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All sources NASA NTRS DOE OSTI

DOE OSTI2024

Direct Visualization of Defect‐Controlled Diffusion in van der Waals Gaps

Abstract Diffusion processes govern fundamental phenomena such as phase transformations, doping, and intercalation in van der Waals (vdW) bonded materials. Here, the diffusion dynamics of W atoms by visualizing the motion of individual atoms at three different vdW interfaces: hexagonal boron nitride (BN)/vacuum, BN/BN, and BN/WSe 2 , by recording scanning transmission electron microscopy movies is quantified. Supported by density functional theory (DFT) calculations, it is inferred that in all cases diffusion is governed by intermittent trapping at electron beam‐generated defect sites. This leads to diffusion properties that depend strongly on the number of defects. These results suggest that diffusion and intercalation processes in vdW materials are highly tunable and sensitive to crystal quality. The demonstration of imaging, with high spatial and temporal resolution, of layers and individual atoms inside vdW heterostructures offers possibilities for direct visualization of diffusion and atomic interactions, as well as for experiments exploring atomic structures, their in situ modification, and electrical property measurements of active devices combined with atomic resolution imaging.

Chemistry↗

NASA NTRS1971

The generation of magnetic fields in astrophysical bodies. III - Turbulent diffusion of fields and efficient dynamos

Galaxy gaseous disk as low mode dynamo, calculating turbulent diffusion coefficient for passive magnetic fields

Parker, E. N.↗

NASA NTRS1992

The compositional structure and the effects of exothermicity in an unpremixed planar jet flame

Results are presented of direct numerical simulations (DNS) of a randomly perturbed compressible, spatially developing planar jet under the influence of a finite rate Arrhenius chemical reaction of the type F + O yields Product + Heat. The objectives of the simulations are to assess the compositional structure of the flame and to determine the influence of reaction exothermicity by means of statistical sampling of the data generated by DNS. It is shown that even with this idealized kinetics model, the simulated results exhibit features in accordance with experimental data. These results indicate that the Damkoehler number is an important parameter in determining the statistical composition of the reacting field, and that the results are insensitive to the mechanism by which this parameter is varied. It is demonstrated that as the intensity of mixing is increased and the effect of finite rate chemistry is more pronounced, the magnitudes of the ensemble mean and rms of the product mass fraction decrease, and those of the reactants mass fraction increase. Also, at higher mixing rates the joint probability density functions of the reactants' mass fractions shift towards higher values within the composition domain indicating a lower reactedness. These trends are consistent with those observed experimentally and are very useful in portraying the statistical structure of non-equilibrium diffusion flames. The DNS generated data are also utilized to examine the applicability of the 'laminar diffusion flamelet model' in predicting the rate of the reactant conversion with finite rate chemistry. This examination indicates that the bounds of the product formation scale reasonably well with those obtained by the flamelet model. However, in the range of the relatively low values of the Damkoehler numbers considered, the scatter of the results is substantially more than that to be completely determined by the closure.

Steinberger, C. J.↗

NASA NTRS1974

Four-D global reference atmosphere technical description, part 1

An empirical atmospheric model was developed which generates values for pressure, density, temperature, and winds from surface levels to orbital altitudes. The output parameters consist of components for: (1) latitude, longitude, and altitude dependent monthly and annual means; (2) quasi-biennial oscillations; and (3) random perturbations to simulate partially the variability due to synoptic, diurnal, planetary wave, and gravity wave variations. Quasi-biennial and random variation perturbations are computed from parameters determined from various empirical studies and are added to the monthly mean values. This model has been developed as a computer program called PROFILE which can be used to generate altitude profiles of atmospheric parameters along any simulated trajectory through the atmosphere. The PROFILE program was developed for design applications in the space shuttle program. Other applications of the model are discussed, such as for global circulation and diffusion studies, and for generating profiles for comparison with other atmospheric measurement techniques, (e.g. satellite measured temperature profiles).

Justus, C. G.↗

DOE OSTI2019

High Performance Gas Diffusion Layer (Phase I Final Report)

Hydrogen fuel cells are of interest for automotive applications because they produce zero emissions. However, fuel cells currently suffer from the high cost associated with the fuel cell stack. Power is limited by water management in the cathode. In this project, pH Matter, LLC synthesized and demonstrated the performance of next generation fuel cell Gas Diffusion Layers (GDLs). The materials out-performed current GDLs in terms of power density and cost per power. The materials were shown to meet the application requirements for key properties. At the commercial scale, these materials will be less expensive than GDLs currently used in hydrogen fuel cells, and enable higher power density, thus reducing fuel cell stack costs. Fuel cell system applications that will benefit most from the technology include automotive, materials handling (i.e. forklifts), fleet vehicles, and stationary back-up power.

25 ENERGY STORAGE↗

DOE OSTI2010

A Simplified HTTR Diffusion Theory Benchmark

The Georgia Institute of Technology (GA-Tech) recently developed a transport theory benchmark based closely on the geometry and the features of the HTTR reactor that is operational in Japan. Though simplified, the benchmark retains all the principal physical features of the reactor and thus provides a realistic and challenging test for the codes. The purpose of this paper is twofold. The first goal is an extension of the benchmark to diffusion theory applications by generating the additional data not provided in the GA-Tech prior work. The second goal is to use the benchmark on the HEXPEDITE code available to the INL. The HEXPEDITE code is a Green’s function-based neutron diffusion code in 3D hexagonal-z geometry. The results showed that the HEXPEDITE code accurately reproduces the effective multiplication factor of the reference HELIOS solution. A secondary, but no less important, conclusion is that in the testing against actual HTTR data of a full sequence of codes that would include HEXPEDITE, in the apportioning of inevitable discrepancies between experiment and models, the portion of error attributable to HEXPEDITE would be expected to be modest. If large discrepancies are observed, they would have to be explained by errors in the data fed into HEXPEDITE. Results based on a fully realistic model of the HTTR reactor are presented in a companion paper. The suite of codes used in that paper also includes HEXPEDITE. The results shown here should help that effort in the decision making process for refining the modeling steps in the full sequence of codes.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2005

PAHs and the Diffuse Interstellar Bands. What have we Learned from the New Generation of Laboratory and Observational Studies?

Polycyclic Aromatic Hydrocarbons (PAHs) are an important and ubiquitous component of carbon-bearing materials in space. PAHs are the best-known candidates to account for the IR emission bands (UIR bands) and PAH spectral features are now being used as new probes of the ISM. PAHs are also thought to be among the carriers of the diffuse interstellar absorption bands (DIBs). In the model dealing with the interstellar spectral features, PAHs are present as a mixture of radicals, ions and neutral species. PAH ionization states reflect the ionization balance of the medium while PAH size, composition, and structure reflect the energetic and chemical history of the medium. A major challenge for laboratory astrophysics is to reproduce (in a realistic way) the physical conditions that exist in the emission and/or absorption interstellar zones, An extensive laboratory program has been developed at NASA Ames to characterize the physical and chemical properties of PAHs in astrophysical environments and to describe how they influence the radiation and energy balance in space and the interstellar chemistry. In particular, laboratory experiments provide measurements of the spectral characteristics of interstellar PAH analogs from the ultraviolet and visible range to the infrared range for comparison with astronomical data. This paper will focus on the recent progress made in the laboratory to measure the direct absorption spectra of neutral and ionized PAHs in the gas phase in the near-W and visible range in astrophysically relevant environments. These measurements provide data on PAHs and nanometer-sized particles that can now be directly compared to astronomical observations. The harsh physical conditions of the IS medium - characterized by a low temperature, an absence of collisions and strong V W radiation fields - are simulated in the laboratory by associating a molecular beam with an ionizing discharge to generate a cold plasma expansion. PAH ions are formed from the neutral precursors in an isolated environment at low temperature (of the order of 100 K). The spectra of neutral and ionized PAHs are measured using the high sensitivity methods of cavity ring down spectroscopy (CRDS). These experiments provide unique information on the spectra of free, cold large carbon molecules and ions in the gas phase. Intrinsic band profiles and band positions of cold gas-phase PAHs can now be measured with high- sensitivity spectroscopy and directly compared to the astronomical data. The electronic bands measured for ionized PAH are found to be intrinsically broad (about 20/cm) while the bands associated with the neutral precursors are narrower (of the order of 2 - 10/cm).

Salama, Farid↗

DOE OSTI2026

Generative models on phase space

Deep generative models such as diffusion and flow matching are powerful machine learning tools capable of learning and sampling from high-dimensional distributions. They are particularly useful when the training data appears to be concentrated on a submanifold of the data embedding space. For high-energy physics data, consisting of collections of relativistic energy-momentum 4-vectors, this submanifold can enforce extremely strong physically-motivated priors, such as energy and momentum conservation. If these constraints are learned only approximately, rather than exactly, this can inhibit the interpretability and reliability of such generative models. To remedy this deficiency, we introduce generative models which are, by construction, confined at every step of their sampling trajectory to the manifold of massless N-particle Lorentz-invariant phase space in the center-of-momentum frame. In the case of diffusion models, the "pure noise" forward process endpoint corresponds to the uniform distribution on phase space, which provides a clear starting point from which to identify how correlations among the particles emerge during the reverse (de-noising) process. We demonstrate that our models are able to learn both few-particle and many-particle distributions with various singularity structures, paving the way for future interpretability studies using generative models trained on simulated jet data.

Bogorad, Zachary [Fermilab]↗

DOE OSTI2012

FERMI-LAT OBSERVATIONS OF THE DIFFUSE {gamma}-RAY EMISSION: IMPLICATIONS FOR COSMIC RAYS AND THE INTERSTELLAR MEDIUM

The {gamma}-ray sky >100 MeV is dominated by the diffuse emissions from interactions of cosmic rays with the interstellar gas and radiation fields of the Milky Way. Observations of these diffuse emissions provide a tool to study cosmic-ray origin and propagation, and the interstellar medium. We present measurements from the first 21 months of the Fermi Large Area Telescope (Fermi-LAT) mission and compare with models of the diffuse {gamma}-ray emission generated using the GALPROP code. The models are fitted to cosmic-ray data and incorporate astrophysical input for the distribution of cosmic-ray sources, interstellar gas, and radiation fields. To assess uncertainties associated with the astrophysical input, a grid of models is created by varying within observational limits the distribution of cosmic-ray sources, the size of the cosmic-ray confinement volume (halo), and the distribution of interstellar gas. An all-sky maximum-likelihood fit is used to determine the X{sub CO} factor, the ratio between integrated CO-line intensity and H{sub 2} column density, the fluxes and spectra of the {gamma}-ray point sources from the first Fermi-LAT catalog, and the intensity and spectrum of the isotropic background including residual cosmic rays that were misclassified as {gamma}-rays, all of which have some dependency on the assumed diffuse emission model. The models are compared on the basis of their maximum-likelihood ratios as well as spectra, longitude, and latitude profiles. We also provide residual maps for the data following subtraction of the diffuse emission models. The models are consistent with the data at high and intermediate latitudes but underpredict the data in the inner Galaxy for energies above a few GeV. Possible explanations for this discrepancy are discussed, including the contribution by undetected point-source populations and spectral variations of cosmic rays throughout the Galaxy. In the outer Galaxy, we find that the data prefer models with a flatter distribution of cosmic-ray sources, a larger cosmic-ray halo, or greater gas density than is usually assumed. Our results in the outer Galaxy are consistent with other Fermi-LAT studies of this region that used different analysis methods than employed in this paper.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Coupled cluster and dislocation dynamics modeling of microstructure evolution in irradiated materials

We develop here a coupled cluster and dislocation dynamics framework to study the microstructure evolution of irradiated materials. The framework not only accounts for the three dimensional diffusion of radiation-generated clusters, but also their interaction with dislocation networks and the resultant climb motion of discrete dislocations within finite crystals. The framework is solved with a superposition solution scheme, and is applied to investigate the evolution of the irradiation-induced dislocation loops in zirconium (Zr), considering the effects of various bias factors including the diffusion anisotropy difference (DAD) of interstitials and interstitial clusters, the dislocation bias of defects to discrete dislocation segments, and the production bias of defects from the radiation cascade. We find that the DAD is the most critical factor influencing the kinetics of the loop evolution in Zr, while the recombination/interaction of mobile defects can induce a strong spatial dependence of the loop evolution together with the DAD. Here, the method is also adopted to study the evolution of interstitial $\langle$a$\rangle$ and vacancy $\langle$c$\rangle$ dislocation loop ensembles consistent with the microstructure observed during irradiation-induced growth of Zr. Our findings not only reveal the spatial dependence of the size and ellipticity of the dislocation loops, but also suggest a limit on the anisotropy factor of interstitials to reproduce the co-growth of $\langle$a$\rangle$ and $\langle$c$\rangle$ loops in zirconium, in good agreement with experimental observations and other simulation results.

Bias factors↗

DOE OSTI2022

Charge sharing in pixelated semiconductor sensors

The charge sharing between neighboring pixels in pixelated sensors can be used to measure particle or x-ray coordinates with accuracy better than the pixel pitch. The accurate model of the charge distribution shape is essential to achieve ultimate coordinate accuracy. The charge sharing is caused by charge carriers' diffusion on the path from the generation point to pixels. This paper is focused on the diffusion of the initially compact charge cloud in the field free region. The diffusion equation solutions are obtained using separation of variable and Fourier synthesis method for different initial conditions and resulting charge distributions are integrated over pixel areas. In conclusion, the look up table containing pre-calculated values for pixel charge fractions is proposed to speed up numerical calculations.

47 OTHER INSTRUMENTATION↗

DOE OSTI2019

Governing Constraints of Chromium(VI) Formation from Chromium(III)-Bearing Minerals in Soils and Sediments

The potential for geogenic Cr(VI) contamination is vast, yet it is difficult to predict susceptible environments as groundwater Cr(VI) concentrations vary significantly, even within a given aquifer, due to physical and hydrologic heterogeneity. The physical structure of soils and sediments exerts a dominant control on Cr(VI) production by dictating the separation distance of reactive phases, the diffusion distance from Cr(VI) generation sites to advecting groundwater, and by influencing infiltration rates and porewater velocity. Here, we used a dual-pore domain model to investigate the relative control of these parameters on Cr(VI) production. The reaction distance between Cr(III)-bearing minerals and Mn oxides predominantly controls Cr(VI) export to advecting groundwater, while changes in diffusion distance between sites of Cr(VI) generation and advective flow channels generally have little impact on steady-state Cr(VI) concentrations. Changes in Cr(VI) diffusion distance can, however, increase the time required for groundwater Cr(VI) concentrations to reach a steady-state; thus, under fluctuating hydrologic and biogeochemical conditions, long diffusion distances still have the potential to suppress Cr(VI) supply to advecting water. Furthermore, we show that high porewater flow velocities effectively dilute Cr(VI) diffusing from soil/sediment aggregates, thus minimizing Cr(VI) concentrations relative to lower porewater velocities. The strong control that the physical/hydrologic parameters exert on Cr(VI) production appears to overwhelm the impact of Cr(III)-mineral solubility within soils and sediments.

Hausladen, Debra (ORCID:0000000342356294)↗

DOE OSTI2014

Investigation of particle diffusion and suprathermal electrons in a magnetized helium plasma column

Studying radiative properties of magnetized helium plasma via high-resolution spectroscopy identified close correlations between the particle diffusion and suprathermal electrons for different modes of operation of the MISTRAL installation. The standard diagnostic emission lines in neutral helium (1s3d {sup 3}D-1s2p {sup 3}P, 1s3s {sup 3}S-1s2p {sup 3}P, 1s3d {sup 1}D-1s2p {sup 1}P, and 1s3s {sup 1}S-1s2p {sup 1}P) show anomalous ratios that are related to enhanced particle diffusion and suprathermal electron generation. The supplementary investigation of singlet/triplet Rydberg series (transitions 1snd {sup 3}D-1s2p {sup 3}P and 1s5p {sup 1}P-1s2s {sup 1}S) as well as ionic lines (HeII, transitions n = 3–4 at 469 nm and n = 4–6 at 656 nm) allowed quantitative characterization. Simulations carried out with the atomic physics code SOPHIA demonstrate that simultaneous implementation of diffusion processes and suprathermal electrons matches all experimental findings. Single consideration, however, of either diffusion or hot electrons is in contradiction to the proposed extended set of HeI and HeII emission lines. The high precision achieved with the LSJ-split level structure of SOPHIA coupled to Langmuir probe measurements allowed to conclude to a Bohm type diffusion in MISTRAL.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2016

Radio galaxies dominate the high-energy diffuse gamma-ray background

It has been suggested that unresolved radio galaxies and radio quasars (sometimes referred to as misaligned active galactic nuclei) could be responsible for a significant fraction of the observed diffuse gamma-ray background. In this study, we use the latest data from the Fermi Gamma-Ray Space Telescope to characterize the gamma-ray emission from a sample of 51 radio galaxies. In addition to those sources that had previously been detected using Fermi data, we report here the first statistically significant detection of gamma-ray emission from the radio galaxies 3C 212, 3C 411, and B3 0309+411B. Combining this information with the radio fluxes, radio luminosity function, and redshift distribution of this source class, we find that radio galaxies dominate the diffuse gamma-ray background, generating 77.2(+25.4)(-9.4)% of this emission at energies above ~1 GeV . We discuss the implications of this result and point out that it provides support for scenarios in which IceCube's high-energy astrophysical neutrinos also originate from the same population of radio galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

Conditional distribution estimation of building characteristics with diffusion models for urban energy modeling

Understanding current energy consumption behavior in communities is critical for informing future energy use decisions and enabling efficient energy management. Urban energy models, which are used to simulate these energy use patterns, require large datasets with detailed building characteristics for accurate outcomes. However, such detailed characteristics at the individual building level are often unknown and costly to acquire, or unavailable. Through this work, we propose using a generative modeling approach to generate realistic building attributes to fill in the data gaps and finally provide complete characteristics as inputs to energy models. Our model learns complex, building-level patterns from training on a large-scale residential building stock model containing 2.2 million buildings. We employ a tabular diffusion-based framework that is designed to handle heterogeneous (discrete and continuous) features in tabular building data, such as occupancy, floor area, heating, cooling, and other equipment details. We develop a capability for conditional diffusion, enabling the imputation of missing building characteristics conditioned on known attributes. We conduct a comprehensive validation of our conditional diffusion model, firstly by comparing the generated conditional distributions against the underlying data distribution, and secondly, by performing a case study for a Baltimore residential region, showing the practical utility of our approach. Our work is one of the first to demonstrate the potential of generative modeling to accelerate building energy modeling workflows.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Generative AI for design of nanoporous materials: review and future prospects

Generative artificial intelligence (AI) is emerging as a powerful tool for advancing the design of nanoporous materials such as metal–organic frameworks, covalent–organic frameworks, and zeolites. These materials have potential application in important areas such as carbon capture, catalysis, gas storage, chemical separation, and drug delivery due to their modular, tunable structures, and their performance in these areas depends on precise control over their structure, chemical functionalities, and properties. Herein, we provide a review of generative AI algorithms that are emerging as powerful tools for the design of nanoporous materials, namely generative adversarial networks, variational autoencoders, diffusion models, genetic algorithms, reinforcement learning, and large language models. Some models are particularly good at generating diverse and high-quality designs, while others excel at exploring large design spaces or optimizing materials with desired properties. Certain algorithms also allow for efficient transitions between different designs, and some offer versatility in generating materials based on textual input. We discuss the advantages, limitations, and applications of these algorithms in porous material design and emphasize the future potential of integrating AI with experimental workflows to accelerate the development and validation of AI-generated materials.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Hybrid learning techniques for scientific data reduction with performance guarantees

The research initiatives supported by the U.S. Department of Energy (DOE) Grant DE-SC0022265 are fundamentally aimed at pioneering advanced machine learning (ML) techniques for scientific data compression within high-performance computing (HPC) environments. This comprehensive body of work addresses the critical challenge posed by the exponential growth of data generated by scientific simulations in domains such as fusion energy, climate modeling, and computational fluid dynamics (CFD). A core objective is to develop compression algorithms that achieve substantial data reduction—often by orders of magnitude—while rigorously ensuring the fidelity of both the primary data (PD) and scientifically crucial derived quantities of interest (QoI). The methodologies deployed under this grant integrate sophisticated deep learning architectures, prominently featuring autoencoders, advanced generative models like conditional diffusion, and hybrid learning techniques. Key innovations include the development of Guaranteed Autoencoders (GAE) and the Guaranteed Conditional Diffusion with Tensor Correction (GCDTC) framework, which provide explicit, instance-level error bounds on reconstructed data. Furthermore, specialized strategies such as nonlinear constraint satisfaction are employed to preserve the integrity of QoI, a vital requirement for the trustworthiness of downstream scientific analyses. This research also focuses on the design and implementation of scalable, GPU-accelerated software pipelines that seamlessly integrate into existing HPC workflows, ensuring both computational efficiency and practical applicability. The CAESAR framework, for example, unifies foundation and generative models to create an adaptive and efficient compression solution for spatio-temporal scientific data. Collectively, these efforts represent a significant advancement in mitigating the scientific data deluge, enabling more effective data management, accelerated scientific discovery, and optimized utilization of HPC resources.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Final report- UFL - RAPIDS2: A SciDAC Institute for Computer Science, Data, and Artificial Intelligence

97 MATHEMATICS AND COMPUTING↗