below several future emissions regulation levels, rendering less need for aftertreatment systems and giving a possible lower cost of ownership.

Here, we introduce a mathematically rigorous formulation for a nonlocal interface problem with jumps and propose an asymptotically compatible finite element discretization for the weak form of the interface problem. After proving the well-posedness of the weak form, we demonstrate that solutions to the nonlocal interface problem converge to the corresponding local counterpart when the nonlocal data are appropriately prescribed. Several numerical tests in one and two dimensions show the applicability of our technique, its numerical convergence to exact nonlocal solutions, its convergence to the local limit when the horizons vanish, and its robustness with respect to the patch test.

Many applications require minimizing the sum of smooth and nonsmooth functions. For example, basis pursuit denoising problems in data science require minimizing a measure of data misfit plus an $\ell^1$-regularizer. Similar problems arise in the optimal control of partial differential equations (PDEs) when sparsity of the control is desired. Here, we develop a novel trust-region method to minimize the sum of a smooth nonconvex function and a nonsmooth convex function. Our method is unique in that it permits and systematically controls the use of inexact objective function and derivative evaluations. When using a quadratic Taylor model for the trust-region subproblem, our algorithm is an inexact, matrix-free proximal Newton-type method that permits indefinite Hessians. We prove global convergence of our method in Hilbert space and demonstrate its efficacy on three examples from data science and PDE-constrained optimization.

Here we present a new method for coupled linear elasticity problems whose finite element discretization may lead to spatially non-coincident discretized interfaces. Our approach combines the classical Dirichlet–Neumann coupling formulation with a new set of discretized interface conditions obtained through Taylor series expansions. We show that these conditions ensure linear consistency of the coupled finite element solution. We then formulate an iterative solution method for the coupled discrete system and apply the new coupling approach to two representative settings for which we also provide several numerical illustrations. The first setting is a mesh-tying problem in which both coupled structures have the same Lamé parameters whereas the second setting is an interface problem for which the Lamé parameters in the two coupled structures are different.

Satellite imagery can detect temporary cloud trails or ship tracks formed from aerosols emitted from large ships traversing our oceans, a phenomenon that global climate models cannot directly reproduce. Ship tracks are observable examples of marine cloud brightening, a potential solar climate intervention that shows promise in helping combat climate change. In this paper, we demonstrate a simulation-based approach in learning the behavior of ship tracks based upon a novel stochastic emulation mechanism. Our method uses wind fields to determine the movement of aerosol-cloud tracks and uses a stochastic partial differential equation (SPDE) to model their persistence behavior. This SPDE incorporates both a drift and diffusion term which describes the movement of aerosol particles via wind and their diffusivity through the atmosphere, respectively. We first present our proposed approach with examples using simulated wind fields and ship paths. We then successfully demonstrate our tool by applying the approximate Bayesian computation method-sequential Monte Carlo for data assimilation.

Interfacial segregation and chemical short-range ordering influence the behavior of grain boundaries in complex concentrated alloys. In this study, we use atomistic modeling of a NbMoTaW refractory complex concentrated alloy to provide insight into the interplay between these two phenomena. Hybrid Monte Carlo and molecular dynamics simulations are performed on columnar grain models to identify equilibrium grain boundary structures. Our results reveal extended near-boundary segregation zones that are much larger than traditional segregation regions, which also exhibit chemical patterning that bridges the interfacial and grain interior regions. Furthermore, structural transitions pertaining to an A2-to-B2 transformation are observed within these extended segregation zones. Both grain size and temperature are found to significantly alter the widths of these regions. An analysis of chemical short-range order indicates that not all pairwise elemental interactions are affected by the presence of a grain boundary equally, as only a subset of elemental clustering types are more likely to reside near certain boundaries. The results emphasize the increased chemical complexity that is associated with near-boundary segregation zones and demonstrate the unique nature of interfacial segregation in complex concentrated alloys.

Li-metal batteries (LMBs) employing conversion cathode materials (e.g., FeF₃) are a promising way to prepare inexpensive, environmentally friendly batteries with high energy density. Pseudo-solid-state ionogel separators harness the energy density and safety advantages of solid-state LMBs, while alleviating key drawbacks (e.g., poor ionic conductivity and high interfacial resistance). In this work, a pseudo-solid-state conversion battery (Li-FeF₃) is presented that achieves stable, high rate (1.0 mA cm^–2) cycling at room temperature. The batteries described herein contain gel-infiltrated FeF₃ cathodes prepared by exchanging the ionic liquid in a polymer ionogel with a localized high-concentration electrolyte (LHCE). The LHCE gel merges the benefits of a flexible separator (e.g., adaptation to conversion-related volume changes) with the excellent chemical stability and high ionic conductivity (~2 mS cm^–1 at 25 °C) of an LHCE. The latter property is in contrast to previous solid-state iron fluoride batteries, where poor ionic conductivities necessitated elevated temperatures to realize practical power levels. Importantly, the stable, room-temperature Li-FeF₃ cycling performance obtained with the LHCE gel at high current densities paves the way for exploring a range of architectures including flexible, three-dimensional, and custom shape batteries.

Automatic differentiation (AD) is a well-known technique for evaluating analytic derivatives of calculations implemented on a computer, with numerous software tools available for incorporating AD technology into complex applications. However, a growing challenge for AD is the efficient differentiation of parallel computations implemented on emerging manycore computing architectures such as multicore CPUs, GPUs, and accelerators as these devices become more pervasive. In this work, we explore forward mode, operator overloading-based differentiation of C++ codes on these architectures using the widely available Sacado AD software package. In particular, we leverage Kokkos, a C++ tool providing APIs for implementing parallel computations that is portable to a wide variety of emerging architectures. We describe the challenges that arise when differentiating code for these architectures using Kokkos, and two approaches for overcoming them that ensure optimal memory access patterns as well as expose additional dimensions of fine-grained parallelism in the derivative calculation. We describe the results of several computational experiments that demonstrate the performance of the approach on a few contemporary CPU and GPU architectures. We then conclude with applications of these techniques to the simulation of discretized systems of partial differential equations.

Wind turbine applications that leverage nacelle-mounted Doppler lidar are hampered by several sources of uncertainty in the lidar measurement, affecting both bias and random errors. Two problems encountered especially for nacelle-mounted lidar are solid interference due to intersection of the line of sight with solid objects behind, within, or in front of the measurement volume and spectral noise due primarily to limited photon capture. These two uncertainties, especially that due to solid interference, can be reduced with high-fidelity retrieval techniques (i.e., including both quality assurance/quality control and subsequent parameter estimation). Our work compares three such techniques, including conventional thresholding, advanced filtering, and a novel application of supervised machine learning with ensemble neural networks, based on their ability to reduce uncertainty introduced by the two observed nonideal spectral features while keeping data availability high. The approach leverages data from a field experiment involving a continuous-wave (CW) SpinnerLidar from the Technical University of Denmark (DTU) that provided scans of a wide range of flows both unwaked and waked by a field turbine. Independent measurements from an adjacent meteorological tower within the sampling volume permit experimental validation of the instantaneous velocity uncertainty remaining after retrieval that stems from solid interference and strong spectral noise, which is a validation that has not been performed previously. All three methods perform similarly for non-interfered returns, but the advanced filtering and machine learning techniques perform better when solid interference is present, which allows them to produce overall standard deviations of error between 0.2 and 0.3ms-1, or a 1%-22% improvement versus the conventional thresholding technique, over the rotor height for the unwaked cases. Between the two improved techniques, the advanced filtering produces 3.5% higher overall data availability, while the machine learning offers a faster runtime (i.e., 1/41s to evaluate) that is therefore more commensurate with the requirements of real-time turbine control. The retrieval techniques are described in terms of application to CW lidar, though they are also relevant to pulsed lidar. Previous work by the authors (Brown and Herges, 2020) explored a novel attempt to quantify uncertainty in the output of a high-fidelity lidar retrieval technique using simulated lidar returns; this article provides true uncertainty quantification versus independent measurement and does so for three techniques rather than one.

It is hoped that quantum computers will offer advantages over classical computers for combinatorial optimization. Here, we introduce a feedback-based strategy for quantum optimization, where the results of qubit measurements are used to constructively assign values to quantum circuit parameters. We show that this procedure results in an estimate of the combinatorial optimization problem solution that improves monotonically with the depth of the quantum circuit. Importantly, the measurement-based feedback enables approximate solutions to the combinatorial optimization problem without the need for any classical optimization effort, as would be required for the quantum approximate optimization algorithm. We demonstrate this feedback-based protocol on a superconducting quantum processor for the graph-partitioning problem MaxCut, and present a series of numerical analyses that further investigate the protocol's performance.

This report is the revised (Revision 9) Task F specification for DECOVALEX-2023. Task F is a comparison of the models and methods used in deep geologic repository performance assessment. The task proposes to develop a reference case for a mined repository in a fractured crystalline host rock (Task F1) and a reference case for a mined repository in a salt formation (Task F2). Teams may choose to participate in the comparison for either or both reference cases. For each reference case, a common set of conceptual models and parameters describing features, events, and processes that impact performance will be given, and teams will be responsible for determining how best to implement and couple the models. The comparison will be conducted in stages, beginning with a comparison of key outputs of individual process models, followed by a comparison of a single deterministic simulation of the full reference case, and moving on to uncertainty propagation and uncertainty and sensitivity analysis. This report provides background information, a summary of the proposed reference cases, and a staged plan for the analysis.

As atomic layer deposition (ALD) emerges as a method to fabricate architectures with atomic precision, emphasis is placed on understanding surface reactions and nucleation mechanisms. ALD of titanium dioxide with TiCl₄ and water has been used to investigate deposition processes in general, but the effect of surface termination on the initial TiO₂ nucleation lacks needed mechanistic insights. Here, this work examines the adsorption of TiCl₄ on Cl–, H–, and HO– terminated Si(100) and Si(111) surfaces to elucidate the general role of different surface structures and defect types in manipulating surface reactivity of growth and non-growth substrates. The surface sites and their role in the initial stages of deposition are examined by X-ray photoelectron spectroscopy (XPS) and atomic force microscopy (AFM). Density functional theory (DFT) computations of the local functionalized silicon surfaces suggest oxygen-containing defects are primary drivers of selectivity loss on these surfaces.

Ionic conduction in silicate glasses is mainly influenced by the nature, concentration, and mobility of the network-modifying (NWM) cations. The electrical conduction in SLS is dominated by the ionic migration of sodium moving from the anode to the cathode. An activation energy for this conduction process was calculated to be 0.82eV and in good agreement with values previously reported. The conduction process associated to the leakage current and relaxation peak in TSDC for HPFS is attributed to conduction between nonbridging oxygen hole centers (NBOHC). It is suggested that ≡Si-OH = ≡Si-O^- + H⁰ under thermo-electric poling, promoting hole or proton injection from the anode and responsible for the 1.5eV relaxation peak. No previous TSDC data have been found to corroborate this mechanism. The higher activation energy and lower current intensity for the coated HPFS might be attributed to a lower concentration of NBOHC after heat treatment (Si-OH + OH-Si = SiO-Si + H₂O). This could explain the TSDC signal around room temperature for the coated HPFS. Another possible explanation could be a redox reaction at the anode region dominating the current response.

This development of empirical data to support realistic and science-based input to safety regulations and transportation standards is a critical need for the hazardous material (HM) transportation industry. Current regulations and standards are based on the TNT equivalency model. However, real world experience indicates that use of the TNT equivalency model to predict composite overwrapped pressure vessel (COPV) potential energy release is unrealistically conservative. The purpose of this report is to characterize and quantify rupture events involving damaged COPV’s of the type used in HM transportation regulated by the Department of Transportation (DOT). This was accomplished using a series of five tests; 2 COPV tests for compressed natural gas (CNG), 2 COPV tests for hydrogen, and 1 COPV test for nitrogen. Measured overpressures from these tests were compared to predicted overpressures from a TNT equivalence model and blast curves. Comparison between the measurements and predictions shows that the predictions are generally conservative, and that the extent of conservatism is dominated by predictions of the chemical contribution to overpressure from fuel within the COPVs.

This report provides a summary of measurement results used to compare the performance of the PHDS Fulcrum40h and Ortec Detective-X High Purity Germanium (HPGe) detector systems. Specifically, the measurement data collected was used to assess each detector system for gamma efficiency and resolution, gamma angular response and efficiency for an in-situ surface distribution, neutron efficiency, gamma pulse-pileup response, and gamma to neutron crosstalk.

Cemented annulus fractures are a major leakage path in a wellbore system, and their permeability plays an important role in the behavior of fluid flow through a leaky wellbore. The permeability of these fractures is affected by changing conditions including the external stresses acting on the fracture and the fluid pressure within the fracture. Laboratory gas flow experiments were conducted in a triaxial cell to evaluate the permeability of a wellbore cement fracture under a wide range of confining stress and pore pressure conditions. For the first time, an effective stress law that considers the simultaneous effect of confining stress and pore pressure was defined for the wellbore cement fracture permeability. Here the results showed that the effective stress coefficient (λ) for permeability increased linearly with the Terzaghi effective stress ( -p) with an average of λ = 1 in the range of applied pressures. The relationship between the effective stress and fracture permeability was examined using two physical-based models widely used for rock fractures. The results from the experimental work were incorporated into numerical simulations to estimate the impact of effective stress on the interpreted hydraulic aperture and leakage behavior through a fractured annular cement. Accounting for effective stress-dependent permeability through the wellbore length significantly increased the leakage rate at the wellhead compared with the assumption of a constant cemented annulus permeability.

National security applications require artificial neural networks (ANNs) that consume less power, are fast and dynamic online learners, are fault tolerant, and can learn from unlabeled and imbalanced data. We explore whether two fundamentally different, traditional learning algorithms from artificial intelligence and the biological brain can be merged. We tackle this problem from two directions. First, we start from a theoretical point of view and show that the spike time dependent plasticity (STDP) learning curve observed in biological networks can be derived using the mathematical framework of backpropagation through time. Second, we show that transmission delays, as observed in biological networks, improve the ability of spiking networks to perform classification when trained using a backpropagation of error (BP) method. These results provide evidence that STDP could be compatible with a BP learning rule. Combining these learning algorithms will likely lead to networks more capable of meeting our national security missions.

Terahertz (THz) external-cavity lasers based on quantum-cascade (QC) metasurfaces are emerging as widely-tunable, single-mode sources with the potential to cover the 1--6 THz range in discrete bands with milliwatt-level output power. By operating on an ultra-short cavity with a length on the order of the wavelength, the QC vertical-external-cavity surface-emitting-laser (VECSEL) architecture enables continuous, broadband tuning while producing high quality beam patterns and scalable power output. The methods and challenges for designing the metasurface at different frequencies are discussed. As the QC-VECSEL is scaled below 2 THz, the primary challenges are reduced gain from the QC active region, increased metasurface quality factor and its effect on tunable bandwidth, and larger power consumption due to a correspondingly scaled metasurface area. At frequencies above 4.5 THz, challenges arise from a reduced metasurface quality factor and the excess absorption that occurs from proximity to the Reststrahlen band. The results of four different devices — with center frequencies 1.8 THz, 2.8 THz, 3.5 THz, and 4.5 THz — are reported. Each device demonstrated at least 200 GHz of continuous single-mode tuning, with the largest being 650 GHz around 3.5 THz. The limitations of the tuning range are well modeled by a Fabry-Pérot cavity which accounts for the reflection phase of the metasurface and the effect of the metasurface quality factor on laser threshold. Lastly, the effect of different output couplers on device performance is studied, demonstrating a significant trade-off between the slope efficiency and tuning bandwidth.

Several studies suggest that metal ordering within metal-organic frameworks (MOFs) is important for understanding how MOFs behave in relevant applications; however, these siting trends can be difficult to determine experimentally. To garner insight into the energetic driving forces that may lead to nonrandom ordering within heterometallic MOFs, we employ density functional theory (DFT) calculations on several bimetallic metal-organic crystals composed of Nd and Yb metal atoms. We also investigate the metal siting trends for a newly synthesized MOF. Our DFT-based energy of mixing results suggest that Nd will likely occupy sites with greater access to electronegative atoms and that local homometallic domains within a mixed-metal Nd-Yb system are favored. We also explore the use of less computationally extensive methods such as classical force fields and cluster expansion models to understand their feasibility for large system sizes. This study highlights the impact of metal ordering on the energetic stability of heterometallic MOFs and crystal structures.

We have measured, analyzed, and simulated the ground state valence photoelectron spectrum, x-ray absorption (XA) spectrum, x-ray photoelectron (XP) spectrum as well as normal and resonant Auger-Meitner electron (AE) spectrum of oxazole at the carbon, oxygen, and nitrogen K-edge in order to understand its electronic structure. Experimental data are compared to theoretical calculations performed at the coupled cluster, restricted active space perturbation theory to second-order and time-dependent density functional levels of theory. We demonstrate (1) that both N and O K-edge XA spectra are sensitive to the amount of dynamical electron correlation included in the theoretical description and (2) that for a complete description of XP spectra, additional orbital correlation and orbital relaxation effects need to be considered. The normal AE spectra are dominated by a singlet excitation channel and well described by theory. The resonant AE spectra, however, are more complicated. While the participator decay channels, dominating at higher kinetic energies, are well described by coupled cluster theory, spectator channels can only be described satisfactorily using a method that combines restricted active space perturbation theory to second order for the bound part and a one-center approximation for the continuum.

A laser-strike detection system includes an imaging sensor mounted on a platform, and a computing device. The imaging sensor outputs image frames that are each representative of a portion of the platform at a different time, during which a laser may be striking the platform. The computing device receives the image frames, and computes a delay map that indicates time-of-arrival delays of the laser beam at points on the portion of the platform. The computing device converts the delay map to a path-length variation map by multiplying the delay map by the propagation speed of light. The computing device fits a plane to the path-length variation map constrained by a topological model of the platform. The computing device computes angular deflections in x- and y-directions based upon the fit, which angular deflections define a direction from the platform to an emitter of the laser beam.

In order to meet 2025 goals for enhanced peak power (100 kW), specific power (50 kW/L), and reduced cost (3.3 $\$$/kW) in a motor that can operate at ≥ 20,000 rpm, improved soft magnetic materials must be developed. Better performing soft magnetic materials will also enable rare earth free electric motors. In fact, replacement of permanent magnets with soft magnetic materials was highlighted in the Electrical and Electronics Technical Team (EETT) Roadmap as a R&D pathway for meeting 2025 targets. Eddy current losses in conventional soft magnetic materials, such as silicon steel, begin to significantly impact motor efficiency as rotational speed increases. Soft magnetic composites (SMCs), which combine magnetic particles with an insulating matrix to boost electrical resistivity (ρ) and decrease eddy current losses, even at higher operating frequencies (or rotational speeds), are an attractive solution. Today, SMCs are being fabricated with values of ρ ranging between 10^-3 to 10^-1 μohm∙m, which is significantly higher than 3% silicon steel (~0.05 μohm∙m). The isotropic nature of SMCs is ideally suited for motors with 3D flux paths, such as axial flux motors. Additionally, the manufacturing cost of SMCs is low and they are highly amenable to advanced manufacturing and net-shaping into complex geometries, which further reduces manufacturing costs. There is still significant room for advancement in SMCs, and therefore additional improvements in electrical machine performance. For example, despite the inclusion of a non-magnetic insulating material, the electrical resistivities of SMCs are still far below that of soft ferrites (10 – 10⁸ μohm∙m).

More efficient power conversion devices are able to transmit greater electrical power across larger distances to satisfy growing global electrical needs. A critical requirement to achieve more efficient power conversion are the soft magnetic materials used as core materials in transformers, inductors, and motors. To that effect it is well known that the use of non-equilibrium microstructures, which are, for example, nanocrystalline or consist of single phase solid solutions, can yield high saturation magnetic polarization and high electrical resistivity necessary for more efficient soft magnetic materials. In this work, we synthesized CoFe – P soft magnetic alloys containing nanocrystalline, single phase solid solution microstructures and studied the effect of a secondary intermetallic phase on the saturation magnetic polarization and electrical resistivity of the consolidated alloy. Single phase solid solution CoFe – P alloys were prepared through mechanically alloying metal powders and phase decomposition was observed after subsequent consolidation via spark plasma sintering (SPS) at various temperatures. The secondary intermetallic phase was identified as the orthorhombic (CoxFe1−x)2P phase and the magnetic properties of the (CoxFe1−x)2P intermetallic phase were found to be detrimental to the soft magnetic properties of the targeted CoFe – P alloy.

Abstract not provided.

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.

Abstract not provided.

We report the method-of-moments implementation of the electric-field integral equation (EFIE) yields many code-verification challenges due to the various sources of numerical error and their possible interactions. Matters are further complicated by singular integrals, which arise from the presence of a Green's function. To address these singular integrals, an approach is presented in wherein both the solution and Green's function are manufactured. Because the arising equations are poorly conditioned, they are reformulated as a set of constraints for an optimization problem that selects the solution closest to the manufactured solution. In this paper, we demonstrate how, for such practically singular systems of equations, computing the truncation error by inserting the exact solution into the discretized equations cannot detect certain orders of coding errors. On the other hand, the discretization error from the optimal solution is a more sensitive metric that can detect orders less than those of the expected convergence rate.

Clays are known for their small particle sizes and complex layer stacking. We show here that the limited dimension of clay particles arises from the lack of long-range order in low-dimensional systems. Because of its weak interlayer interaction, a clay mineral can be treated as two separate low-dimensional systems: a 2D system for individual phyllosilicate layers and a quasi-1D system for layer stacking. The layer stacking or ordering in an interstratified clay can be described by a 1D Ising model while the limited extension of individual phyllosilicate layers can be related to a 2D Berezinskii–Kosterlitz–Thouless transition. This treatment allows for a systematic prediction of clay particle size distributions and layer stacking as controlled by the physical and chemical conditions for mineral growth and transformation. Clay minerals provide a useful model system for studying a transition from a 1D to 3D system in crystal growth and for a nanoscale structural manipulation of a general type of layered materials.

This study explores the effect of surface re-finishing on the corrosion behavior of electron beam manufactured (EBM) Ti-G5 (Ti-6Al-4V), including the novel application of an electron beam surface remelting (EBSR) technique. Specifically, the relationship between material surface roughness and corrosion resistance was examined. Surface roughness was tested in the as-printed (AP), mechanically polished (MP), and EBSR states and compared to wrought (WR) counterparts. Electrochemical measurements were performed in chloride-containing media. It was observed that surface roughness, rather than differences in the underlying microstructure, played a more significant role in the general corrosion resistance in the environment explored here. While both MP and EBSR methods reduced surface roughness and enhanced corrosion resistance, mechanical polishing has many known limitations. The EBSR process explored herein demonstrated positive preliminary results. The surface roughness (Ra) of the EBM-AP material was considerably reduced by 82%. Additionally, the measured corrosion current density in 0.6 M NaCl for the EBSR sample is 0.05 µA cm−2, five times less than the value obtained for the EBM-AP specimen (0.26 µA cm−2).

The growing demand for bandwidth makes photonic systems a leading candidate for future telecommunication and radar technologies. Integrated photonic systems offer ultra-wideband performance within a small footprint, which can naturally interface with fiber-optic networks for signal transmission. However, it remains challenging to realize narrowband (∼MHz) filters needed for high-performance communications systems using integrated photonics. In this paper, we demonstrate all-silicon microwave-photonic notch filters with 50× higher spectral resolution than previously realized in silicon photonics. This enhanced performance is achieved by utilizing optomechanical interactions to access long-lived phonons, greatly extending available coherence times in silicon. We use a multi-port Brillouin-based optomechanical system to demonstrate ultra-narrowband (2.7 MHz) notch filters with high rejection (57 dB) and frequency tunability over a wide spectral band (6 GHz) within a microwave-photonic link. We accomplish this with an all-silicon waveguide system, using CMOS-compatible fabrication techniques.

The extreme miniaturization of a cold-atom interferometer accelerometer requires the development of novel technologies and architectures for the interferometer subsystems. Here, we describe several component technologies and a laser system architecture to enable a path to such miniaturization. We developed a custom, compact titanium vacuum package containing a microfabricated grating chip for a tetrahedral grating magneto-optical trap (GMOT) using a single cooling beam. In addition, we designed a multi-channel photonic-integrated-circuit-compatible laser system implemented with a single seed laser and single sideband modulators in a time-multiplexed manner, reducing the number of optical channels connected to the sensor head. In a compact sensor head containing the vacuum package, sub-Doppler cooling in the GMOT produces 15 μK temperatures, and the GMOT can operate at a 20 Hz data rate. We validated the atomic coherence with Ramsey interferometry using microwave spectroscopy, then demonstrated a light-pulse atom interferometer in a gravimeter configuration for a 10 Hz measurement data rate and T = 0–4.5 ms interrogation time, resulting in Δg/g = 2.0 × 10−6. This work represents a significant step towards deployable cold-atom inertial sensors under large amplitude motional dynamics.

Spin–orbit effects, inherent to electrons confined in quantum dots at a silicon heterointerface, provide a means to control electron spin qubits without the added complexity of on-chip, nanofabricated micromagnets or nearby coplanar striplines. Here, we demonstrate a singlet–triplet qubit operating mode that can drive qubit evolution at frequencies in excess of 200 MHz. This approach offers a means to electrically turn on and off fast control, while providing high logic gate orthogonality and long qubit dephasing times. We utilize this operational mode for dynamical decoupling experiments to probe the charge noise power spectrum in a silicon metal-oxide-semiconductor double quantum dot. In addition, we assess qubit frequency drift over longer timescales to capture low-frequency noise. We present the charge noise power spectral density up to 3 MHz, which exhibits a 1/fα dependence consistent with α ~ 0.7, over 9 orders of magnitude in noise frequency.

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.

Abstract not provided.

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.

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.

Advances in machine learning (ML) have enabled the development of interatomic potentials that promise the accuracy of first principles methods and the low-cost, parallel efficiency of empirical potentials. However, ML-based potentials struggle to achieve transferability, i.e., provide consistent accuracy across configurations that differ from those used during training. In order to realize the promise of ML-based potentials, systematic and scalable approaches to generate diverse training sets need to be developed. This work creates a diverse training set for tungsten in an automated manner using an entropy optimization approach. Subsequently, multiple polynomial and neural network potentials are trained on the entropy-optimized dataset. A corresponding set of potentials are trained on an expert-curated dataset for tungsten for comparison. The models trained to the entropy-optimized data exhibited superior transferability compared to the expert-curated models. Furthermore, the models trained to the expert-curated set exhibited a significant decrease in performance when evaluated on out-of-sample configurations.

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.

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.

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.