Publications

Systems engineering today faces a wide array of challenges, ranging from new operational environments to disruptive technological — necessitating approaches to improve research and development (R&D) efforts. Yet, emphasizing the Aristotelian argument that the “whole is greater than the sum of its parts” seems to offer a conceptual foundation creating new R&D solutions. Invoking systems theoretic concepts of emergence and hierarchy and analytic characteristics of traceability, rigor, and comprehensiveness is potentially beneficial for guiding R&D strategy and development to bridge the gap between theoretical problem spaces and engineering-based solutions. In response, this article describes systems–theoretic process analysis (STPA) as an example of one such approach to aid in early-systems R&D discussions. STPA—a ‘top-down’ process that abstracts real complex system operations into hierarchical control structures, functional control loops, and control actions—uses control loop logic to analyze how control actions (designed for desired system behaviors) may become violated and drive the complex system toward states of higher risk. By analyzing how needed controls are not provided (or out of sequence or stopped too soon) and unneeded controls are provided (or engaged too long), STPA can help early-system R&D discussions by exploring how requirements and desired actions interact to either mitigate or potentially increase states of risk that can lead to unacceptable losses. This article will demonstrate STPA's benefit for early-system R&D strategy and development discussion by describing such diverse use cases as cyber security, nuclear fuel transportation, and US electric grid performance. Together, the traceability, rigor, and comprehensiveness of STPA serve as useful tools for improving R&D strategy and development discussions. In conclusion, leveraging STPA as well as related systems engineering techniques can be helpful in early R&D planning and strategy development to better triangulate deeper theoretical meaning or evaluate empirical results to better inform systems engineering solutions.

Magnetic properties of more than 20 Cantor alloy samples of varying composition were investigated over a temperature range of 5 K to 300 K and in fields of up to 70 kOe using magnetometry and muon spin relaxation. Two transitions are identified: a spin-glass-like transition that appears between 55K and 190K, depending on composition, and a ferrimagnetic transition that occurs at approximately 43K in multiple samples with widely varying compositions. The magnetic signatures at 43K are remarkably insensitive to chemical composition. A modified Curie-Weiss model was used to fit the susceptibility data and to extract the net effective magnetic moment for each sample. The resulting values for the net effective moment were either diminished with increasing Cr or Mn concentrations or enhanced with decreasing Fe, Co, or Ni concentrations. Beyond a sufficiently large effective moment, the magnetic ground state transitions from ferrimagnetism to ferromagnetism. The effective magnetic moments, together with the corresponding compositions, are used in a global linear regression analysis to extract element-specific effective magnetic moments, which are compared to the values obtained by ab initio based density functional theory calculations. Finally, these moments provide the information necessary to controllably tune the magnetic properties of Cantor alloy variants.

Abstract not provided.

Process variations within Field Programmable Gate Arrays (FPGAs) provide a rich source of entropy and are therefore well-suited for the implementation of Physical Unclonable Functions (PUFs). However, careful considerations must be given to the design of the PUF architecture as a means of avoiding undesirable localized bias effects that adversely impact randomness, an important statistical quality characteristic of a PUF. Here in this paper, we investigate a ring-oscillator (RO) PUF that leverages localized entropy from individual look-up table (LUT) primitives. A novel RO construction is presented that enables the individual paths through the LUT primitive to be measured and isolated at high precision, and an analysis is presented that demonstrates significant levels of localized design bias. The analysis demonstrates that delay-based PUFs that utilize LUTs as a source of entropy should avoid using FPGA primitives that are localized to specific regions of the FPGA, and instead, a more robust PUF architecture can be constructed by distributing path delay components over a wider region of the FPGA fabric. Compact RO PUF architectures that utilize multiple configurations within a small group of LUTs are particularly susceptible to these types of design-level bias effects. The analysis is carried out on data collected from a set of identically designed, hard macro instantiations of the RO implemented on 30 copies of a Zynq 7010 SoC.

Organic co-crystals have emerged as a promising class of semiconductors for next-generation optoelectronic devices due to their unique photophysical properties. This paper presents a joint experimental-theoretical study comparing the crystal structure, spectroscopy, and electronic structure of two charge transfer co-crystals. Reported herein is a novel co-crystal Npe:TCNQ, formed from 4-(1-naphthylvinyl)pyridine (Npe) and 7,7,8,8-tetracyanoquinodimethane (TCNQ) via molecular self-assembly. This work also presents a revised study of the co-crystal composed of Npe and 1,2,4,5-tetracyanobenzene (TCNB) molecules, Npe:TCNB, herein reported with a higher-symmetry (monoclinic) crystal structure than previously published. Npe:TCNB and Npe:TCNQ dimer clusters are used as theoretical model systems for the co-crystals; the geometries of the dimers are compared to geometries of the extended solids, which are computed with periodic boundary conditions density functional theory. UV-Vis absorption spectra of the dimers are computed with time-dependent density functional theory and compared to experimental UV-Vis diffuse reflectance spectra. Both Npe:TCNB and Npe:TCNQ are found to exhibit neutral character in the S0 state and ionic character in the S1 state. The high degree of charge transfer in the S1 state of both Npe:TCNB and Npe:TCNQ is rationalized by analyzing the changes in orbital localization associated with the S1 transitions.

Maximizing the production of heterologous biomolecules is a complex problem that can be addressed with a systems-level understanding of cellular metabolism and regulation. Specifically, growth-coupling approaches can increase product titers and yields and also enhance production rates. However, implementing these methods for non-canonical carbon streams is challenging due to gaps in metabolic models. Over four design-build-test-learn cycles, we rewire Pseudomonas putida KT2440 for growth-coupled production of indigoidine from para-coumarate. We explore 4,114 potential growth-coupling solutions and refine one design through laboratory evolution and ensemble data-driven methods. The final growth-coupled strain produces 7.3 g/L indigoidine at 77% maximum theoretical yield in para-coumarate minimal medium. The iterative use of growth-coupling designs and functional genomics with experimental validation was highly effective and agnostic to specific hosts, carbon streams, and final products and thus generalizable across many systems.

A new capability for modeling graded density reactive flow materials in the shock physics hydrocode, CTH, is demonstrated here. Previously, materials could be inserted in CTH with graded material properties, but the sensitivity of the material was not adjusted based on these properties. Of particular interest are materials that are graded in density, sometimes due to pressing or other assembly operations. The sensitivity of explosives to both density and temperature has been well demonstrated in the literature, but to-date the material parameters for use in a simulation were fit to a single condition and applied to the entire material, or the material had to be inserted in sections and each section assigned a condition. The reactive flow model xHVRB has been extended to shift explosive sensitivity with initial density, so that sensitivity is also graded in the material. This capability is demonstrated for use in three examples. The first models detonation transfer in a graded density pellet of HNS, the second is a shaped charge with density gradients in the explosive, and the third is an explosively formed projectile.

For reactive burn models in hydrocodes, an equilibrium closure assumption is typically made between the unreacted and product equations of state. In the CTH [1] (not an acronym) hydrocode the assumption of density and temperature equilibrium is made by default, while other codes make a pressure and temperature equilibrium assumption. The main reason for this difference is the computational efficiency in making the density and temperature assumption over the pressure and temperature one. With fitting to data, both assumptions can accurately predict reactive flow response using the various models, but the model parameters from one code cannot necessarily be used directly in a different code with a different closure assumption. A new framework is intro-duced in CTH to allow this assumption to be changed independently for each reactive material. Comparisons of the response and computational cost of the History Variable Reactive Burn (HVRB) reactive flow model with the different equilibrium assumptions are presented.

Work evaluating spent nuclear fuel (SNF) dry storage canister surface environments and canister corrosion progressed significantly in FY23, with the goal of developing a scientific understanding of the processes controlling initiation and growth of stress corrosion cracking (SCC) cracks in stainless steel canisters in relevant storage environments. The results of the work performed at Sandia National Laboratories (SNL) will guide future work and will contribute to the development of better tools for predicting potential canister penetration by SCC.

The purpose of this report is to document updates on the apparatus to simulate commercial vacuum drying procedures 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. Scaled tests that incorporate relevant physics and well-controlled boundary conditions are essential to provide insight and guidance to the simulation of prototypic systems undergoing drying processes. This report documents fiscal year 2023 (FY23) updates on 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. In FY23, a series of four simulated commercial drying tests was completed. This report presents the temperature and pressure histories of the drying tests as well as axial temperature profiles that can be compared to data from the Electric Power Research Institute (EPRI) High Burnup Demonstration TN-32B cask. Water content measurements and dew point calculations from a Hiden Analytical HPR-30 mass spectrometer are also presented in this report. Due to familiarization with this first-of-a-kind system, refinements to equipment calibration and test procedures have been identified to better match commercial drying cycles for future simulated tests. However, the presented data demonstrate the successful construction and operation of a viable research platform for quantifying residual water content closely approaching that expected in dry storage canisters during commercial drying procedures.

For the first time the optimal local truncation error method (OLTEM) with 125-point stencils and unfitted Cartesian meshes has been developed in the general 3-D case for the Poisson equation for heterogeneous materials with smooth irregular interfaces. The 125-point stencils equations that are similar to those for quadratic finite elements are used for OLTEM. The interface conditions for OLTEM are imposed as constraints at a small number of interface points and do not require the introduction of additional unknowns, i.e., the sparse structure of global discrete equations of OLTEM is the same for homogeneous and heterogeneous materials. The stencils coefficients of OLTEM are calculated by the minimization of the local truncation error of the stencil equations. These derivations include the use of the Poisson equation for the relationship between the different spatial derivatives. Such a procedure provides the maximum possible accuracy of the discrete equations of OLTEM. In contrast to known numerical techniques with quadratic elements and third order of accuracy on conforming and unfitted meshes, OLTEM with the 125-point stencils provides 11-th order of accuracy, i.e., an extremely large increase in accuracy by 8 orders for similar stencils. The numerical results show that OLTEM yields much more accurate results than high-order finite elements with much wider stencils. The increased numerical accuracy of OLTEM leads to an extremely large increase in computational efficiency. Additionally, a new post-processing procedure with the 125-point stencil has been developed for the calculation of the spatial derivatives of the primary function. The post-processing procedure includes the minimization of the local truncation error and the use of the Poisson equation. It is demonstrated that the use of the partial differential equation (PDE) for the 125-point stencils improves the accuracy of the spatial derivatives by 6 orders compared to post-processing without the use of PDE as in existing numerical techniques. At an accuracy of 0.1% for the spatial derivatives, OLTEM reduces the number of degrees of freedom by 900 - 4∙10⁶ times compared to quadratic finite elements. The developed post-processing procedure can be easily extended to unstructured meshes and can be independently used with existing post-processing techniques (e.g., with finite elements).

In this study, we demonstrate the ability of polarity inversion of sputtered aluminum scandium nitride thin films through post-fabrication processes with domain widths as small as 220 nm at a periodicity of 440 nm. An approach using photo- and electron-beam lithography to generate sub-quarter micrometer feature size with adjustable duty cycle through a lift-off process is presented. The film with a coercive field Ec+ of 5.35 MV/cm was exercised first with a 1 kHz triangular double bipolar wave and ultimately poled with a 0.5 kHz double monopolar wave using a Radiant Precision Premier II tester. The metal polar (M-polar) and nitrogen polar (N-polar) domains were identified and characterized through potassium hydroxide wet etching as well as piezoresponse force microscopy (PFM). Well-distinguished boundaries between the oppositely polarized domain regions were confirmed through the phase diagram of the PFM results. The relationship between the electrode width, poling voltage, and domain growth was experimentally studied and statistically analyzed, where 7.96 nm/V domain width broadening vs escalating poling voltage was observed. This method produces extremely high domain spatial resolution in III-nitride materials via poling and is transferable to a CMOS-compatible photolithography process. The spatial resolution of the periodically poled Al0.68Sc0.32N is suitable for second-harmonic generation of deep ultraviolet through quasi-phase-matching and RF MEMS operating in the X-Band spectrum.

Accurate fuel oxidation mechanisms can enable predictive capabilities that aid in advancing combustion technologies. High-level computational kinetics can yield reasonable rate coefficients with uncertainties, in some cases, below a factor of 2. Computed rate coefficients can be constrained further by optimizing against experimental data. Here, we explore the application of genetic algorithm (GA) optimization to constrain computed rate coefficients in complex fuel oxidation mechanisms in conjunction with temperature-dependent species mole fractions from jet-stirred reactor (JSR) measurements. Cyclohexane is a model candidate for understanding the reactivity of cyclic fuels. In this work, we optimize the rate coefficients of the most recent literature cyclohexane mechanism, which incorporates theoretically computed rate coefficients for the reaction networks stemming from the first and second O2 addition pathways, against the experimental results of two separate literature JSR studies. Optimization consistency is evaluated by carrying out three GA optimizations: fitting to the temperature-dependent species mole fractions in each JSR experiment separately and simultaneously fitting the species mole fractions in both experiments. Local sensitivity analyses are used to identify five influential low-temperature oxidation reactions for optimization. Although the three optimizations do not yield identical rate coefficients, the direction of change in all five rate coefficients is consistent among the three optimizations. Performance of the models from the three optimizations is assessed against literature ignition delay times with differences in the level of agreement observed among the different optimizations. Comparisons are made with our recent optimization work of a cyclopentane oxidation master-equation model against time-resolved species concentrations, and insights and improvements of the strategy for constraining rate coefficients using GA optimization are discussed.

Tritium permeability in zirconium-based tritium getter critically impacts tritium storage and environmental safety during operation of tritium-producing burnable absorber rods (TPBARs). Previous experiments indicated that during irradiation operation, the hydrogen equilibrium pressured is increased. Further experimental and modeling studies suggested that the enhanced tritium release observed for reactor scale assemblies might be related to a thermal diffusion known as the Soret effect. A direct measurement of the Soret factor, however, has not been performed. To improve TPBAR and other nuclear applications, here we have applied two non-equilibrium molecular dynamics methods to study thermal diffusion of hydrogen isotopes in low-concentration zirconium hydrides. One of the methods produces sufficiently converged results to distinguish crystal orientation, isotope type, and concentration effects. In conclusion, with this method, crystal orientation, isotope type, and concentration effects are discussed.

Local crystallographic features negatively affect quantum spin defects by changing the local electrostatic environment, often resulting in degraded or varied qubit optical and coherence properties. Few tools exist that enable the deterministic synthesis and study of such intricate systems on the nano-scale, making defect-to-defect strain environment quantification difficult. In this paper, we highlight state-of-the-art capabilities from the U.S. Department of Energy’s Nanoscale Science Research Centers that directly address these shortcomings. Specifically, we demonstrate how complementary capabilities of nano-implantation and nano-diffraction can be used to demonstrate the quantum relevant, spatially deterministic creation of neutral divacancy centers in 4H silicon carbide, while investigating and characterizing these systems on the ≤ 25 nm scale with strain sensitivities on the order of 1 × 10 − 6 , relevant to defect formation dynamics. This work lays the foundation for ongoing studies into the dynamics and deterministic formation of low strain homogeneous quantum relevant spin defects in the solid state.

Microneedle sensors could enable minimally-invasive, continuous molecular monitoring – informing on disease status and treatment in real-time. Wearable sensors for pharmaceuticals, for example, would create opportunities for treatments personalized to individual pharmacokinetics. Here, we demonstrate a commercial-off-the-shelf (COTS) approach for microneedle sensing using an electrochemical aptamer-based sensor that detects the high-toxicity antibiotic, vancomycin. Wearable monitoring of vancomycin could improve patient care by allowing targeted drug dosing within its narrow clinical window of safety and efficacy. To produce sensors, we miniaturize the electrochemical aptamer-based sensors to a microelectrode format, and embed them within stainless steel microneedles (sourced from commercial insulin pen needles). The microneedle sensors achieve quantitative measurements in body-temperature undiluted blood. Further, the sensors effectively maintain electrochemical signal within porcine skin. This COTS approach requires no cleanroom fabrication or specialized equipment, and produces individually-addressable, sterilizable microneedle sensors capable of easily penetrating the skin. In the future, this approach could be adapted for multiplexed detection, enabling real-time monitoring of a range of biomarkers.

The Sibling Pin test campaign is a Department of Energy (DOE) research activity within the Spent Fuel and Waste Science and Technology (SFWST) program that is tasked with characterization of high burnup (HBU) fuel in support of the High Burnup Spent Fuel Data Project. Of the 25 fuel rods in the Sibling Pin inventory, approximately 9 rod lengths have been consumed during the first phase (Phase I) of the test campaign leaving approximately 16 rod lengths for the second phase (Phase II) of testing. This plan outlines the Phase II testing and the motivations for performing these tests. Priorities for Phase II testing are based on previously identified knowledge gaps, lessons-learned from Phase I work, the original objectives of the High Burnup Spent Fuel Data Project and the Sibling Pin test campaign, and input from external stakeholders. The priorities for Phase II testing are to obtain data to characterize the effects of annealing on cladding mechanical properties and fuel rod performance, to quantify the creep behavior of cladding materials and fuel rods and the effects of creep deformations on the performance of cladding and fuel rods, and to gather data to support the final closure of the hydride reorientation and radial hydride induced embrittlement gap for HBU fuel rods.

Translating the surging interest in neuromorphic electronic components, such as those based on nonlinearities near Mott transitions, into large-scale commercial deployment faces steep challenges in the current lack of means to identify and design key material parameters. These issues are exemplified by the difficulties in connecting measurable material properties to device behavior via circuit element models. Here, the principle of local activity is used to build a model of VO2/SiN Mott threshold switches by sequentially accounting for constraints from a minimal set of quasistatic and dynamic electrical and high-spatial-resolution thermal data obtained via in situ thermoreflectance mapping. By combining independent data sets for devices with varying dimensions, the model is distilled to measurable material properties, and device scaling laws are established. The model can accurately predict electrical and thermal conductivities and capacitances and locally active dynamics (especially persistent spiking self-oscillations). The systematic procedure by which this model is developed has been a missing link in predictively connecting neuromorphic device behavior with their underlying material properties, and should enable rapid screening of material candidates before employing expensive manufacturing processes and testing procedures.

Motivated by recent experimental results we calculate from first-principles the lifetime of low-energy quasiparticles in bilayer graphene (BLG). Here, we take into account the scattering rate arising from electron-electron interactions within the GW approximation for the electron self-energy and consider several p-type doping levels ranging from 0 to ρ ≈ 2.4 × 10¹² holes/cm². In the undoped case we find that the average inverse lifetime scales linearly with energy away from the charge neutrality point, with values in good agreement with experiments. The decay rate is approximately three times larger than in monolayer graphene, a consequence of the enhanced screening in BLG. In the doped case, the dependence of the inverse lifetime on quasiparticle energy acquires a non-linear component due to the opening of an additional decay channel mediated by acoustic plasmons.

Here, we study the impact of deep-level defects on trap-assisted Auger–Meitner recombination in c-plane InGaN/GaN LEDs using a small-signal electroluminescence (SSEL) method and deep-level optical spectroscopy (DLOS). Carrier dynamics information, including carrier lifetime, recombination rate, and carrier density, is obtained from SSEL, while DLOS is used to obtain the deep-level defect density. Through fitting the nonradiative recombination rates of wafers with different deep-level defect densities, we obtain the Shockley–Read–Hall (SRH) and trap-assisted Auger–Meitner recombination (TAAR) coefficients. We show that defect-related nonradiative recombination, including both SRH and TAAR, accounts for a relatively small fraction of the total nonradiative recombination, which is dominated by intrinsic Auger–Meitner recombination. The interplay between carrier localization and Coulomb enhancement has a different impact on radiative and intrinsic Auger–Meitner recombination. Evidence is presented that the imbalance between the change of radiative and intrinsic Auger–Meitner recombination is the primary cause of the efficiency droop at high carrier densities in the samples studied.

We study the impact of deep-level defects on trap-assisted Auger-Meitner recombination in c-plane InGaN/GaN LEDs using a small-signal electroluminescence (SSEL) method and deep-level optical spectroscopy (DLOS). Carrier dynamics information, including carrier lifetime, recombination rate, and carrier density, is obtained from SSEL, while DLOS is used to obtain the deep-level defect density. Through fitting the nonradiative recombination rates of wafers with different deep-level defect densities, we obtain the Shockley-Read-Hall (SRH) and trap-assisted Auger-Meitner recombination (TAAR) coefficients. We show that defect-related nonradiative recombination, including both SRH and TAAR, accounts for a relatively small fraction of the total nonradiative recombination, which is dominated by intrinsic Auger-Meitner recombination. The interplay between carrier localization and Coulomb enhancement has a different impact on radiative and intrinsic Auger-Meitner recombination. Evidence is presented that the imbalance between the change of radiative and intrinsic Auger-Meitner recombination is the primary cause of the efficiency droop at high carrier densities in the samples studied.

Cast Monel alloys are used in applications requiring a combination of good mechanical properties and excellent resistance to corrosion. Despite prevalent industrial use, relatively few studies have been conducted to investigate the relationships between composition, solidification behavior, and microstructure. Given that these alloys are used in the cast and welded conditions, these factors have a significant influence over the material properties. Here, in this work, microstructural characterization, electron probe microanalysis, X-ray diffraction, and differential scanning calorimetry were used to study how changes in Si and Nb concentrations affected the solidification path and microstructure of Monel alloys. It was found that increasing Nb concentration stabilized higher amounts of MC carbides and suppressed graphite formation during solidification. It was also found that the high nominal concentration and segregation of Si to the liquid led to the formation of Ni₃₁Si₁₂ and other silicides via terminal eutectic reactions at the end of solidification. A pseudo-binary solidification diagram was constructed using experimental data and was applied to predict the mass fraction of solidified eutectic as a function of composition. The modeled microstructures were found to be in good agreement with experimentally measured phase fractions.

Here, we perform all-atom molecular dynamics simulations of lithium triflate in 1,2-dimethoxyethane using six different literature force fields. This system is representative of many experimental studies of lithium salts in solvents and polymers. We show that multiple historically common force fields for lithium ions give qualitatively incorrect results when compared with those from experiments and quantum chemistry calculations. We illustrate the importance of correctly selecting force field parameters and give recommendations on the force field choice for lithium electrolyte applications.

Alkene ozonolysis generates short-lived Criegee intermediates that are a significant source of hydroxyl (OH) radicals. This study demonstrates that roaming of the separating OH radicals can yield alternate hydroxycarbonyl products, thereby reducing the OH yield. Specifically, hydroxybutanone has been detected as a stable product arising from roaming in the unimolecular decay of the methyl-ethyl-substituted Criegee intermediate (MECI) under thermal flow cell conditions. The dynamical features of this novel multistage dissociation plus a roaming unimolecular decay process have also been examined with ab initio kinetics calculations. Experimentally, hydroxybutanone isomers are distinguished from the isomeric MECI by their higher ionization threshold and distinctive photoionization spectra. Moreover, the exponential rise of the hydroxybutanone kinetic time profile matches that for the unimolecular decay of MECI. A weaker methyl vinyl ketone (MVK) photoionization signal is also attributed to OH roaming. Complementary multireference electronic structure calculations have been utilized to map the unimolecular decay pathways for MECI, starting with 1,4 H atom transfer from a methyl or methylene group to the terminal oxygen, followed by roaming of the separating OH and butanonyl radicals in the long-range region of the potential. Roaming via reorientation and the addition of OH to the vinyl group of butanonyl is shown to yield hydroxybutanone, and subsequent C-O elongation and H-transfer can lead to MVK. A comprehensive theoretical kinetic analysis has been conducted to evaluate rate constants and branching yields (ca. 10-11%) for thermal unimolecular decay of MECI to conventional and roaming products under laboratory and atmospheric conditions, consistent with the estimated experimental yield (ca. 7%).

As a part of NASA's efforts in space, options are being examined for an Artemis moon base project to be deployed. This project requires a system of interconnected, but separate, DC microgrids for habitation, mining, and fuel processing. This in-place use of power resources is called in-situ resource utilization (ISRU). These microgrids are to be separated by 9-12 km and each contains a photovoltaic (PV) source, energy storage systems (ESS), and a variety of loads, separated by level of criticality in operation. The separate microgrids need to be able to transfer power between themselves in cases where there are generation shortfall, faults, or other failures in order to keep more critical loads running and ensure safety of personnel and the success of mission goals. In this work, a 2 grid microgrid system is analyzed involving a habitation unit and a mining unit separated by a tie line. A set of optimal controls that has been developed, including power flow controls on the tie line, dispatch of PV generation, and dispatch of non-critical loads, is analyzed, and validated in hardware on the Secure Scalable Microgrid Testbed (SSMTB). This testbed includes hardware emulators for a variety of energy sources, energy storage devices, pulsed loads, and other loads.

This report describes specific activities in the Fiscal Year (FY) 2023 associated with the Geologic Disposal Safety Assessment (GDSA) Repository Systems Analysis (RSA) work package funded by the Spent Fuel and Waste Science and Technology (SFWST) Campaign of the U.S. Department of Energy Office of Nuclear Energy (DOE-NE), Office of Spent Fuel and Waste Disposition (SFWD).

Abstract not provided.

The wave energy control competition established a benchmark problem which was offered as an open challenge to the wave energy system control community. The competition had two stages: In the first stage, competitors used a standard wave energy simulation platform (WEC-Sim) to evaluate their controllers while, in the second stage, competitors were invited to test their controllers in a real-time implementation on a prototype system in a wave tank. The performance function used was based on converted energy across a range of standard sea states, but also included aspects related to economic performance, such as peak/average power, peak force, etc. This paper compares simulated and experimental results and, in particular, examines if the results obtained in a linear system simulation are borne out in reality. Overall, within the scope of the device tested, the range of sea states employed, and the performance metric used, the conclusion is that high-performance WEC controllers work well in practice, with good carry-over from simulation to experimentation. However, the availability of a good WEC mathematical model is deemed to be crucial.

Abstract not provided.

Achieving brain-like efficiency in computing requires a co-design between the development of neural algorithms, brain-inspired circuit design, and careful consideration of how to use emerging devices. The recognition that leveraging device-level noise as a source of controlled stochasticity represents an exciting prospect of achieving brain-like capabilities in probabilistic neural algorithms, but the reality of integrating stochastic devices with deterministic devices in an already-challenging neuromorphic circuit design process is formidable. Here, we explore how the brain combines different signaling modalities into its neural circuits as well as consider the implications of more tightly integrated stochastic, analog, and digital circuits. Further, by acknowledging that a fully CMOS implementation is the appropriate baseline, we conclude that if mixing modalities is going to be successful for neuromorphic computing, it will be critical that device choices consider strengths and limitations at the overall circuit level.

Abstract not provided.

Abstract not provided.

Frontal polymerization involves the propagation of a thermally driven polymerization wave through a monomer solution to rapidly generate high-performance polymeric materials with little energy input. The balance between latent catalyst activation and sufficient reactivity to sustain a front can be difficult to achieve and often results in systems with poor storage lives. This is of particular concern for frontal ring-opening metathesis polymerization (FROMP) where gelation occurs within a single day of resin preparation due to the highly reactive nature of Grubbs-type catalysts. In this report we demonstrate the use of encapsulated catalysts to provide remarkable latency to frontal polymerization systems, specifically using the highly active dicyclopentadiene monomer system. Negligible differences were observed in the frontal velocities or thermomechanical properties of the resulting polymeric materials. FROMP systems with encapsulated catalyst particles are shown with storage lives exceeding 12 months and front rates that increase over a well-characterized 2 month period. Moreover, the modularity of this encapsulation method is demonstrated by encapsulating a platinum catalyst for the frontal polymerization of silicones by using hydrosilylation chemistry.

Abstract not provided.

Living document updating the 5.14 version, SAND2023-03603 of May 2023.

The injection and storage of anthropogenic CO2 in the subsurface is being deployed as a climate change mitigation tool; however, diagenetic-paragenetic heterogeneity in sandstone reservoirs often contributes to interval specific chemomechanical changes that affect injection and can increase leakage risk. Here, we address reservoir heterogeneities’ impact on chemomechanical changes in a macroporous-dominated lithofacies of Morrow B sandstone, a formation containing several diagenetically-distinct hydraulic facies while undergoing enhanced oil recovery (EOR) and carbon dioxide (CO2) sequestration. We performed three flow-through experiments using a CO2-charged or uncharged formation water combined with four indirect tensile strength tests per post-test sample. We then used the microstructure and paragenetic sequence to understand chemomechanical weakening with key observations as follows: dissolution of carbonates and feldspars changed porosity; increased permeability led to reclassifying each sample in a different hydraulic flow unit; decreased ultrasonic velocity; and did not lead to a loss of tensile strength. Tensile strength maintenance occurred due to the low abundance and minor dissolution of siderite, the stability of quartz, and the relative position of diagenetic ankerite within feldspar. This macroporous-dominated lithofacies is the primary reservoir for the Morrow B Sandstone, and is analogous to other porous sandstone reservoirs. It represents an end-member of a chemomechanically low-risk siliceous CO2 sequestration and CO2-EOR reservoir.

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

This project applies methods in Bayesian inference and modern statistical methods to quantify the value of new experimental data, in the form of new or modified diagnostic configurations and/or experiment designs. We demonstrate experiment design methods that can be used to identify the highest priority diagnostic improvements or experimental data to obtain in order to reduce uncertainties on critical inferred experimental quantities and select the best course of action to distinguish between competing physical models. Bayesian statistics and information theory provide the foundation for developing the necessary metrics, using two high impact experimental platforms on Z as exemplars to develop and illustrate the technique. We emphasize that the general methodology is extensible to new diagnostics (provided synthetic models are available), as well as additional platforms. We also discuss initial scoping of additional applications that began development in the last year of this LDRD.

Modeling of phenomena such as anomalous transport via fractional-order differential equations has been established as an effective alternative to partial differential equations, due to the inherent ability to describe large-scale behavior with greater efficiency than fully resolved classical models. In this review article, we first provide a broad overview of fractional-order derivatives with a clear emphasis on the stochastic processes that underlie their use. We then survey three exemplary application areas — subsurface transport, turbulence, and anomalous materials — in which fractional-order differential equations provide accurate and predictive models. For each area, we report on the evidence of anomalous behavior that justifies the use of fractional-order models, and survey both foundational models as well as more expressive state-of-the-art models. We also propose avenues for future research, including more advanced and physically sound models, as well as tools for calibration and discovery of fractional-order models.

Crystal plasticity finite element model (CPFEM) is a powerful numerical simulation in the integrated computational materials engineering toolboxes that relates microstructures to homogenized materials properties and establishes the structure–property linkages in computational materials science. However, to establish the predictive capability, one needs to calibrate the underlying constitutive model, verify the solution and validate the model prediction against experimental data. Bayesian optimization (BO) has stood out as a gradient-free efficient global optimization algorithm that is capable of calibrating constitutive models for CPFEM. In this paper, we apply a recently developed asynchronous parallel constrained BO algorithm to calibrate phenomenological constitutive models for stainless steel 304 L, Tantalum, and Cantor high-entropy alloy.

The ion velocity distribution functions of thermonuclear plasmas generated by spherical laser direct drive implosions are studied using deuterium-tritium (DT) and deuterium-deuterium (DD) fusion neutron energy spectrum measurements. A hydrodynamic Maxwellian plasma model accurately describes measurements made from lower temperature (<10 keV), hydrodynamiclike plasmas, but is insufficient to describe measurements made from higher temperature more kineticlike plasmas. The high temperature measurements are more consistent with Vlasov-Fokker-Planck (VFP) simulation results which predict the presence of a bimodal plasma ion velocity distribution near peak neutron production. These measurements provide direct experimental evidence of non-Maxwellian ion velocity distributions in spherical shock driven implosions and provide useful data for benchmarking kinetic VFP simulations.

This study presents a deep learning based methodology for both remote sensing and design of acoustic scatterers. The ability to determine the shape of a scatterer, either in the context of material design or sensing, plays a critical role in many practical engineering problems. This class of inverse problems is extremely challenging due to their high-dimensional, nonlinear, and ill-posed nature. To overcome these technical hurdles, we introduce a geometric regularization approach for deep neural networks (DNN) based on non-uniform rational B-splines (NURBS) and capable of predicting complex 2D scatterer geometries in a parsimonious dimensional representation. Then, this geometric regularization is combined with physics-embedded learning and integrated within a robust convolutional autoencoder (CAE) architecture to accurately predict the shape of 2D scatterers in the context of identification and inverse design problems. An extensive numerical study is presented in order to showcase the remarkable ability of this approach to handle complex scatterer geometries while generating physically-consistent acoustic fields. The study also assesses and contrasts the role played by the (weakly) embedded physics in the convergence of the DNN predictions to a physically consistent inverse design.

This paper describes a process for forming a buried field shield in GaN by an etch-and-regrowth process, which is intended to protect the gate dielectric from high fields in the blocking state. GaN trench MOSFETs made at Sandia serve as the baseline to show the limitations in making a trench gated device without a method to protect the gate dielectric. Device data coupled with simulations show device failure at 30% of theoretical breakdown for devices made without a field shield. Implementation of a field shield reduces the simulated electric field in the dielectric to below 4 MV/cm at breakdown, which eliminates the requirement to derate the device in order to protect the dielectric. For realistic lithography tolerances, however, a shield-to-channel distance of 0.4 μm limits the field in the gate dielectric to 5 MV/cm and requires a small margin of device derating to safeguard a long-term reliability and lifetime of the dielectric.

Abstract not provided.

Abstract not provided.

We explore the use of reduced physics models for efficient kinetic particle simulations of space charge limited (SCL) emission in inner magnetically insulated transmission lines (inner MITLs), with application to Sandia National Laboratories' Z machine. We propose a drift kinetic (guiding center) model of electron motion in place of a fully kinetic model and electrostatic-magnetostatic fields in place of electromagnetic fields. The validity of these approximations is suggested by the operational parameters of the Z machine, namely, current pulse lengths of order 100 ns compared with Larmor periods typically smaller than 10-11 s, typical Larmor radii of a few (tens) of microns (magnetic fields of tens to hundreds of Tesla) compared with MITL dimensions of a few centimeters, and transient time of light waves along the inner MITL of order a fraction of a nanosecond. Guiding center orbits eliminate the fast electron gyromotion, which enables the use of tens to hundreds of times larger time steps in the numerical particle advance. Electrostatic-magnetostatic fields eliminate the Courant-Friedrichs-Lewy (CFL) numerical stability limit on the time step and allow the use of higher grid resolutions or, alternatively, larger time steps in the fields advance. Overall, potential computational cost savings of tens to hundreds of times exists. The applicability of the reduced physics models is examined on two problems. First, in the simulation of space charge limited emission of electrons from the cathode surface due to high electric fields in a radial inner MITL geometry with a short load. In particular, it is shown that a drift kinetic-based particle-in-cell (PIC) model with electrostatic-magnetostatic fields is able to accurately reproduce well-known physics of electron vortex formation, spatially and temporally. Second, deeper understanding is gained of the mechanism behind vortex formation in this MITL geometry by considering an exemplar problem of an electron block of charge. This simpler setup reveals that the main mechanism of vortex formation can be attributed to pure drift motion of the electrons, that is, the (fully kinetic) gyromotion of the electrons is inessential to the process. This exemplar problem also suggests a correlation of the spatial dimensions of vortices to the thickness of the electron layer, as observed in SCL simulations. It also confirms that the electromagnetic nature of the fields does not play an essential role. Finally, an improved hybrid fully kinetic and drift kinetic model for electron motion is proposed, as means of capturing finite Larmor radius (FLR) effects; the particular FLR physics that is missed by the drift kinetic model is the particle-wall interaction. By initializing SCL emitted electrons as fully kinetic and later transitioning them to drift kinetic, according to simple criteria, the accuracy of SCL simulations can be improved, while preserving the potential for computational efficiency.

In polymer-filled granular composites, damage may develop in mechanical loading prior to material failure. Damage mechanisms such as microcracking or plastic deformation in the binder phase can substantially alter the material's mesostructure. For energetic materials, such as solid propellants and plastic bonded explosives, these mesostructural changes can have far reaching effects including degraded mechanical properties, potentially increased sensitivity to further insults, and changes in expected performance. Unfortunately, predicting damage is nontrivial due to the complex nature of these composites and the entangled interactions between inelastic mechanisms. In this work, we assess the current literature of experimental knowledge, focusing on the pressure-dependent shear response, and propose a simple simulation framework of bonded particles to study four limiting-case material formulations at both meso- and macro-scales. To construct the four cases, we systematically vary the relative interfacial strength between the polymer binder and granular filler phase and also vary the polymer's glass transition temperature relative to operating temperature which determines how much the binder can plastically deform. These simulations identify key trends in global mechanical response, such as the emergence of strain hardening or softening regimes with increasing pressure which qualitatively resemble experimental results. By quantifying the activation of different inelastic mechanisms, such as bonds breaking and plastically straining, we identify when each mechanism becomes relevant and provide insight into potential origins for changes in mechanical responses. The locations of broken bonds are also used to define larger, mesoscopic cracks to test various metrics of damage. We primarily focus on triaxial compression, but also test the opposite case of triaxial extension to highlight the impact of Lode angle on mechanical behavior.

Code verification plays an important role in establishing the credibility of computational simulations by assessing the correctness of the implementation of the underlying numerical methods. In computational electromagnetics, the numerical solution to integral equations incurs multiple interacting sources of numerical error, as well as other challenges, which render traditional code-verification approaches ineffective. In this paper, we provide approaches to separately measure the numerical errors arising from these different error sources for the method-of-moments implementation of the combined-field integral equation. We demonstrate the effectiveness of these approaches for cases with and without coding errors.

Update to prior 5.14 user manual. I think updates are minor and mostly in the Johnson-cook section. In there those updates are more writing and less on technical changes.

Abstract not provided.