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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 235 records · Page 13

Intrinsic rotation modulation by diffusive neutral particles in tokamaks

Abstract The modulated transport model, a model kinetic ion transport equation for the pedestal and scrape-off layer (SOL), is generalized to self-consistently include effects of a single neutral particle species. The neutrals contribute additional transport terms, modifying the v ∥ -dependent orbit-averaged ion diffusivities of the original work and the resulting predicted intrinsic rotation of the ions. After making simplifying assumptions of the neutral transport, in particular taking the continuous transport limit via a short charge-exchange step expansion, we derive relatively simple analytic expressions that capture the diffusive neutral physics. Within the scope of the model’s validity, the neutral-driven intrinsic rotation can compete with the turbulence-driven intrinsic rotation. However, for physically motivated parameters, the neutral-driven intrinsic rotation appears negligible, either on a term-by-term basis or due to a strong cancellation between the neutral-driven momentum diffusion and pinch terms. It appears that a treatment containing finite charge-exchange steps is necessary to capture neutral transport of strong flow momentum into the confined region from the SOL.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Thermal cycling-driven microstructural changes of eutectic Al–Si phase change materials in SS304 containers revealed by multi-modal imaging

Aluminum-based Al–Si alloys are widely used as phase change materials (PCMs) in thermal energy storage (TES) systems owing to their high volumetric latent heat and superior thermal conductivity. However, their long-term reliability is limited by degradation processes that remain insufficiently understood. In this work, we employ a multimodal, correlative characterization framework to systematically resolve the degradation behavior of eutectic Al–Si PCMs in contact with SS304 containers under repeated thermal cycling. By integrating high-resolution electron microscopy, three-dimensional X-ray fluorescence (3D XRF) imaging, and differential scanning calorimetry (DSC), we directly link spatially resolved compositional and microstructural evolution to changes in thermophysical properties. The correlative analysis reveals that elemental leaching of Fe, Cr, and Ni from the stainless-steel container into the PCM drives the formation of intermetallic compounds (IMCs) both at the interface and within the bulk PCM, leading to pronounced compositional heterogeneity. These interfacial reactions and diffusion-induced transformations progressively destabilize the Al–Si eutectic, reducing the effective phase-transforming fraction. Consistent with these observations, DSC measurements show a decrease in melting temperature and latent heat of fusion with thermal cycling. These results underscore the critical influence of interfacial reactions and material compatibility on the stability, durability, and overall performance of Al–Si-based TES systems.

25 ENERGY STORAGE↗

Computational discovery of fast interstitial oxygen conductors

New highly oxygen-active materials may enhance many energy-related technologies by enabling efficient oxygen-ion transport at lower temperatures, for example, below ~400 °C. Interstitial oxygen conductors have the potential to realize such performance but have received far less attention than vacancy-mediated conductors. Here, in this study, we combine physically motivated structure and property descriptors, ab initio simulations and experiments to demonstrate an approach to discover new fast interstitial oxygen conductors. Multiple new families were found, which adopt completely different structures from known oxygen conductors. From these families, we synthesized and studied oxygen kinetics in La 4 Mn 5 Si 4 O 22+δ , a representative member of the perrierite/chevkinite family. We found that La 4 Mn 5 Si 4 O 22+δ has higher oxygen-ion conductivity than the widely used yttria-stabilized ZrO 2 , and among the highest surface oxygen exchange rates at the intermediate temperature of known materials. The fast oxygen kinetics is the result of simultaneously active interstitial and interstitialcy diffusion pathways. We propose that the essential features for forming an effective interstitial oxygen conductor are the availability of electrons and structural flexibility, enabling a sufficient accessible volume. This work provides a powerful approach for understanding and discovering new interstitial oxygen conductors.

36 MATERIALS SCIENCE↗

Oxygen vacancies in niobium pentoxide as a source of two-level system losses in superconducting niobium

We identify a major source of quantum decoherence in three-dimensional superconducting radio-frequency (SRF) resonators and two-dimensional transmon qubits composed of oxidized niobium: oxygen vacancies in the niobium pentoxide, which drive two-level system (TLS) losses. By probing the effect of sequential in situ vacuum-baking treatments on the rf performance of bulk Nb SRF resonators and on the oxide structure of a representative Nb sample using TOF SIMS, we find a nonmonotonic evolution of cavity quality factor Q 0 , which correlates with the interplay of Nb 2 O 5 vacancy generation and oxide-thickness reduction. We localize this effect to the oxide itself and present the insignificant role of diffused interstitial oxygen in the underlying Nb by regrowing the oxide via wet oxidation, which reveals a mitigation of aggravated TLS losses. We hypothesize that such vacancies in the pentoxide serve as magnetic impurities and are a source of TLS-driven rf loss.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Oxygen vacancies in niobium pentoxide as a source of two-level system losses in superconducting niobium

Two-level systems (TLS) have long been a catch-all explanation for RF loss and quantum decoherence in superconducting devices. In our study, the first to directly link TLS losses to a specific physical mechanism, we demonstrate that oxygen vacancies in the naturally formed Nb₂O₅ on oxidized niobium are a major driver of such dissipation. We performed sequential in situ vacuum-baking treatments on niobium superconducting radio-frequency (SRF) cavities and used time-of-flight secondary ion mass spectrometry (TOF-SIMS) to reveal a nonmonotonic evolution in cavity quality factor (Q₀). This behavior correlates with the interplay of Nb₂O₅ vacancy generation and oxide-thickness dissolution. We localize this effect to the oxide itself and present the insignificant role of diffused interstitial oxygen in the underlying Nb by regrowing the oxide via wet oxidation, revealing a mitigation of aggravated TLS losses. We hypothesize that such vacancies in the pentoxide serve as magnetic impurities and are a source of TLS-driven rf loss. Although our measurements center on 3-D SRF cavities, the insights gained here have significant implications for mitigating decoherence in 2-D superconducting qubits.

Bafia, Daniel P. [Fermilab]↗

Oxygen Vacancies in Niobium Pentoxide as a Source of Two-Level System Losses in Superconducting Niobium

We identify a major source of quantum decoherence in three-dimensional superconducting radio-frequency (SRF) resonators and two-dimensional transmon qubits composed of oxidized niobium: oxygen vacancies in the niobium pentoxide, which drive two-level system (TLS) losses. By probing the effect of sequential in situ vacuum-baking treatments on the rf performance of bulk Nb SRF resonators and on the oxide structure of a representative Nb sample using TOF SIMS, we find a nonmonotonic evolution of cavity quality factor Q0, which correlates with the interplay of Nb2O5 vacancy generation and oxide-thickness reduction. We localize this effect to the oxide itself and present the insignificant role of diffused interstitial oxygen in the underlying Nb by regrowing the oxide via wet oxidation, which reveals a mitigation of aggravated TLS losses. We hypothesize that such vacancies in the pentoxide serve as magnetic impurities and are a source of TLS-driven rf loss.

Bafia, Daniel P. [Fermilab]↗

Improving unfolding and systematic uncertainty estimation using generative diffusion networks (Final Technical Report)

This final technical report summarizes the key accomplishments on the unfolding using diffusion model project, a DOE award received by PI Pierre-Hugues Beauchemin at Tufts University. This project main goal was to investigate the potential of diffusion models for unfolding experimental High Energy Physics data from detector effects while controlling systematics uncertainties. The project accomplished its goals by completing the following objectives: 1) Performing an object-by-object, event-by-event unfolding of various kinematic distributions reconstructed from detector data in HEP in a way that keeps correlations between unfolded observables while demonstrating competitive performance compared to standard algorithms used in the field; 2) Address the generalization problem by developing an unfolding algorithm capable to correctly infer the underlying distributions of observables and processes never seen before, while controlling the dominant theoretical uncertainties affecting the process, therefore increasing the effectiveness, the precision, and the applicability of the developed algorithm; 3) Understand the theoretical foundations between the developed algorithm so to extend it to applications beyond experimental HEP, for broader benefits to the society. This report provides an overview of the accomplishments related to each of these key objectives.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Geospatial Diffusion for Land Cover Imperviousness Change Forecasting

Land-use and land-cover (LULC) has a significant effect on several Earth system processes. For example, impervious surfaces reduce infiltration and speed water flow, impacting regional hydrology and flood risk. While Earth System models have improved forecasting hydrologic and atmospheric processes at higher resolutions, the ability to forecast LULC change has lagged behind. In this paper, we propose a new paradigm exploiting Generative AI (GenAI) for land cover change forecasting by framing it as a data synthesis problem conditioned on historical and auxiliary data-sources. To demonstrate the feasibility of our methodology, we perform experiments where a diffusion model is trained for decadal forecasting of imperviousness change across the entire United States. We find that our model yields MAE lower than a no-change baseline for resolutions ≥ 0.7 X 0.7km2 on average, demonstrating its ability to capture and project accurate spatiotemporal patterns. Finally, we discuss future research to incorporate Earth's physical properties and enabling scenario simulations via driver variables.

Varshney, Debvrat [ORNL] (ORCID:0000000188981736)↗

Anionic Effects on Concentrated Aqueous Lithium Ion Dynamics

In this article, the structural dynamics, chemical reactivity, anisotropy, diffusivity, viscosity, and density were measured for concentrated lithium salt solutions, including lithium chloride (LiCl), lithium bromide (LiBr), lithium nitrite (LiNO 2 ), and lithium nitrate (LiNO 3 ), with methyl thiocyanate as an infrared vibrational probe molecule, using two-dimensional infrared spectroscopy (2D IR), nuclear magnetic resonance (NMR) spectroscopy, and viscometry. 2D IR, NMR, and viscosity results show that LiNO 2 exhibits longer correlation times, lower diffusivity, and nearly four times greater viscosity when compared to the other lithium salt solutions of the same concentration, suggesting that nitrite anions may strongly facilitate structure formation via strengthening water-ion interactions, directly impacting bulk solution properties at sufficiently high concentrations. Additionally, the LiNO 2 and LiNO 3 solutions show significantly reduced chemical reactivity with respect to lithium cations coordinating with the methyl thiocyanate when compared to the lithium halide salts.

2D IR↗

Moving beyond the Aerosol Climatology of WRF-Solar: A Case Study over the North China Plain

Numerical weather prediction (NWP), when accessible, is a crucial input to short-term solar power forecasting. WRF-Solar, the first NWP model specifically designed for solar energy applications, has shown promising predictive capability. Nevertheless, few attempts have been made to investigate its performance under high aerosol loading, which attenuates incoming radiation significantly. The North China Plain is a polluted region due to industrialization, which constitutes a proper testbed for such investigation. Here, in this paper, aerosol direct radiative effect (DRE) on three surface shortwave radiation components (i.e., global, beam, and diffuse) during five heavy pollution episodes is studied within the WRF-Solar framework. Results show that WRF-Solar overestimates instantaneous beam radiation up to 795.3 W m -2 when the aerosol DRE is not considered. Although such overestimation can be partially offset by an underestimation of the diffuse radiation of about 194.5 W m -2 , the overestimation of the global radiation still reaches 160.2 W m -2 . This undesirable bias can be reduced when WRF-Solar is powered by Copernicus Atmosphere Monitoring Service (CAMS) aerosol forecasts, which then translates to accuracy improvements in photovoltaic (PV) power forecasts. This work also compares the forecast performance of the CAMS-powered WRF-Solar with that of the European Centre for Medium-Range Weather Forecasts model. Under high aerosol loading conditions, the irradiance forecast accuracy generated by WRF-Solar increased by 53.2% and the PV power forecast accuracy increased by 6.8%.

54 ENVIRONMENTAL SCIENCES↗

Effect of TiN coating on suppressing Ce-Fe interaction under irradiation

Advanced cladding is critical for fast reactors with the adequate thermal conductivity, mechanical stability and radiation tolerance of the cladding base material, corrosion resistance and high temperature coolant compatibility of the cladding surface, and chemical stability of the cladding inner wall against fuel cladding chemical interaction (FCCI). The preliminary results of recent ion irradiation studies of two diffusion-couple samples of cerium (Ce)/oxide-dispersion strengthened steel (ODS) and Ce/TiN/ODS, irradiated with 80 MeV xenon (Xe) ions to 100 displacements per atom (dpa) at 500°C, are summarized. Significant Ce-Fe interaction occurred in the Ce/ODS sample, and no noticeable Ce-Fe interaction was found in the Ce/TiN/ODS sample. It shows the effectiveness of 1-µm TiN diffusion barrier coated by the pulsed laser deposition on suppressing Ce-Fe interaction, a major contributor to FCCI in cladding. Here, density function theory (DFT) calculations of the impurity diffusivities of Ce and Fe within the Ti sublattice of TiN were performed to assist a mechanistic understanding of the experimental results.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

In Situ Observation of Ion Migration in a Ferroelectric Ionic Conductor Rb-KTP during Thermal Annealing

Ion exchange in Rb-doped KTiOPO 4 has facilitated significant advancements in ferroelectric domain engineering, yet understanding the underlying mechanisms remains in its infancy. We perform time-of-flight secondary ion mass spectrometry analysis on multiple periodically ion-exchanged and periodically poled Rb-doped KTiOPO 4 samples under different temperatures and annealing durations. The results are compared between annealing in air, which involved ex situ annealing before periodic poling, and vacuum annealing conducted in situ after periodic poling. The Rb + diffusion profile after periodic ion exchange forms a tooth-shaped pattern. We show that in situ annealing causes a surface pinning effect on the nonpolar face, limiting Rb + migration along the polar axis at the surface. Once the pinned layer is removed through milling, the underlying Rb + diffusion is distinctively different from the surface. Additionally, the rate of Rb + diffusion during in situ annealing is linear, while the periodic domain structures remain stable after annealing. These results contribute to understanding the ionic diffusion process in a ferroelectric ionic conductor and using ion exchange to tailor the linear and nonlinear properties of KTiOPO 4 .

36 MATERIALS SCIENCE↗

Modeling inter‐reader variability in clinical target volume delineation for soft tissue sarcomas using diffusion model

Abstract Background Accurate delineation of the clinical target volume (CTV) is essential in the radiotherapy treatment of soft tissue sarcomas. However, this process is subject to inter‐reader variability due to the need for clinical assessment of risk and extent of potential microscopic spread. This can lead to inconsistencies in treatment planning, potentially impacting treatment outcomes. Most existing automatic CTV delineation methods do not account for this variability and can only generate a single CTV for each case. Purpose This study aims to develop a deep learning‐based technique to generate multiple CTV contours for each case, simulating the inter‐reader variability in the clinical practice. Methods We employed a publicly available dataset consisting of fluorodeoxyglucose positron emission tomography (FDG‐PET), x‐ray computed tomography (CT), and pre‐contrast T1‐weighted magnetic resonance imaging (MRI) scans from 51 patients with soft tissue sarcoma, along with an independent validation set containing five additional patients. An experienced reader drew a contour of the gross tumor volume (GTV) for each patient based on multi‐modality images. Subsequently, two additional readers, together with the first one, were responsible for contouring three CTVs in total based on the GTV. We developed a diffusion model‐based deep learning method that is capable of generating arbitrary number of different and plausible CTVs to mimic the inter‐reader variability in CTV delineation. The proposed model incorporates a separate encoder to extract features from the GTV masks, leveraging the critical role of GTV information in accurate CTV delineation. Results The proposed diffusion model demonstrated superior performance with the highest Dice Index (0.902 compared to values below 0.881 for state‐of‐the‐art models) and the best generalized energy distance (GED) (0.209 compared to values exceeding 0.221 for state‐of‐the‐art models). It also achieved the second‐highest recall and precision metrics among the compared ambiguous image segmentation models. Results from both datasets exhibited consistent trends, reinforcing the reliability of our findings. Additionally, ablation studies exploring different model structures and input configurations highlighted the significance of incorporating prior GTV information for accurate CTV delineation. Conclusions The proposed diffusion model successfully generates multiple plausible CTV contours for soft tissue sarcomas, effectively capturing inter‐reader variability in CTV delineation.

Dong, Yafei [Yale Biomedical Imaging Institute Yal↗

A mechanistic, multiscale model for predicting Pd penetration in TRISO fuels using BISON

TRistructural ISOtropic (TRISO) particles use silicon carbide (SiC) as the primary structural member and barrier against metallic fission product (FP) release. palladiums (PDs), produced by fission in the fuel kernel, can diffuse to and chemically interact with the SiC layer, degrading its structural integrity and ability to contain radioactive FPs. Existing temperature-dependent correlations for predicting Pd penetration rely on experimental data with significant scatter due to varying conditions, potentially complicating ongoing fuel qualification and licensing efforts for advanced reactors that would subject TRISO fuels to operating conditions outside of those examined in the experiments. A mechanistic model of Pd production, transport, and reaction is developed in this work to better understand and predict PD attack of SiC in TRISO particles. molecular dynamicss (MDs) simulations are utilized to calculate the Pd diffusivity in SiC grain bulk and grain boundaries. A mesoscale phase-field diffusion model, informed by the MD diffusivities, is used to develop a reduced order model (ROM) for the effect of SiC microstructure on the Pd penetration rate. The engineering scale BISON model calculates Pd production and transport, utilizing the ROM to predict penetration rates consistent with experimental data. This novel mechanistic ROM captures the effect of temperature, microstructure, and irradiation history on Pd penetration. In conclusion, these new capabilities are expected to support ongoing qualification and licensing efforts associated with near-term TRISO-fueled reactor applications.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Surface Dynamics of Selective Hydration of Rutile TiO 2 : A Kinetic Monte Carlo Approach

The utility of atomic layer deposition (ALD) continues to expand beyond conformal thin-film fabrication to include area- or site-selective ALD. We previously identified a strategy for site-selective ALD (SS-ALD) via the evaluation of thermodynamically preferred hydration of rutile TiO 2 surfaces, as deduced from electronic structure calculations. Here, we report a novel kinetic Monte Carlo (KMC) model that allows for the investigation of surface dynamics and kinetics that improves our understanding of and intuition for the selective hydration strategy. Here we demonstrate the validity of the strategy with respect to step-edge defects for the lowest energy (110) facet as well as report results for the other common facets which agree with experimental STM observations. The results here indicate that the selective hydration strategy is feasible both thermodynamically (evaluated in our previous publication) and kinetically (from the KMC model). Because diffusion has a slower rate than others, we find that any proximity effects between terrace and defect sites are unlikely to affect the selective hydration strategy for rutile TiO 2 . The KMC model further provides relevant timescales for achieving selectivity experimentally and establishes the kinetic viability of the selective hydration approach to SS-ALD.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Enabling hydrogen chemisorption on charged graphene

Two-dimensional (2D) materials, including graphitic derivatives, have long been of interest for hydrogen storage applications, due to their high theoretical storage capacity, low weight, and other useful properties. However, poor kinetics for hydrogen adsorption and surface diffusion as part of the proposed spillover process for hydrogenation have limited their technological potential. Here, we use first-principles calculations to study electronic doping as a means to improve hydrogen chemisorption on graphene, which we use here as a proxy for graphitic derivatives more broadly. We find that positively charged graphene sheets have vastly improved kinetics for hydrogen diffusion and adsorption, while they limit unwanted hydrogen desorption. This combination of effects should favor hydrogen chemisorption via spillover. We connect these trends to the C–H bond, which introduces states near the Fermi level. These states are depopulated as electrons are removed, thereby lowering the bond energy and permitting more facile movement of hydrogen. Our results suggest that spillover mechanisms for hydrogen chemisorption should be revisited if strategies to apply a large charge to graphitic systems can be realized. Moreover, switchable application of the charge may lead to the reversible chemisorption of hydrogen. While the large magnitude of charging required suggests that graphene itself may not be suitable for reversible hydrogen chemisorption, the factors we identify and discuss could significantly boost the prospects of graphitic derivatives and other 2D or layered materials for hydrogen storage applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mechanistic understanding of carbon mineralization in fracture systems using microfluidics

Carbon mineralization in mafic and ultramafic rocks presents an opportunity for permanent carbon storage in the Earth's subsurface. However, due to their lower permeability, pre-existing fracture networks are key for mineralization to occur. Therefore, to fully develop this technology, a mechanistic understanding of the mineralization behavior in fractures with the consideration of hydrodynamic components is required. We use high-pressure microfluidics to investigate key mechanisms influencing dissolution–precipitation in a fracture network. The experiments were conducted in micromodels made of natural rocks with a comb-shaped flow channel to mimic a fracture network. This enabled studying the effect of injection rate on coupled dissolution–precipitation in advection and diffusion-dominated flow paths. We used gypsum carbonation as an analog reaction to allow for realistic experimental time frames due to its rapid reaction kinetics. The experimental work is coupled with high-fidelity numerical simulations to enhance our understanding of the parameters affecting the mineralization reaction. Our results demonstrate the importance of flow rate on the rate and nature of the gypsum carbonation reaction revealing that higher flow rates enable deeper penetration of the mineral precipitation front into the dead-end channels. This is an important finding since for sustained mineralization in a fracture network, precipitation in dead-ends while still allowing for flowing fractures is critical. Detailed characterization of the precipitates showed that lower flow rates led to porous and loose precipitates in the form of aragonite while higher flow rates mimicked supersaturation behavior leading to the formation of calcite. The reactive transport simulations further demonstrated the significance of flow velocity in advection-dominated channels to influence the efficiency of carbon mineralization in diffusion-dominated channels, potentially clogging of dead-end channels. These findings highlight the need for coupling chemical, mechanical, and hydrodynamic processes to evaluate the nature and extent of carbon mineralization in fractured media critical for permanent storage in mafic and ultramafic formations. This research further highlights the need for more investigation in potential subsurface fracture generation techniques to aid carbon mineralization.

25 ENERGY STORAGE↗

Atomic layer deposition of nanofilms on porous polymer substrates: Strategies for success

Atomic layer deposition (ALD) is a versatile technique for engineering the surfaces of porous polymers, imbuing the flexible, high-surface-area substrates with inorganic and hybrid material properties. Previously reported enhancements include fouling resistance, electrical conductance, thermal stability, photocatalytic activity, hydrophilicity, and oleophilicity. However, there are many poorly understood phenomena that introduce challenges in applying ALD to porous polymers. In this paper, we address five common challenges and ways to overcome them: (1) entrapped precursor, (2) embrittlement, (3) film fracture, (4) deformation, and (5) pore collapse. These challenges are often interrelated and can exacerbate one another. To investigate these phenomena, we applied various ALD chemistries to porous polymers including polyethersulfone, polysulfone, polyvinylidene fluoride, and polycarbonate track-etched membranes. Reaction-diffusion modeling revealed why certain precursors and processing conditions result in embrittling subsurface material growth, entrapment of unreacted precursors, and nongrowth. We quantify the limits of ALD processing temperatures that are dictated by thermal expansion mismatch and can lead to fractured ALD films. The results herein allow us to make recommendations to avoid, mitigate, or overcome the difficulties encountered when performing ALD and plasma-enhanced ALD on porous polymers. We intend this article to serve as a “lessons learned” guide informed by previous experience to provide a better understanding of the difficulties and limitations of ALD on porous polymers and knowledge-based guidelines for successful depositions. This knowledge can accelerate future research and help experimentalists navigate and troubleshoot as they expose porous polymers to reactive precursor vapors.

36 MATERIALS SCIENCE↗