Publications

Structural alloys may experience corrosion when exposed to molten chloride salts due to selective dissolution of active alloying elements. One way to prevent this is to make the molten salt reducing. For the KCl + MgCl₂ eutectic salt mixture, pure Mg can be added to achieve this. However, Mg can form intermetallic compounds with nickel at high temperatures, which may cause alloy embrittlement. This work shows that an optimum level of excess Mg could be added to the molten salt which will prevent corrosion of alloys like 316 H, while not forming any detectable Ni-Mg intermetallic phases on Ni-rich alloy surfaces.

The ability to form pristine interfaces after etching and regrowth of GaN is a prerequisite for epitaxial selective area doping, which in turn is needed for the formation of lateral PN junctions and advanced device architectures. In this work, we report the electrical properties of etched-and-regrown GaN PN diodes using an in situ Cl-based precursor, tertiary butylchloride (TBCl). We demonstrated a regrowth diode with I–V characteristics approaching that from a continuously grown reference diode. The sources of unintentional contamination from the silicon (Si) impurity and the mediating effect of Si during the TBCl etching are also investigated in this study. Furthermore, this work points to the potential of in situ TBCl etching toward the realization of GaN lateral PN junctions.

Waveform modeling is crucial to improving our understanding of observed seismograms. Forward simulation of wavefields provides quantitative methods of testing interactions between complicated source functions and the propagation medium. Here, we discuss three experiments designed to improve under standing of high frequency seismic wave propagation. First, we compare observed and predicted travel times of crustal phases for a set of real observed earthquakes with calculations and synthetic seismograms. Second, we estimate the frequency content of a series of nearly co-located earthquakes of varying magnitude for which we have a relatively well- known 1D velocity model. Third, we apply stochastic perturbations on top of a 3D tomographic model and qualitatively assess how those variations map to differences in the seismograms. While different in scope and aim, these three vignettes illustrate the current state of crustal scale waveform modeling and the potential for future studies to better constrain the structure of the crust.

The following SNL document contains requested radiological survey information, as part of the documentation for the LANL MLU shipment performed by the LANL MLU team the week of October 18th . The surveys were performed in TA-5 October 19th – 21st, 2021. The surveys were for the official shipments of 4 loaded TRUPACTs and 2 empty TRUPACTs. Surveys were completed after the trucks were hitched to their respective trailers.

The galvanostatic intermittent titration technique (GITT) is widely used to evaluate solid-state diffusion coefficients in electrochemical systems. However, the existing analysis methods for GITT data require numerous assumptions, and the derived diffusion coefficients typically are not independently validated. To investigate the validity of the assumptions and derived diffusion coefficients, we employ a direct-pulse fitting method for interpreting the GITT data that involves numerically fitting an electrochemical pulse and subsequent relaxation to a one-dimensional, single-particle, electrochemical model coupled with non-ideal transport to directly evaluate diffusion coefficients. Our non-ideal diffusion coefficients, which are extracted from GITT measurements of the intercalation regime of FeS2 and independently verified through discharge predictions, prove to be 2 orders of magnitude more accurate than ideal diffusion coefficients extracted using conventional methods. We further extend our model to a polydisperse set of particles to show the validity of a single-particle approach when the modeled radius is proportional to the total volume-to-surface-area ratio of the system.

This work demonstrated both NbN and Nb make good electrodes for stabilizing orthorhombic phase of Hf_0.6Zr_0.4O₂ ferroelectric films. Wake up are < 100 cycles. P_r can be as high as 30 µC/cm² - respectively 14 and 18 µC/cm² here. Further, capacitance suggests an orthorhombic phase can be stabilized. Addition of a linear dielectric under modest thickness can tune the P_r and reduce leakage.

Area-selective atomic layer deposition (AS-ALD) is an appealing bottom-up fabrication technique that can produce atomic-scale device features, overcoming challenges in current industrial techniques such as edge alignment errors. TiCI₄ is a common thermal ALD precursor for Ti0₂ thin films, which are appealing candidates for DRAM capacitors due to their excellent dielectric constants. Hydrogen and chlorine termination passivate the Si surface, allowing for selective deposition of TiCI₄ onto HO-terminated areas. However, selectivity loss occurs after several ALD cycles. Ti oxide nucleates onto surface defects on Cl- and H-Si resists. Previously, the use of H-Si as an ALD resist has been studied extensively, but less work has focused on chemical forces driving nucleation, especially for Cl-Si. Here, formation of defect nuclei was investigated with selectivity loss during Ti0₂ ALD with TiCI₄ and water on the (100) and (111) crystal surfaces of hydrogenated, chlorinated, and oxidized Si.

This report documents the activities in a preliminary phase of development for three models: 1) waste package breach model, 2) fuel/basket degradation model, and 3) dual-purpose canister (DPC) crush model. The waste package breach model describes the coupling of mass flow, heat transport, and canister shell deformation in response to a heat-generating (criticality) event. The fuel/basket degradation model describes potential weakening and disaggregation of the DPC structure from corrosion, possibly accelerated by seismic ground motion. Progressively degraded three-dimensional (3D) configurations of the fuel, basket, and shell are generated for future analysis of reactivity (with as-loaded DPC fuel characteristics). Another important application for the fuel/basket degradation model is validation of the two stylized degradation cases currently being used by other investigators for analysis of the as-loaded DPC inventory under disposal conditions. The DPC crush model investigates stability of a typical DPC after breach of the disposal overpack allows fluids from the repository near-field environment to penetrate and externally pressurize the canister shell. Preliminary results show that large deformation of the DPC could occur for external pressure on the order of 10 to 15 MPa, or the shell could be stable (not collapse) with pressure of 20 MPa or greater if the basket plates are fully welded at the connections.

The security of the electric grid and supporting energy systems is crucial to national security. One of the complexities in analyzing the security of energy systems is the safety consequences that may result from accidents. For energy systems, the goal is to ensure that they operate as intended and that any consequences are mitigated or prevented. The integration of safety and security is paramount to protecting these systems from attacks and ensuring that large consequences are prevented. This report describes an integrated safety and security methodology to evaluate cybersecurity events that can lead to large consequences. This novel approach first describes how Systems-Theoretic Process Analysis (STPA) provides a digital causal analysis for Bayesian Networks (BNs). The use of STPA causal analysis provides a systematic approach to constructing BNs that adequately model cyber scenarios that result in consequences. When combined with the technical principles described in Risk-Informed Management of Enterprise Systems (RIMES), a comprehensive risk-informed cybersecurity analysis results that allows decision-makers to prioritize systems that most impact risk.

Solar thermochemical hydrogen (STCH) production is a promising method to generate carbon neutral fuels by splitting water utilizing metal oxide materials and concentrated solar energy. The discovery of materials with enhanced water-splitting performance is critical for STCH to play a major role in the emerging renewable energy portfolio. While perovskite materials have been the focus of many recent efforts, materials screening can be time consuming due to the myriad chemical compositions possible. This can be greatly accelerated through computationally screening materials parameters including oxygen vacancy formation energy, phase stability, and electron effective mass. In this work, the perovskite Gd0.5La0.5Co0.5Fe0.5O3 (GLCF), was computationally determined to be a potential water splitter, and its activity was experimentally demonstrated. During water splitting tests with a thermal reduction temperature of 1,350°C, hydrogen yields of 101 μmol/g and 141 μmol/g were obtained at re-oxidation temperatures of 850 and 1,000°C, respectively, with increasing production observed during subsequent cycles. This is a significant improvement from similar compounds studied before (La0.6Sr0.4Co0.2Fe0.8O3 and LaFe0.75Co0.25O3) that suffer from performance degradation with subsequent cycles. Confirmed with high temperature x-ray diffraction (HT-XRD) patterns under inert and oxidizing atmosphere, the GLCF mainly maintained its phase while some decomposition to Gd2-xLaxO3 was observed.

Bayesian optimization (BO) is an efficient and flexible global optimization framework that is applicable to a very wide range of engineering applications. To leverage the capability of the classical BO, many extensions, including multi-objective, multi-fidelity, parallelization, and latent-variable modeling, have been proposed to address the limitations of the classical BO framework. In this work, we propose a novel multi-objective BO formalism, called srMO-BO-3GP, to solve multi-objective optimization problems in a sequential setting. Three different Gaussian processes (GPs) are stacked together, where each of the GPs is assigned with a different task. The first GP is used to approximate a single-objective computed from the multi-objective definition, the second GP is used to learn the unknown constraints, and the third one is used to learn the uncertain Pareto frontier. At each iteration, a multi-objective augmented Tchebycheff function is adopted to convert multi-objective to single-objective, where the regularization with a regularized ridge term is also introduced to smooth the single-objective function. Finally, we couple the third GP along with the classical BO framework to explore the convergence and diversity of the Pareto frontier by the acquisition function for exploitation and exploration. The proposed framework is demonstrated using several numerical benchmark functions, as well as a thermomechanical finite element model for flip-chip package design optimization.

Two-dimensional (2D) materials with robust ferromagnetic behavior have attracted great interest because of their potential applications in next-generation nanoelectronic devices. Aside from graphene and transition metal dichalcogenides, Bi-based layered oxide materials are a group of prospective candidates due to their superior room-temperature multiferroic response. Here, an ultrathin Bi3Fe2Mn2O10+δ layered supercell (BFMO322 LS) structure was deposited on an LaAlO3 (LAO) (001) substrate using pulsed laser deposition. Microstructural analysis suggests that a layered supercell (LS) structure consisting of two-layer-thick Bi-O slabs and two-layer-thick Mn/Fe-O octahedra slabs was formed on top of the pseudo-perovskite interlayer (IL). A robust saturation magnetization value of 129 and 96 emu cm-3 is achieved in a 12.3 nm thick film in the in-plane (IP) and out-of-plane (OP) directions, respectively. The ferromagnetism, dielectric permittivity, and optical bandgap of the ultrathin BFMO films can be effectively tuned by thickness and morphology variation. In addition, the anisotropy of all ultrathin BFMO films switches from OP dominating to IP dominating as the thickness increases. This study demonstrates the ultrathin BFMO film with tunable multifunctionalities as a promising candidate for novel integrated spintronic devices. This journal is

The following SNL document contains requested forms related to used equipment, as part of the documentation for the MLU shipment that was performed by the LANL MLU team and Crane Services personnel.

The following SNL document contains requested radiological survey information, as part of the documentation for the MLU shipment being performed by the LANL MLU team. The survey was performed in TA-5, on October 19th, 2021. This survey was for radiological coverage for the disassembly of two TRUPACTs, the assembly and loading of their payloads, and the reassembly of the TRUPACTs.

Sandia National Labs (SNL)-designed, portable chemical warfare agent (CWA) detection systems consist of three-stages: collection, separation, and detection. We use microfabrication technologies to miniaturize these stages and to reduce the overall size, weight, power, and (potentially) cost of the final system. Our newest system consists of a multi-dimensional separation stage and an miniature ion mobility spectrometer (IMS) detector for unprecedented system sensitivity, selectivity, and depth of target list.

As new and modernized systems are fielded by the U.S. and Russia, and as China expands its nuclear stockpile with 21st century technology, it is important to ask when do new technologies in the nuclear domain actually matter? When do emerging capabilities and replacements of existing systems change the military realities of the world’s nuclear powers and the lived experiences of the people in these countries? Specifically, it is important to consider what are the attributes of emerging weapon systems that may impact nuclear strategic stability, or in even narrower terms, which attributes of newly fielded military systems may make nuclear conflict more likely or less likely? It is through this understanding that policy makers, voters, and the broader nuclear weapons community can evaluate when and how to respond to emerging technology while reducing the likelihood of nuclear escalation.

Vertical GaN p-n diodes combine excellent efficiencies with incredibly fast protection from unwanted electromagnetic pulses.

Timing spread between the thirty-six Saturn modules affects peak electrical power delivered to the Bremsstrahlung diode and can affect vacuum power flow and impedance behavior of the load. To reduce the module spread, a new megavolt gas-insulated closing switch was developed employing design techniques developed for the Z-machine laser triggered switches while retaining Saturn’s simpler electrical triggering. Two modules were temporarily outfitted with the new switches and used separately into local resistive loads (instead of the usual Saturn electron beam load). A reliable operating point and switch time jitter at that point were the goals of the experiments. The target switch reliability is less than one pre-fire in one thousand switch-shots, and a timing standard deviation of 4 nanoseconds. The switches were able to meet both requirements but the number of tests at the chosen point are limited.

The recent introduction of a new generation of "smart NICs" have provided new accelerator platforms that include CPU cores or reconfigurable fabric in addition to traditional networking hardware and packet offloading capabilities. While there are currently several proposals for using these smartNICs for low-latency, in-line packet processing operations, there remains a gap in knowledge as to how they might be used as computational accelerators for traditional high-performance applications. This work aims to look at benchmarks and mini-applications to evaluate possible benefits of using a smartNIC as a compute accelerator for HPC applications. We investigate NVIDIA's current-generation BlueField-2 card, which includes eight Arm CPUs along with a small amount of storage, and we test the networking and data movement performance of these cards compared to a standard Intel server host. We then detail how two different applications, YASK and miniMD can be modified to make more efficient use of the BlueField-2 device with a focus on overlapping computation and communication for operations like neighbor building and halo exchanges. Our results show that while the overall compute performance of these devices is limited, using them with a modified miniMD algorithm allows for potential speedups of 5 to 20% over the host CPU baseline with no loss in simulation accuracy.

A fade study was performed for the Thermo Electron Model 8825 whole-body dosimeter over a six-month period. The fade equation was evaluated using the method described the Thermo dose calculation algorithm (Thermo, 2007).

The following SNL document contains requested radiological survey information, as part of the documentation for the MLU shipment being performed by the LANL MLU team. The surveys were performed in TA-5, on October 11th - 15th, 2021. These surveys were of the shipping containers, the dunnage container, MLU equipment trailer, and contracted mobile crane.

Neuromorphic computers are hardware systems that mimic the brain’s computational process phenomenology. This is in contrast to neural network accelerators, such as the Google TPU or the Intel Neural Compute Stick, which seek to accelerate the fundamental computation and data flows of neural network models used in the field of machine learning. Neuromorphic computers emulate the integrate and fire neuron dynamics of the brain to achieve a spiking communication architecture for computation. While neural networks are brain-inspired, they drastically oversimplify the brain’s computation model. Neuromorphic architectures are closer to the true computation model of the brain (albeit, still simplified). Neuromorphic computing models herald a 1000x power improvement over conventional CPU architectures. Sandia National Labs is a major contributor to the research community on neuromorphic systems by performing design analysis, evaluation, and algorithm development for neuromorphic computers. Space-based remote sensing development has been a focused target of funding for exploratory research into neuromorphic systems for their potential advantage in that program area; SNL has led some of these efforts. Recently, neuromorphic application evaluation has reached the NA-22 program area. This same exploratory research and algorithm development should penetrate the unattended ground sensor space for SNL’s mission partners and program areas. Neuromorphic computing paradigms offer a distinct advantage for the SWaP-constrained embedded systems of our diverse sponsor-driven program areas.

With this work, we aim to speed up simulation and reduce computational complexity of Converter Dominated Power System (CDPS) within an acceptable accuracy.

In this position paper, we discuss exciting recent advancements in sketching algorithms applied to distributed systems. That is, we look at randomized algorithms that simultaneously reduce the data dimensionality, offer potential privacy benefits, while maintaining verifiably high levels of algorithm accuracy and performance in multi-node computational setups. We look at next steps and discuss the applicability to real systems.

The objective of this project was to eliminate and/or render bulk agent unusable by a threat entity via neutralization and/or polymerization of the bulk agent using minimal quantities of additives. We proposed the in situ neutralization and polymerization of bulk chemical agents (CAs) by performing reactions in the existing CA storage container via wet chemical approaches using minimal quantities of chemical based materials. This approach does not require sophisticated equipment, fuel to power generators, electricity to power equipment, or large quantities of decontaminating materials. By utilizing the CA storage container as the batch reactor, the amount of logistical resources can be significantly reduced. Fewer personnel are required since no sophisticated equipment needs to be set up, configured, or operated. Employing the CA storage container as the batch reactor enables the capability to add materials to multiple containers in a short period of time as opposed to processing one container at a time for typical batch reactor approaches. In scenarios where a quick response is required, the material can be added to all the CA containers and left to react on its own without intervention. Any attempt to filter the CA plus material solution will increase the rate of reaction due to increased agitation of the solution.