Publications

We introduce physics-informed multimodal autoencoders (PIMA)-a variational inference framework for discovering shared information in multimodal datasets. Individual modalities are embedded into a shared latent space and fused through a product-of-experts formulation, enabling a Gaussian mixture prior to identify shared features. Sampling from clusters allows cross-modal generative modeling, with a mixture-of-experts decoder that imposes inductive biases from prior scientific knowledge and thereby imparts structured disentanglement of the latent space. This approach enables cross-modal inference and the discovery of features in high-dimensional heterogeneous datasets. Consequently, this approach provides a means to discover fingerprints in multimodal scientific datasets and to avoid traditional bottlenecks related to high-fidelity measurement and characterization of scientific datasets.

We consider numerical approaches for deterministic, finite-dimensional optimal control problems whose dynamics depend on unknown or uncertain parameters. We seek to amortize the solution over a set of relevant parameters in an offline stage to enable rapid decision-making and be able to react to changes in the parameter in the online stage. To tackle the curse of dimensionality arising when the state and/or parameter are highdimensional, we represent the policy using neural networks. We compare two training paradigms: First, our model-based approach leverages the dynamics and definition of the objective function to learn the value function of the parameterized optimal control problem and obtain the policy using a feedback form. Second, we use actor-critic reinforcement learning to approximate the policy in a data-driven way. Using an example involving a two-dimensional convection-diffusion equation, which features high-dimensional state and parameter spaces, we investigate the accuracy and efficiency of both training paradigms. While both paradigms lead to a reasonable approximation of the policy, the model-based approach is more accurate and considerably reduces the number of PDE solves.

The Reference Model (RM) project developed six marine energy converter concepts using a sequential design methodology, which, while widely adopted in the industry, often overlooks interactions between system components, resulting in suboptimal designs. One such example is the Reference Model 3 (RM3), a two-body point absorber wave energy converter (WEC). An assessment using the Technology Performance Level (TPL) revealed that RM3’s low power-to-cost ratio, partly due to expensive steel construction, limits its techno-economic performance. This study aims to redesign RM3 by reducing its scale and employing control co-design to integrate WEC and Power Take-Off (PTO) dynamics, constraints, and cost considerations within an optimization framework. We demonstrate the limitations of RM3’s current PTO design and explore the benefits of scaling down to enhance techno-economic viability by lowering material costs. Using WecOptTool, we conduct a parameter sweep over gear ratios and spring stiffnesses for various Commercial Off-The-Shelf generators in irregular wave conditions. Our findings emphasize the importance of aligning PTO components with WEC dynamics, showing that control co-design and strategic scaling can improve RM3’s power-to-cost ratio. This study presents a transferable example of applied control co-design for other WECs, supporting early-stage developers in their design decisions.

An increasing magnetic field perpendicular to an undoped semiconductor surface at low temperature is known to strengthen the binding of localized electrons to stationary ions, as the wavefunction's tails evolve from exponential to Gaussian. It is also known that application of a high bias voltage to a depleted semiconductor can liberate bound charge and induce a large drop in electrical resistance. We connect these established results to experimental electrical transport measurements on off-state germanium Schottky-barrier metal-oxide-semiconductor field-effect transistor (MOSFETs) with an aluminum oxide insulating dielectric and platinum germanide contacts. We make measurements at the three distinct orientations of the magnetic field with respect to the substrate and the current. At 6 K, we observe sharp attenuation of current by more than 2 orders of magnitude, within 60 mT, at a crossover magnetic field perpendicular to the substrate. A 1 T magnetic field attenuates the current by more than 4 orders of magnitude. The strength of the attenuation and the value of the crossover field are controlled by both the gate-source and drain-source voltages. The attenuation is much weaker when the magnetic field is parallel to the current. Finally, we orient the magnetic field parallel to the substrate, but perpendicular to the current, allowing us to distinguish charge hopping at the oxide interface from charge hopping in the bulk. This large off-state magnetoresistance can be exploited for cryogenic magnetic- and photo-detection, and for high-bias, low-leakage MOSFETs.

Hydrogen is a key pillar in the global Net Zero strategy. Rapid scaling up of hydrogen production, transport, distribution and utilization is expected. This entails that hydrogen, which is traditionally an industrial gas, will come into proximity of populated urban areas and in some situations handled by the untrained public. To realize all their benefits, hydrogen and its technologies must be safely developed and deployed. The specific properties of hydrogen involving wide flammability range, low ignition energy and fast flame speed implies that any accidental release of hydrogen can be easily ignited. Comparing with conventional fuels, combustion systems fueled by hydrogen are also more prone to flame instability and abnormal combustion. This paper aims to provide a comprehensive review about combustion research related to hydrogen safety. It starts with a brief introduction which includes some overview about risk analysis, codes and standards. The core content covers ignition, fire, explosions and deflagration to detonation transition (DDT). Considering that DDT leads to detonation, and that detonation may also be induced directly under special circumstances, the subject of detonation is also included for completeness. The review covers laboratory, medium and large-scale experiments, as well as theoretical analysis and numerical simulation results. While highlights are provided at the end of each section, the paper closes with some concluding remarks highlighting the achievements and key knowledge gaps.

Chirality plays a crucial role in the helicity mismatch between surface acoustic waves and magnetic spin waves, leading to nonreciprocal transmission of acoustic power for coupled magnetoacoustic modes. Acoustic modes with both longitudinal and shear strain exhibit elliptical particle displacements, making them chiral, and different acoustic modes can exhibit different helicities of this elliptical particle displacement. Here, we study chiral acoustic modes with different helicities supported on the same piezoelectric platform and their interaction with magnetic spin waves. Our study demonstrates that the nonreciprocal transmission of acoustic power is driven by the helicity mismatch effect and, specifically, that the handedness of the nonreciprocity is based on whether the surface acoustic wave has retrograde (Rayleigh mode) or prograde (Sezawa mode) elliptical particle displacement with respect to the propagation direction. We found the transmission nonreciprocity to be significant, with 7.3 dB/mm for the retrograde particle displacement (Rayleigh mode at 2.358 GHz) and 3.3 dB/mm for prograde particle displacement (Sezawa mode at 3.112 GHz). This work highlights that piezoelectric platforms can be engineered to support acoustic modes with opposite helicities to enable frequency-selective nonreciprocal radiofrequency and microwave components, such as isolators and circulators, through coupled acoustic spin wave interactions.

The magnetostrictive response of a Terfenol-D pellet was measured via a laboratory-based X-ray diffractometer. X-ray diffraction patterns were collected from the pellet sample with and without the presence of an applied magnetic field (~30 mT) generated by placing a large magnet under the pellet. A standard reference material, Silicon 640c, was employed as an internal standard. Magnetostriction values of 323 and 227 ppm Δl/l were determined for the (104) and (110) indexed peaks, respectively, assuming a rhombohedral structure for Terfenol-D. A threshold noise level value of ~20 to 30 ppm Δl/l was suggested based on before/after measurements in the absence of the applied field. No clear evidence of domain wall rotation was detected via changes in relative intensities of diffraction peaks in the presence of the applied magnetic field.

High-dimensional quantum systems are a valuable resource for quantum information processing. They can be used to encode error-correctable logical qubits, which has been demonstrated using continuous-variable states in microwave cavities or the motional modes of trapped ions. For example, high-dimensional systems can be used to realize ‘Schrödinger cat’ states, which are superpositions of widely displaced coherent states that can be used to illustrate quantum effects at large scales. Recent proposals have suggested encoding qubits in high-spin atomic nuclei, which are finite-dimensional systems that can host hardware-efficient versions of continuous-variable codes. Here we demonstrate the creation and manipulation of Schrödinger cat states using the spin-7/2 nucleus of an antimony atom embedded in a silicon nanoelectronic device. We use a multi-frequency control scheme to produce spin rotations that preserve the symmetry of the qudit, and we constitute logical Pauli operations for qubits encoded in the Schrödinger cat states. Our work demonstrates the ability to prepare and control non-classical resource states, which is a prerequisite for applications in quantum information processing and quantum error correction, using our scalable, manufacturable semiconductor platform.

The objective of this work was to develop a machine learning ensemble that could assist pebble bed reactor verification by evaluating whether a given pebble circulating through a PBR was normal or anomalous using gamma spectroscopy measurements from a notional PBR burnup measurement system. Using a PBR reference design, data sets of synthetic gamma spectra representative of BUMS measurements of normal and anomalous pebbles that may be used to produce special fissile material were generated to train and test an ML anomaly detection ensemble on two reference scenarios – substitution of normal pebbles with target pebbles for production of Pu or ²³³U. The ML ensemble correctly identified all anomalous pebbles in the testing data set, and while perfect ensemble performance is normally indicative of overfitting, it was concluded that significantly lower photon intensity of target pebbles produced distinctly less intense photon spectra to where perfect ensemble performance was expected.

One of the objectives of the United States Department of Energy Office of Nuclear Energy’s Office of Spent Fuel and High-Level Waste Disposition is to better understand the technical bases, risks, and uncertainties associated with the safe and secure disposition of spent nuclear fuel and high-level radioactive waste. Domestic defense and research activities have generated a few thousand metric tons of spent nuclear fuel and high-level radioactive waste, much of which has been or will be processed and vitrified into high-level waste glass. The Nuclear Waste Policy Act 1982 makes the Department of Energy responsible for disposal of these materials.

This document evaluates a hypothetical nuclear powerplant and associated protective force personnel using modern modeling and simulation tools. The facility incorporates security early in the design to consider and integrate methods to resolve security issues and vulnerabilities via the facility’s inherent design characteristics before construction. The evaluation in this document is an example only. It is not intended to recommend or evaluate the effectiveness of existing physical security requirements or identify any method that the U.S. Nuclear Regulatory Commission staff may find acceptable for complying with existing requirements.

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Sandia is a federally funded research and development center (FFRDC) focused on developing and applying advanced science and engineering capabilities to mitigate national security threats. This is accomplished through the exceptional staff leading research at the Labs and partnering with universities and companies. Sandia’s LDRD program aims to maintain the scientific and technical vitality of the Labs and to enhance the Labs’ ability to address future national security needs. The program funds foundational, leading-edge discretionary research projects that cultivate and utilize core science, technology, and engineering (ST&E) capabilities. Per Congressional intent (P.L. 101-510) and Department of Energy (DOE) guidance (DOE Order 413.2C, Chg 1), Sandia’s LDRD program is crucial to maintaining the nation’s scientific and technical vitality.

This report provides a comprehensive assessment of physical security modeling and simulation tools available for use in the vulnerability assessment (VA) process for nuclear facilities. It outlines the historical evolution of VA methodologies, emphasizing the transition from traditional layer-based approaches to a more holistic framework that integrates detection probabilities directly into combat simulations. The document details the critical components of the VA process, including the characterization of targets, threats, and protective measures, as well as the development of adversary scenarios that reflect both insider and outsider threats. It highlights the importance of performance assurance programs, emphasizing the need for continuous evaluation and testing of security systems to ensure their effectiveness against evolving threats. Additionally, the report discusses the significance of utilizing accredited modeling and simulation tools in accredited areas to accurately represent adversary actions and the corresponding responses of protective forces. By establishing a systematic approach to VA, this document aims to enhance the overall security posture of nuclear facilities, ensuring compliance with regulatory standards while effectively mitigating risks associated with potential adversarial actions.

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Reliably simulating experiments relevant to the National Nuclear Security Administration (NNSA) requires a detailed description of material properties across a wide range of conditions. Such properties include the equations of state, charged-particle transport coefficients, and optical properties like the opacity. Together, these properties make up the material models used in radiation-magnetohydrodynamic simulations of nuclear fusion experiments. Many of these models do not incorporate uncertainties in the data used to produce them. It is unknown whether these uncertainties significantly impact the interpretation of simulation results and diagnostics. The purpose of this work is to quantify how such uncertainties impact simulations of pulsed-power experiments. We accomplished this task by first assessing discrepancies between approaches used to generate the data. This included bringing together members of the high-energy-density community spanning the three NNSA laboratories and multiple universities. Then, using these data, we developed a general framework that systematically incorporates physical uncertainties within the material models suitable for uncertainty quantification analyses. The framework utilizes machine learning, Bayesian inference, and incorporates multi-fidelity datasets. We demonstrated the framework by quantifying the impact that material model uncertainties have on simulations of pulsed-power experiments underway on Z at Sandia National Laboratories. As a result of this work, we discovered that modest uncertainties in material models (roughly 20%) correspond to significant uncertainties in the outputs from simulations. Our framework has enabled rapid construction of material models through an automated procedure and allows for the generation of material models of interest to the NNSA.

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Synthetic aperture radar (SAR) images formed with dechirp-on-receive data collection and rectangular format processing algorithm are the result of a two-dimensional discrete Fourier transform (DFT) applied to sampled data. There are several steps required to compute the range and Doppler values associated with each pixel in a SAR range-Doppler image. This memo walks readers through the process.

Based on planning and reviews conducted in 2020, it is clear today that the Z Facility must be sustained through 2040 or longer. This requires a well-developed and executed maintenance and sustainment effort. Z’s Sustainment Plan outlines the approach that Sandia’s Pulsed Power Sciences Center will pursue to assure that the Z Facility maintains its world class research and development program supporting the NNSA’s Science Based Stockpile Stewardship efforts. In FY24, the Pulsed Power Center at SNL planned and executed many substantial sustainment projects as well as maintenance-driven-sustainment aligned to the Sustainment Plan. These projects are listed in this section with brief descriptions of the work executed.

Salt formations have long been recognized as a highly favorable host rock for the final disposal of high-level radioactive waste (HLW) in deep geological repositories. Their unique properties, including exceptional impermeability, self-healing capabilities, and thermal conductivity, make them a reliable natural barrier for the deep disposal of radioactive waste. This report focuses on the development and application of a methodology for assessing the integrity and per formance of the Engineered Barrier System (EBS) within salt-based repositories, a critical component of the multi-barrier system ensuring safe radioactive waste disposal.

The purpose of this protocol is to define procedures and practices to be used by the PACT center for field testing of metal halide perovskite (MHP) photovoltaic (PV) modules. The protocol defines the physical, electrical, and analytical configuration of the tests and applies equally to mounting systems at a fixed orientation or sun tracking systems. While standards exist for outdoor testing of conventional PV modules, these do not anticipate the unique electrical behavior of perovskite cells. Further, the existing standards are oriented toward mature, relatively stable products with lifetimes that can be measured on the scale of years to decades. The state of the art for MHP modules is still immature with considerable sample to sample variation among nominally identical modules. Version 0.0 of this protocol does not define a minimum test duration, although the intent is for modules to be fielded for periods ranging for weeks to months. This protocol draws from relevant parts of existing standards, and where necessary includes modifications specific to the behavior of perovskites.

This report documents a cross-site effort to identify and evaluate materials that are suitable replacements for the polyurethanes known as EN-7 and EN-8. EN-7 and EN-8 are commercial formulations that contain free toluene diisocyanate (TDI) and which are used as adhesives and as encapsulants in many weapon applications. TDI is an OSHA-regulated volatile diisocyanate and has been targeted for elimination from future weapons use, prompting the need for a TDI-free replacement material.