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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 OSTI2024

Diffusion bonding of tungsten-vanadium-zirconium using vacuum hot pressing for the development of a low decay heat cladding solution for tungsten spallation targets

Tantalum has been used as cladding material for water-cooled solid tungsten targets at many leading spallation neutron production facilities thanks to its high neutron yield, manageable radiation damage behavior, and excellent corrosion/erosion resistance in radiation environments. However, from a safety hazard perspective, thermal neutron capture of tantalum in spallation environments causes a high specific decay heat in the target volume, which often becomes a limiting factor in increasing the beam power on the target. In this paper, we studied vacuum hot pressing (VHP) parameters to diffusion bond zirconium to tungsten to explore the feasibility of using zirconium alloys as an alternative cladding material to tantalum. Zirconium alloys have long been used as cladding material for early generation solid spallation targets, and nuclear fuel rods. In spallation environments zirconium has significantly lower decay heat with shorter decay time compared to tantalum. The hot isostatic pressing (HIP) of zirconium and tungsten is known to produce limited bonding quality due to the formation of the brittle ZrW2 intermetallic layer. To overcome this problem, placing a vanadium interlayer between tungsten and zirconium has been proposed by exploring parameter space in binary alloy phase diagrams. Under the VHP conditions, 860 ◦C at 70 MPa for 4 hours, Zr-V and V-W showed good diffusion bonding, which demonstrates the feasibility of a single step HIP process to make the zirconium alloy clad tungsten spallation volumes.

Lee, Yong Joong↗
DOE OSTI2024

Oxide dissolution and oxygen diffusion scenarios in niobium and implications on the Bean–Livingston barrier in superconducting cavities

We generalize a native Nb2O5 dissolution model [G. Ciovati, Appl. Phys. Lett. 89, 022507 (2006)] to sequential overlayer dissolutions, multilayer dissolution, and realistic temperature profiles, which may be applicable to other materials. The model is applied to secondary ion mass spectrometry depth profile measurements for varying temperature profiles and two-step oxide dissolution in Nb and found to agree well. In the context of the Meissner screening response due to impurity profiles on the length scale of the London penetration depth, the shallow diffusion of O impurities results in a substantial decrease in the peak supercurrent density near the surface. In this framework, oxide dissolution and oxygen diffusion can account for a rise in peak supportable magnetic field in SRF cavities with baking time and a suppression after the optimal baking time is reached, in good agreement with peak-field baking temperatures and times as well as recent quench field measurements.

Lechner, Eric↗
DOE OSTI2025

CalTestBed - Twelve Benefit Co - Understanding Degradation of Water Management Properties in Gas Diffusion Layers (CRADA Final Report)

The research between Lawrence Berkeley National Lab and Twelve Benefit Co. enhanced Twelve’s understanding of how chemical changes to the gas diffusion layer lead to failure of their CO 2 electrolyzers. During the CRADA period, LBNL team tested Twelve’s gas diffusion layer samples (GDL), some with microporous layer (MPL) and some without MPL using the water-air capillary pressure setup. LBNL team also tested microporous layer samples using the fuel cell test stands and compared those results with commercial GDL and MPL. Understanding the hydrophobicity of the material, along with electrochemical performance is the key to determining Twelve’s ability to scale their platform. Further improvements to Twelve’s CO 2 electrolyzer can enhance the net zero emissions with their technology.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Establishment of a Vertically Integrated Domestic Manufacturing Process for Production of Substrates Needed for Manufacture of Gas Diffusion Layers

In this project, AvCarb, LLC evaluated the baseline performance metrics of commercial carbon veils and their corresponding Gas Diffusion Layers (GDLs) with the goal of establishing an optimized, vertically integrated production system for wet-laid nonwoven substrates used in gas diffusion media for electrochemical energy storage and conversion devices. Mechanical testing and microstructural characterization were conducted and used to develop a multiscale computational model capable of simulating and predicting the performance of GDLs in fuel cells. Although the project successfully generated foundational transport and modeling data, it was terminated prior to identifying the critical GDL design parameters necessary for full optimization. The program aimed to improve carbon veil fabrication through enhanced fiber dispersion, fiber-fiber adhesion control, and improved web formation, enabling the production of high-quality, uniform substrates. Simulations were intended to guide mixing and solution delivery system design and process conditions, followed by production-scale trials to evaluate fiber dispersion, web uniformity, and mechanical robustness. At full deployment, the proposed production line would have been capable of producing approximately 650,000 m² of carbon veil annually. This capability remains strategically important, as the United States currently lacks a domestic source of wet-laid nonwoven carbon substrates that satisfy the stringent quality requirements for fuel-cell GDLs and electrolyzers representing an ongoing supply-chain vulnerability. Beyond supply-chain benefits, the project established a robust benchmarking dataset for existing commercial carbon veils while advancing next-generation material concepts targeting improved performance and manufacturing consistency.

Olson, Cynthia Lemay↗
DOE OSTI2026

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↗
DOE OSTI2026

Development of in situ thickness sensor for vapor diffused Nb3Sn films

Fermilab is one of the leaders in development of vapor diffused Nb3Sn films inside niobium cavities. This material has a higher critical temperature (Tc) than niobium, enabling cavity operation at 4.2 K. This higher operational temperature significantly reduces the infrastructure required for cooling compared to 2 K systems, making superconducting radio-frequency (SRF) technology more accessible. Current deposition methods have relied on iterative testing to determine nominal film thickness, a process that can be time-consuming and imprecise. To address this, we are developing a sensor to measure the thickness of Nb3Sn thin film in situ during vapor diffusion. Our design involves the resistance measurement of a thin film of niobium. During coating, the change in resistance reflects the conversion of the film to Nb3Sn, which allows simple integration with the current furnace infrastructure. This sensor would allow real time measurement of the thickness, allowing for increased precision in future depositions.

Howard, K. [Unlisted] (ORCID:0000000325613308)↗
DOE OSTI2026

Development of in situ thickness sensor for vapor diffused Nb3Sn films

Fermilab is one of the leaders in development of vapor diffused Nb3Sn films inside niobium cavities. This material has a higher critical temperature (Tc) than niobium, enabling cavity operation at 4.2 K. This higher operational temperature significantly reduces the infrastructure required for cooling compared to 2 K systems, making superconducting radio-frequency (SRF) technology more accessible. Current deposition methods have relied on iterative testing to determine nominal film thickness, a process that can be time-consuming and imprecise. To address this, we are developing a sensor to measure the thickness of Nb3Sn thin film in situ during vapor diffusion. Our design involves a four-point resistance measurement of a thin film of niobium, inside the coating region. During coating, the change in resistance reflects the conversion of the film from Nb to Nb3Sn, which allows simple integration with the current furnace infrastructure. This sensor would allow real time measurement of the Nb3Sn film thickness, allowing for increased precision in future depositions for cavity applications.

Howard, K. [Chicago U.] (ORCID:0000000325613308)↗
DOE OSTI2025

Transformation of TiN to TiNO Films via In-Situ Temperature-Dependent Oxygen Diffusion Process and Their Electrochemical Behavior

Titanium oxynitride (TiNO) thin films represent a multifaceted material system applicable in diverse fields, including energy storage, solar cells, sensors, protective coatings, and electrocatalysis. This study reports the synthesis of TiNO thin films grown at different substrate temperatures using pulsed laser deposition. A comprehensive structural investigation was conducted by X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), Non-Rutherford backscattering spectrometry (N-RBS), and X-ray absorption spectroscopy (XAS), which facilitated a detailed analysis that determined the phase, composition, and crystallinity of the films. Structural control was achieved via temperature-dependent oxygen in-diffusion, nitrogen out-diffusion, and the nucleation growth process related to adatom mobility. The XPS analysis indicates that the TiNO films consist of heterogeneous mixtures of TiN, TiNO, and TiO2 phases with temperature-dependent relative abundances. The correlation between the structure and electrochemical behavior of the thin films was examined. The TiNO films with relatively higher N/O ratio, meaning less oxidized, were more electrochemically active than the films with lower N/O ratio, i.e., more oxidized films. Films with higher oxidation levels demonstrated enhanced crystallinity and greater stability under electrochemical polarization. These findings demonstrate the importance of substrate temperature control in tailoring the properties of TiNO film, which is a fundamental part of designing and optimizing an efficient electrode material.

Cherono, Sheilah↗
DOE OSTI2025

Virtual element approximations of the time-fractional nonlinear convection-diffusion equation on polygonal meshes

We extend the Virtual Element Method to a two-dimensional unsteady nonlinear convection-diffusion equation characterized by a fractional-order derivative with respect to the time variable. Our methodology is based on three fundamental technical components: a fractional version of the Grunwald-Letnikov approximation, discrete maximal regularity, and the regularity theory associated with non-linearity. We prove the method's well-posedness, i.e., the approximate solution's existence and uniqueness to the time-fractional convection-diffusion equation with a Lipschitz nonlinear source term. The fully discrete scheme inherently maintains stability and consistency by leveraging the discrete maximal regularity and the energy projection operator. The convergence in the L 2 -norm and H 1 -norm to various mesh configurations is validated by numerical results, underlining the practical effectiveness of the proposed method.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Diffusion Codes: Self-Correction from Small(er)-Set Expansion with Tunable Non-locality

Optimal constructions of classical LDPC codes can be obtained by choosing the Tanner graph uniformly at random among biregular graphs. We introduce a class of codes that we call ``diffusion codes'', defined by placing each edge connecting bits and checks on some graph, and acting on that graph with a random SWAP network. By tuning the depth of the SWAP network, we can tune a tradeoff between the amount of randomness -- and hence the optimality of code parameters -- and locality with respect to the underlying graph. For diffusion codes defined on the cycle graph, if the SWAP network has depth $\sim Tn$ with $T> n^{2β}$ for arbitrary $β>0$, then we prove that almost surely the Tanner graph is a lossless ``smaller set'' vertex expander for small sets up size $δ\sim \sqrt T \sim n^β$, with bounded bit and check degree. At the same time, the geometric size of the largest stabilizer is bounded by $\sqrt T$ in graph distance. We argue, based on physical intuition, that this result should hold more generally on arbitrary graphs. By taking hypergraph products of these classical codes we obtain quantum LDPC codes defined on the torus with smaller-set boundary and co-boundary expansion and the same expansion/locality tradeoffs as for the classical codes. These codes are self-correcting and admit single-shot decoding, while having the geometric size of the stabilizer growing as an arbitrarily small power law. Our proof technique establishes mixing of a random SWAP network on small subsystems at times scaling with only the subsystem size, which may be of independent interest.

Combinatorics (math.CO)↗
DOE OSTI2025

In-Pile Irradiation Induced Defects and the Effect on Thermal Diffusivity of MgO

The effects of neutron irradiation temperature and dose on thermal diffusivity are compared between non-irradiated and in-pile irradiated MgO samples. MgO pellets were irradiated in-pile of the Advanced Test Reactor at Idaho National Laboratory. Samples were irradiated at 623 and 973 K to fast neutron fluences of 1 x 1025 (1.5 dpa) and 2 x 1025 n/m2 (3 dpa). Post irradiation examination included X-ray diffraction, scanning electron microscopy, laser flash thermal diffusivity, and transmission electron microscopy. The radiation induced thermophysical and structural evolution of MgO is reported

T. Moorea, Donald↗
DOE OSTI2024

Advancing earth system model calibration: a diffusion-based method

Understanding of climate impact on ecosystems globally requires site-specific model calibration. Here we introduce a novel diffusion-based uncertainty quantification (DBUQ) method for efficient model calibration. DBUQ is a score-based diffusion model that leverages Monte Carlo simulation to estimate the score function and evaluates a simple neural network to quickly generate samples for approximating parameter posterior distributions. DBUQ is stable, efficient, and can effectively calibrate the model given diverse observations, thereby enabling rapid and site-specific model calibration on a global scale. This capability significantly advances Earth system modeling and our understanding of climate impacts on Earth systems. We demonstrate DBUQ's capability in E3SM land model calibration at the Missouri Ozark AmeriFlux forest site. Both synthetic and real-data applications indicate that DBUQ produces accurate parameter posterior distributions similar to those generated by Markov Chain Monte Carlo sampling but with 30X less computing time. This efficiency marks a significant stride in model calibration, paving the way for more effective and timely climate impact analyses.

Liu, Yanfang↗
DOE OSTI2025

$S^5$: Tidal Disruption in Crater 2 and Formation of Diffuse Dwarf Galaxies in the Local Group

We present results of a spectroscopic campaign around the diffuse dwarf galaxy Crater 2 (Cra2) and its tidal tails as part of the Southern Stellar Stream Spectroscopic Survey ($S^5$). Cra2 is a Milky Way dwarf spheroidal satellite with extremely cold kinematics, but a huge size similar to the Small Magellanic Cloud, which may be difficult to explain within collisionless cold dark matter. We identify 143 Cra2 members, of which 114 belong to the galaxy's main body and 29 are deemed part of its stellar stream. We confirm that Cra2 is dynamically cold (central velocity dispersion $2.51^{+0.33}_{-0.30}\,{\rm km\,s^{-1}}$) and also discover a $\approx$7$σ$ velocity gradient consistent with its tidal debris track. We separately estimate the stream velocity dispersion to be $5.74^{+0.98}_{-0.83}\,{\rm km\,s^{-1}}$. We develop a suite of $N$-body simulations with both cuspy and cored density profiles on a realistic Cra2 orbit to compare with $S^5$ observations. We find that the velocity dispersion ratio between Cra2 stream and galaxy ($2.30^{+0.41}_{-0.35}$) is difficult to reconcile with a cuspy halo with fiducial concentration and an initial mass predicted by standard stellar mass$-$halo mass relationships. Instead, either a cored halo with relatively small core radius or a low-concentration cuspy model can reproduce this ratio. Despite tidal mass loss, Cra2 is metal-poor ($\langle \rm[Fe/H]\rangle=-2.16\pm0.04$) compared to the stellar mass$-$metallicity relation for its luminosity. Other diffuse dwarf galaxies similar to Cra2 in the Local Group (Antlia 2 and Andromeda 19) also challenge galaxy formation models. Finally, we discuss possible formation scenarios for Cra2, including ram-pressure stripping of a gas-rich progenitor combined with tides.

Limberg, Guilherme [Chicago U., KICP; Chicago U.] ↗
DOE OSTI2025

Towards stabilization of pressurized oxy-coal diffusion flames

Designing an effective burner is vital for the development of pressurized oxy-fuel combustion technologies. Turbulent jet diffusion burners are adopted for the pressurized oxy-combustor in this research and a bluff-body is employed to create a recirculation zone to stabilize the flame in pressurized oxy-combustor. The objective of this numerical work is to perform a systematic analysis of the characteristics of this pressurized non-premixed flame. Specifically, a 15-bar POFC combustor of power 100 kWth is modeled employing the Ansys FLUENT commercial platform, using Reynolds-averaged Navier-Stokes (RANS) modeling. The present computational work focuses on identifying the aerothermodynamic features of the isothermal and reacting flow with a disk-shape bluff-body. Results show that fuel-oxidizer stream momentum ratio has great impacts on the temperature profile of the down-fired, co-axial, pressurized oxy-coal, diffusion flame. Parametric study of the width of the burner tip identifies an optimal range for this pressurized burner.

Li, Lei↗
DOE OSTI2025

Models and Measurements Quantify Photon Recycling, Charge-Carrier Diffusion and Photon Scattering Contributions to Photoluminescence in InP Nanowire Arrays

Nanowire arrays present many unique advantages for solar-to-chemical energy conversion. One possible advantage is that photon recycling between neighboring nanowires has the potential to increase solar energy conversion efficiencies. Here, in this work, we explore three underlying mechanisms of optical and electronic coupling between neighboring nanowires─incident photon scattering, photon recycling, and charge-carrier transport from the photoexcited nanowire to the neighboring nanowire via the underlying substrate─using single nanowire-level microscopy and spectroscopy measurements. We present a comprehensive analysis of light absorption and emission of a single nanowire at open circuit, and subsequent re-absorption and re-emission by a neighboring nanowire. We developed a novel correlated single nanowire microspectroscopy and widefield imaging methodology to spatially resolve photon communication pathways between neighboring nanowires and selectively image re-emitted and reflected photons. We developed unique multiphysics models to couple wave optics and semiconductor photophysics to especially isolate contributions from photon recycling and electronic transport to photon emission from neighboring nanowires. By systematically varying the morphologies of the nanowires modeled, we identified pathways to maximize photon recycling between neighboring nanowires. We concluded that the measured photoluminescence is more strongly influenced by the diffusion of charge carriers as compared to photon recycling in materials with moderate-to-large charge-carrier mobilities (>10 cm 2 V –1 s –1 ), and that photon recycling dictates photoluminescence intensity only when the charge-carrier mobility is low (<1 cm 2 V –1 s –1 ). The experimental and simulation platforms developed herein for photon management strategies can be leveraged by the semiconductor photocatalysis community to enhance solar-to-chemical conversion efficiencies in semiconductor nanowire arrays.

25 ENERGY STORAGE↗
DOE OSTI2024

Role of Exciton Diffusion in the Efficiency of Mn Dopant Emission in Two-Dimensional Perovskites

Two-dimensional (2D) metal-halide perovskites have promising characteristics for optoelectronic applications. By incorporating Mn 2+ ions into the perovskite structure, improved photoluminescence quantum yield can be achieved. This has been attributed to the formation of defect states that act as efficient recombination centers. Here, we make use of transient photoluminescence microscopy to characterize important material parameters of Mn 2+ -doped 2D perovskites with different doping levels. From these measurements, we visualize the importance of exciton transport as an intermediate step in the excitation of Mn 2+ . We model the spatiotemporal dynamics of the excited states to extract the diffusion constant and the transfer rate of the excitations to the Mn dopant sites. Interestingly, from these models, we find that the average distance an exciton needs to travel before transferring to a Mn site is significantly larger than expected from the Mn concentration obtained from elemental analysis. These insights are critical from a device design perspective.

2D perovskites↗
DOE OSTI2025

Generative diffusion model surrogates for mechanistic agent-based biological models

Mechanistic, multicellular, agent-based models are commonly used to investigate tissue, organ, and organism-scale biology at single-cell resolution. The Cellular-Potts Model (CPM) is a powerful and popular framework for developing and interrogating these models. CPMs become computationally expensive at large space- and time- scales making application and investigation of developed models difficult. Surrogate models may allow for the accelerated evaluation of CPMs of complex biological systems. However, the stochastic nature of these models means each set of parameters may give rise to different model configurations, complicating surrogate model development. In this work, we leverage denoising diffusion probabilistic models (DDPMs) to train a generative AI surrogate of a CPM used to investigate in vitro vasculogenesis. We describe the use of an image classifier to learn the characteristics that define unique areas of a 2-dimensional parameter space. We then apply this classifier to aid in surrogate model selection and verification. Our CPM model surrogate generates model configurations 20,000 timesteps ahead of a reference configuration and demonstrates approximately a 22x reduction in computational time as compared to native code execution. Our work represents a step towards the implementation of DDPMs to develop digital twins of stochastic biological systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

High‐Asymmetry Metasurface: A New Solution for Terahertz Resonance via Active Learning‐Augmented Diffusion Model

Terahertz (THz) metamaterials with high‐figure‐of‐merit (high‐FoM) performance resonance are essential for advancing sensors, detectors, and imagers. Conventional designs focus on symmetric or low‐asymmetry geometric structures, leaving high‐asymmetry designs largely unexplored due to the inefficiency of trial‐and‐error‐based rational design. Recent deep learning techniques offer automation and acceleration but are constrained by the need for large datasets inherent to their data‐driven nature. Here, a novel prior knowledge‐guided generative model augmented by a physics‐constrained active learning mechanism to design high‐asymmetry metamaterials. An advanced diffusion model learns features from a small set of classical structures with high‐FoM THz resonance and generates new high‐asymmetry structures. To mitigate the limited number of classical structures, the generated high‐asymmetry structures are actively selected and integrated into the initial training dataset based on their physical characteristics. Experimental results demonstrate the superior resonance performance of the generated high‐asymmetry metamaterials over classical designs, exhibiting improvements exceeding 30% in key resonance metrics. Remarkably, this performance is attained using only 68 classical structures as the initial training dataset, significantly reducing the data requirements for deep learning‐based metamaterial design. The proposed scheme for generating high‐asymmetry structures provides a new effective and efficient solution for high‐FoM resonance, expanding applications in high‐sensitivity THz metadevices.

diffusion model↗