Publications

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Sandia’s Grid Modernization and Energy Storage program works to advance a national vision of a secure, resilient, and sustainable electric system for all users. Our achievements reflect a strategic approach combining technology development; modeling, simulation, and data analytics; and partnered demonstrations and outreach to further the adoption of advanced grid and storage technologies. Our FY22 efforts leverage the strengths of our partnerships—spanning Sandia’s core science and technology competencies as well as external technology leaders—to develop the solutions today which enable the grid of tomorrow. Much of the material in this report comes from the separate 2022 Accomplishments Report compiled by our Energy Storage subprogram team, a cornerstone of our grid research and achievements. The Grid Energy Storage Program at Sandia is focused on making energy storage cost-effective through research and development (R&D) in new battery technologies, advanced power electronics and power conversion systems, improved safety and reliability for energy storage systems, analytical tools for the valuation of energy storage, and the validation of new energy storage technologies through demonstration projects. During the 2022 fiscal year, Sandia executed R&D work supported by the U.S. Department of Energy’s (DOE) Office of Electricity – Energy Storage Program under the leadership of Dr. Imre Gyuk. This report indicates key areas of research and engagement and summarizes the impact of Sandia’s contributions through notable accomplishments, journal publications, patents, and technical conferences and presentations. It is provided with the hope that readers discover ways we can further team to create our modern grid and apply the outcomes of our efforts. The bulk of work described herein is funded by the DOE Office of Electricity and key programs within the DOE Office of Energy Efficiency and Renewable Energy. As we indicated in our report from last year, the contributors to our successes are too numerous to name here, though our team wishes to express our deep gratitude to the numerous program and project sponsors at the US Department of Energy, who often function equally as technical collaborators; our many partners in industry, academia, utilities, and other national labs; and fellow researchers and business partners at Sandia whose leadership and creativity have enabled the accomplishments described herein.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Lignocellulose forms plant cell walls, and its three constituent polymers, cellulose, hemicellulose and lignin, represent the largest renewable organic carbon pool in the terrestrial biosphere. Insights into biological lignocellulose deconstruction inform understandings of global carbon sequestration dynamics and provide inspiration for biotechnologies seeking to address the current climate crisis by producing renewable chemicals from plant biomass. Organisms in diverse environments disassemble lignocellulose, and carbohydrate degradation processes are well defined, but biological lignin deconstruction is described only in aerobic systems. It is currently unclear whether anaerobic lignin deconstruction is impossible because of biochemical constraints or, alternatively, has not yet been measured. We applied whole cell-wall nuclear magnetic resonance, gel-permeation chromatography and transcriptome sequencing to interrogate the apparent paradox that anaerobic fungi (Neocallimastigomycetes), well-documented lignocellulose degradation specialists, are unable to modify lignin. We find that Neocallimastigomycetes anaerobically break chemical bonds in grass and hardwood lignins, and we further associate upregulated gene products with the observed lignocellulose deconstruction. These findings alter perceptions of lignin deconstruction by anaerobes and provide opportunities to advance decarbonization biotechnologies that depend on depolymerizing lignocellulose.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Plasmonic heating by nanoparticles has been used to promote a range of chemical reactions. Now, thermoplasmonic activation has been applied to latent ruthenium catalysts, enabling olefin metathesis initiated by visible and infrared light. Additionally, the desire to harness light to drive chemical transformations has surely existed as long as the study of chemistry itself. In the earliest documented applications, light was used simply as a heat source — for example, in the distillation of liquids. Since that time, our knowledge of how light and matter interact has increased exponentially, with greater mechanistic and molecular understanding enabling modern photochemists to design molecules with a myriad of finely tuned optical properties for catalysis, biochemistry, optoelectronics and more. Nonetheless, the design and optimization of molecules to achieve specific optical properties is still challenging, and for some applications, a return to the ‘simplest’ transformation — that of light to heat — can offer a more efficient approach to achieve light-mediated chemical reactions. Now, writing in Nature Chemistry, Yossi Weizmann and colleagues describe a strategy for organic and polymer synthesis driven by the conversion of light to heat.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Fogs, low lying clouds, and other highly scattering environments pose a challenge for many commercial and national security sensing systems. Current autonomous systems rely on optical sensors for navigation whose performance is degraded by highly scattering environments. In our previous simulation work, we have shown that polarized light can penetrate through a scattering environment such as fog. We have demonstrated that circularly polarized light maintains its initial polarization state better than linearly polarized light, even through large numbers of scattering events and thus ranges. This has recently been experimentally verified by other researchers. In this work, we present the design, construction, and testing of active polarization imagers at short-wave infrared and visible wavelengths. We explore multiple polarimetric configurations for the imagers, focusing on linear and circular polarization states. The polarized imagers were tested at the Sandia National Laboratories Fog Chamber under realistic fog conditions. We show that active circular polarization imagers can increase range and contrast in fog better than linear polarization imagers. We show that when imaging typical road sign and safety retro-reflective films, circularly polarized imaging has enhanced contrast throughout most fog densities/ranges compared to linearly polarized imaging and can penetrate over 15 to 25 m into the fog beyond the range limit of linearly polarized imaging, with a strong dependence on the interaction of the polarization state with the target materials.

ATP-5 aluminum alloy was considered as an alternative to 6061-T651 aluminum alloy to minimize machining distortion. ATP-5 is a proprietary cast alloy that is compositionally similar to 5083 aluminum and is purported to have excellent machinability, stability, and corrosion response. Dimensional stability tests, mechanical testing, chemical analysis, microstructural analysis, and fractography were completed to understand the metallurgy of the ATP-5 alloy and assess its potential as a 6061-T651 alloy alternative. Ultimately, the ATP-5 was found to retain dimensional stability issues, albeit to a lesser extent, relative to the 6061-T651 alloy. Combined with the residual cast structure observed microstructurally and lot-to-lot mechanical property variation, the alloy was deemed not suitable for a structural application. Alternative uses of ATP-5 include tooling, molds, vacuum chucks, fixtures, and jigs, where the material can shine in non-load bearing applications with a need for dimensional control and machinability.

In this report, we developed and validated a network protector relay digital twin model and interfaced a commonly used network protector relay hardware with our real-time simulation system. Hardware-in-the-loop protection studies are performed to assess the impact of distributed energy resources (DER) and benchmark a rate-of-change-based mitigation strategy. Simulation results suggest that the network protector reverse trip and auto-reclose functions are negatively impacted by the high distributed energy resource penetration. To accommodate DER backfeed while remaining secure and reliable for faults on primary feeders, we recommend options for a rate-of-change-based blocking scheme and a protection setting change. Finally, future mitigation ideas and standard revisions are discussed.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Confidence assessment is critical for effective automatic target recognition (ATR). Productive use and interpretation of ATR results by analysts or downstream algorithms requires not only algorithmic declarations of target presence and identity, but also algorithmic assessment of the certainty of those declarations in comparison to the certainties of alternative target-identity possibilities. Unfortunately, despite its importance, confidence assessment is an understudied, underdeveloped, and often-neglected function of ATR systems. This lack of regard stems not only from the difficulty of accurate algorithmic determination of target-identity certainty, but also from a general lack of understanding and careful consideration about what confidence should actually represent. We present a framework for confidence assessment that establishes a clear definition of confidence and provides a straightforward theoretical basis for its calculation. This framework is grounded in a hypothesis-theoretic consideration of ATR and it springs from from a handful of axiomatic principles concerning the nature and meaning of confidence in this context. This framework establishes a rigorous mathematical definition of confidence and it provides equations relating confidence to other information that is almost always provided by ATRs. We present an approach for computing confidence within this framework, using an advance process of ATR characterization followed by a simple computation at the time of ATR execution. We discuss practical difficulties with our approach, and we suggest methods for effective mitigation of these difficulties in implemented systems.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Neodymium (Nd), a rare earth element (REE), is critical to numerous industries. Neodymium can be extracted from ore concentrates, waste materials, or recycled materials such as recycled Nd-Fe-B permanent magnets. In a standard process, concentrated sulfuric acid (H2SO4) is used as an extraction/leaching agent. Therefore, knowledge of Nd(III)–sulfate interaction at high ionic strengths is important for optimization of the extraction process. In addition, sulfate is also a major species in natural surface waters and present in nuclear waste streams. Nd(III) has been used a chemical analog to trivalent actinides in nuclear waste research and development. Consequently, knowledge of Nd(III)-sulfate interactions is also impactful to the field of nuclear waste management. In this study, we have developed a thermodynamic model that can describe the interaction of Nd(III) with sulfate to ionic strengths up to ~ 16.5 mol·kg–1 and to temperatures up to 100 °C. The model adopts the Pitzer formulation to describe activity coefficients of aqueous species. This model can be used to design and optimize a chemical process for REE recovery from ore concentrates, recycled materials, and acid mine drainage (AMD) and to understand the mobility of REEs and actinides in the environment.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

The computational modeling of nearly incompressible materials is a difficult task for many numerical methods, and even after several decades of investigation, it is still an active research area. This report seeks to address the treatment of incompressible materials in meshfree methods using a synergistic combination of two treatments. The first treatment is an $\bar{F}$ method, where the decomposed dilatational and deviatoric parts are calculated over different smoothing domains. The second treatment “activates” additional nodes throughout the domain to increase the flexibility of the model. We implement this synergistic combination in the context of the reproducing kernel particle method (RKPM) and present results for the Cook’s membrane benchmark problem. The results are compared with those using the composite tet10 finite element with a volume-averaged J formulation. We show that the combined treatment is an effective way to deal with nearly incompressible materials in a meshfree framework and compares well with other highly-effective treatments.

Abstract not provided.

Seismic waveform data are generally contaminated by noise from various sources, which interfere with the signals of interest. In this study, we implemented and applied several noise suppression methods using data recorded by the regional network of the University of Utah Seismograph stations. The denoising methods, consisting of approaches based on nonlinear thresholding of continuous wavelet transforms (CWTs, e.g., Langston and Mousavi, 2019), convolutional neural network (CNN) denoising (Tibi et al., 2021), and frequency filtering, were all subjected to the same analyses and level of scrutiny. We found that for frequency filtering, the improvement in signal-to-noise ratio (SNR) decreases quickly with decreasing SNR of the input waveform, and that below an input SNR of about 32 dB the improvement is relatively marginal and nearly constant. In contrast, the SNR gains are low at high-input SNR and increase with decreasing input SNR to reach the top of the plateaus corresponding to gains of about 18 and 23 dB, respectively, for CWT and CNN denoising. The low gains at high-input SNRs for these methods can be explained by the fact that for an input waveform with already high SNR (low noise), only very little improvement can be achieved by denoising, if at all. Results involving 4780 constructed waveforms suggest that in terms of degree of fidelity for the denoised waveforms with respect to the ground truth seismograms, CNN denoising outperforms both CWT denoising and frequency filtering. Onset time picking analyses by an experienced expert analyst suggest that CNN denoising allows more picks to be made com-pared with frequency filtering or CWT denoising and is on par with the expert analyst’s processing that follows current operational procedure. The CWT techniques are more likely to introduce artifacts that made the waveforms unusable.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

In this study, oils from various sources were subjected to pyrolysis conditions; that is, without oxidizer, as the samples were heated to 500 °C, and held at that temperature. The oils studied included: (1) heavy oil from Grassy Creek, Missouri; (2) oil from tar sands of Asphalt Ridge in Utah; (3) mid-continent oil shales of three formations (two of Chattanooga formation, Pennsylvanian (age) formation, and Woodford formation); and (4) a Colorado Piceance Basin shale. Differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA) with either gas chromatography (GC) or mass spectrometry (MS) were used to quantify the produced gases evolved in the tests. Purge gases of helium, argon, and humid carbon dioxide were utilized. Larger scale pyrolysis tests were conducted in a tube furnace coupled to a MS and a GC. The results consistently showed that pyrolysis occurred between 300 °C and 500 °C, with the majority of gases being mainly hydrogen and light alkanes. This behavior was essentially consistent, regardless of the oil source.

Abstract not provided.

Abstract not provided.

Abstract not provided.

For computational physics simulations, code verification plays a major role in establishing the credibility of the results by assessing the correctness of the implementation of the underlying numerical methods. In computational electromagnetics, surface integral equations, such as the method-of-moments implementation of the magnetic-field integral equation, are frequently used to solve Maxwell's equations on the surfaces of electromagnetic scatterers. These electromagnetic surface integral equations yield many code-verification challenges due to the various sources of numerical error and their possible interactions. In this paper, we provide approaches to separately measure the numerical errors arising from these different error sources. We demonstrate the effectiveness of these approaches for cases with and without coding errors.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

The Source Physics Experiment series is a long-term research and development (R&D) effort under the U.S. Department of Energy’s National Nuclear Security Administration focused on improving the physical understanding of how chemical explosions generate seismoacoustic signals. Beginning in 2011, a series of subsurface chemical explosions in two different and highly contrasting geologies were conducted at the Nevada National Security Site in Nevada, USA with the objective of improving simulation and modeling approaches to explosion identification, yield estimation and other monitoring applications. The two executed phases of the series provide new explosion signature source data from a wide range of geophysical diagnostic equipment; recorded data from the test series is now openly available to the broader seismoacoustic community. This manuscript details the executed test series, deployed seismoacoustic networks, and summarizes major scientific achievements utilizing recorded signatures from the explosive tests.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

An analytical expression is derived for the thermal response observed during spontaneous imbibition of water into a dry core of zeolitic tuff. Sample tortuosity, thermal conductivity, and thermal source strength are estimated from fitting an analytical solution to temperature observations during a single laboratory test. The closed-form analytical solution is derived using Green's functions for heat conduction in the limit of “slow” water movement; that is, when advection of thermal energy with the wetting front is negligible. The solution has four free fitting parameters and is efficient for parameter estimation. Laboratory imbibition data used to constrain the model include a time series of the mass of water imbibed, visual location of the wetting front through time, and temperature time series at six locations. The thermal front reached the end of the core hours before the visible wetting front. Thus, the predominant form of heating during imbibition in this zeolitic tuff is due to vapor adsorption in dry zeolitic rock ahead of the wetting front. The separation of the wetting front and thermal front in this zeolitic tuff is significant, compared to wetting front behavior of most materials reported in the literature. This work is the first interpretation of a thermal imbibition response to estimate transport (tortuosity) and thermal properties (including thermal conductivity) from a single laboratory test.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

The predictive capability maturity model (PCMM) uses the expert elicitation process to generate credibility evidence for a particular analysis. To ensure Gemma has the capability to efficiently produce this credibility evidence, next generation workflows (NGW) are created for the solution verification, calibration/validation, and input uncertainty quantification portions of the PCMM assessment. These workflows are then used on the Higgins cylinder problem, which is representative of applications involving external-to-internal electromagnetic field coupling through a slot. The uncertainties calculated using these workflows are then used to calculate the validation comparison error and the validation uncertainty for the model following the American Society of Mechanical Engineers (ASME) verification and validation (V&V) 20 standard. These workflows will enable analysts to iterate each element of PCMM more efficiently than if completed without using a NGW workflow. An example of this iterative process is shown in Section 7.2.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Chalcogenide Phase Change Materials (PCM) and metal insulator transition (MIT) materials are a group of materials that are capable of switching between low resistance and high resistance states. These emerging materials have been widely used in optical storage media and memory devices. Over the past recent years, there have been interests in exploiting the PCM and MIT materials, especially germanium antimony telluride (GST) alloys and vanadium dioxide (VO2), for radio frequency (RF) applications. The PCM and MIT-based RF devices are expected to bridge the gap between semiconductor switches and microelectromechanical system (MEMS) switches as they combine the low insertion loss performance of MEMS technology and the small size and reliability performance of semiconductor technology. This article presents an overview of the PCM and MIT materials for RF circuits and discusses the recent advancements in reconfigurable millimeter-wave (mmWave) devices based on PCM and MIT materials in depth.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Software reverse engineering (RE) requires analysts to closely read and make decisions about code. Little is known about what makes an analyst successful, making it difficult to train new analysts or design tools to augment existing ones. The goal of this project was to quantify the eye movement behaviors supporting RE and code comprehension more generally. We applied eye-tracking methods from the language comprehension literature to understand where analysts direct their attention over time when completing tasks (e.g., function identification, bug detection). Across three studies, we manipulated aspects of code hypothesized to impact comprehension (e.g., variable name meaningfulness, code complexity) and presentation methods (e.g., line-by-line, free viewing, gaze-contingent moving window) to understand effects on accuracy and gaze patterns. Results showed clear benefits of meaningful variable names, and effects of expertise on global and line-specific viewing patterns. Findings could inspire empirically-supported tool or analytic adaptations that help to reduce analyst workload.

Abstract not provided.

Pitting corrosion was evaluated on stainless steels 304H, 304, and 316L the surfaces of which had ASTM seawater printed on them as a function of surface roughness after exposure to an exemplar realistic atmospheric diurnal cycle for up to one year. Methods to evaluate pitting damage included optical imaging, scanning electron microscopy imaging, profilometry analysis, and polarization scans. The developed cyclic exposure environment did not significantly influence pitting morphology nor depth in comparison to prior static exposure environments. Cross-hatching was observed in a majority of pits for all material compositions with the roughest surface finish (#4 finish) and in all surface finishes for the 304H composition. Evidence is provided that cross-hatched pit morphologies are caused by slip bands produced during the grinding process for the #4 finish or by material processing. Additionally, micro-cracking was observed in pits formed on samples with the #4 surface finish and was greatly reduced or absent for pits formed on samples with smooth surface finishes. This suggests that both a low RH leading to an MgCl2-dominated environment and a rough surface containing significant residual stress are necessary for micro-cracking. Finally, the use of various characterization techniques and cross sectioning was employed to both qualitatively and quantitatively assess pitting damage across all SS compositions and surface finishes.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Radiation-hard high-voltage vertical GaN p-n diodes are being developed for use in power electronics subjected to ionizing radiation. We present a comparison of the measured and simulated photocurrent response of diodes exposed to ionizing irradiation with 70 keV and 20 MeV electrons at dose rates in the range of 1.4× 107 - 5.0× 108 rad(GaN)/s. The simulations correctly predict the trend in the measured steady-state photocurrent and agree with the experimental results within a factor of 2. Furthermore, simulations of the transient photocurrent response to dose rates with uniform and non-uniform ionization depth profiles uncover the physical processes involved that cannot be otherwise experimentally observed due to orders of magnitude larger RC time constant of the test circuit. The simulations were performed using an eXploratory Physics Development code developed at Sandia National Laboratories. The code offers the capability to include defect physics under more general conditions, not included in commercially available software packages, extending the applicability of the simulations to different types of radiation environments.

This work describes a structured, risk-based approach for analyzing questions related to the potential deployment of a climate intervention in any user-established future scenario, and further provides a structured means for considering what the potential consequences of such interventions may be. Because the climatological, technological, and geopolitical conditions are currently not believed to be supportive of climate intervention use, the framework establishes a three-pronged approach to frame key analytical questions predicated on future scenarios of interest to the user. These three pieces are: (1) Building a scenario. (2) Assessing the likelihood of that scenario based on assumptions about an actor and their motivations for deploying a climate intervention. (3) Analyzing the potential consequences of that climate intervention. Finally, results from this consequence analysis are compared against projected consequences of unabated climate change as a complete risk analysis of deploying a climate intervention.

Abstract not provided.

Abstract not provided.

Nanocrystalline metals are inherently unstable against thermal and mechanical stimuli, commonly resulting in significant grain growth. Also, while these metals exhibit substantial Hall-Petch strengthening, they tend to suffer from low ductility and fracture toughness. With regard to the grain growth problem, alloying elements have been employed to stabilize the microstructure through kinetic and/or thermodynamic mechanisms. And to address the ductility challenge, spatially-graded grain size distributions have been developed to facilitate heterogeneous deformation modes: high-strength at the surface and plastic deformation in the bulk. In the present work, we combine these two strategies and present a new methodology for the fabrication of gradient nanostructured metals via compositional means. We have demonstrated that annealing a compositionally stepwise Pt-Au film with a homogenous microstructure results in a film with a spatial microstructural gradient, exhibiting grains which can be twice as wide in the bulk compared to the outer surfaces. Additionally, phase-field modeling was employed for the comparison with experimental results and for further investigation of the competing mechanisms of Au diffusion and thermally induced grain growth. This fabrication method offers an alternative approach for developing the next generation of microstructurally stable gradient nanostructured films.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

The Sandia National Laboratories, in California (Sandia/CA) is a research and development facility, owned by the U.S. Department of Energy’s National Nuclear Security Administration agency (DOE/NNSA). The laboratory is located in the City of Livermore (the City) and is comprised of approximately 410 acres. The Sandia/CA facility is operated by National Technology and Engineering Solutions of Sandia, LLC (NTESS) under a contract with the DOE/NNSA. The DOE/ NNSA’s Sandia Field Office (SFO) oversees the operations of the site. North of the Sandia/CA facility is the Lawrence Livermore National Laboratory (LLNL), in which Sandia/CA’s sewer system combines with before discharging to the City’s Publicly Owned Treatment Works (POTW) for final treatment and processing. The City’s POTW authorizes the wastewater discharge from Sandia/CA via the assigned Wastewater Discharge Permit #1251 (the Permit), which is issued to the DOE/NNSA’s main office for Sandia National Laboratories, located in New Mexico (Sandia/NM). The Permit requires the submittal of this Monthly Sewer Monitoring Report to the City by the twenty-fifth day of each month.

Abstract not provided.

Abstract not provided.

The marine energy (ME) industry historically lacked a standardized data processing toolkit for common tasks such as data ingestion, quality control, and visualization. The marine and hydrokinetic toolkit (MHKiT) solved this issue by providing a public software deployment (open-source and free) toolkit for the ME industry to store and maintain commonly used functionality for wave, tidal, and river energy. This paper demonstrates an initial model verification study in MHKiT. Using Delft3D, a numerical model of the Tanana River Test Site (TRTS) at Nenana, Alaska was created. Field data from the site was collected using an Acoustic Doppler Current Profiler (ADCP) at the proposed Current Energy Converter (CEC) locations. MHKiT is used to process model simulations from Delft3D and compare them to the transect data from the ADCP measurements at TRTS. The ability to use a single tool to process simulation and field data demonstrates the ease at which the ME industry can obtain results and collaborate across specialties, reducing errors and increasing efficiency.

Abstract not provided.

Abstract not provided.

Abstract not provided.

For computational physics simulations, code verification plays a major role in establishing the credibility of the results by assessing the correctness of the implementation of the underlying numerical methods. In computational electromagnetics, surface integral equations, such as the method-of-moments implementation of the magnetic-field integral equation, are frequently used to solve Maxwell's equations on the surfaces of electromagnetic scatterers. These electromagnetic surface integral equations yield many code-verification challenges due to the various sources of numerical error and their possible interactions. In this paper, we provide approaches to separately measure the numerical errors arising from these different error sources. We demonstrate the effectiveness of these approaches for cases with and without coding errors.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Bassalto is a newly isolated phage of Mycobacterium smegmatis mc2155 from the campus grounds of Norfolk State University in Norfolk, VA. Bassalto belongs to the cluster B and subcluster B3 mycobacteriophages, based on the nucleotide composition and comparison to known mycobacteriophages.

Abstract not provided.

Simulation of radar returns, full-duplex systems, and signal repeaters require hundreds of ns of programmable broadband radio frequency (RF) delay in the signal path to simulate large distances in the case of radar returns, for signal cancellation in full-duplex, and for isolation from reflections in signal repeaters. However, programmable broadband RF delay has been limited to ones of ns due to challenges in miniaturization with low loss and low power consumption. In this work, we present a 0.2–2 GHz digitally programmable RF delay element based on a time-interleaved multistage switched-capacitor (TIMS-SC) approach. The proposed approach enables hundreds of ns of broadband RF delay by employing sample time expansion in multiple stages of switched-capacitor storage elements. Further, the delay element was implemented in a 45 nm SOI CMOS process and achieves a 2.55–448.6 ns programmable delay range with < 0.12% delay variation across 1.8 GHz of bandwidth at maximum delay, 2.42 ns programmable delay steps, and 330 ns/mm ² area efficiency. Through the proposed approach, the device shows minimal delay change across a -40 °C to 85 °C temperature range and < 0.25 dB gain variation across delay settings. The device achieves 26 dB gain, 7.4 dB noise figure, and consumes 74 mW from a 1 V supply with an active area of 1.36 mm ².

The proliferation resistance optimization (PRO-X) program is actively supporting the design of nuclear systems by developing a framework to both optimize the fuel cycle infrastructure for nuclear reactor (including both advanced reactors (ARs) and research reactors (RRs)) and minimize the potential for production of weapons-usable nuclear material (Figure 1). One area of interest is in the impact a modular approach to bulk handling fuel cycle facilities could have on meeting safeguards requirements to identify future areas of growth within the proliferation resistance space. This study evaluates how changing the number of streams within a fuel cycle facility could impact a facilities ability to meet both domestic and international safeguards requirements.

Sandia National Laboratories (Sandia) has hosted the International Training Course on the Physical Protection of Nuclear Materials and Nuclear Facilities since 1978. This course is the flagship training course of the International Atomic Energy Agency (IAEA). On behalf of the National Nuclear Security Administration (NNSA), Sandia manages, develops, and coordinates all course materials, and works closely with the IAEA to arrange all logistical details for the course ITC-29 incorporated some updates to the facility models, based on feedback received in ITC-28 and the ITC-29 dry run. In addition, all the graphics were refreshed after ITC-28 and implemented in the posters, data handbooks, etc. As in ITC-28, the ITC-29 staff worked closely with the IAEA on course materials, including a peer review process to ensure all course materials were aligned with Nuclear Security Series No. 13 and other relevant international guidance documentation from the IAEA. Due to the COVID-19 pandemic, ITC-29 was postponed twice and eventually took place in the late summer/early fall of 2022. Due to ongoing COVID-19 restrictions and safety requirements, the number of participants was reduced by about 31 percent from 59 participants in ITC-28 to 41 in ITC-29. As a result, the number of subgroups also decreased from eight in ITC-28 to six for ITC-29. This enabled the Sandia team to implement more opportunities for social distancing, particularly in the large classrooms. Despite the challenges, ITC-29 still passed a significant milestone, with the one-thousandth participant of the international training course attending during this event. Finally, the ITC staff continued the use of its improved method of evaluation to capture participants’ satisfaction with the updated course and to gather feedback concerning future improvements. This document provides a brief description of ITC-29, including a summary of lessons learned and key recommendations for future development efforts.

The purpose of this report is to document updates on testing of the apparatus built to simulate commercial drying procedures for spent nuclear fuel at the Nuclear Energy Work Complex at Sandia National Laboratories. Validation of the extent of water removal in a dry spent nuclear fuel storage system based on drying procedures used at nuclear power plants is needed to close existing technical gaps. Operational conditions leading to incomplete drying may have potential impacts on the fuel, cladding, and other components in the system during subsequent storage and disposal. A general lack of data suitable for model validation of commercial nuclear canister drying processes necessitates well-designed investigations of drying process efficacy and water retention that incorporate relevant physics and well-controlled boundary conditions. This report documents testing updates for the Advanced Drying Cycle Simulator (ADCS). This apparatus was built to simulate commercial drying procedures and quantify the amount of residual water remaining in a pressurized water reactor (PWR) fuel assembly after drying. The ADCS was constructed with a prototypic 17×17 PWR fuel skeleton and waterproof heater rods to simulate decay heat. These waterproof heaters are the next generation design to heater rods developed and tested at Sandia National Laboratories in FY20. This report describes preliminary testing of the ADCS through measurement and analysis of the thermal response of the system to a subset of commercial drying conditions that exclude the introduction of water, namely simulated decay heats and pressures relevant to commercial drying. This test series, referred to as a “dry” test series in this report, spans three uniform waterproof heater rod powers (representing spent fuel decay heats), four helium fill pressures, and six vacuum levels. This test series was conducted to cover the range of expected ADCS testing conditions for upcoming “wet” testing, where water will be introduced and a simulated commercial drying cycle will be performed. The dry test conditions were derived from the commercial drying conditions seen in the High Burnup Demonstration and the vacuum drying conditions chosen for a smaller scale Dashpot Drying Apparatus tested at Sandia National Laboratories in FY22. For a given uniform power and pressure/vacuum level, the ADCS was operated at constant power and pressure and allowed to reach steady state conditions. The thermal data obtained from these tests were analyzed, and the results can inform computational models built to simulate commercial drying processes by providing baseline thermal data prior to the introduction of water. Following the preliminary dry tests, a test plan for the ADCS will be developed to implement a drying procedure that begins with the introduction of water to the system and is based on measurements from the drying process used for the High Burnup Demonstration Project. While applying power to the simulated fuel rods, this procedure is expected to consist of filling the ADCS vessel with water, draining the water with applied pressure and multiple helium blowdowns, evacuating additional water with a vacuum drying sequence at successively lower pressures, and backfilling the vessel with helium. Additional investigations are expected to feature failed fuel rod simulators with engineered cladding defects and guide tubes with obstructed dashpots to challenge the drying system with multiple water retention sites. The data from these investigations is expected to inform the efficacy of commercial drying operations through the quantification of residual water in a prototypic-length dry storage canister.

X-ray imaging offers unique possibilities for Digital Image Correlation (DIC), opening the door for full-field deformation measurements of a test article in complex environments where optical DIC suffers severe biases or is impossible. While X-ray DIC has been performed in the past with standard DIC codes designed for optical images, the path-integrated nature of X-ray images places constraints on the experimental setup, predominantly that only a single surface of interest moves/deforms. These requirements are difficult to realize for many practical situations and limit the amount of information that can be garnered in a single test. Other X-ray based diagnostics such as Digital Volume Correlation (DVC) and Projection DVC (P-DVC) overcome these obstacles, but DVC is limited to quasi-static tests, and both DVC and P-DVC necessitate high-resolution computed tomography (CT) scan(s) and often require a potentially invasive pattern throughout the volume of the specimen. Here this work presents a novel approach to measure time-resolved displacements and strains on multiple surfaces from a single series of 2D, path-integrated (PI) X-ray images, called PI-DIC. The principle of optical flow or conservation of intensity—the foundation of DIC—was reframed for path-integrated images, for an exemplar setup comprised of two plates moving and deforming independently. Synthetic images were generated for rigid translations, rigid rotations, and uniform stretches, where each plate underwent a unique motion/deformation. Experimental specimens were fabricated (either an aluminum plate with tantalum features or a plastic plate with steel features) and the two specimens were independently translated. PI-DIC was successfully demonstrated with the synthetic images and validated with the experimental images. Prescribed displacements were recovered for each plate from the single set of path-integrated, deformed images. Errors were approximately 0.02 px for the synthetic images with 1.5% image noise, and 0.05 px for the experimental images. These results provide the foundation for PI-DIC to measure motion and deformation of multiple, independent surfaces with subpixel accuracy from a single series of path-integrated X-ray images.

We investigated the electronic interactions between transition metal phthalocyanine (TMPc's) on a refractory transition metal nitride support, specifically copper phthalocyanine (CuPc) on titanium nitride (TiN). X-ray Photoelectron Spectroscopy (XPS) results suggest a presence of a few nanometer native oxide layer on the surface of the TiN nanoparticles, which consists of TiN, TiO2, and Titanium oxynitrides (TixOyNz). A TiNCuPc nanocomposite was synthesized via a simple mixing method due to the strong binding between CuPc and TiN confirmed by density functional theory (DFT) calculations. Both XPS data and DFT calculations revealed an electron transfer from TiN substrate to CuPc molecule. The nature of charge transfer is not influenced by the presence of an oxide layer on the surface of TiN. Substantial deviations are however found between photoelectron emission microscopy (PEEM) measured work function for TiN (4.68 eV) and theoretically calculated work function for pristine stoichiometric TiN (2.63 eV). This behavior is attributed to the presence of an oxide layer on the TiN surface. TiNCuPc composite system has a work function value between those of TiN and CuPc. Our studies open up an opportunity to apply a new class of materials based on transition metal phthalocyanine/transition metal nitride composites to catalysis and optoelectronic devices.

Atomic-precision advanced manufacturing enables unique silicon quantum electronics built on quantum dots fabricated from small numbers of phosphorus dopants. The number of dopant atoms comprising a dot plays a central role in determining the behavior of charge and spin confined to the dots and thus overall device performance. In this work, we use both theoretical and experimental techniques to explore the combined impact of lithographic variation and stochastic kinetics on the number of P incorporations in quantum dots made using these techniques and how this variation changes as a function of the size of the dot. Using a kinetic model of PH3 dissociation augmented with novel reaction barriers, we demonstrate that for a 2 × 3 silicon dimer window the probability that no donor incorporates goes to zero, allowing for certainty in the placement of at least one donor. However, this still comes with some uncertainty in the precise number of incorporated donors (either one or two), and this variability may still impact certain applications. We also examine the impact of the size of the initial lithographic window, finding that the incorporation fraction saturates to δ-layer-like coverage as the circumference-to-area ratio decreases. We predict that this incorporation fraction depends strongly on the dosage of the precursor and that the standard deviation of the number of incorporations scales as ∼√n, as would be expected for a sequence of largely independent incorporation events. Finally, we characterize an array of 36 experimentally prepared multidonor 3 × 3 nm lithographic windows with scanning tunneling microscopy, measuring the fidelity of the lithography to the desired array and the final location of PHx fragments within these lithographic windows. We use our kinetic model to examine the expected variability due to the observed lithographic error, predicting a negligible impact on incorporation statistics. We find good agreement between our model and the inferred incorporation locations in these windows from scanning tunneling microscope measurements.

Commercial generation of energy by nuclear power plants in the United States (U.S.) has produced thousands of metric tons of spent nuclear fuel (SNF), the disposal of which is the responsibility of the U.S. Department of Energy (DOE). Utilities typically utilize the practice of storing this SNF in dual-purpose canisters (DPCs). DPCs were designed, licensed, and loaded to meet Nuclear Regulatory Commission (NRC) requirements that preclude the possibility of a criticality event during SNF storage and transport, but were not designed or loaded to preclude the possibility of a criticality event during the regulated post-closure period following disposal, which could be up to 1,000,000 years (Price, 2019).

Here, this Letter reports the growth, fabrication, and characterization of molecular beam epitaxy (MBE)-grown quaternary InAlGaAs/GaAs quantum dot (QD) lasers emitting at sub-900 nm. The presence of Al in QD-based active regions acts as the origin of defects and non-radiative recombination centers. Applying optimized thermal annealing annihilates the defects in p-i-n diodes, thus lowering the reverse leakage current by six orders of magnitude compared to as-grown devices. A systematic improvement in the optical properties of the devices is also observed in the laser devices with increasing annealing time. At an annealing temperature of 700°C for 180 s, Fabry–Pérot lasers exhibit a lower pulsed threshold current density at infinite length of 570 A/cm².

The characterization of the uncertainty in radiation damage metrics presents many challenges. This paper examines the current approaches to characterizing radiation damage metrics such as hydrogen and helium gas production, material heating, trapped charge in microelectronics, and lattice displacement damage. Critical uncertainty aspects go beyond just the material cross sections and involve the consideration of energy-dependent cross reaction correlations, the recoil ion energy spectrum, and models used for the partitioning of the recoil ion energy into various forms of energy deposition. This paper starts with a review of terminology and then examines the current approaches in the characterization of uncertainty in radiation damage metrics for several applications. The major deficiencies in the uncertainty of the damage metric characterization are also identified.

Oxidative instability of the liquid electrolyte at or near battery cathode oxide surfaces has significant detrimental effects on batteries. Organic solvent molecules are often the fuel and precursors of such degradation processes, releasing electrons and protons that react with cathode oxides and electrolyte anions. These reactions contribute to cathode-electrolyte interphase (CEI) film formation, transition-metal ion dissolution, and phase transformation of the surface regions of the cathode. Here we apply density functional theory calculations to examine four criteria of oxidative stability (oxidation potential, hydrogen removal energies, and initial reactivity on two types of oxide facets) using four different solvent/additive molecules (ethylene carbonate, fluoroethylene carbonate, 1,3-dioxolane, and dimethyl ether). The ranking of molecular stability differs with each criterion. Surprisingly, the all-oxygen-terminated basal planes of layered oxides exhibit lower reaction barriers than spinel surface facets with exposed transition-metal cations, especially for ether solvents; the calculations also suggest basal planes contribute to the dissolution of transition-metal ions. The structure-degradation relation complexity underscores the challenge of understanding the function of the CEI but also offers a guide to future degradation-mitigation strategies including facet engineering. Our predictions and models help establish a framework for future studies relevant to high-voltage conditions.

Calcium-ion batteries (CIBs) are a promising next-generation energy storage system given the low redox potential of calcium metal and high abundance of calcium compounds. For continued CIB development, the discovery of high energy density calcium ion cathodes is needed to achieve practical energy density values. Here, we report on the use of elemental Se as a promising candidate for a high-capacity cathode material for CIBs that operates via a conversion mechanism in a Ca metal battery at room temperature. The Se electrodes demonstrate a reversible specific capacity of 180 mA h g-1 with a discharge plateau near 2.0 V (vs Ca2+/Ca) at 100 mA g-1 using an electrolyte based on the salt calcium tetrakis(hexafluoroisopropyloxy)borate (Ca(B(hfip)4)2) in 1,2-dimethoxyethane (DME) and Ca metal. The reversible electrochemical reaction between calcium and selenium is investigated using operando synchrotron-based techniques and the possible reaction mechanism discussed.

Mixed-acid vanadium redox flow batteries (VRFBs) are an attractive option to increase energy density and temperature stability relative to conventional VRFBs for grid energy storage applications. However, the inclusion of hydrochloric acid introduces a significant safety risk through chlorine gas (Cl2) evolution. Here, we present the first direct measurements of Cl2 generation in a mixed-acid VRFB. Cl2 is generated through an electrochemical reaction when the system is charged above ∼74% state of charge with concentrations exceeding 3% of the system headspace. We explore how Cl2 evolution is enabled and propose mitigation strategies.

Practical Mg batteries require electrolytes that are stable both toward reduction by Mg metal and oxidation by high voltage cathodes. State-of-the-art Mg electrolytes based on weakly coordinating Mg salts utilize standard ether-type solvents (usually glymes) due to their reductive stability. However, the oxidative stabilities of these solvents are less than ideal, leading to difficulties in realizing the high oxidative stabilities of recently developed salts. On the other hand, alternative solvents with greater oxidative stability are typically unable to support Mg cycling. In this work, we report a selective solvation approach involving the combination of glyme and hydrofluoroether solvents. Selective solvation of Mg2+ by the glyme solvent component increases the oxidative stability of the glyme while maintaining sufficient reductive stability of the non-coordinating hydrofluoroether. We show that this approach enables the design of electrolytes with greater oxidative stability than glyme-only electrolytes while retaining enough reductive stability to cycle Mg metal. We also relate the influence of various coordination interactions among the solvents and anions with Mg2+ to their electrochemical stabilities to better inform the design of future electrolytes.

Coupling the mimetic finite difference method with the tensor-train format results in a very effective method for low-rank numerical approximations of the solutions of the time-dependent Maxwell wave propagation equations in three dimensions. To this end, we discretize the curl operators on the primal/dual tensor product grid complex and we couple the space discretization with a staggered-in-time second-order accurate time-marching scheme. The resulting solver is accurate to the second order in time and space, and still compatible, so that the approximation of the magnetic flux field has zero discrete divergence with a discrepancy close to the machine precision level. Our approach is not limited to the second-order of accuracy. We can devise higher-order formulations in space through suitable extensions of the tensor-train stencil to compute the derivatives of the mimetic differential operators. Employing the tensor-train format improves the solver performance by orders of magnitude in terms of CPU time and memory storage. A final set of numerical experiments confirms this expectation.

A shadow molecular dynamics scheme for flexible charge models is presented, where the shadow Born-Oppenheimer potential is derived from a coarse-grained approximation of range-separated density functional theory. The interatomic potential, including the atomic electronegativities and the charge-independent short-range part of the potential and force terms, are modeled by the linear atomic cluster expansion (ACE), which provides a computationally efficient alternative to many machine learning methods. The shadow molecular dynamics scheme is based on extended Lagrangian (XL) Born-Oppenheimer molecular dynamics (BOMD) [Eur. Phys. J. B 94, 164 (2021)]. XL-BOMD provides a stable dynamics, while avoiding the costly computational overhead associated with solving an all-to-all system of equations, which normally is required to determine the relaxed electronic ground state prior to each force evaluation. To demonstrate the proposed shadow molecular dynamics scheme for flexible charge models using the atomic cluster expansion, we emulate the dynamics generated from self-consistent charge density functional tight-binding (SCC-DFTB) theory using a second-order charge equilibration (QEq) model. The charge-independent potentials and electronegativities of the QEq model are trained for a supercell of uranium oxide (UO2) and a molecular system of liquid water. The combined ACE + XL-QEq dynamics are stable over a wide range of temperatures both for the oxide and the molecular systems, and provide a precise sampling of the Born-Oppenheimer potential energy surfaces. Accurate ground Coulomb energies are produced by the ACE-based electronegativity model during an NVE simulation of UO₂, predicted to be within 1 meV of those from SCC-DFTB on average during comparable simulations.

Numerous experimental investigations indicated that expansive clays such as montmorillonite can intercalate CO2 preferentially into their interlayers and therefore potentially act as a material for CO2 separation, capture, and storage. However, an understanding of the energy-structure relationship during the intercalation of CO2 into clay interlayers remains elusive. Here, we use metadynamics molecular dynamics simulations to elucidate the energy landscape associated with CO2 intercalation. Our free energy calculations indicate that CO2 favorably partitions into nanoconfined water in clay interlayers from a gas phase, leading to an increase in the CO2/H2O ratio in clay interlayers as compared to that in bulk water. CO2 molecules prefer to be located at the centers of charge-neutral hydrophobic siloxane rings, whereas interlayer spaces close to structural charges tend to avoid CO2 intercalation. The structural charge distribution significantly affects the amount of CO2 intercalated in the interlayers. These results provide a mechanistic understanding of CO2 intercalation in clays for CO2 separation, capture, and storage.

Here we present a classical molecular-spin dynamics (MSD) methodology that enables accurate computations of the temperature dependence of the magnetocrystalline anisotropy as well as magnetoelastic properties of magnetic materials. The nonmagnetic interactions are accounted for by a spectral neighbor analysis potential (SNAP) machine-learned interatomic potential, whereas the magnetoelastic contributions are accounted for using a combination of an extended Heisenberg Hamiltonian and a Néel pair interaction model, representing both the exchange interaction and spin-orbit-coupling effects, respectively. All magnetoelastic potential components are parameterized using a combination of first-principles and experimental data. Our framework is applied to the α phase of iron. Initial testing of our MSD model is done using a 0 K parametrization of the Néel interaction model. After this, we examine how individual Néel parameters impact the $B$₁ and $B$₂ magnetostrictive coefficients using a moment-independent δ sensitivity analysis. The results from this study are then used to initialize a genetic algorithm optimization which explores the Néel parameter phase space and tries to minimize the error in the B₁ and B₂ magnetostrictive coefficients in the range of 0–1200 K. Our results show that while both the 0 K and genetic algorithm optimized parametrization provide good experimental agreement for $B$₁ and $B$₂, only the genetic algorithm optimized results can capture the second peak in the $B$₁ magnetostrictive coefficient which occurs near approximately 800 K.

Alkyl-substituted oxetanes are cyclic ethers formed via unimolecular reactions of QOOH radicals produced via a six-membered transition state in the preceding isomerization step of organic peroxy radicals, ROO. Owing to radical isomer-specific formation pathways, cyclic ethers are unambiguous proxies for inferring QOOH reaction rates. Therefore, accounting for subsequent oxidation of cyclic ethers is important in order to accurately determine rates for QOOH → products. Cyclic ethers can react via unimolecular reaction (ring-opening) or via bimolecular reaction with O2 to form cyclic ether-peroxy adducts. The computations herein provide reaction mechanisms and theoretical rate coefficients for the former type in order to determine competing pathways for the cyclic ether radicals. Rate coefficients of unimolecular reactions of 2,4-dimethyloxetanyl radicals were computed using master equation modeling from 0.01 to 100 atm and from 300 to 1000 K. Coupled-cluster methods were utilized for stationary-point energy calculations, and uncertainties in the computed rate coefficients were accounted for using variation in barrier heights and in well depths. The potential energy surfaces reveal accessible channels to several species via crossover reactions, such as 2-methyltetrahydrofuran-5-yl and pentanonyl isomers. For the range of temperature over which 2,4-dimethyloxetane forms during n-pentane oxidation, the following are the major channels: 2,4-dimethyloxetan-1-yl → acetaldehyde + allyl, 2,4-dimethyloxetan-2-yl → propene + acetyl, and 2,4-dimethyloxetan-3-yl → 3-butenal + methyl, or, 1-penten-3-yl-4-ol. Well-skipping reactions were significant in a number of channels and also exhibited a markedly different pressure dependence. The calculations show that rate coefficients for ring-opening are approximately an order of magnitude lower for the tertiary 2,4-dimethyloxetanyl radicals than for the primary and secondary 2,4-dimethyloxetanyl radicals. Unlike for reactions of the corresponding ROO radicals, however, unimolecular rate coefficients are independent of the stereochemistry. Moreover, rate coefficients of cyclic ether radical ring-opening are of the same order of magnitude as O2 addition, underscoring the point that a competing network of reactions is necessary to include for accurate chemical kinetics modeling of species profiles for cyclic ethers.

An experimental investigation and the optical modeling of the structural coloration produced from total internal reflection interference within 3D microstructures are described. Ray-tracing simulations coupled with color visualization and spectral analysis techniques are used to model, examine, and rationalize the iridescence generated for a range of microgeometries, including hemicylinders and truncated hemispheres, under varying illumination conditions. An approach to deconstruct the observed iridescence and complex far-field spectral features into its elementary components and systematically link them to ray trajectories that emanate from the illuminated microstructures is demonstrated. The results are compared with experiments, wherein microstructures are fabricated with methods such as chemical etching, multiphoton lithography, and grayscale lithography. Microstructure arrays patterned on surfaces with varying orientation and size lead to unique color-traveling optical effects and highlight opportunities for how total internal reflection interference can be used to create customizable reflective iridescence. The findings herein provide a robust conceptual framework for rationalizing this multibounce interference mechanism and establish approaches for characterizing and tailoring the optical and iridescent properties of microstructured surfaces.

Tungsten (W) is a material of choice for the divertor material due to its high melting temperature, thermal conductivity, and sputtering threshold. However, W has a very high brittle-to-ductile transition temperature, and at fusion reactor temperatures (≥1000 K), it may undergo recrystallization and grain growth. Dispersion-strengthening W with zirconium carbide (ZrC) can improve ductility and limit grain growth, but much of the effects of the dispersoids on microstructural evolution and thermomechanical properties at high temperatures are still unknown. We present a machine learned Spectral Neighbor Analysis Potential for W-ZrC that can now be used to study these materials. In order to construct a potential suitable for large-scale atomistic simulations at fusion reactor temperatures, it is necessary to train on ab initio data generated for a diverse set of structures, chemical environments, and temperatures. Further accuracy and stability tests of the potential were achieved using objective functions for both material properties and high temperature stability. Validation of lattice parameters, surface energies, bulk moduli, and thermal expansion is confirmed on the optimized potential. Tensile tests of W/ZrC bicrystals show that although the W(110)-ZrC(111) C-terminated bicrystal has the highest ultimate tensile strength (UTS) at room temperature, observed strength decreases with increasing temperature. At 2500 K, the terminating C layer diffuses into the W, resulting in a weaker W-Zr interface. Meanwhile, the W(110)-ZrC(111) Zr-terminated bicrystal has the highest UTS at 2500 K.

Here in this work, we investigate the applicability of the harmonic balance method (HBM) to predict periodic solutions of a single degree-of-freedom forced Duffing oscillator with freeplay nonlinearity. By studying the route to impact, which refers to a parametric study as the contact stiffness increases from soft to hard, the convergence behavior of the HBM can be understood in terms of the strength of the non-smooth forcing term. HBM results are compared to time-integration results to facilitate an evaluation of the accuracy of nonlinear periodic responses. An additional contribution of this study is to perform convergence and stability analysis specifically for isolas generated by the non-smooth nonlinearity. Residual error analysis is used to determine the approximate number of harmonics required to get results accurate to a given error tolerance. Hill’s method and Floquet theory are employed to compute the stability of periodic solutions and identify the types of bifurcations in the system.

A recently developed measure-theoretic framework solves a stochastic inverse problem (SIP) for models where uncertainties in model output data are predominantly due to aleatoric (i.e., irreducible) uncertainties in model inputs (i.e., parameters). The subsequent inferential target is a distribution on parameters. Another type of inverse problem is to quantify uncertainties in estimates of “true” parameter values under the assumption that such uncertainties should be reduced as more data are incorporated into the problem, i.e., the uncertainty is considered epistemic. A major contribution of this work is the formulation and solution of such a parameter identification problem (PIP) within the measure-theoretic framework developed for the SIP. The approach is novel in that it utilizes a solution to a stochastic forward problem (SFP) to update an initial density only in the parameter directions informed by the model output data. In other words, this method performs “selective regularization” only in the parameter directions not informed by data. The solution is defined by a maximal updated density (MUD) point where the updated density defines the measure-theoretic solution to the PIP. Another significant contribution of this work is the full theory of existence and uniqueness of MUD points for linear maps with Gaussian distributions. Data-constructed Quantity of Interest (QoI) maps are also presented and analyzed for solving the PIP within this measure-theoretic framework as a means of reducing uncertainties in the MUD estimate. We conclude with a demonstration of the general applicability of the method on two problems involving either spatial or temporal data for estimating uncertain model parameters. The first problem utilizes spatial data from a stationary partial differential equation to produce a MUD estimate of an uncertain boundary condition. The second problem utilizes temporal data obtained from the state-of-the-art ADvanced CIRCulation (ADCIRC) model to obtain a MUD estimate of uncertain wind drag coefficients for a simulated extreme weather event near the Shinnecock Inlet located in the Outer Barrier of Long Island, NY, USA.

The Z machine is a current driver producing up to 30 MA in 100 ns that utilizes a wide range of diagnostics to assess accelerator performance and target behavior conduct experiments that use the Z target as a source of radiation or high pressures. Here, we review the existing suite of diagnostic systems, including their locations and primary configurations. The diagnostics are grouped in the following categories: pulsed power diagnostics, x-ray power and energy, x-ray spectroscopy, x-ray imaging (including backlighting, power flow, and velocimetry), and nuclear detectors (including neutron activation). We will also briefly summarize the primary imaging detectors we use at Z: image plates, x-ray and visible film, microchannel plates, and the ultrafast x-ray imager. The Z shot produces a harsh environment that interferes with diagnostic operation and data retrieval. We term these detrimental processes “threats” of which only partial quantifications and precise sources are known. Finally, we summarize the threats and describe techniques utilized in many of the systems to reduce noise and backgrounds.

The development of highly accurate constitutive models for materials that undergo path-dependent processes continues to be a complex challenge in computational solid mechanics. Challenges arise both in considering the appropriate model assumptions and from the viewpoint of data availability, verification, and validation. Recently, data-driven modeling approaches have been proposed that aim to establish stress-evolution laws that avoid user-chosen functional forms by relying on machine learning representations and algorithms. However, these approaches not only require a significant amount of data but also need data that probes the full stress space with a variety of complex loading paths. Furthermore, they rarely enforce all necessary thermodynamic principles as hard constraints. Hence, they are in particular not suitable for low-data or limited-data regimes, where the first arises from the cost of obtaining the data and the latter from the experimental limitations of obtaining labeled data, which is commonly the case in engineering applications. In this work, we discuss a hybrid framework that can work on a variable amount of data by relying on the modularity of the elastoplasticity formulation where each component of the model can be chosen to be either a classical phenomenological or a data-driven model depending on the amount of available information and the complexity of the response. The method is tested on synthetic uniaxial data coming from simulations as well as cyclic experimental data for structural materials. The discovered material models are found to not only interpolate well but also allow for accurate extrapolation in a thermodynamically consistent manner far outside the domain of the training data. This ability to extrapolate from limited data was the main reason for the early and continued success of phenomenological models and the main shortcoming in machine learning-enabled constitutive modeling approaches. Training aspects and details of the implementation of these models into Finite Element simulations are discussed and analyzed.

This paper presents a method for simulating evaporation in a compressible, interface-resolved framework appropriate for modeling problems of engineering interest. In order to achieve robustness and broad applicability, the method has been designed to discretely enforce consistent mass and thermal energy transport at the phase interface, to globally conserve mass, momentum, and energy, and to be capable of modeling compressible and incompressible systems. Verification is performed via the Sod-shock test, one-dimensional heat conduction, evaporation from a planar interface, and evaporation of three-dimensional droplets. Convergence with increasing mesh resolution is demonstrated in all tested configurations, and conservation is maintained near machine precision for a translating droplet. Conservation and accurate phase change rates are preserved at the low numerical resolutions commonly encountered in engineering calculations. Following verification, the method is validated by comparison to an empirical correlation for evaporating droplets in high temperature crossflow, and the presentation concludes with the simulation of an iso-octane spray at conditions representative of gasoline direct injection. Successful verification, validation, and demonstrated practical utility suggest the method to be an accurate, efficient, and robust approach for the study of phase change in engineering systems.

A common approach for the development of partitioned schemes employing different time integrators on different subdomains is to lag the coupling terms in time. This can lead to accuracy issues, especially in multistage methods. Here, in this article, we present a novel framework for partitioned heterogeneous time-integration methods, which allows the coupling of arbitrary multistage and multistep methods without reducing their order of accuracy. At the core of our approach are accurate estimates of the interface flux obtained from the Schur complement of an auxiliary monolithic system. We use these estimates to construct a polynomial-in-time approximation of the interface flux over the current time coupling window. This approximation provides the interface boundary conditions necessary to decouple the subdomain problems at any point within the coupling window. In so doing our framework enables a flexible choice of time-integrators for the individual subproblems without compromising the time-accuracy at the coupled problem level. This feature is the main distinction between our framework and other approaches. To demonstrate the framework, we construct a family of partitioned heterogeneous time-integration methods, combining multistage and multistep methods, for a simplified tracer transport component of the coupled air-sea system in Earth system models. We report numerical tests evaluating accuracy and flux conservation for different pairs of time-integrators from the explicit Runge-Kutta and Adams-Moulton families.

BaCe0.25Mn0.75O3−δ (BCM), a non-stoichiometric oxide with a layered perovskite-like crystal structure, has recently emerged as a prospective contender for application in renewable energy harvesting by solar thermochemical hydrogen generation. Using solar-thermal energy and a reducing environment, oxygen vacancies can be created in high-temperature BCM, and the reduced crystal so obtained can, in turn, produce H2 by stripping oxygen from H2O. Therefore, a first step toward understanding the working mechanism and optimizing the performance of BCM is a thorough and comparative analysis of the electronic structure of the pristine and the reduced material. In this paper, we probe the electronic structure of BCM using the combined effort of first-principles calculations and experimental O K-edge X-ray absorption spectroscopy (XAS). The computed projected density of states (PDOS) and orbital plots are used to propose a simplified model for orbital mixing between the oxygen and metal atoms. With the help of state-of-the-art simulations, we are able to find the origins of the XAS peaks and categorize them on the basis of contribution from Ce and Mn. For the reduced crystal, the calculations show that the change in electron density resulting from the reduction is strongly localized around the oxygen vacancy. Experimental measurements reveal a marked lowering of the first O K-edge peak in the reduced crystal. Using theoretical analysis, this is shown to result from lifting of spin degeneracy in the absorption peaks as well as from a diminished O 2p contribution to the frontier unoccupied orbitals, in accordance with the tight binding scheme. The simulated results serve as a reference for the extent of spectral change as a function of the percentage of oxygen vacancies in the reduced crystal. Our study paves the way for the investigation of the working mechanism of BCM and for computational and experimental efforts aimed at design and discovery of efficient water-splitting oxides.

The present contribution emphasizes the formation of oligomeric products in various depolymerization approaches of lignin, namely reductive catalytic fractionation, oxidative catalytic fractionation, and pyrolysis. Three possible routes to form such oligomers in these depolymerization processes are summarized and compared from various studies conducted on model compounds. Next, the main identification techniques for characterizing oligomeric products are highlighted. Particular focus is given to 2D-HSQC-NMR, GPC, Maldi-TOF-MS and FT-ICR-MS, which represent the state-of-art characterization of lignin. Special attention was paid to the transferability of these techniques for depolymerized oligomeric lignin. Finally, both the existing and expected potential lignin valorization routes are discussed for these oligomers, and technical hurdles and recommendations are provided in an attempt to catalyze the development of new discoveries and enabling technologies.

Here we used aerosol mass spectrometry coupled with tunable synchrotron photoionization to measure radical and closed-shell species associated with particle formation in premixed flames and during pyrolysis of butane, ethylene, and methane. We analyzed photoionization (PI) spectra for the C₇H₇ radical to identify the isomers present during particle formation. For the combustion and pyrolysis of all three fuels, the PI spectra can be fit reasonably well with contributions from four radical isomers: benzyl, tropyl, vinylcyclopentadienyl, and o-tolyl. Although there are significant experimental uncertainties in the isomeric speciation of C7H₇, the results clearly demonstrate that the isomeric composition of C₇H₇ strongly depends on the combustion or pyrolysis conditions and the fuel or precursors. Fits to the PI spectra using reference curves for these isomers suggest that all of these isomers may contribute to m/z 91 in butane and methane flames, but only benzyl and vinylcyclopentadienyl contribute to the C₇H₇ isomer signal in the ethylene flame. Only tropyl and benzyl appear to play a role during pyrolytic particle formation from ethylene, and only tropyl, vinylcyclopentadienyl, and o-tolyl appear to participate during particle formation from butane pyrolysis. There also seems to be a contribution from an isomer with an ionization energy below 7.5 eV for the flames but not for the pyrolysis conditions. Kinetic models with updated and new reactions and rate coefficients for the C₇H₇ reaction network predict benzyl, tropyl, vinylcyclopentadienyl, and o-tolyl to be the primary C₇H₇ isomers and predict negligible contributions from other C₇H₇ isomers. These updated models provide better agreement with the measurements than the original versions of the models but, nonetheless, underpredict the relative concentrations of tropyl, vinylcyclopentadienyl, and o-tolyl in both flames and pyrolysis and overpredict benzyl in pyrolysis. Our results suggest that there are additional important formation pathways for the vinylcyclopentadienyl, tropyl, and o-tolyl radicals and/or loss pathways for the benzyl radical that are currently unaccounted for in the present models.

Herein, the International Commission on Illumination (CIE) designed its color space to be perceptually uniform so that a given numerical change in the color code corresponds to perceived change in color. This color encoding is demonstrated to be advantageous in scientific visualization and analysis of vector fields. The specific application is analysis of ice motion in the Arctic where patterns in smooth monthly-averaged ice motion are seen. Furthermore, fractures occurring in the ice cover result in discontinuities in the ice motion. This vector jump in displacement can also be visualized. We then analyze modeled and observed fractures through the use of a metric on the color space, and image amplitude and phase metrics. Amplitude and phase metrics arise from image registration that is accomplished by sampling images using space filling curves, thus reducing the image registration problem to the more reliable functional alignment problem. We demonstrate this through an exploration of the metrics to compare model runs to an observed ice crack.

Tritium population thermodynamics and transport kinetics critically define the tritium storage performance of zirconium tritides that can be used for a variety of nuclear applications including tritium-producing burnable absorber rods. Both thermodynamic and kinetic properties can be sensitive to grain sizes of materials and can be significantly altered by irradiated defects during operation under the reactor environments. A thorough experimental characterization of how these properties evolve under different reactor conditions and different initial grain structures is extremely challenging. Here molecular dynamics simulations are used to investigate tritium population and diffusion in zirconium with and without different planar symmetric and asymmetric tilt grain boundaries and irradiated defects. Here, we found that in addition to trapping tritium, the most significant effect of planar grain boundaries is to increase tritium diffusivity on the boundary plane. Furthermore, fine grain structures are found to mitigate the change of tritium diffusivity due to irradiated point defects as these point defects are likely to migrate to and sink at grain boundaries.

Here, the effectiveness of continuous vibro-impact forcing representations for the cantilevered pipe that conveys fluid is explored and analyzed. The previously accepted forcing model utilizing a smoothened trilinear spring is estimated using three continuous forcing representations, namely, polynomial, rational polynomial, and hyperbolic tangent. The accuracy of the estimated forcing functions is investigated and analyzed by calculating the root mean square error, and bifurcation diagrams are generated and compared to the nominal system. Additionally, the dynamic response of the system is further characterized using Poincare maps, power spectra, and basins of attraction. Once all continuous forcing representations are analyzed and compared to the nominal system, the computational cost of each method is examined, and further limitations of the hyperbolic tangent method are discovered. It is proved that the hyperbolic tangent forcing representation most accurately captures the dynamic response of the pipeline, and the least accurate representation is the rational polynomial representation. Additionally, considerable computational cost is saved when employing the hyperbolic tangent representation compared to the discontinuous representation.

Abstract not provided.

Increase in the number and frequency of widespread outages in recent years has been directly linked to drastic climate change necessitating better preparedness for outage mitigation. Severe weather conditions are experienced more frequently and on larger scales, challenging system operation and recovery time after an outage. The impact is more evident and concerning than before, considering the increased dependency on electricity in all aspects of our lives.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Twinning is a frequent deformation mechanism in nanocrystalline metals, and segregation of solute atoms at twin boundaries is a thermodynamic process that plays an important role in the stability and strengthening of these materials. In pristine, defect-free twin boundaries, solute segregation generally follows a single- or multilayer patterned coverage of solutes that is uniformly and symmetrically distributed at segregation sites across the boundary. However, when a disconnection, a type of interfacial line defect, is present at the twin boundary, we report a possible discontinuity of the segregation patterns across this defect for a broad range of binary alloys. The change of segregation pattern is explained by a break of the local symmetry across the disconnection terraces. The characteristics of this change are dictated by the orientation of the dislocation content sitting at the step region of the disconnection and its synergistic/antagonistic interactions with the step character. These findings not only advance our understanding of the origin of the interface segregation phenomena and the key contribution from interfacial defects, but they also shed light on applications for tailoring atomically precise interfacial structures to design alloys with emerging properties.

The resolution of computed tomography (CT) has become high enough to monitor morphological changes due to aging in materials in long-term applications. We explored the utility of the critic of a generative adversarial network (GAN) to automatically detect such changes. The GAN was trained with images of pristine Pharmatose, which is used as a surrogate energetic material. It is important to note that images of the material with altered morphology were only used during the test phase. The GAN-generated images reproduced the microstructure of Pharmatose well, although some unrealistic particle fusion was seen. Calculated morphological metrics (volume fraction, interfacial line length, and local thickness) for the synthetic images also showed good agreement with the training data, albeit with signs of mode collapse in the interfacial line length. While the critic exposed changes in particle size, it showed limited ability to distinguish images by particle shape. The detection of shape differences was also a more challenging task for the selected morphological metrics that related to energetic material performance. We further tested the critic with images of aged Pharmatose. Subtle changes due to aging are difficult for the human analyst to detect; but both critic and morphological metrics analysis showed image differentiation.

Abstract not provided.

Network segmentation of a power grid's communication system can make the grid more resilient to cyberattacks. We develop a novel trilevel programming model to optimally segment a grid communication system, taking into account the actions of an information technology (IT) administrator, attacker, and grid operator. The IT administrator is allowed to segment existing networks, and the attacker is given a budget to inflict damage on the grid by attacking the segmented communication system. Finally, the grid operator can redispatch the grid after the attack to minimize damage. The resulting problem is a trilevel interdiction problem that we solve using a branch and bound algorithm for bilevel problems. We demonstrate the benefits of optimal network segmentation through case studies on the 9-bus Western System Coordinating Council (WSCC) system and the 30-bus IEEE system. These examples illustrate that network segmentation can significantly reduce the threat posed by a cyberattacker.

This research presents a simple method to additively manufacture Cone 5 porcelain clay ceramics by using the direct ink-write (DIW) printing technique. DIW has allowed the application of extruding highly viscous ceramic materials with relatively high-quality and good mechanical properties, which additionally allows a freedom of design and the capability of manufacturing complex geometrical shapes. Clay particles were mixed with deionized (DI) water at different ratios, where the most suitable composition for 3D printing was observed at a 1:5 w/c ratio (16.2 wt.%. of DI water). Differential geometrical designs were printed to demonstrate the printing capabilities of the paste. In addition, a clay structure was fabricated with an embedded wireless temperature and relative humidity (RH) sensor during the 3D printing process. The embedded sensor read up to 65% RH and temperatures of up to 85 °F from a maximum distance of 141.7 m. The structural integrity of the selected 3D printed geometries was confirmed through the compressive strength of fired and non-fired clay samples, with strengths of 70 MPa and 90 MPa, respectively. This research demonstrates the feasibility of using the DIW printing of porcelain clay with embedded sensors, with fully functional temperature- and humidity-sensing capabilities.

Abstract not provided.

The outbreak of SARS-CoV-2 has emphasized the need for a deeper understanding of infectivity, spread, and treatment of airborne viruses. Bacteriophages (phages) serve as ideal surrogates for respiratory pathogenic viruses thanks to their high tractability and the structural similarities tailless phages bear to viral pathogens. However, the aerosolization of enveloped SARS-CoV-2 surrogate phi6 usually results in a .3-log10 reduction in viability, limiting its usefulness as a surrogate for aerosolized coronavirus in “real world” contexts, such as a sneeze or cough. Recent work has shown that saliva or artificial saliva greatly improves the stability of viruses in aerosols and microdroplets relative to standard dilution/storage buffers like suspension medium (SM) buffer. These findings led us to investigate whether we could formulate media that preserves the viability of phi6 and other phages in artificially derived aerosols. Results indicate that SM buffer supplemented with bovine serum albumin (BSA) significantly improves the recovery of airborne phi6, MS2, and 80a and outperforms commercially formulated artificial saliva. Particle sizing and acoustic particle trapping data indicate that BSA supplementation dose-dependently improves viral survivability by reducing the extent of particle evaporation. These data suggest that our viral preservation medium may facilitate a lower-cost alternative to artificial saliva for future applied aerobiology studies. IMPORTANCE We have identified common and inexpensive lab reagents that confer increased aerosol survivability on phi6 and other phages. Our results suggest that soluble protein is a key protective component in nebulizing medium. Protein supplementation likely reduces exposure of the phage to the air-water interface by reducing the extent of particle evaporation. These findings will be useful for applications in which researchers wish to improve the survivability of these (and likely other) aerosolized viruses to better approximate highly transmissible airborne viruses like SARS-CoV-2.

Reconstructing the patterns of Homo sapiens expansion out of Africa and across the globe has been advanced using demographic and travel-cost models. However, modelled routes are ipso facto influenced by migration rates, and vice versa. We combined movement ‘superhighways’ with a demographic cellular automaton to predict one of the world's earliest peopling events — Sahul between 75000 and 50000 years ago. Novel outcomes from the superhighways-weighted model include (i) an approximate doubling of the predicted time to continental saturation (∼10,000 years) compared to that based on the directionally unsupervised model (∼5000 years), suggesting that rates of migration need to account for topographical constraints in addition to rate of saturation; (ii) a previously undetected movement corridor south through the centre of Sahul early in the expansion wave based on the scenarios assuming two dominant entry points into Sahul; and (iii) a better fit to the spatially de-biased, Signor-Lipps-corrected layer of initial arrival inferred from dated archaeological material. Our combined model infrastructure provides a data-driven means to examine how people initially moved through, settled, and abandoned different regions of the globe.

Abstract not provided.

Fireballs produced from the detonation of high explosives often contain particulates primarily composed of various phases of carbon soot. The transport and concentration of these particulates is of interest for model validation and emission characterization. This work proposes ultra-high-speed imaging techniques to observe a fireball's structure and optical depth. An extinction-based diagnostic applied at two wavelengths indicates that extinction scales inversely with wavelength, consistent with particles in the Rayleigh limit and dimensionless extinction coefficients which are independent of wavelength. Within current confidence bounds, the extinction-derived soot mass concentrations agree with expectations based upon literature reported soot yields. Results also identify areas of high uncertainty where additional work is recommended.

Matter at extreme temperatures and pressures - commonly known as warm dense matter (WDM) - is ubiquitous throughout our Universe and occurs in astrophysical objects such as giant planet interiors and brown dwarfs. Moreover, WDM is very important for technological applications such as inertial confinement fusion and is realized in the laboratory using different techniques. A particularly important property for the understanding of WDM is given by its electronic density response to an external perturbation. Such response properties are probed in x-ray Thomson scattering (XRTS) experiments and are central for the theoretical description of WDM. In this work, we give an overview of a number of recent developments in this field. To this end, we summarize the relevant theoretical background, covering the regime of linear response theory and nonlinear effects, the fully dynamic response and its static, time-independent limit, and the connection between density response properties and imaginary-time correlation functions (ITCF). In addition, we introduce the most important numerical simulation techniques, including path-integral Monte Carlo simulations and different thermal density functional theory (DFT) approaches. From a practical perspective, we present a variety of simulation results for different density response properties, covering the archetypal model of the uniform electron gas and realistic WDM systems such as hydrogen. Moreover, we show how the concept of ITCFs can be used to infer the temperature from XRTS measurements of arbitrary complex systems without the need for any models or approximations. Finally, we outline a strategy for future developments based on the close interplay between simulations and experiments.

Abstract not provided.

Vertical-axis wind turbines (VAWTs) have a long history, with a wide variety of turbine archetypes that have been designed and tested since the 1970s. While few utility-scale VAWTs currently exist, the placement of the generator near the turbine base could make VAWTs advantageous over tradition horizontal-axis wind turbines for floating offshore wind applications via reduced platform costs and improved scaling potential. However, there are currently few numerical design and analysis tools available for VAWTs. One existing engineering toolset for aero-hydro-servo-elastic simulation of VAWTs is the Offshore Wind ENergy Simulator (OWENS), but its current modeling capability for floating systems is non-standard and not ideal. This article describes how OWENS has been coupled to several OpenFAST modules to update and improve modeling of floating offshore VAWTs and discusses the verification of these new capabilities and features. The results of the coupled OWENS verification test agree well with a parallel OpenFAST simulation, validating the new modeling and simulation capabilities in OWENS for floating VAWT applications. These developments will enable the design and optimization of floating offshore VAWTs in the future.

Titanium alloys are used in a large array of applications. In this work we focus our attention on the most used alloy, Ti-6Al-4V (Ti64), which has excellent mechanical and biocompatibility properties with applications in aerospace, defense, biomedical, and other fields. Here we present high-fidelity experimental shock compression data measured on Sandia's Z machine. We extend the principal shock Hugoniot for Ti64 to more than threefold compression, up to over 1.2 TPa. We use the data to validate our ab initio molecular dynamics simulations and to develop a highly reliable, multiphase equation of state (EOS) for Ti64, spanning a broad range of temperature and pressures. The first-principles simulations show very good agreement with Z data and with previous three-stage gas gun data from Sandia's STAR facility. The resulting principal Hugoniot and the broad-range EOS and phase diagram up to 10 TPa and 105 K are suitable for use in shock experiments and in hydrodynamic simulations. The high-precision experimental results and high-fidelity simulations demonstrate that the Hugoniot of the Ti64 alloy is stiffer than that of pure Ti and reveal that Ti64 melts on the Hugoniot at a significantly lower pressure and temperature than previously modeled.

Compliance monitoring is used to evaluate and confirm the adequacy of assumptions, data, parameterizations, and analyses used to demonstrate performance of a given geologic repository site. Repository performance demonstration is accomplished via a performance assessment methodology. Performance assessment provides a reasonable expectation of long-term repository performance with quantified uncertainty. In this paper, the linkage between compliance monitoring and performance assessment is explored. The U.S. Waste Isolation Pilot Plant and the suspended Yucca Mountain site are used to illustrate the discussion.

Mixtures of gas-phase hydrogen isotopologues (diatomic combinations of protium, deuterium, and tritium) can be separated using columns containing a solid such as palladium that reversibly absorbs hydrogen. A temperature-swing process can transport hydrogen into or out of a column by inducing temperature-dependent absorption or desorption reactions. We consider two designs: a thermal cycling absorption process, which moves hydrogen back and forth between two columns, and a simulated moving bed (SMB), where columns are in a circular arrangement. We present a numerical mass and heat transport model of absorption columns for hydrogen isotope separation. It includes a detailed treatment of the absorption-desorption reaction for palladium. By comparing the isotope concentrations within the columns as a function of position and time, we observe that SMB can lead to sharper separations for a given number of thermal cycles by avoiding the remixing of isotopes.

Variational quantum algorithms are a class of techniques intended to be used on near-term quantum computers. The goal of these algorithms is to perform large quantum computations by breaking the problem down into a large number of shallow quantum circuits, complemented by classical optimization and feedback between each circuit execution. One path for improving the performance of these algorithms is to enhance the classical optimization technique. Given the relative ease and abundance of classical computing resources, there is ample opportunity to do so. In this work, we introduce the idea of learning surrogate models for variational circuits using a few experimental measurements, and then performing parameter optimization using these models as opposed to the original data. We demonstrate this idea using a surrogate model based on kernel approximations, through which we reconstruct local patches of variational cost functions using batches of noisy quantum circuit results. Through application to the quantum approximate optimization algorithm and preparation of ground states for molecules, we demonstrate the superiority of surrogate-based optimization over commonly used optimization techniques for variational algorithms.

Abstract not provided.

Experiments have shown that pitting corrosion can develop in aluminum surfaces at potentials > − 0.5 V relative to the standard hydrogen electrode (SHE). Until recently, the onset of pitting corrosion in aluminum has not been rigorously explored at an atomistic scale because of the difficulty of incorporating a voltage into density functional theory (DFT) calculations. We introduce the Quantum Continuum Approximation (QCA) which self-consistently couples explicit DFT calculations of the metal-insulator and insulator-solution interfaces to continuum Poisson-Boltzmann electrostatic distributions describing the bulk of the insulating region. By decreasing the number of atoms necessary to explicitly simulate with DFT by an order of magnitude, QCA makes the first-principles prediction of the voltage of realistic electrochemical interfaces feasible. After developing this technique, we apply QCA to predict the formation energy of chloride atoms inserting into oxygen vacancies in Al(111)/α-Al2O3 (0001) interfaces as a function of applied voltage. We predict that chloride insertion is only favorable in systems with a grain boundary in the Al2O3 for voltages > − 0.2 V (SHE). Our results roughly agree with the experimentally demonstrated onset of corrosion, demonstrating QCA’s utility in modeling realistic electrochemical systems at reasonable computational cost.

Abstract not provided.

The ground truth program used simulations as test beds for social science research methods. The simulations had known ground truth and were capable of producing large amounts of data. This allowed research teams to run experiments and ask questions of these simulations similar to social scientists studying real-world systems, and enabled robust evaluation of their causal inference, prediction, and prescription capabilities. We tested three hypotheses about research effectiveness using data from the ground truth program, specifically looking at the influence of complexity, causal understanding, and data collection on performance. We found some evidence that system complexity and causal understanding influenced research performance, but no evidence that data availability contributed. The ground truth program may be the first robust coupling of simulation test beds with an experimental framework capable of teasing out factors that determine the success of social science research.

A multiple input multiple output (MIMO) power line communication (PLC) model for industrial facilities was developed that uses the physics of a bottom-up model but can be calibrated like top-down models. The PLC model considers 4-conductor cables (three-phase conductors and a ground conductor) and has several load types, including motor loads. The model is calibrated to data using mean field variational inference with a sensitivity analysis to reduce the parameter space. The results show that the inference method can accurately identify many of the model parameters, and the model is accurate even when the network is modified.

Control of nonlinear dynamical systems is a complex and multifaceted process. Essential elements of many engineering systems include high-fidelity physics-based modeling, offline trajectory planning, feedback control design, and data acquisition strategies to reduce uncertainties. This article proposes an optimization-centric perspective which couples these elements in a cohesive framework. We introduce a novel use of hyper-differential sensitivity analysis to understand the sensitivity of feedback controllers to parametric uncertainty in physics-based models used for trajectory planning. These sensitivities provide a foundation to define an optimal experimental design which seeks to acquire data most relevant in reducing demand on the feedback controller. Our proposed framework is illustrated on the Zermelo navigation problem and a hypersonic trajectory control problem using data from NASA’s X-43 hypersonic flight tests.

Quantifying uncertainty associated with the microstructure variation of a material can be a computationally daunting task, especially when dealing with advanced constitutive models and fine mesh resolutions in the crystal plasticity finite element method (CPFEM). Numerous studies have been conducted regarding the sensitivity of material properties and performance to the mesh resolution and choice of constitutive model. However, a unified approach that accounts for various fidelity parameters, such as mesh resolutions, integration time-steps and constitutive models simultaneously is currently lacking. This paper proposes a novel uncertainty quantification (UQ) approach for computing the properties and performance of homogenized materials using CPFEM, that exploits a hierarchy of approximations with different levels of fidelity. In particular, we illustrate how multi-level sampling methods, such as multi-level Monte Carlo (MLMC) and multi-index Monte Carlo (MIMC), can be applied to assess the impact of variations in the microstructure of polycrystalline materials on the predictions of homogenized materials properties. We show that by adaptively exploiting the fidelity hierarchy, we can significantly reduce the number of microstructures required to reach a certain prescribed accuracy. Finally, we show how our approach can be extended to a multi-fidelity framework, where we allow the underlying constitutive model to be chosen from either a phenomenological plasticity model or a dislocation-density-based model.

In real-time remote sensing application, frames of data are continuously flowing into the processing system. The capability of detecting objects of interest and tracking them as they move is crucial to many critical surveillance and monitoring missions. Detecting small objects using remote sensors is an ongoing, challenging problem. Since object(s) are located far away from the sensor, the target’s Signal-to-Noise-Ratio (SNR) is low. The Limit of Detection (LOD) for remote sensors is bounded by what is observable on each image frame. In this paper, we present a new method, a “Multi-frame Moving Object Detection System (MMODS)”, to detect small, low SNR objects that are beyond what a human can observe in a single video frame. This is demonstrated by using simulated data where our technology-detected objects are as small as one pixel with a targeted SNR, close to 1:1. We also demonstrate a similar improvement using live data collected with a remote camera. The MMODS technology fills a major technology gap in remote sensing surveillance applications for small target detection. Our method does not require prior knowledge about the environment, pre-labeled targets, or training data to effectively detect and track slow- and fast-moving targets, regardless of the size or the distance.

Abstract not provided.