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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Advanced Manufactured Strain Sensors for Extreme Environments

Experimentation at irradiation test facilities are essential for reducing the innovation time of developmental fuels, fuel cladding, and structural materials employed in next-generation nuclear reactors. However, due to the harsh conditions generated in such reactors and limited instrumentation space, the evaluation of a material’s mechanical properties is often limited to characterization after the materials have been removed from reactor conditions, or post-irradiation examination. These experiments are costly, time-consuming, and fail to capture the critical time-evolving phenomena that occur during the irradiation experiments. Advanced manufactured digital image correlation patterns and strain sensor devices serve as two promising technologies that can be deployed in the confined and challenging orientations of these irradiation experiments while also providing key insight on salient materials phenomena (i.e., mechanical properties).To guide the development of the printed strain sensors prior to their deployment in critical experiments, the adhesion strength between the substrate and printed film interface is measured via tensile testing and a non-contact laser-induced spallation technique. The establishment of these process control steps helped guide the successful fabrication and testing of direct-write strain sensing devices discussed in this work. The fabrication process controls are necessary for enabling the sustained operation of these strain sensing device through experimentation and minimize the potential for premature failure.

36 - MATERIALS SCIENCE↗
DOE OSTI2026

Radiation Effects in Used Next Generation Nuclear Fuel Reprocessing Strategies

Given global commitments to significantly increase nuclear energy capacity, it is now more important than ever to develop efficient used nuclear fuel (UNF) management strategies to encourage widespread adoption of closed fuel cycles. To achieve this ambitious goal, a comprehensive understanding of radiation effects is essential for these next generation technologies, as radiolysis often limits longevity and performance. Here, we present new findings on: (i) the radiation robustness and performance of advanced sulfur chloride-based chlorination processes in the presence of nuclear materials (Fig. 1A); and (ii) the impacts of voloxidized uranium and rhenium complexation on monoamide-based UNF direct dissolution strategies (Fig 1B). These studies employed a combination of time-resolved electron pulse and dose accumulation gamma and electron beam irradiation techniques.

38 - RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCL↗
DOE OSTI2022

Deep learning to estimate permeability using geophysical data

Time-lapse electrical resistivity tomography (ERT) is a popular geophysical method to estimate three-dimensional (3D) permeability fields from electrical potential difference measurements. Traditional inversion and data assimilation methods are used to ingest this ERT data into hydrogeophysical models to estimate permeability. Due to ill-posedness and the curse of dimensionality, existing inversion strategies provide poor estimates and low resolution of the 3D permeability field. Recent advances in deep learning provide us with powerful algorithms to overcome this challenge. This paper presents a deep learning (DL) framework to estimate the 3D subsurface permeability from time-lapse ERT data. To test the feasibility of the proposed framework, we train DL-enabled inverse models on simulation data. Each measurement in both synthetic and field data is standardized by removing the mean and scaling the time-series to unit variance. This pre-processing step is necessary to bring simulation data closer to field observations. Subsurface process models based on hydrogeophysics are used to generate this synthetic data. Training performed on limited simulation data resulted in the DL model over-fitting. An advanced data augmentation based on mixup is implemented to generate additional training samples to overcome this issue. This mixup technique creates weakly labeled (low-fidelity) samples from strongly labeled (high-fidelity) data. The weakly labeled training data is then used to develop DL-enabled inverse models and reduce over-fitting. As both time-lapse ERT (1133048 features/realization) and 3D permeability (585453 features/realization) data samples are from a high-dimensional space, principal component analysis (PCA) is employed to reduce dimensionality. Encoded ERT and encoded permeability are generated using the trained PCA estimators. A deep neural network is then trained to map the encoded ERT to encoded permeability. This mixup training and unsupervised learning allowed us to build a fast and reasonably accurate DL-based inverse model under limited simulation data. Results show that proposed weak supervised learning can capture salient spatial features in the 3D permeability field. Quantitatively, the average mean squared error (in terms of the natural log) on the strongly labeled training, validation, and test datasets is less than 0.5. The R 2 -score (global metric) is greater than 0.75, and the percent error in each cell (local metric) is less than 10%. Finally, an added benefit in terms of computational cost is that the proposed DL-based inverse model is at least O(10 4 ) times faster than running a forward model once it is trained. Data generation, DL model training, and hyperparameter tuning to identify optimal neural network architectures utilized high-performance computing resources while the DL inference is performed on a standard laptop. Approximately, O(10 5 ) processor hours are used for generating data and DL tuning and training. We acknowledge that the data generation and DL model development are expensive. But once a DL model is trained, it can be re-used for inversion rapidly for the given system, with set physics and domain. Note that traditional inversion may require multiple forward model simulations (e.g., in the order of 10 to 1000), which are very expensive. This computational savings ≈ O(10 5 ) – O(10 7 )) makes the proposed DL-based inverse model attractive for subsurface imaging and real-time ERT monitoring applications due to fast and yet reasonably accurate estimations of permeability field.

58 GEOSCIENCES↗
DOE OSTI2024

Microscopy modality transfer of steel microstructures: Inferring scanning electron micrographs from optical microscopy using generative AI

Scanning electron microscopy (SEM) is resource intensive, which limits its throughput in some applications. As an alternative, we propose applying computer vision and machine learning to generate high-quality synthetic SEM micrographs from micrographs obtained using light optical microscopy (LOM). Working with a correlated LOM/SEM dataset of dual-phase steel images, we test generative models of various architectures, including encoder-decoder networks, generative adversarial networks (GANs), and diffusion-based models. We find that the diffusion models significantly outperform other methods on both qualitative and quantitative assessments, while preserving key metallurgical meaning. This work establishes diffusion as the state-of-the-art for microscopy modality transfer and demonstrates the potential of AI-powered microscopy to enhance LOM with micron scale structural recreation.

Computer vision↗
DOE OSTI2020

Technology Assessment for Radioiodine at the Hanford Site - 20240

An evaluation was conducted to assess the practicability of technologies of sufficient promise and maturity to warrant treatability tests for remediating radioiodine (I-129) in groundwater at the 200-UP-1 operable unit at the U.S. Department of Energy Hanford Site. Technologies were evaluated based on recent updated knowledge of subsurface iodine transport behavior at Hanford, and the effectiveness, implementability, and cost of potential treatment technologies for I-129. Because more than two-thirds of the iodine at Hanford is estimated to be present in its oxidized form as iodate, treatment technologies were evaluated with respect to addressing iodate. In situ treatments were identified as having limited implementability because the plume core is located directly beneath the Environmental Restoration Disposal Facility disposal cells, a landfill used for the disposal of low-level radioactive, hazardous, and mixed wastes generated from Hanford cleanup activities. Further limitations in treatment technologies for radioiodine were due to the isotopic distribution of subsurface iodine. Data indicate that stable iodine (I- 127) concentrations are up to three orders of magnitude greater than I-129, limiting the effectiveness of potential technologies because they are not isotope-specific. Ex situ approaches also lacked the effectiveness and maturity required to treat I-129. Hence, the technology evaluation did not identify any technologies that needed treatability testing, driven by site and contaminant properties that hinder effectiveness and/or implementability of the technologies. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Improved MPACT energy deposition and explicit heat generation coupling with CTF

The CASL neutronics code MPACT assumes local energy deposition with equilibrium delayed energy for steady-state and transient calculations. These approximations limit the accurate representation of the heat generation in space and its variations over time, both of which are essential for power distribution and thermal–hydraulic coupling analyses. This paper presents an explicit energy deposition model considering the neutron and gamma heating of all regions and the time-dependent delayed energy. The MPACT/CTF interfaces are updated to transfer the explicit heat sources. The new model agrees well with MCNP for problems without thermal–hydraulic feedback. The MPACT/CTF coupled calculation for a hot-full-power quarter-core case using the new model exhibits a reduction of peak pin power by 2.3% and fuel centerline temperature by 17 K. The new model also shows a keff difference up to -100 pcm in depletion and a 30 K peak fuel temperature reduction in a reactivity-initiated-accident problem.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2026

Plasmonic Hot-Carrier Generation and Catalysis in Ti 3 C 2 O 2 from Real-Time TDDFT Simulations

Photoinduced hot electrons are central to plasmon-driven catalysis. Atomically thin Ti 3 C 2 O 2 , with high carrier density and broad optical absorption, offers a promising platform for plasmon-driven reactions. However, comprehensive investigations of its plasmon resonance, hot-carrier generation, and plasmonic catalytic performance remain limited. In this work, real-time time-dependent density functional theory (rt-TDDFT) was employed to study Ti 3 C 2 O 2 ’s plasmon excitation and hot-carrier generation from nonradiative plasmon damping. The temporal evolution of the dipole moment reveals plasmon resonance in Ti 3 C 2 O 2 , followed by strong plasmon damping that redistributes the stored energy to generate hot carriers. Ti 3 C 2 O 2 with low oxygen vacancy concentration (O v -Ti 3 C 2 O 2 ) exhibits plasmonic behavior resembling the pristine surface, and the plasmon-generated hot electrons can markedly reduce the dissociation barrier of CO 2 at the oxygen vacancy. These findings provide fundamental insights into the plasmonic properties of Ti 3 C 2 O 2 and how they drive its catalytic performance in surface reactions, which is valuable for advancing plasmon-driven catalysis.

CO2 reduction↗
DOE OSTI2021

Twisted bilayer graphene. III. Interacting Hamiltonian and exact symmetries

We derive the explicit Hamiltonian of twisted bilayer graphene (TBG) with Coulomb interaction projected into the flat bands and study the symmetries of the Hamiltonian. First, we show that all projected TBG Hamiltonians can be written as positive semidefinite Hamiltonians, an example of which was found in work by Kang and Vafek [Phys. Rev. Lett. 122, 246401 (2019)]. We then prove that the interacting TBG Hamiltonian exhibits an exact U(4) symmetry in the exactly flat band (nonchiral-flat) limit. We further define, besides a first chiral limit where the AA stacking hopping is zero, a second chiral limit where the AB/BA stacking hopping is zero. In the first chiral-flat limit (or second chiral-flat limit) with exactly flat bands, the TBG is enhanced to have an exact U(4) × U(4) symmetry, whose generators are different between the two chiral limits. While in the first chiral limit and in the nonchiral case these symmetries have been found in work by Bultinck et al. [Phys. Rev. X 10, 031034 (2020)], for the eight lowest bands, we here prove that they are valid for projection into any 8 n max particle-hole symmetric TBG bands, with n max > 1 being the practical case for small twist angles < 1°. Furthermore, in the first or second chiral-nonflat limit without flat bands, an exact U(4) symmetry still remains. We also elucidate the link between the U(4) symmetry presented here and the similar but different U(4) of Kang and Vafek [Phys. Rev. Lett. 122, 246401 (2019)]. Additionally, we show that our projected Hamiltonian can be viewed as the normal-ordered Coulomb interaction plus a Hartree-Fock term from passive bands, and exhibits a many-body particle-hole symmetry which renders the physics symmetric around charge neutrality. We also provide an efficient parametrization of the interacting Hamiltonian. The existence of two chiral limits with an enlarged symmetry suggests a possible duality of the model yet undiscovered.

2-dimensional systems↗
DOE OSTI2023

Control of energy storage to reduce electric power system off-nominal frequency deviations

A hybrid power generation system is formed by the combination of an energy storage system (ESS) and a rotating synchronous power generator (SPG). Energy is stored in or released from the ESS in response to measurements of the at least one angle parameter, selected from rotor, torque, or power angle of the SPG, to provide active frequency damping of electrical power output. The control of ESS energy exchange increases the stabilizing impact of the SPG inertia on the frequency of electricity in an electrical network or power grid. The hybrid power generation system can have an effective equal area criterion for stability limit that is greater than that of the SPG operating without the ESS. The hybrid power generation system can enable the electrical network to have a greater proportion of variable or distributed energy resource (DER) power generation systems without otherwise exceeding stability limits.

Vartanian, Charles K.↗
DOE OSTI2023

Net Load Forecasting With Disaggregated Behind-the-Meter PV Generation

As worldwide use of residential photovoltaic (PV) systems grows, system operators and utilities will need to transition from forecasting pure demand to forecasting net load with behind-the-meter (BTM) PV generation. However, PV generation can be difficult to predict and the measurements of PV generation from BTM residential systems are often invisible behind a measurement of the net load, making net load forecasting challenging. This paper proposes a novel two-stage framework for net load forecasting in areas with limited observability and high BTM PV generation. First, the profiles of observable customers are used to disaggregate the net load measurements into the pure load and PV generation. Then, separate models are used to forecast the PV generation and pure load individually, and the results are combined for a net load forecast. Further, this paper also proposes a compensator for correcting the error of the net load forecast, using historical forecast errors of the PV generation, pure load, and net load. The proposed framework is tested through two case studies for areas with high BTM PV penetration and less than 10% observable customers. The two-stage forecasting model is compared to two benchmark methods - a time series forecasting model, and a model that forecasts the net load directly using historical net load measurements. Results show that the proposed disaggregation-forecasting framework reduces the error of the net load forecast compared to both benchmark models. In addition, when the net load forecast error is periodic, the compensator can correct the error to improve the forecast accuracy.

14 SOLAR ENERGY↗
DOE OSTI2024

Automated Grain Boundary (GB) Segmentation and Microstructural Analysis in 347H Stainless Steel Using Deep Learning and Multimodal Microscopy

Austenitic 347H stainless steel offers superior mechanical properties and corrosion resistance required for extreme operating conditions such as high temperature. The change in microstructure due to composition and process variations is expected to impact material properties. Identifying microstructural features such as grain boundaries thus becomes an important task in the process-microstructure-properties loop. Applying convolutional neural network (CNN)-based deep learning models is a powerful technique to detect features from material micrographs in an automated manner. In contrast to microstructural classification, supervised CNN models for segmentation tasks require pixel-wise annotation labels. However, manual labeling of the images for the segmentation task poses a major bottleneck for generating training data and labels in a reliable and reproducible way within a reasonable timeframe. Microstructural characterization especially needs to be expedited for faster material discovery by changing alloy compositions. Here, in this study, we attempt to overcome such limitations by utilizing multimodal microscopy to generate labels directly instead of manual labeling. We combine scanning electron microscopy images of 347H stainless steel as training data and electron backscatter diffraction micrographs as pixel-wise labels for grain boundary detection as a semantic segmentation task. The viability of our method is evaluated by considering a set of deep CNN architectures. We demonstrate that despite producing instrumentation drift during data collection between two modes of microscopy, this method performs comparably to similar segmentation tasks that used manual labeling. Additionally, we find that naïve pixel-wise segmentation results in small gaps and missing boundaries in the predicted grain boundary map. By incorporating topological information during model training, the connectivity of the grain boundary network and segmentation performance is improved. Finally, our approach is validated by accurate computation on downstream tasks of predicting the underlying grain morphology distributions which are the ultimate quantities of interest for microstructural characterization.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Multilayered regulation by RNA thermometers enables precise control of Cas9 expression in E. coli

Cas9-based genome editing technologies can rapidly generate mutations to probe a diverse array of mutant genotypes. However, aberrant Cas9 nuclease translation and activity can occur despite the use of inducible promoters to control expression, leading to extensive cell death. This background killing caused by promoter leakiness severely limits the application of Cas9 for generating mutant libraries because of the potential for population skew. We demonstrate the utility of temperature sensitive RNA elements as a layer of post-transcriptional regulation to reduce the impact of promoter leak. We observe significant temperature-dependent increases in cell survival when certain RNA thermometers (RNATs) are placed upstream of the cas9 coding sequence. We also show that the most highly repressing RNAT, hsp17rep, significantly reduces population skew with a library of characterized guide RNAs in Escherichia coli. This strategy should be applicable to all bacterial Cas9-based methods and technologies.

Kammerdiener, Elise K. [Oak Ridge National Laborat↗
DOE OSTI2020

Transients following the loss of detonation confinement

We present a theory for the evolution of a one-dimensional, steady-state detonation reaction zone to a two-dimensional reaction zone, when the explosive experiences a sudden loss of side-on confinement as a boundary of the explosive is impulsively withdrawn. Our focus is on condensed-phase explosives, which we describe as having a constant adiabatic gamma equation of state and an irreversible, state-independent reaction rate. We consider two detonation models: (i) the instantaneous reaction heat release Chapman–Jouguet (CJ)-limit and (ii) the spatially resolved reaction heat-release Zel’dovich–von Neumann–Döring (ZND) model, in the limit where only a small fraction of the energy release is resolved (the SRHR-limit). Two competing rarefaction waves are generated by this loss of confinement: (i) a smooth wave coming off the full length of the withdrawn boundary and (ii) a singular fan spreading out from the point where the detonation shock and the withdrawn boundary meet. For the CJ-limit, in all cases the singular rarefaction fan eventually dominates the competition to control the steady-state behaviour. For the SRHR-limit, the spatially resolved heat release moderates this competition. When the withdrawal speed is fast, the rarefaction fan dominates; when the withdrawal speed is slower, the smooth rarefaction eventually dominates, although the flow features a fan at early times. By examining the mathematical properties of the steady two-dimensional fan-based solution, we set down a mechanism for this transition in behaviours.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Gas Stopper Developments for Improved Purity and Intensity of Low-Energy, Rare Isotope Ion Beams (Final Technical Report)

This final technical report summarizes the work of the Michigan State University (MSU) team supported by grant # DE-SC0021423 awarded by the Office of Nuclear Physics, Department of Energy. Objectives: The successful fulfillment of the FRIB science mission hinges on ensuring the availability of fast, stopped, and reaccelerated beams consisting of rare isotopes. This project's research and development focus was dedicated to supporting the advancement and creation of a cutting-edge linear gas stopper. The primary aim is to efficiently convert the high-intensity fast beams of rare isotopes provided by FRIB into high-quality, low-energy beams. These beams are essential for conducting stopped beam experiments or for subsequent reacceleration. The overarching goal is to advance technology, aiming to increase the beam rate capability of the linear gas stopper for medium-to-heavy-mass rare isotopes by more than tenfold compared to the currently most effective gas stopper in operation, and to improve the purity of the delivered beams. Project Description: The existing technology employed in gas stopping devices designed for low-energy, rare-isotope beams presents limitations in both the purity of extracted beams and the intensities of injected beams. These limitations are incompatible with the requirements of the recently commissioned rare isotope beam facility, FRIB. Our research and development efforts, aligned with the previously outlined objectives, focused on addressing the most critical aspects for enhancing beam-rate capability and purity. Specifically, advanced particle-in-cell simulations were developed and integrated into a simulation pipeline to explore the efficacy of multi-layer RF carpets on increasing ion transport efficiency with high incoming beam rates that generate space charge fields which can limit it. We also explored the possibility of using a collision-induced-dissociation (CID) gas cell to break up molecular contaminant ions that are generated during the stopping process. A prototype CID gas cell was constructed and tested with beams from an offline ion source, validating the concept with the successful demonstration of breaking of molecular ions. The outcome of this research enabled the formulation a conceptual design for a next-generation linear gas stopping device specifically tailored for FRIB. This device is envisioned to deliver rare-isotope-ion beams at a rate of 10 8 particles per second or higher, accompanied by advancements in purity. Methods employed: This project leverages advancements in technologies initially designed for the Advanced Cryogenic Gas Stopper (ACGS), the current state-of-the-art linear gas stopper, through the use of new simulations and beam purification via collision-induced-dissociation. The methods include: 1. Development of a prototype low-energy, low-pressure CID gas stopper. This prototype features a thin, approximately 20 nm, Si 3 N 4 entrance window designed for dissociating stable and rare-isotope molecular ions. The goal is to enhance beam purification and overall efficiency. 2. Creation of Particle-in-cell (PIC) simulations to assess the advantages of multi-layer RF carpets and multi-point extraction for ion transport efficiency. These simulations rely on the 3DCylPIC package, specifically designed for studying devices of this nature. The goal is to quantify and mitigate ion transport losses due to space charge generated in the stopping process of large numbers of ions. 3. Perform ion transport simulations across an RF carpet using an 8-phase travelling wave and evaluate its performance. Compared to the 4-phase RF carpets used in ACGS, the 8-phase carpets will double the wavelength of the generated traveling wave allowing for larger maximum RF amplitudes that could result in improved ion transport efficiency for high-intensity incoming beams when large space charge fields are present. Impact: Tackling the primary challenges associated with transforming high-energy projectile fragment beams into low-energy beams—specifically, addressing efficiency and purity—holds significant promise for advancing FRIB science. This advancement will particularly impact precision mass measurements, laser spectroscopy of short-lived nuclei, and studies in astrophysics and nuclear reactions using reaccelerated beams. These domains play a crucial role in addressing key questions outlined in the 2023 NSAC long-range plan, spanning nuclear structure, nuclear astrophysics, and fundamental symmetries. Additionally, they contribute to addressing 10 out of the 17 benchmarks identified by the NRC RISAC. The development of a next-generation gas stopping device capable of delivering low-energy, rare-isotope beams at a rate of 10 8 particles per second, or more, with high purity holds the potential to unlock experiments that would otherwise be unfeasible. Furthermore, it is expected to reduce the time required for experiments at FRIB, thereby maximizing scientific output. The research and development activities performed as part of this project bolstered essential competencies at FRIB in beam physics and ion source technologies, provided valuable training opportunities for junior scientists.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Thermal generation, manipulation and thermoelectric detection of skyrmions

The efficient generation, manipulation and detection of magnetic skyrmions are important for the development of future spintronic devices. One approach is to use electric-current-induced spin torques. Recently, thermally induced skyrmion motion has also been observed, but wider experimental evidence and its capabilities remain limited. Here we report the thermal generation, manipulation and thermoelectric detection of nanoscale skyrmions in microstructured metallic multilayers integrated with on-chip heaters. The local application of heat can facilitate a domain morphological transition and the formation of skyrmions at the device edge, where a low energy barrier exists. Here, we observe the unidirectional diffusion of skyrmions from hot regions to cold regions, which is due to the interplay among the repulsive forces between skyrmions, thermal spin–orbit torques, entropic forces and magnonic spin torques. The thermally generated skyrmions can also be electrically detected via the Nernst voltage.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Novel, Middle and Long Wave Infrared Laser Sources For Accelerator Applications

The main accomplishment during Years 2020-2024 of the DOE Accelerator Stewardship Program is proof-of-principle demonstration of amplification of an ultrashort 10 µm seed pulse in a multiatmosphere CO 2 laser optically pumped by nanosecond pulses of either a ~4.3 µm Fe:ZnSe laser or a 2.8 µm electro-optically (EO) Q-switched Er: Laser. This has been accomplished at the UCLA Neptune Laboratory by using about 100 mJ, ~100 ns long pulses generated by the pump laser built for this purpose by the UAB team. Implementation of EO Q-switching regime in the solid-state Er:laser system made possible nanosecond synchronization between the pump pulse and the 0.5 ps seed pulse produced by a commercial Ti:sapphire laser based mid-IR OPA/DFG. The injection mode-locking regime realized in a compact Mult atmosphere 3 Hz CO 2 -He regenerative amplifier enabled generation of a train of ultrashort pulses separated by the cavity round-trip time of ~3.2 ns. The measured gain lifetime of ~1 µs at a total pressure of ~12-15 atm indicates that lifetime of the upper laser level is a critical limiting factor in designing high-pressure CO 2 amplifiers. A single picosecond 10 mm pulse with an energy 0.1-0.2 mJ was extracted from the amplifier’s cavity using an ultrafast Ge semiconductor switch whose reflectivity was photo-induced by a femtosecond 800 nm pulse. For direct amplification regime, nonlinear absorption in Ge at 10 mm at GW/cm 2 intensities limited the extracted energy. Therefore, the generated energy could be further increased by minimizing losses in the switch and optimizing the cavity mode size. Based on the obtained data in collaboration with BNL colleagues, we have designed a high-pressure CO 2 amplifier to be used as a preamplifier for the future experiments at the ATF BNL. The latter work is the subject of funding availability.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Oxygen Limit for Flammability of a Gas Mixture of Helium – Hydrogen – Oxygen in the U.S. Department of Energy Standard Canister

The radiolytic breakdown of residual free, physisorbed, and chemisorbed waters is anticipated in the sealed dry storage of spent nuclear fuel (SNF), releasing H 2 gas into the initial cover gas of helium. For aluminum-clad SNF (ASNF) in particular, the expected total hydrogen in the canister is enough to dominate the cover gas mixture if fully released, and based on experimental rates of H 2 generation, H 2 percentages exceeding the lower flammability limit appear likely. However, no evidence of radiolytic generation of O 2 has been observed to date, so the potential for flammability is averted due to the lack O 2 . Lack of oxygen has been credited for avoiding flammability in some existing storage and transportation approaches for SNF and other waste. This report reviews literature on flammability limits with a focus on the limiting oxygen concentration to provide technical underpinnings to refine a flammability criterion for gas mixtures of helium, hydrogen, and oxygen where the oxygen is expected to be the limiting species. While there is general consensus on H 2 flammability limits at standard temperature and pressure, the decay heat and gas generation within ASNF sealed dry storage canisters could push them to elevated temperatures and pressures, so the goal is to identify an oxygen threshold that will bound the behavior over the temperature and pressure range of the U.S. Department of Energy (DOE) Standard Canister. The information reviewed in this document supports the criterion that the oxygen concentration in a He-H 2 -O 2 mixture should be less than 1.5% to avoid flammability at temperatures and pressures relevant to sealed dry storage of ASNF in the DOE Standard Canister, i.e., up to 343°C (650°F) and 500 psig, respectively. Note that while data covering the full range of temperature at atmospheric pressure and nearly the full range of pressure at room temperature were available, data for the combined effects was available only at moderate temperatures and pressures; the recommended 1.5% O 2 threshold is based on the breadth of available data reported here and apparent trends therein.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Generative Models for Crystalline Materials

Understanding structure-property relationships in materials is fundamental in condensed matter physics and materials science. Over the past few years, machine learning (ML) has emerged as a powerful tool for advancing this understanding and accelerating materials discovery. Early ML approaches primarily focused on constructing and screening large material spaces to identify promising candidates for various applications. More recently, research efforts have increasingly shifted toward generating crystal structures using end-to-end generative models. This review analyzes the current state of generative modeling for crystal structure prediction and de novo generation. It examines crystal representations, outlines the generative models used to design crystal structures, and evaluates their respective strengths and limitations. Furthermore, the review highlights experimental considerations for evaluating generated structures and provides recommendations for suitable existing software tools. Emerging topics, such as modeling disorder and defects, integration in advanced characterization, incorporating synthetic feasibility constraints, and model explainability are explored. Ultimately, this work aims to inform both experimental scientists looking to adapt suitable ML models to their specific circumstances and ML specialists seeking to understand the unique challenges related to inverse materials design and discovery.

Metni, Houssam [Karlsruhe Inst. of Technology (KIT↗