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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

THE COSMIC BATTERY IN ASTROPHYSICAL ACCRETION DISKS

The aberrated radiation pressure at the inner edge of the accretion disk around an astrophysical black hole imparts a relative azimuthal velocity on the electrons with respect to the ions which gives rise to a ring electric current that generates large-scale poloidal magnetic field loops. This is the Cosmic Battery established by Contopoulos and Kazanas in 1998. In the present work we perform realistic numerical simulations of this important astrophysical mechanism in advection-dominated accretion flows, ADAFs. We confirm the original prediction that the inner parts of the loops are continuously advected toward the central black hole and contribute to the growth of the large-scale magnetic field, whereas the outer parts of the loops are continuously diffusing outward through the turbulent accretion flow. This process of inward advection of the axial field and outward diffusion of the return field proceeds all the way to equipartition, thus generating astrophysically significant magnetic fields on astrophysically relevant timescales. We confirm that there exists a critical value of the magnetic Prandtl number between unity and 10 in the outer disk above which the Cosmic Battery mechanism is suppressed.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2011

DISSIPATION AND VERTICAL ENERGY TRANSPORT IN RADIATION-DOMINATED ACCRETION DISKS

Standard models of radiation-supported accretion disks generally assume that diffusive radiation flux is solely responsible for vertical heat transport. This requires that heat must be generated at a critical rate per unit volume if the disk is to be in hydrostatic and thermal equilibrium. This raises the question of how heat is generated and how energy is transported in MHD turbulence. By analysis of a number of radiation/MHD stratified shearing-box simulations, we show that the divergence of the diffusive radiation flux is indeed capped at the critical rate, but deep inside the disk, substantial vertical energy flux is also carried by advection of radiation. Work done by radiation pressure is a significant part of the energy budget, and much of this work is dissipated later through damping by radiative diffusion. We show how this damping can be measured in the simulations and identify its physical origins. Radiative damping accounts for as much as tens of percent of the total dissipation and is the only realistic physical mechanism for dissipation of turbulence that can actually be resolved in numerical simulations of accretion disks. Buoyancy associated with dynamo-driven, highly magnetized, nearly isobaric nonlinear slow magnetosonic fluctuations is responsible for the radiation advection flux and also explains the persistent periodic magnetic upwelling seen at all values of the radiation to gas pressure ratio. The intimate connection between radiation advection and magnetic buoyancy is the first example we know of in astrophysics in which a dynamo has direct impact on the global energetics of a system.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

DRACO: An Overview [Slides]

DRACO (Diffusion ReACtiOn) is a diffusion and chemistry code designed to: 1) Operate on 3D with an unstructured grid defining an arbitrary geometry of interacting parts. 2) Generate its own meshes and use meshes created by other software. 3)Model the transport of any number of diffusing quantities: Concentrations, pressures, temperature, etc. 4) Allow diffusion coefficients to depend in an arbitrary way on concentration, temperature, position, time, etc. 5) Model general chemistry between concentrations with arbitrary reaction rates. 6) Allow arbitrary initial conditions, boundary conditions, and sources/sinks. 7) Allow all of the above to be specified by the user.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Prediction of vacancy defect diffusion paths in high entropy alloys via machine learning on molecular dynamics data

Identifying the diffusion path of point defects is a critical step in understanding their evolution and the mechanisms of related phenomena. Defect diffusion occurs at small length and time scales, with impacts on material properties that may continue to evolve over ns to μs, ms, and the continuum scale (s, min, etc., and cm, m, etc.). The time scale accessible to molecular dynamics (MD) simulations is limited by small step sizes, typically in the fs range. Thus, surrogate models of MD simulations through machine learning (ML)-based algorithms are of great interest, especially for complex systems such as high entropy alloys (HEAs). In this work, dynamics governing vacancy migration in HEA were approximated with graph convolutional network (GCN) models as ansatzes for kinetic Monte Carlo (KMC) rate catalogs. Network design considered that diffusion in crystalline solids generally depends on interactions between defects and their immediate neighbor atoms. Graphs represented the vacancy surroundings, MD-generated trajectories provided training and comparison datasets, and unsupervised GCN models approximated interatomic dynamics governing vacancy migration in HEAs as ansatzes for KMC. A proof-of-concept model trained on MD data for the Fe, Ni, Cr, Co, and Cu HEA environment was used with two different neighbor interactions to assess the feasibility of training a GCN to predict vacancy defect transition rates in the HEA environment. The resulting setup rapidly generated MD-formatted synthetic trajectories based on dynamics learned from the MD training set, with a time acceleration of roughly two orders of magnitude and a similar diffusion coefficient to MD observations. Additionally, Nudged Elastic Band (NEB) calculations were performed on randomly generated FeNiCrCoCu HEA structures to determine vacancy migration barriers across nearest-neighbor sites. Transition probabilities for each jump, categorized by atomic type, were extracted from these calculations. NEB-based and GCN-based approaches led to similar outcomes.

Reimer, C↗
NASA NTRS1983

Numerical experiments with a stochastic zonal climate model

A zonally averaged energy balance climate model is developed to generate zonal temperature variability through fluctuating meridional energy transports. Stochastic transport fluctuations are included in the model by multiplying the eddy diffusion coefficients by Gaussian random deviates. For a variability of eddy coefficients of 50 percent, the model is found to generate an interannual temperature variability of 0.03 K for the global temperature, and 0.04 and 0.05 K for the Northern and Southern Hemispheres, respectively. It is shown that the temperature variability level generated is linearly related to the transport variability level introduced. An increase in the level of model-generated temperature variability and a change in the shape of variance spectra of temperature anomaly time series are obtained by switching from the multiplicative noise model to an additive noise model. The results of these model studies are compared with a time series of central England temperatures as well as GCM generated climate variability.

Schneider, S. H.↗
DOE OSTI2024

Effectiveness of denoising diffusion probabilistic models for fast and high-fidelity whole-event simulation in high-energy heavy-ion experiments

Artificial intelligence (AI) generative models, such as generative adversarial networks (GANs), variational autoencoders, and normalizing flows, have been widely used and studied as efficient alternatives for traditional scientific simulations. However, they have several drawbacks, including training instability and inability to cover the entire data distribution, especially for regions where data are rare. This is particularly challenging for whole-event, full-detector simulations in high-energy heavy-ion experiments, such as sPHENIX at the Relativistic Heavy Ion Collider and Large Hadron Collider experiments, where thousands of particles are produced per event and interact with the detector. This work investigates the effectiveness of denoising diffusion probabilistic models (DDPMs) as an AI-based generative surrogate model for the sPHENIX experiment that includes the heavy-ion event generation and response of the entire calorimeter stack. DDPM performance in sPHENIX simulation data is compared with a popular rival, GANs. Results show that both DDPMs and GANs can reproduce the data distribution where the examples are abundant (low-to-medium calorimeter energies). Nonetheless, DDPMs significantly outperform GANs, especially in high-energy regions where data are rare. Additionally, DDPMs exhibit superior stability compared to GANs. The results are consistent between both central and peripheral centrality heavy-ion collision events. Moreover, DDPMs offer a substantial speedup of approximately a factor of 100 compared to the traditional Geant4 simulation method.

42 ENGINEERING↗
DOE OSTI2022

Spontaneous carrier generation and low recombination in high-efficiency non-fullerene solar cells

The current research reveals the unique photo physical properties and carrier generation mechanisms of high efficiency non-fullerene acceptor-based organic photovoltaic blends. The analysis of device performance, morphology, and photo physics reveals that the interface carrier generation cannot support the device's current output. It is seen that primary photon excitons can dissociate into charge carriers in Y6, which displays a time scale of ∼0.3 ps with polaron yields above 28% in neat and blended thin films. This characteristic in combination with a large exciton diffusion length enables high morphology tolerance in Y6-overloaded blends. The carrier generation process is also combined with recombination studies. The recombination rate quantified by flux-dependent transient absorption measurements yields less than 5% total recombination and nearly 0% geminate recombination. Furthermore, these results define the advantages of the Y6 non-fullerene acceptor (NFA) and reveal the fundamental importance of developing new NFA materials with superior photo physical properties.

14 SOLAR ENERGY↗
NASA NTRS1978

Use of coherence and phase data between two receivers in evaluation of noise environments

For certain types of noise control problems, where transducers cannot be mounted on suspected sources, valuable information can often be obtained by comparing the coherence and phase data measured between two closely spaced microphones with analytical models deduced from the physics of the problem. However, the application of such analysis techniques must be pursued with care, particularly when the measurements are made in a reverberant area. A simple illustration is presented where the acoustic field in the test section of a wind tunnel is evaluated by modelling the field as a combination of diffuse noise due to the boundary layer turbulence in the test section and propagating noise generated by the tunnel fan and possible flow disturbances outside the test section. The coherence and phase between two closely spaced microphones in the tunnel test section are predicted for various ratios of diffuse to propagating noise contributions and compared to actual measurements under several different tunnel operating conditions.

Piersol, A. G.↗
DOE OSTI2012

Kinetic Monte Carlo Study of Ambipolar Lithium Ion and Electron–Polaron Diffusion into Nanostructured TiO2

Nanostructured titania (TiO2) polymorphs have proved to be promising electrode materials for next generation lithium-ion batteries. However, there is still a lack of understanding of the fundamental microscopic processes that control charge transport in these materials. Here we present microscopic simulations of the collective dynamics of lithium-ion (Li+) and charge compensating electron polarons (e-) in rutile TiO2 nanoparticles in contact with idealized conductive matrix and electrolyte. Kinetic Monte Carlo simulations are used, parameterized by molecular dynamics-based predictions of activation energy barriers for Li+ and e- diffusion. Simulations reveal the central role of electrostatic coupling between Li+ and e- on their collective drift diffusion at the nanoscale. They also demonstrate that high contact area between conductive matrix and rutile nanoparticles leads to undesirable coupling-induced surface saturation effects during Li+ insertion, which limits the overall capacity and conductivity of the material. These results help provide guidelines for design of nanostructured electrode materials with improved electrochemical performance.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

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↗
DOE OSTI2025

Measurement of Zero-Frequency Fluctuations Generated by Coupling between Alfvén Modes in the JET Tokamak

We report the first experimental detection of a zero-frequency fluctuation that is pumped by an Alfvén mode in a magnetically confined plasma. Core-localized Alfvén modes of frequency inside the toroidicity-induced gap (and its harmonics) exhibit three-wave coupling interactions with a zero-frequency fluctuation. The observation of the zero-frequency fluctuation is consistent with theoretical and numerical predictions of zonal modes pumped by Alfvén modes, and is correlated with an increase in the deep core ion temperature, temperature gradient, confinement factor H 89,P , and a reduction in the main ion heat diffusivity. Despite the energetic particle transport induced by the Alfvén eigenmodes, the generation of a zero-frequency fluctuation that can suppress the turbulence leads to an overall improvement of confinement.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1998

The Origin and Time Dependence of the Amount and Composition of Non-Constituent Gases Present in Crystal Growth Systems

Presence of different, non-constituent gases may be a critical factor in crystal growth systems. In Physical Vapor Transport processes the cras(es) can be used intentionally (to prevent excessively high, unstable growth conditions), or can evolve unintentionally during the course of the process (which may lead to undesired reduction in the -rowth rate). In melt growth, particularly under low gravity conditions (reduced hydrostatic pressure) the gas present in the system may contribute to formation of voids in the growing crystals and even to a separation of the crystal and the liquid phase [1]. On the other hand, some amount of gas may facilitate 'contactless' crystal growth particularly under reduced gravity conditions [2 - 6]. Different non-constituent gases may be present in growth ampoules, and their amount and composition may change during the crystallization process. Some gases can appear even in empty ampoules sealed originally under high vacuum: they may diffuse in from the outside, and/or desorb from the ampoule walls. Residual gases can also be generated by the source materials: even very high purity commercial elements and compounds may contain trace amounts of impurities, particularly oxides. The oxides may have low volatilities themselves but their reaction with other species, particularly carbon and hydrogen, may produce volatile compounds like water or carbon oxides. The non-constituent gases, either added initially to the system or evolved during the material processing, may diffuse out of the ampoule during the course of the experiment. Gases present outside (e.g. as a protective atmosphere or thermal conductor) may diffuse into the ampoule. In either case the growth conditions and the quality of the crystals may be affected. The problem is of a particular importance in sealed systems where the amount of the gases cannot be directly controlled. Therefore a reasonable knowledge and understanding of the origin, composition, magnitude, and change with time of gases present in sealed ampoules may be important for a meaningful control and interpretation of crystal growth processes. This problem is of a particular importance for processing of electronic materials in space because (i) safety considerations require using sealed systems only, and (ii) high cost of crystal growth experiments in microgravity calls for a throughout, accurate description of the processing conditions necessary for a meaningful, efficient, and conclusive interpretation of the space results. In this paper we present the results of our extensive studies on gases in closed crystal growth systems which include: (a) Degassing properties of fused silica; (b) Generation of inert gases by source materials (CdTe, ZnTe, CdZnTe, ZnSe, PbTe, PbSe, PbSeTe); (c) Diffusive cas losses from silica glass ampoules.

Palosz, Witold↗
DOE OSTI2021

Scanning ultrafast electron microscopy reveals photovoltage dynamics at a deeply buried $p^- \mathrm{Si/SiO_2}$ interface

The understanding and control of charge carrier interactions with defects at buried insulator/semiconductor interfaces is essential for achieving optimum performance in modern electronics. In this work, we report on the use of scanning ultrafast electron microscopy (SUEM) to remotely probe the dynamics of excited carriers at a Si surface buried below a thick thermal oxide. Our measurements illustrate a previously unidentified SUEM contrast mechanism, whereby optical modulation of the space-charge field in the semiconductor modulates the electric field in the thick oxide, thus affecting its secondary electron yield. By analyzing the SUEM contrast as a function of time and laser fluence we demonstrate the diffusion mediated capture of excited carriers by interfacial traps.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS2023

Oxidation of Silicon Particles Suspended in Mullite Matrix With Dual-Mode Vacancy Diffusion of Oxygen

Mullite bond coats filled with silicon particles have recently been proposed for the next generation of environmental barrier coatings (EBCs). The sacrificial oxidation of the silicon particles eliminates some of the environmental durability issues associated with traditional EBC designs. To investigate this novel design approach, a mathematical formulation and resulting numerical method have been developed for simulating the oxidation of silicon particles embedded in a mullite matrix. The focus is on the oxidation of the silicon in a dry oxygen environment where the oxidant is presumably oxygen. Oxygen transport from the exterior environment through the mullite is assumed to occur via two lattice defect diffusion mechanisms. As a result, the rate of oxygen transport is dictated by the self-diffusivity of the lattice defects. The numerical method is implemented using the COMSOL Multiphysics® program (COMSOL, Inc.). The method is applied to simulate the oxidation of silicon particles in a mullite pellet in recent oxidation experiments. Numerical results compare favorably with the oxidation behavior observed in the oxidation experiments. The numerical method is also used to investigate the effects of various features of the mullite-silicon particle system on the oxidation behavior.

silicon oxidation↗
NASA NTRS1999

Low-Frequency Oscillations and Transport Processes Induced by Multiscale Transverse Structures in the Polar Wind Outflow: A Three-Dimensional Simulation

Multiscale transverse structures in the magnetic-field-aligned flows have been frequently observed in the auroral region by FAST and Freja satellites. A number of multiscale processes, such as broadband low-frequency oscillations and various cross-field transport effects are well correlated with these structures. To study these effects, we have used our three-dimensional multifluid model with multiscale transverse inhomogeneities in the initial velocity profile. Self-consistent-frequency mode driven by local transverse gradients in the generation of the low field-aligned ion flow and associated transport processes were simulated. Effects of particle interaction with the self-consistent time-dependent three-dimensional wave potential have been modeled using a distribution of test particles. For typical polar wind conditions it has been found that even large-scale (approximately 50 - 100 km) transverse inhomogeneities in the flow can generate low-frequency oscillations that lead to significant flow modifications, cross-field particle diffusion, and other transport effects. It has also been shown that even small-amplitude (approximately 10 - 20%) short-scale (approximately 10 km) modulations of the original large-scale flow profile significantly increases low-frequency mode generation and associated cross-field transport, not only at the local spatial scales imposed by the modulations but also on global scales. Note that this wave-induced cross-field transport is not included in any of the global numerical models of the ionosphere, ionosphere-thermosphere, or ionosphere-polar wind. The simulation results indicate that the wave-induced cross-field transport not only affects the ion outflow rates but also leads to a significant broadening of particle phase-space distribution and transverse particle diffusion.

Ganguli, Supriya B.↗
DOE OSTI2016

Milestone report: The simulation of radiation driven gas diffusion in UO 2 at low temperature

Below 1000 K it is thought that fission gas diffusion in nuclear fuel during irradiation occurs through atomic mixing due to radiation damage. This is an important process for nuclear reactor performance as it affects fission gas release, particularly from the periphery of the pellet where such temperatures are normal. Here we present a molecular dynamics study of Xe and Kr diffusion due to irradiation. Thermal spikes and cascades have been used to study the electronic stopping and ballistic phases of damage, respectively. Our results predict that O and Kr exhibit the greatest diffusivity and U the least, while Xe lies in between. It is concluded that the ballistic phase does not sufficiently account for the experimentally observed diffusion. Preliminary thermal spike calculations indicate that the electronic stopping phase generates greater fission gas displacement than the ballistic phase, although further calculation must be carried out to confirm this. A good description of the system by the empirical potentials is important over the very wide temperatures induced during thermal spike and damage cascade simulations. This has motivated the development of a parameter set for gas-actinide and gas-oxygen interactions that is complementary for use with a recent many-body potential set. A comprehensive set of density functional theory (DFT) calculations were used to study Xe and Kr incorporation at a number of sites in CeO 2 , ThO 2 , UO 2 and PuO 2 . These structures were used to fit a potential, which was used to generate molecular dynamics (MD) configurations incorporating Xe and Kr at 300 K, 1500 K, 3000 K and 5000 K. Subsequent matching to the forces predicted by DFT for these MD configurations was used to refine the potential set. This fitting approach ensured weighted fitting to configurations that are thermodynamically significant over a broad temperature range, while avoiding computationally expensive DFT-MD calculations. The resultant gas potentials were validated against DFT binding energies and are suitable for simulating combinations of Xe and Kr in solid solutions of CeO 2 , ThO 2 , UO 2 and PuO 2 , providing a powerful tool for the atomistic simulation of conventional nuclear reactor fuel UO 2 as well as advanced MOX fuels.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2013

ANOVA-HDMR structure of the higher order nodal diffusion solution

Nodal diffusion methods still represent a standard in global reactor calculations, but employ some ad-hoc approximations (such as the quadratic leakage approximation) which limit their accuracy in cases where reference quality solutions are sought. In this work we solve the nodal diffusion equations utilizing the so-called higher-order nodal methods to generate reference quality solutions and to decompose the obtained solutions via a technique known as High Dimensional Model Representation (HDMR). This representation and associated decomposition of the solution provides a new formulation of the transverse leakage term. The HDMR structure is investigated via the technique of Analysis of Variance (ANOVA), which indicates why the existing class of transversely-integrated nodal methods prove to be so successful. Furthermore, the analysis leads to a potential solution method for generating reference quality solutions at a much reduced calculational cost, by applying the ANOVA technique to the full higher order solution. (authors)

97 MATHEMATICS AND COMPUTING↗