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Results for “generative diffusion”

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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Analysis and experimental study on formation conditions of large-scale barrier-free diffuse atmospheric pressure air plasmas in repetitive pulse mode

Atmospheric air diffuse plasmas have enormous application potential in various fields of science and technology. Without dielectric barrier, generating large-scale air diffuse plasmas is always a challenging issue. This paper discusses and analyses the formation mechanism of cold homogenous plasma. It is proposed that generating stable diffuse atmospheric plasmas in open air should meet the three conditions: high transient power with low average power, excitation in low average E-field with locally high E-field region, and multiple overlapping electron avalanches. Accordingly, an experimental configuration of generating large-scale barrier-free diffuse air plasmas is designed. Based on runaway electron theory, a low duty-ratio, high voltage repetitive nanosecond pulse generator is chosen as a discharge excitation source. Using the wire-electrodes with small curvature radius, the gaps with highly non-uniform E-field are structured. Experimental results show that the volume-scaleable, barrier-free, homogeneous air non-thermal plasmas have been obtained between the gap spacing with the copper-wire electrodes. The area of air cold plasmas has been up to hundreds of square centimeters. The proposed formation conditions of large-scale barrier-free diffuse air plasmas are proved to be reasonable and feasible.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
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 OSTI2025

Harnessing emergent multiple scattering resonances in a photonic glass structure for photoelectrochemical energy conversion

Light trapping nanostructures are often necessary to improve carrier collection yields in semiconductor photoelectrodes with intrinsically poor electron transport. Photonic crystal templates can generate tailorable light trapping via periodic and precise nanostructure, though this is not a scalable strategy for photoelectrochemical (PEC) applications. It is therefore critical to identify alternative mechanisms for light trapping that tolerate disorder. Light trapping in disordered media is generated by the diffusive transport caused by multiple scattering. In some cases, multiple scattering can generate resonances that resemble those observed in photonic crystals. While resonant multiple scattering is a disorder tolerant light trapping mechanism, it is unclear if the effect is sufficiently adaptable, or even useful, for PEC applications. Here, we describe a photonic omission glass, a nanostructure that can controllably induce resonances in multiple scattering transport. We characterized the emergence of these resonances after coating a disordered SiO 2 colloidal structure with a layer of TiO 2 , which functions both as dielectric contrast and as a light absorbing semiconductor. We show in finite element simulations and spectroscopic characterization that the resonant multiple scattering effect improves light trapping near the interface between the structure and the bulk electrolyte. This effect, coupled with the increased electrochemically active surface area, results in a hierarchically structured TiO 2 photoanode with orders of magnitude higher photocurrents compared to an equivalent planar photoanode for PEC reactions such as alkaline water oxidation. We show that controlling this resonant multiple scattering effect can be advantageous for improving PEC energy conversion in disordered photoelectrodes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Linking pore-scale and basin-scale effects on diffusive methane transport in hydrate bearing environments through multi-scale reservoir simulations

We explore the gas hydrate-generating capacity of diffusive methane transport induced by solubility gradients due to pore size contrasts in lithologically heterogeneous marine sediments. Through the use of 1D, 2D, and 3D reactive transport simulations, we investigate scale-dependent processes in diffusion-dominated gas hydrate systems. These simulations all track a sand body, or series of sands, surrounded by clays as they are buried through the gas hydrate stability zone. Methane is sourced by microbial methanogenesis in the clays surrounding the sand layers. In 1D, simulations performed in a Lagrangian reference frame demonstrate that gas hydrate in thin sands (3.6 m thick) can occur in high saturations (upward of 70%) at the edges of sand bodies within the upper 400 meters below the seafloor. Diffusion of methane toward the center of the sand layer depends on the concentration gradient within the sand: broader sand pore size distributions with smaller median pore sizes enhance diffusive action toward the sand’s center. Incorporating downhole log- and laboratory-derived sand pore size distributions, gas hydrate saturations in the center of the sand can reach 20% of the hydrate saturations at the sand’s edges. Furthermore, we show that hydrate-free zones exist immediately above and below the sand and are approximately 5 m thick, depending on the sand-clay solubility contrast. A moving reference frame is also adopted in 2D, and the angle of gravity is rotated relative to the grid system to simulate a dipping sand layer. This is important to minimize diffusive edge effects or numerical diffusion that might be associated with a dipping sand in an Eulerian grid system oriented orthogonal to gravity. Two-dimensional simulations demonstrate the tendency for gas hydrate to accumulate downdip in a sand body because of greater methane transport at depth due to larger sand-clay solubility contrasts. In 3D, basin-scale simulations illuminate how convergent sand layers in a multilayered system can compete for diffusion from clays between them, resulting in relatively low hydrate saturations. All simulations suggest that when hydrate present in clays dissociates with burial, the additional dissolved methane is soaked up by nearby sands preserving high hydrate saturations.

Nole, Michael↗
DOE OSTI2018

Kinetics of Transformation of Al{sub 2}O{sub 3} to MgO·Al{sub 2}O{sub 3} Spinel Inclusions in Mg-Containing Steel

During ladle furnace refining, initial Al{sub 2}O{sub 3} inclusions generally transform into MgO·Al{sub 2}O{sub 3} spinel inclusions; these generated spinel inclusions consequently deteriorate the product quality. In this study, the transformation from Al{sub 2}O{sub 3} to MgO·Al{sub 2}O{sub 3} was investigated by immersing an Al{sub 2}O{sub 3} rod into molten steel, which was in equilibrium with both MgO and MgO·Al{sub 2}O{sub 3} spinel-saturated slag. A spinel layer, with a thickness of 4 μm, was generated on the Al{sub 2}O{sub 3} rod surface just 10 s after its immersion at 1873 K (1600 °C). The thickness of the formed spinel layer increased with the immersion period and temperature. Moreover, the MgO content of the generated spinel layer also increased with the immersion period. In this study, the chemical reaction rate at 1873 K (1600 °C) was assumed to be sufficiently high, and only diffusion was considered as a rate-controlling step for this transformation. By evaluating the activation energy, MgO diffusion in the generated spinel layer was found to be the rate-controlling step. In addition, this estimation was confirmed by observing the Mg and Al concentration gradients in the generated spinel layer. The results of this study suggest that the MgO diffusion in the spinel inclusions plays a substantial role with regard to their formation kinetics.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Simulations of ion acceleration at non-relativistic shocks. III. Particle diffusion

We use large hybrid (kinetic-protons-fluid-electrons) simulations to investigate the transport of energetic particles in self-consistent electromagnetic configurations of collisionless shocks. In previous papers of this series, we showed that ion acceleration may be very efficient (up to 10%-20% in energy), and outlined how the streaming of energetic particles amplifies the upstream magnetic field. Here, we measure particle diffusion around shocks with different strengths, finding that the mean free path for pitch-angle scattering of energetic ions is comparable with their gyroradii calculated in the self-generated turbulence. For moderately strong shocks, magnetic field amplification proceeds in the quasi-linear regime, and particles diffuse according to the self-generated diffusion coefficient, i.e., the scattering rate depends only on the amount of energy in modes with wavelengths comparable with the particle gyroradius. For very strong shocks, instead, the magnetic field is amplified up to non-linear levels, with most of the energy in modes with wavelengths comparable to the gyroradii of highest-energy ions, and energetic particles experience Bohm-like diffusion in the amplified field. We also show how enhanced diffusion facilitates the return of energetic particles to the shock, thereby determining the maximum energy that can be achieved in a given time via diffusive shock acceleration. The parameterization of the diffusion coefficient that we derive can be used to introduce self-consistent microphysics into large-scale models of cosmic ray acceleration in astrophysical sources, such as supernova remnants and clusters of galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Flow matching meets biology and life science: a survey

Over the past decade, advances in generative modeling, such as generative adversarial networks, masked autoencoders, and diffusion models, have significantly transformed biological research and discovery, enabling breakthroughs in molecule design, protein generation, catalysis discovery, drug discovery, and beyond. At the same time, biological applications have served as valuable testbeds for evaluating the capabilities of generative models. Recently, flow matching has emerged as a powerful and efficient alternative to diffusion-based generative modeling, with growing interest in its application to problems in biology and life sciences. This paper presents the first comprehensive survey of recent developments in flow matching and its applications in biological domains. We begin by systematically reviewing the foundations and variants of flow matching, and then categorize its applications into three major areas: biological sequence modeling, molecule generation and design, and peptide and protein generation. For each, we provide an in-depth review of recent progress. We also summarize commonly used datasets and software tools, and conclude with a discussion of potential future directions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Stress and Diffusion in Stored Pu ZPPR Fuel from Alpha Generation

ZPPR (Zero Power Physics Reactor) is a research reactor that has been used to investigate breeder reactor fuel designs. The reactor has been dismantled but its fuel is still stored there. Of concern are its plutonium containing metal fuel elements which are enclosed in stainless steel cladding with gas space filled with helium–argon gas and welded air tight. The fuel elements which are 5.08 cm by 0.508 cm up to 20.32 cm long (2 in × 0.2 in × 8 in) were manufactured in 1968. A few of these fuel elements have failed releasing contamination raising concern about the general state of the large number of other fuel elements. Inspection of the large number of fuel elements could lead to contamination release so analytical studies have been conducted to estimate the probability of failed fuel elements. This paper investigates the possible fuel failures due to generation of helium in the metal fuel from the decay of Pu and its possible damage to the fuel cladding from metal fuel expansion or from diffusion of helium into the fuel gas space. This paper (1) calculates the initial gas loading in a fuel element and its internal free volume after it has been brought into the atmosphere at ZPPR, (2) shows that the amount of helium generated by decay of Pu over 46 years since manufacture is significantly greater than this initial loading, (3) determines the amount of fuel swelling if the helium stays fixed in the fuel plate and estimates the amount of helium which diffuses out of the fuel plate into the fuel plenum assuming the helium does not remain fixed in the fuel plate but can diffuse to the plenum and possibly through the cladding. Since the literature is not clear as to which possibility occurs, as with Schroedinger’s cat, both possibilities are analyzed. The paper concludes that (1) if the gas generated is fixed in the fuel, then the fuel swelling it can cause would not cause any fuel failure and (2) if the helium does diffuse out of the fuel (in accordance diffusivities estimated from the literature), then it is unlikely that fuel element bulging will occur.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2019

Simulated Contrast of Two Dislocations

A three-dimensional Monte Carlo simulation algorithm is used to study the contrast of two dislocations perpendicular to the irradiated surface of an n-doped silicon sample in the electron beam induced current mode. The dislocations are positioned in the irradiation trajectory, and each of both is considered as a cylinder where the minority carrier diffusion length varies abruptly from a low inside dislocations up to a high value outside dislocations. The EBIC contrast was obtained by simulating the random diffusion of carriers generated at point-like sources randomly distributed within the generation volume. Results are analyzed on the basis of change in the generation volume in the bulk of the sample and of carrier trapping process inside dislocations. The EBIC contrast increases with the increase of the electron beam energy. It also increases when the minority diffusion length inside dislocations, or their separating distance decreases.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

Simulation of space charge compensation in a multibeamlet negative ion beam

Ion beam space charge compensation occurs by cumulating in the beam potential well charges having opposite polarity, usually generated by collisional processes. In this paper we investigate the case of a H{sup −} ion beam drift, in a bi-dimensional approximation of the NIO1 (Negative Ion Optimization phase 1) negative ion source. H{sup −} beam ion transport and plasma formation are studied via particle-in-cell simulations. Differential cross sections are sampled to determine the velocity distribution of secondary particles generated by ionization of the residual gas (electrons and slow H{sub 2}{sup +} ions) or by stripping of the beam ions (electrons, H, and H{sup +}). The simulations include three beamlets of a horizontal section, so that multibeamlet space charge and secondary particle diffusion between separate generation regions are considered, and include a repeller grid biased at various potentials. Results show that after the beam space charge is effectively screened by the secondary plasma in about 3 μs (in agreement with theoretical expectations), a plasma grows across the beamlets with a characteristic time three times longer, and a slight overcompensation of the electric potential is verified as expected in the case of negative ions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Generative AI models for learning flow maps of stochastic dynamical systems in bounded domains

Simulating stochastic differential equations (SDEs) in bounded domains, presents significant computational challenges due to particle exit phenomena, which requires accurate modeling of interior stochastic dynamics and boundary interactions. Despite the success of machine learning-based methods in learning SDEs, existing learning methods are not applicable to SDEs in bounded domains because they cannot accurately capture the particle exit dynamics. We present a unified hybrid data-driven approach that combines a conditional diffusion model with an exit prediction neural network to capture both interior stochastic dynamics and boundary exit phenomena. Our ML model consists of two major components: a neural network that learns exit probabilities using binary cross-entropy loss with rigorous convergence guarantees, and a training-free diffusion model that generates state transitions for non-exiting particles using closed-form score functions. The two components are integrated through a probabilistic sampling algorithm that determines particle exit at each time step and generates appropriate state transitions. Here, the performance of the proposed approach is demonstrated via three test cases: a one-dimensional simplified problem for theoretical verification, a two-dimensional advection-diffusion problem in a bounded domain, and a three-dimensional problem of interest to magnetically confined fusion plasmas.

Bounded domains↗
DOE OSTI2012

Data from HANE-Generated Radiation Belts and the Origin of Diffusion Theory [Slides]

In this presentation we briefly review some of the published data regarding the artificial radiation belts produced by the Starfish and R2 high altitude nuclear explosions in 1962. The data showed slow temporal variations of the belts in altitude (L) and pitch angle ({alpha}) that could be modeled as a diffusion process. That early work formed the basis for more complex radiation belt diffusion models that are in use at present.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2014

Dynamic Surface Tension and Diffusivity Measurements of NG-CSSX Next Generation Solvent

Since 2008, the Savannah River Site has processed more than four million gallons of radioactive supernatant. To continue compliance with downstream processes, MCU is switching to the improved solvent called Next Generation Solvent (NG-CSSX). The new solvent formulation promises higher cesium removal efficiency and laboratory testing suggests the potential of higher processing rates. Similarly, laboratory testing demonstrated improvements in separation of the solvent from the effluent aqueous streams. To complete implementation at MCU, additional work was needed to develop methods that can measure physical properties relevant to the performance of the new solvent. This work measures two relevant physical properties: static interfacial tension and diffusvity. Both properties play a relevant role in mixing and separating immiscible liquids. This work evaluated the impact of changes in composition or aqueous phase on these physical properties to gauge the sensitivity of the system to the losses of chemical components.

Fondeur, F. F.↗
DOE OSTI2025

Latent diffusion can map beam loss to two-dimensional phase-space projections

Beam loss monitors (BLMs) and beam current monitors (BCMs) are ubiquitous at particle accelerators around the world. These simple devices provide noninvasive high-level beam measurements but give no insight into the detailed 6D (𝑥,𝑦,𝑧,𝑝 𝑥 ,𝑝 𝑦 ,𝑝 𝑧 ) beam phase-space distributions or dynamics. We show that generative conditional latent diffusion models can learn intricate patterns to solve the extreme inverse problem of mapping waveforms of tens of BLMs or BCMs along an accelerator to detailed 2D projections of a charged particle beam’s 6D phase-space density. This transformational method can be used at any particle accelerator to transform simple noninvasive devices into detailed beam phase-space diagnostics. We demonstrate this concept via multiparticle simulations of the high-intensity beam in the kilometer-long Los Alamos Neutron Science Center linear proton accelerator.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Field-level reconstruction from foreground-contaminated 21-cm maps

Current and upcoming 21-cm experiments will soon be able to map 21-cm spatial fluctuations in three dimensions for a wide range of redshifts. However, bright foreground contamination and the nature of radio interferometry create significant challenges, making it difficult to access rich cosmological information from the Fourier modes that lie within the “foreground wedge”. Here, in this work, we introduce two approaches aiming to reconstruct the full 21-cm density field, including the missing modes in the wedge: (a) a field-level inference under an effective field theory (EFT) framework; (b) a diffusion-based deep generative model trained on simulations. Under the EFT framework, we implement a fully differentiable forward model that maps the initial conditions of matter fluctuations to the observed, foreground-filtered 21-cm maps. This enables a gradient-based sampler to simultaneously sample the initial conditions and bias parameters, allowing a physically motivated mode reconstruction. Alternatively, we apply a variational diffusion model to perform 21-cm density reconstruction at the map level. Our model is trained on semi-numerical simulations over a wide range of astrophysical parameters. Our results from both approaches should provide improved cosmological constraints from the field level and also enable cross-correlation between experiments that have little or no overlapping modes.

cosmological perturbation theory↗
DOE OSTI2014

Computational studies for plasma filamentation by magnetic field in atmospheric microwave discharge

Plasma filamentation is induced by an external magnetic field in an atmospheric discharge using intense microwaves. A discrete structure is obtained at low ambient pressure if a strong magnetic field of more than 1 T is applied, due to the suppression of electron diffusion, whereas a diffusive pattern is generated with no external field. Applying a magnetic field can slow the discharge front propagation due to magnetic confinement of the electron transport. If the resonance conditions are satisfied for electron cyclotron resonance and its higher harmonics, the propagation speed increases because the heated electrons easily ionize neutral particles. The streamer velocity and the pattern of the microwave plasma are positively controlled by adjusting two parameters—the electron diffusion coefficient and the ionization frequency—through the resonance process and magnetic confinement, and hot, dense filamentary plasma can be concentrated in a compact volume to reduce energy loss in a plasma device like a microwave rocket.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗