Publications

Abstract not provided.

In this report, we document the process related to developing a regional geologic model of a 605 x 1334 km area centered around Utah and encompassing surrounding states. This model is developed to test the effect that composition of a model has on the generation of synthetic data with the intent of using this information to improve upon full waveform moment tensor inversions. We compare observed data from three seismic events and five stations to the synthetic data generated by a preliminary model derived from a geologic framework model (GFM) developed by the USGS. The synthetic data and observed data comparisons indicate that our preliminary model performs well at smaller offset distances in the northern and central sections of the model. However, the southern stations consistently display synthetic data P- and S-wave arrival times that do not match the observed data arrival times, indicating that the velocity structure of the southern part of the model especially is inaccurate.

Abstract not provided.

Accurate simulation of the evolution of polar ice-sheets requires a massive amount of computational power. In order to take advantage of the newest generation of supercomputing clusters, the Albany Land Ice code has been modernized for performance portability across a variety of parallel architectures, with a focus on enabling end-to-end GPU capability. Albany uses a multigrid preconditioning approach for solving linear systems via performance portable smoothers from the Trilinos package Ifpack2. Since the Albany Land Ice code is constantly evolving and both Albany and Trilinos are in constant development, it is likely that the optimal choice of solver parameters will change over time. It is therefore critical to have an automatic performance tuning framework to ensure that the best possible performance is maintained. Toward this effect, we have developed an automatic performance tuning framework to determine the best fine- and coarse-grid smoothing algorithms and parameters. We treat the underlying performance model of the linear solve as a black box and use the python-based GPTune Bayesian optimization library to determine the optimal smoother choice and parameters. Using this approach, we have found smoothers and their corresponding parameters that result in, on average, 1.2 times faster, and up to 1.5 times faster solve-times than our manually-tuned parameters. We also show that the proposed auto-tuning approach produces reliably better parameters than naive black box optimization techniques like random search for a given function evaluation budget. By implementing our tuning framework in the Python-based workflow management tool parsl, we also ensure that we efficiently use available computing resources during the tuning process and avoid unnecessary long wait times in computing cluster job queues.

Abstract not provided.

Quantum point contacts (QPC) are the building blocks of quantum dot qubits and semiconducting quantum electrical metrology circuits. QPCs also make highly sensitive electrical amplifiers with the potential to operate in the quantum-limited regime. Though the inherent operational bandwidth of QPCs can eclipse the THz regime, the impedance mismatch with the external circuitry limits the operational frequency to a few kHz. Lumped-element impedance-matching circuits are successful only up to a few hundreds of MHz in frequency. QPCs are characterised by a complex impedance consisting of quantized resistance, capacitance, and inductance elements. Characterising the complex admittance at higher frequencies and understanding the coupling of QPC to other circuit elements and electromagnetic environments will provide valuable insight into its sensing and backaction properties. In this work, we couple a QPC galvanically to a superconducting stub tuner impedance matching circuit realised in a coplanar waveguide architecture to enhance the operation frequency into the GHz regime and investigate the electrical amplification and complex admittance characteristics. The device, operating at ~1.96 $GHz$ exhibits a conductance sensitivity of 2.92 X 10^-5(e²/h)/$\sqrt{Hz}$ with a bandwidth of 13 $MHz$. Besides, the RF reflected power unambiguously reveals the complex admittance characteristics of the QPC, shining more light on the behaviour of quantum tunnel junctions at higher operational frequencies.

Carbon capture is essential to meeting climate change mitigation goals. One approach currently being commercialized utilizes liquid-based solvents to capture CO₂ directly from the atmosphere but is limited by slow absorption of CO₂ into the liquid. Improved air/solvent liquid mixing increases CO₂ absorption rate, and this increased CO₂ absorption efficiency allows for smaller carbon capture systems with lower capital costs and better economic viability. In this project, we study the use of passive micromixers fabricated by metal additive manufacturing. The micromixer’s small-scale surface geometric features perturb and mix the liquid film to enhance mass transfer and CO₂ absorption. In this project, we evaluated this hypothesis through computational and experimental studies. Computational investigations focused on developing capabilities to simulate thin film (~ 100μm) fluid flow on rough surfaces. Such thin films are in a surface-tension dominated regime and simulations in this regime are prone to instabilities. Improvements to the Nalu code completed in this project resulted in a 10x timestep stability improvement for these problems.

The modern global economy relies heavily on carbon-based products that are derived from petroleum, which presents sustainability, resource management, and greenhouse gas exacerbated climate change challenges. Due to these challenges, there is the need for a global industrial transition towards green and sustainable production. Microbial production of valuable chemicals from renewable biomass represents one promising route. However, high-volume low-value products such as commodity chemicals are still difficult to make profitable. One fundamental bottleneck is a waste of more than 1/3 of the feedstock carbon as CO₂ in the fermentation process. Here the project focuses on fundamentally reconfiguring the metabolism to reduce CO₂ loss in central metabolic pathways thereby also improving bioproduct yields. Here we present technologies to prevent CO₂ loss and balance reducing equivalents within the cell to enable complete conversion of glucose from renewable feedstocks into bioproducts.

Global climate change has prompted many national plans for rapid emissions reductions. For example, the United States recently committed to transitioning to 100% carbon-free electricity by 2035 and net-zero emissions economy-wide by 2050. Parallel to conversations surrounding emissions reductions is the call for energy justice, or the demand for more equitable distribution of energy-related burdens and benefits among communities. To date, energy justice has evolved as a mostly academic conversation, which may limit its utility to praxis. In response, we offer an interdisciplinary framework that aims to organize existing knowledge and lessons learned from energy development. Specifically, we developed the Meaningful Marine Renewable Energy (MRE) Development Framework and conducted a literature review using MRE as a case study. MRE was chosen because it is a nascent renewable energy technology in the US with projects mostly in demonstration stages and no commercial deployment, making it a useful case study to apply lessons learned from other energy sectors and other countries. Discussion of current resources being developed among the MRE community and their implications for furthering energy justice priorities are also explored. We conclude the review with a compiled list of questions meant to support stakeholders in translating theoretical concepts of Meaningful MRE Development to practice. Although the Meaningful MRE framework was developed using MRE as a use case, our interdisciplinary theoretical framework can be applied beyond MRE to other sustainable and renewable energy projects.

In this work, thermogravimetric analysis (TGA) was performed on samples of a carbon fiber epoxy composite, a glass fiber epoxy composite, and a mixed carbon fiber/glass fiber epoxy composite, as well on each constituent material (polymer epoxy, carbon fibers and glass fibers). TGA was conducted for heating rates from 1-20 C/min with purified purge gases of nitrogen and dry air. For the fiberglass composite, we find that ~70% of the material remains after heating in air to 1200 C. For the carbon fiber epoxy composite, we observe greater mass loss as the carbon fibers can oxidize, leaving little material by the end of the test. The mixed composite, which has a 2:1 ratio of glass fibers to carbon fibers, experienced a total mass loss between the two other composites. By determining the relationship between the thermal decomposition of a composite material and its constituent materials, we can predict the fire behavior of novel composites during the material design phase.

Although visualizations are a useful tool for helping people to understand information, they can also have unintended effects on human cognition. This is especially true for uncertain information, which is difficult for people to understand. Prior work has found that different methods of visualizing uncertain information can produce different patterns of decision making from users. However, uncertainty can also be represented via text or numerical information, and few studies have systematically compared these types of representations to visualizations of uncertainty. We present two experiments that compared visual representations of risk (icon arrays) to numerical representations (natural frequencies) in a wildfire evacuation task. Like prior studies, we found that different types of visual cues led to different patterns of decision making. In addition, our comparison of visual and numerical representations of risk found that people were more likely to evacuate when they saw visualizations than when they saw numerical representations. These experiments reinforce the idea that design choices are not neutral: seemingly minor differences in how information is represented can have important impacts on human risk perception and decision making.

This report summarizes the measurement and analysis results of initial performance demonstrator wafers patterned at LumArray in January 2023 in accordance with the project Statement of Work.

We demonstrate the discrimination of ground-state hyperfine manifolds of a cesium atom in an optical tweezer using a simple probe beam with Formula Presented% detection fidelity and 0.9(2)% detection-driven loss of bright-state atoms. Our detection infidelity of Formula Presented% is an order of magnitude better than previously published low-loss readout results for alkali-metal atoms in optical tweezers. We achieve these results by identifying and mitigating an extra depumping mechanism due to stimulated Raman transitions induced by trap light in the presence of probe light. In this work, complex optical systems and stringent vacuum pressures are not required, enabling straightforward adoption of our techniques on contemporary experiments.

This primary purpose of this project was to evaluate alternative gas mixtures to sulfur hexafluoride (SF6) developed for high voltage power delivery applications for use in high voltage spark gap switches. These SF6 alternatives lower global warming potential emissions and enable improvements to the pressure-voltage design space. A combined experimental, computational, and theoretical study was used to quantify the impact of persistent breakdown products on the breakdown distribution of SF6-replacement gas mixtures. Viable SF6 replacements suitable for use in spark gap switches were studied to enable performance and agility improvements for next-generation pulsed power research relevant to national security missions. Experimental campaign included establishing parameters of switch gases as function of concentration. Various concentrations and pressures were tested for trends in breakdown voltage, repeatability, and durability, and breakdown constituents. A zero-dimensional plasma global model was used to simulate the plasma arc decay and recombination process in spark-gap switches relevant to the Z machine. Finally, a complete and consistent set of electron-neutral collision cross-sections for the novel insulating gas C4F7N is reported.

The Canada-US Blended Cyber-Physical Exercise was a successful, first of its kind, multiorganization and multi-laboratory exercise that culminated years of complex system development and planning. The project aimed to answer three driving research questions, (1) How do cyberattacks support malicious acts leading to theft or sabotage [at a nuclear site]? (2) What are aspects of an effective combined cyber-physical response? (3) How to evaluate effectiveness of that response? Which derived the following primary objectives, 1. The May 2023 Cyber-Physical Exercise shall present a cyber-attack scenario that supports malicious acts leading to theft or sabotage. 2. The May 2023 Cyber-Physical Exercise shall define aspects of an effective combined cyber-physical response. 3. Analysis of the May 2023 Cyber-Physical Exercise shall evaluate the effectiveness of the incident response against pre-established exercise evaluation criteria. 4. Analysis of the May 2023 Cyber-Physical Exercise shall assess the effectiveness of the evaluation criteria itself. 5. Exercises shall be performed in a real-life environment. The team believes these objectives were met, and the evidence will be presented in this report. Due to the novelty of the exercise, there were several lessons learned that will be presented in this report.

Abstract not provided.

Abstract not provided.

Laser powder bed fusion (LPBF) Additive Manufacturing (AM) has the potential to enable the production of components with novel designs and material properties unachievable otherwise. However, process repeatability is a challenge, making qualification ill-defined and greatly reducing the utility of what could be an important manufacturing technology. In this work, a combination of modeling, uncertainty quantification (UQ), and experimentation are used in an effort to predict and bound the range of possible outcomes of the LPBF process. Quantities of interest predicted are melt pool dimensions, microstructure features, and mechanical distortions. A combination of high fidelity thermal-fluid models, microstructure growth models, and reduced fidelity, rapid thermal and mechanical models are used. Uncertainty propagation techniques are used to predict probability distributions of quantities of interest from estimates of process uncertainties. Repeated experiments are done to quantify observed probability distributions and compared to predicted distributions to determine if predictions are precise and accurate. Novel modeling methods are microstrucutre characterization techniques are also discussed. It is found that high fidelity models do a generally good job bounding experimentally observed melt pool morphologies for both bead-on-plate and powder bed cases. Microstructure models are able to bound a number of experimentally observed microstructure statistics, but with low precision due to challenges with calibrating the microstructure growth model parameters. A developed modified inherent strain distortion model does not accurately predict observed distortions. A lumped laser distortion model shows promise in being both accurately and precisely bounding observed outcomes from the deflection comb build, but requires further evaluation on more builds and geometries.

We combine crossed-beam velocity map imaging with high-level ab initio/transition state theory modeling of the reaction of S(3P) with 1,3-butadiene and isoprene under single collision conditions. For the butadiene reaction, we detect both H and H2 loss from the initial adduct, and from reaction with isoprene, we see both H loss and methyl loss. Theoretical calculations confirm these arise following intersystem crossing to the singlet surface forming long-lived intermediates. For the butadiene reaction, these lose H2 to form thiophene as the dominant channel, H to form the detected 2H-thiophenyl radical, or ethene, giving thioketene. For isoprene, additional reaction products are suggested by theory, including the observed H and methyl loss radicals, but also methyl thiophene, thioformaldehyde, and thioketene. The results for S(3P) + 1,3-butadiene, showing direct cyclization to the aromatic product and yielding few bimolecular product channels, are in striking contrast to those for the analogous O(3P) reaction.

The US Department of Energy (DOE) is investigating the use of different materials that could be used to fill the void space inside a dual-purpose canister (DPC) loaded with spent nuclear fuel (SNF) just before it is emplaced in a deep geologic repository. The purpose of adding filler material is to maintain subcritical conditions in the repository during the postclosure period, which can span up to 1,000,000 years. Several types of materials have been proposed, including metals, cements, particulates, and glass. Part of this investigation addresses how the presence of filler material inside a DPC will affect the performance of the repository with respect to the repository features; the consequences of events that may occur; and the multiple thermal, hydrologic, chemical, and mechanical processes that may occur in a deep geologic repository over long timescales. This report describes some of the filler materials that have been proposed and studied; identifies 11 features, 6 events, and 25 processes that may be affected by the presence of filler materials; and discusses the effects that may require consideration for each feature, event, or process. The results of this study can be used to direct appropriate research and to develop suitable models if the DOE decides to use fillers to maintain subcritical conditions in DPCs used to dispose of SNF.

This report represents the milestone deliverable M2SF-23SN010301072 “Evaluation of Nuclear Spent Fuel Disposal in Clay-Bearing Rock - Process Model Development and Experimental Studies” The report provides a status update of FY23 activities for the work package Argillite Disposal work packages for the DOE-NE Spent Fuel Waste Form Science and Technology (SFWST) Program. Clay-rich geological media (often referred as shale or argillite) are among the most abundant type of sedimentary rock near the Earth’s surface. Argillaceous rock formations have the following advantageous attributes for deep geological nuclear waste disposal: widespread geologic occurrence, found in stable geologic settings, low permeability, self-sealing properties, low effective diffusion coefficient, high sorption capacity, and have the appropriate depth and thickness to host nuclear waste repository concepts. The DOE R&D program under the Spent Fuel Waste Science Technology (SFWST) campaign has made key progress (through experiment, modeling, and testing) in the study of chemical and physical phenomena that could impact the long-term safety assessment of heat-generating nuclear waste disposition in clay/shale/argillaceous rock. International collaboration activities comprising field-scale heater tests, field data monitoring, and laboratory-scale experiments provide key information on changes to the engineered barrier system (EBS) material exposed high thermal loads. Moreover, consideration of direct disposal of large capacity dual-purpose canisters (DPCs) as part of the back-end SNF waste disposition strategy has generated interest in improving our understanding of the effects of elevated temperatures on the engineered barrier system (EBS) design concepts. Chemical and structural analyses of sampled bentonite material from laboratory tests at elevated temperatures are key to the characterization of thermal effects affecting bentonite clay barrier performance. The knowledge provided by these experiments is crucial to constrain the extent of sacrificial zones in the EBS design during the thermal period. Thermal, hydrologic, mechanical, and chemical (THMC) data collected from heater tests and laboratory experiments have been used in the development, validation, and calibration of THMC simulators to model near-field coupled processes. This information leads to the development of simulation approaches to assess issues on coupled processes involving porous media flow, transport, geomechanical phenomena, chemical interactions with barrier/geologic materials, and the development of EBS concepts. These lines of knowledge are central to the design of deep geological backfilled repository concepts where temperature plays a key role in the EBS behavior, potential interactions with host rock, and long-term performance in the safety assessment.

Pressure-shear plate impact experiments were performed to quantify flow strength of wrought, as-built additively manufactured (AM), and heat-treated and recrystallized AM 304 L stainless steel (SS304L) under combined loading. Impact velocities spanned between 0.03 and 0.24 mm/μs, resulting in corresponding pressures of 0.62–5.93 GPa. Flow strength measurements are comparable for the sample variants across the studied loading conditions; however, shear wave structures significantly differ between sample type. Microstructurally aware simulations indicate local strain differences attributed to anisotropic elastic constants of large grains (~1 mm) in the as-built and heat-treated AM may impede the ability to uniformly transmit a shear wave.

This paper explores the utility of organizational system modeling frameworks to provide valuable insight into information flows within organizations and subsequently the opportunities for increasing resilience against disinformation campaigns targeting the system's ability to utilize information within its decision making. Disinformation is a growing challenge for many organizations and in recent years has created delay in decision making. Here the paper has utilized the viable systems model (VSM) to characterize organizational systems and used this approach to outline potential subsystem requirements to promote resilience of the system. The results of this paper can support the development of simulations and models considering the human elements within the system as well as support the development of quantitative measures of resilience.

Here, a method for the nonintrusive and structure-preserving model reduction of canonical and noncanonical Hamiltonian systems is presented. Based on the idea of operator inference, this technique is provably convergent and reduces to a straightforward linear solve given snapshot data and gray-box knowledge of the system Hamiltonian. Examples involving several hyperbolic partial differential equations show that the proposed method yields reduced models which, in addition to being accurate and stable with respect to the addition of basis modes, preserve conserved quantities well outside the range of their training data.

This paper is concerned with goal-oriented a posteriori error estimation for nonlinear functionals in the context of nonlinear variational problems solved with continuous Galerkin finite element discretizations. A two-level, or discrete, adjoint-based approach for error estimation is considered. The traditional method to derive an error estimate in this context requires linearizing both the nonlinear variational form and the nonlinear functional of interest which introduces linearization errors into the error estimate. In this paper, we investigate these linearization errors. In particular, we develop a novel discrete goal-oriented error estimate that accounts for traditionally neglected nonlinear terms at the expense of greater computational cost. We demonstrate how this error estimate can be used to drive mesh adaptivity. Here, we show that accounting for linearization errors in the error estimate can improve its effectivity for several nonlinear model problems and quantities of interest. We also demonstrate that an adaptive strategy based on the newly proposed estimate can lead to more accurate approximations of the nonlinear functional with fewer degrees of freedom when compared to uniform refinement and traditional adjoint-based approaches.

Grid-scale battery energy storage systems (BESSs) are vulnerable to false data injection attacks (FDIAs), which could be used to disrupt state of charge (SoC) estimation. Inaccurate SoC estimation has negative impacts on system availability, reliability, safety, and the cost of operation. In this article a combination of a Cumulative Sum (CUSUM) algorithm and an improved input noise-aware extended Kalman filter (INAEKF) is proposed for the detection and identification of FDIAs in the voltage and current sensors of a battery stack. The series-connected stack is represented by equivalent circuit models, the SoC is modeled with a charge reservoir model and the states are estimated using the INAEKF. Further, the root mean squared error of the states’ estimation by the modified INAEKF was found to be superior to the traditional EKF. By employing the INAEKF, this article addresses the research gap that many state estimators make asymmetrical assumptions about the noise corrupting the system. Additionally, the INAEKF estimates the input allowing for the identification of FDIA, which many alternative methods are unable to achieve. The proposed algorithm was able to detect attacks in the voltage and current sensors in 99.16% of test cases, with no false positives. Utilizing the INAEKF compared to the standard EKF allowed for the identification of FDIA in the input of the system in 98.43% of test cases.

The formation of a stress corrosion crack (SCC) in the canister wall of a dry cask storage system (DCSS) has been identified as a potential issue for the long-term storage of spent nuclear fuel. The presence of an SCC in a storage system could represent a through-wall flow path from the canister interior to the environment. Modern, vertical DCSSs are of particular interest due to the commercial practice of using higher backfill pressures in the canister, up to approximately 800 kPa, compared to their horizontal counterparts. This pressure differential offers a relatively high driving potential for blowdown of any particulates that might be present in the canister. In this study, the rates of gas flow and aerosol transmission of a spent fuel surrogate through an engineered microchannel with dimensions representative of an SCC were evaluated experimentally using coupled mass flow and aerosol analyzers. The microchannel was formed by mating two gage blocks with a linearly tapering slot orifice nominally 13 μm (0.005 in.) tall on the upstream side and 25 μm (0.0010 in.) tall on the downstream side. The orifice is 12.7 mm (0.500 in.) wide by 8.86 mm (0.349 in.) long (flow length). Surrogate aerosols of cerium oxide, CeO₂, were seeded and mixed with either helium or air inside a pressurized tank. The aerosol characteristics were measured immediately upstream and downstream of the simulated SCC at elevated and ambient pressures, respectively. These data sets are intended to add to previous testing that characterized SCCs under well-controlled boundary conditions through the inclusion of testing improvements that establish initial conditions in a more consistent way. While the engineered microchannel has dimensions similar to actual SCCs, it does not reproduce the tortuous path the aerosol laden flow would have to traverse for eventual transmission. SCCs can be rapidly grown in a laboratory setting given the right conditions, and initial characterization and clean-flow testing has begun on lab grown crack samples provided to Sandia National Laboratories (SNL). Many such samples are required to produce statistically relevant transmission results, and SNL is developing a procedure to produce samples in welded steel plates. These ongoing testing efforts are focused on understanding the evolution in both size and quantity of a hypothetical release of aerosolized spent fuel particles from failed fuel to the canister interior and ultimately through an SCC.

Sierra/SolidMechanics (Sierra/SM) is a Lagrangian, three-dimensional code for finite element analysis of solids and structures. It provides capabilities for explicit dynamic, implicit quasistatic and dynamic analyses. The explicit dynamics capabilities allow for the efficient and robust solution of models with extensive contact subjected to large, suddenly applied loads. For implicit problems, Sierra/SM uses a multi-level iterative solver, which enables it to effectively solve problems with large deformations, nonlinear material behavior, and contact. Sierra/SM has a versatile library of continuum and structural elements, and a large library of material models. The code is written for parallel computing environments enabling scalable solutions of extremely large problems for both implicit and explicit analyses. It is built on the SIERRA Framework, which facilitates coupling with other SIERRA mechanics codes. This document describes the functionality and input syntax for Sierra/SM.

Presented in this document is a small portion of the tests that exist in the Sierra/SolidMechanics (Sierra/SM) verification test suite. Most of these tests are run nightly with the Sierra/SM code suite, and the results of the test are checked versus the correct analytical result. For each of the tests presented in this document, the test setup, a description of the analytic solution, and comparison of the Sierra/SM code results to the analytic solution is provided. Mesh convergence is also checked on a nightly basis for several of these tests. This document can be used to confirm that a given code capability is verified or referenced as a compilation of example problems. Additional example problems are provided in the Sierra/SM Example Problems Manual. Note, many other verification tests exist in the Sierra/SM test suite, but have not yet been included in this manual.

Using compressive mechanical forces, such as pressure, to induce crystallographic phase transitions and mesostructural changes while modulating material properties in nanoparticles (NPs) is a unique way to discover new phase behaviors, create novel nanostructures, and study emerging properties that are difficult to achieve under conventional conditions. In recent decades, NPs of a plethora of chemical compositions, sizes, shapes, surface ligands, and self-assembled mesostructures have been studied under pressure by in-situ scattering and/or spectroscopy techniques. As a result, the fundamental knowledge of pressure-structure-property relationships has been significantly improved, leading to a better understanding of the design guidelines for nanomaterial synthesis. In the present review, we discuss experimental progress in NP high-pressure research conducted primarily over roughly the past four years on semiconductor NPs, metal and metal oxide NPs, and perovskite NPs. We focus on the pressure-induced behaviors of NPs at both the atomic- and mesoscales, inorganic NP property changes upon compression, and the structural and property transitions of perovskite NPs under pressure. We further discuss in depth progress on molecular modeling, including simulations of ligand behavior, phase-change chalcogenides, layered transition metal dichalcogenides, boron nitride, and inorganic and hybrid organic-inorganic perovskites NPs. These models now provide both mechanistic explanations of experimental observations and predictive guidelines for future experimental design. We conclude with a summary and our insights on future directions for exploration of nanomaterial phase transition, coupling, growth, and nanoelectronic and photonic properties.

Intimately intertwined atomic and electronic structures of point defects govern diffusion-limited corrosion and underpin the operation of optoelectronic devices. For some materials, complex energy landscapes containing metastable defect configurations challenge first-principles modeling efforts. Here, we thoroughly reevaluate native point defect geometries for the illustrative case of α-Al2O3 by comparing three methods for sampling candidate geometries in density functional theory calculations: displacing atoms near a naively placed defect, initializing interstitials at high-symmetry points of a Voronoi decomposition, and Bayesian optimization. We find symmetry-breaking distortions for oxygen vacancies in some charge states, and we identify several distinct oxygen split-interstitial geometries that help explain literature discrepancies involving this defect. We also report a surprising and, to our knowledge, previously unknown trigonal geometry favored by aluminum interstitials in some charge states. These new configurations may have transformative impacts on our understanding of defect migration pathways in aluminum-oxide scales protecting metal alloys from corrosion. Overall, the Voronoi scheme appears most effective for sampling candidate interstitial sites because it always succeeded in finding the lowest-energy geometry identified in this study, although no approach found every metastable configuration. Finally, we show that the position of defect levels within the band gap can depend strongly on the defect geometry, underscoring the need to conduct careful searches for ground-state geometries in defect calculations.

Presented in this document are tests that exist in the Sierra/SolidMechanics example problem suite, which is a subset of the Sierra/SM regression and performance test suite. These examples showcase common and advanced code capabilities. A wide variety of other regression and verification tests exist in the Sierra/SM test suite that are not included in this manual.

This user’s guide documents capabilities in Sierra/SolidMechanics which remain “in-development” and thus are not tested and hardened to the standards of capabilities listed in Sierra/SM 5.16 User’s Guide. Capabilities documented herein are available in Sierra/SM for experimental use only until their official release. These capabilities include, but are not limited to, novel discretization approaches such as the conforming reproducing kernel (CRK) method, numerical fracture and failure modeling aids such as the extended finite element method (XFEM) and J-integral, explicit time step control techniques, dynamic mesh rebalancing, as well as a variety of new material models and finite element formulations.

Presented in this document are the theoretical aspects of capabilities contained in the Sierra/SM code. This manuscript serves as an ideal starting point for understanding the theoretical foundations of the code. For a comprehensive study of these capabilities, the reader is encouraged to explore the many references to scientific articles and textbooks contained in this manual. It is important to point out that some capabilities are still in development and may not be presented in this document. Further updates to this manuscript will be made as these capabilities come closer to production level.

Pultrusion manufacturing of fiber reinforced polymers has been shown to yield some of the highest mechanical properties for unidirectional composites, having a high degree of fiber alignment with consistent performance. Pultrusions offer a low-cost manufacturing approach for producing unidirectional composites with a constant cross-section and are used in many applications, including spar caps of wind turbine blades. However, as an intermediate processing step for wind blades, the additional cost of manufacturing pultrusions must be accompanied by sufficient increases in mechanical performance and system benefits. Wind turbine blades are manufactured using vacuum-assisted resin transfer molding with infused unidirectional fiberglass or carbon pultrusions for the spar cap. Infused fiberglass composites are among the most cost-effective structural materials available and replacing this material in the cost-driven wind industry has proven challenging, where infused fiberglass spar caps are still the predominant material system in use. To evaluate alternative material systems in a pultruded composite form, it is necessary to understand the costs for this additional manufacturing step which are shown to add 33%–55% on top of the material costs. A pultrusion cost model has been developed and used to quantify cost sensitivities to various processing parameters. The mechanical performance for pultruded composites is improved versus resin-infusion manufacturing with a 17% increase in design strength at a constant fiber volume fraction, but also enables higher achievable fiber volume fractions. The cost-specific mechanical performance is compared as a function of processing parameters for pultruded composites to identify the opportunities for alternative material and manufacturing approaches for wind turbine spar caps. Finally, four materials are compared in a representative wind turbine blade model to assess the performance of pultruded carbon fiber systems and pultruded fiberglass relative to infused fiberglass, where the pultruded systems produce lower weight blades with various cost distinctions.

The objective of the crystalline disposal work packages is to advance our understanding of long-term disposal of used fuel in crystalline rocks and to develop necessary experimental and computational capabilities to evaluate various disposal concepts in such media.

Combinatorial research, the incorporation of multiple domains in a unified research agenda, is a strong contributor to the growing corpus of scientific knowledge and technological advancements worldwide. In 2019, a study team at Sandia National Laboratories (Sandia, the Labs) used a systems approach to understand if and how combinatorial research agendas were playing out at Sandia, one of America’s premiere national security research venues. The study team used the data collection effort described in this report to ground the discussion of the broad social environment and particular organizational environments within which combinatorial research agendas are developed, as described in the full study. The team interviewed twenty-five staff members engaged in combinatorial research at Sandia in New Mexico and California during the months of June – September 2019. Analysis of this corpus of ethnographic data, combined with knowledge drawn from relevant literature, concluded that there is an individual type who would be most likely to engage in combinatoric research, described by both demographic and psychographic components. This type demonstrates both intellectual depth and the curiosity which leads to breadth. The analysis also showed that Sandia as an organization and as perceived by the respondents, set up tension for the combinatorial researcher. While Sandia was generally agnostic towards combinatorial research, that agnostic posture depended on whether the researcher was able to fulfill all her customer obligations – obligations that are structured primarily in transactional relationships with customers with relatively short time horizons. This report concludes with suggestions for additional research in the ethnographic domain.

Barium titanate (BTO) is a widely researched ferroelectric useful for energy storage. While BTO’s surface chemistry is commonly studied using density functional theory, little has been published on the TiO₂ surface. Here, we determined that BTO’s surface response can be decoupled from the ferroelectric response by using a pre-optimized ferroelectric slab and allowing only the top three atomic z-layers to respond to ligand binding. Multiple favorable binding modes were identified for hydrogen, hydroxyl, water, and tert-butyl phosphonic acid on BTO’s TiO₂ surface. Of these ligands, tBuPA dominates surface binding with binding energies as low as -2.61 eV for its nine configurations.

The hydrogen sorption properties of single-phase bcc (TiVNb)100-xCrx alloys (x = 0-35) are reported. All alloys absorb hydrogen quickly at 25 °C, forming fcc hydrides with storage capacity depending on the Cr content. A thermodynamic destabilization of the fcc hydride is observed with increasing Cr concentration, which agrees well with previous compositional machine learning models for metal hydride thermodynamics. The steric effect or repulsive interactions between Cr-H might be responsible for this behavior. The cycling performances of the TiVNbCr alloy show an initial decrease in capacity, which cannot be explained by a structural change. Pair distribution function analysis of the total X-ray scattering on the first and last cycled hydrides demonstrated an average random fcc structure without lattice distortion at short-range order. If the as-cast alloy contains a very low density of defects, the first hydrogen absorption introduces dislocations and vacancies that cumulate into small vacancy clusters, as revealed by positron annihilation spectroscopy. Finally, the main reason for the capacity drop seems to be due to dislocations formed during cycling, while the presence of vacancy clusters might be related to the lattice relaxation. Having identified the major contribution to the capacity loss, compositional modifications to the TiVNbCr system can now be explored that minimize defect formation and maximize material cycling performance.

Immune checkpoint immunotherapy (ICI) can re-activate immune reactions against neoantigens, leading to remarkable remission in cancer patients. Nevertheless, only a minority of patients are responsive to ICI, and approaches for prediction of responsiveness are needed to improve the success of cancer treatments. While the tumor mutational burden (TMB) correlates positively with responsiveness and survival of patients undergoing ICI, the influence of the subcellular localizations of the neoantigens remains unclear. Here, we demonstrate in both a mouse melanoma model and human clinical datasets of 1,722 ICI-treated patients that a high proportion of membrane-localized neoantigens, particularly at the plasma membrane, correlate with responsiveness to ICI therapy and improved overall survival across multiple cancer types. We further show that combining membrane localization and TMB analyses can enhance the predictability of cancer patient response to ICI. Our results may have important implications for establishing future clinical guidelines to direct the choice of treatment toward ICI.

Recent advances in the growth of aluminum scandium nitride films on silicon suggest that this material platform could be applied for quantum electromechanical applications. Here, we model, fabricate, and characterize microwave frequency silicon phononic delay lines with transducers formed in an adjacent aluminum scandium nitride layer to evaluate aluminum scandium nitride films, at 32% scandium, on silicon interdigital transducers for piezoelectric transduction into suspended silicon membranes. We achieve an electromechanical coupling coefficient of 2.7% for the extensional symmetric-like Lamb mode supported in the suspended material stack and show how this coupling coefficient could be increased to at least 8.5%, which would further boost transduction efficiency and reduce the device footprint. The one-sided transduction efficiency, which quantifies the efficiency at which the source of microwave photons is converted to microwave phonons in the silicon membrane, is 10% at 5 GHz at room temperature and, as we discuss, there is a path to increase this toward near-unity efficiency based on a combination of modified device design and operation at cryogenic temperatures.

This FY2023 report is the second update to the Disposal Research (DR) Research and Development (R&D) 5-year plan for the Spent Fuel and Waste Science and Technology (SFWST) Campaign DR R&D activities. In the planning for FY2020 in the U.S. Department of Energy (DOE) NE-81 SFWST Campaign, the DOE requested development of a high-level summary plan for activities in the DR R&D program for the next five (5)-year period, with periodic updates to this summary plan. The DR R&D 5-year plan was provided to the DOE based initially on the FY2020 priorities and program structure (initial 2020 version of this 5-year plan) and provides a strategic summary guide to the work within the DR R&D technical areas (Control Accounts, CA), focusing on the highest priority technical thrusts. This 5-year plan is a living document (planned to be updated periodically) that provides review of SFWST R&D accomplishments (as seen on the 2021 revision of this 5-year plan), describes changes to technical R&D prioritization based on (a) progress in each technical area (including external technical understanding) with specific accomplishments and (b) any changes in SFWST Campaign objectives and/or funding levels (i.e., Program Direction). Updates to this 5-year plan include the DR R&D adjustments to high-priority knowledge gaps to be investigated in the near-term, as well as the updated longer-term DR R&D directions for the program activities. This plan fulfills the Milestone M2SF23SN010304083 in DR Work Package (WP) SF-23SN01030408 (GDSA - Framework Development – SNL).

Here, we present a classical interatomic force field, silica-DDEC, to describe the interactions of amorphous and crystalline silica surfaces, parametrized using density functional theory-based charges. Charge schemes for silica surfaces were developed using the density-derived electrostatic and chemical (DDEC) method, which reproduces atomic charges of the periodic models as well as the electrostatic potential away from the atom sites. Lennard–Jones parameters were determined by requiring the correct description of (i) the amorphous silica density, coordination defects, and local coordination geometry, relative to experimental measurements, and (ii) water-silica interatomic distances compared with ab initio results. Deprotonated surface silanol sites are also described within the model based on DDEC charges. The result is a general electronic structure-derived model for describing fully flexible amorphous and crystalline silica surfaces and interactions of liquids with silica surfaces of varying structure and protonation state.

This report summarizes the activities performed by Sandia National Laboratories in FY23 to identify and test coating materials for the prevention, mitigation, and/or repair of potential chloride-induced stress corrosion cracking in spent nuclear fuel dry storage canisters. This work continues efforts by Sandia National Laboratories that are summarized in previous reports from FY20 through FY22 on the same topic. In FY23, Sandia National Laboratories, in collaboration with five industry partners through a memorandum of understanding, evaluated the physical, mechanical, and corrosion-resistance properties of eight different coating systems. The evaluation included thermal and radiation environments relevant to various time periods of storage for spent nuclear fuel canisters. The coating systems include polymeric (polyetherketoneketone, modified polyimide/polyurea, modified phenolic resin, epoxy), organic/inorganic ceramic hybrids (silane-based polyurethane hybrid and a quasi-ceramic sol-gel polyurethane hybrid), and coatings utilizing a Zn-rich primer applied to stainless steel coupons. The results and implications of these tests are summarized in this report. These analyses will be used to identify the most effective coatings for potential use on spent nuclear fuel dry storage canisters and to identify specific needs for further optimization of coating technologies for application on spent nuclear fuel canisters.

Here we have observed the behavior of striations caused by ionization waves propagating in low-pressure helium DC discharges using the non-invasive laser-collision induced fluorescence (LCIF) diagnostic. To achieve this, we developed an analytic fit of collisional radiative model (CRM) predictions to interpret the LCIF data and recover quantitative two-dimensional spatial maps of the electron density, n_e, and the ratios of LCIF emission states that can be correlated with T_e with the use of accurate distribution functions at localized positions within striated helium discharges at 500 mTorr, 750 mTorr, and 1 Torr. To our knowledge, these are the first spatiotemporal, laser-based, experimental measurements of n_e in DC striations. The n_e and 447:588 ratio distributions align closely with striation theory. Constriction of the positive column appears to occur with decreased gas pressure, as shown by the radial n_e distribution. We identify a transition from a slow ionization wave to a fast ionization wave between 750 mTorr and 1 Torr. These experiments validate our analytic fit of n_e, allowing the implementation of an LCIF diagnostic in helium without the need to develop a CRM.

Chemically robust, low-power sensors are needed for the direct electrical detection of toxic gases. Metal-organic frameworks (MOFs) offer exceptional chemical and structural tunability to meet this challenge, though further understanding is needed regarding how coadsorbed gases influence or interfere with the electrical response. To probe the influence of competitive gases on trace NO2 detection in a simulated flue gas stream, a combined structure-property study integrating synchrotron powder diffraction and pair distribution function analyses was undertaken, to elucidate how structural changes associated with gas binding inside Ni-MOF-74 pores correlate with the electrical response from Ni-MOF-74-based sensors. Data were evaluated for 16 gas combinations of N2, NO2, SO2, CO2, and H2O at 50 °C. Fourier difference maps from a rigid-body Rietveld analysis showed that additional electron density localized around the Ni-MOF-74 lattice correlated with large decreases in Ni-MOF-74 film resistance of up to a factor of 6 × 103, observed only when NO2 was present. These changes in resistance were significantly amplified by the presence of competing gases, except for CO2. Without NO2, H2O rapidly (<120 s) produced small (1-3×) decreases in resistance, though this effect could be differentiated from the slower adsorption of NO2 by the evaluation of the MOF’s capacitance. Furthermore, samples exposed to H2O displayed a significant shift in lattice parameters toward a larger lattice and more diffuse charge density in the MOF pore. Evaluating the Ni-MOF-74 impedance in real time, NO2 adsorption was associated with two electrically distinct processes, the faster of which was inhibited by competitive adsorption of CO2. Together, this work points to the unique interaction of NO2 and other specific gases (e.g., H2O, SO2) with the MOF’s surface, leading to orders of magnitude decrease in MOF resistance and enhanced NO2 detection. Understanding and leveraging these coadsorbed gases will further improve the gas detection properties of MOF materials.

We present an experimental study on a terahertz quantum cascade laser (THz QCL) design that combines both two-well injector and direct-phonon scattering schemes, i.e., a so-called two-well injector direct-phonon design. As a result of the two-well injector direct-phonon scheme presented here, the lasers benefit from both a direct phonon scattering scheme for the lower laser level depopulation and a setback for the doping profile that reduces the overlap of the doped region with active laser states. Additionally, our design also has efficient isolation of the active laser levels from excited and continuum states as indicated by negative differential resistance behavior all the way up to room temperature. This scheme serves as a good platform for improving the temperature performance of THz QCLs as indicated by the encouraging temperature performance results of the device with a relatively high doping level of 7.56 × 10¹⁰ cm⁻² and T_max ∼ 167 K. With the right optimization of the molecular beam epitaxy growth and interface quality, the injection coupling strength, and the doping density and its profile, the device could potentially reach higher temperatures than the latest records reached for the maximum operating temperature (T_max) of THz QCLs.

Short-ranged and line-gapped non-Hermitian Hamiltonians have strong topological invariants given by an index of an associated Fredholm operator. It is shown how these invariants can be accessed via the signature of a suitable spectral localizer. Here, this numerical technique is implemented in an example with relevance to the design of topological photonic systems, such as topological lasers.

Over the past few decades, inorganic nitride materials have grown in importance in part due to their potential as catalysts for the synthesis of NH3, a key ingredient in fertilizer and precursor to industrial chemicals. Of particular interest are the ternary (ABN) or higher-order nitrides with high metal-to-nitrogen ratios that show promise in enhancing NH3 synthesis reaction rates and yields via heterogeneous catalysis or chemical looping. Although metal nitrides are predicted to be numerous, the stability of nitrogen triple bonds found in N2, especially in comparison to the metal-nitrogen bonds, has considerably hindered synthetic efforts to produce complex nitride compounds. In this study, we present an exhaustive down-selection process to identify ternary nitrides for a promising chemical looping NH3 production mechanism. We also report on a facile and efficient two-step synthesis method that can produce well-characterized η-carbide Co3Mo3N/Fe3Mo3N or filled β-manganese Ni2Mo3N ternaries, as well as their associated quaternary, (Co,Fe)3Mo3N, (Fe,Ni)2Mo3N, and (Co,Ni)2Mo3N, solid solutions. To further explore the quaternary space, syntheses of (Co,Ni)3Mo3N (Ni ≤ 10 mol %) and Co3(Mo,W)3N (W ≤ 10 mol %) were also investigated. The structures of the nitrides were characterized via X-ray powder diffraction. The morphology and compositions were characterized with scanning electron microscopy. The multitude of chemically unique, but structurally related, nitrides suggests that properties such as nitrogen activity may be tunable, making the materials of great interest for NH3 synthesis schemes.

Cryosphere/Ocean Distributed Acoustic Sensing (CODAS) data collected from the Beaufort Sea, Alaska, using ~37.4 km of dark telecommunications fiber located at Oliktok Point, Alaska. Data were collected with a Silixa iDAS, using 10 m gauge length, 2 m spatial resolution, and 1000 Hz sample rate. Provided here are the DAS-recorded time series for the rapid refreeze event described in Baker & Abbott (2022) (see link below). This covers a date range of 2021-11-10 15:00 UTC to 2021-11-11 17:00 UTC. Data have been decimated to 100 Hz and 20 m (i.e., every 10th channel for 1831 channels, total), as used in Baker & Abbott (2022). Data have been extracted from raw format into 1-hour long .sac* files and organized into directories by channel number, spanning channels 100 to 18400. Time series units are nano-strainrate (nm/m/s). For distribution, data have been compressed into .zip files containing all time series files for 100 channels. *For information on the Seismic Analysis Code (SAC) file format: https://seiscode.iris.washington.edu/projects/sac