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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

A Scintillating Xenon Bubble Chamber for Dark Matter Detection. Final Report

This report describes the progress in the search for particle dark matter achieved under DOE award DE-SC0012161, as well as the invention of a new dark matter and neutrino detection technique. Work supported by this award follows in three distinct thrusts: (1) the successful completion of the Generation-1 Direct Detection experiment PICO-60, which set the world-leading limit on the spin-dependent coupling of dark matter to protons and achieved a precise understanding of the response of bubble chambers to nuclear-recoil signals and electron-recoil backgrounds; (2) the construction of the Generation-2 Direct Detection experiment LZ, which will soon be the world's most sensitive dark matter detector; and (3) the demonstration of the first scintillating bubble chamber. The development of a scintillating liquid noble bubble chamber was the primary goal of the proposed work, with the aim of combining the excellent background rejection of a PICO-style bubble chamber with the event-by-event energy resolution of a liquid-noble detector such as LZ. This work produced the first ever observation of coincident scintillation and bubble nucleation by a nuclear recoil in a superheated fluid and also revealed an unexpected benefit to the use of noble liquids in a bubble chamber, namely the ability to increase the degree of superheat by an order of magnitude beyond that achievable in PICO-style detectors while maintaining PICO's world-leading background rejection. This discovery has led to new projects in the US and Canada, developing noble liquid bubble chambers both as detectors for low-mass dark matter and as detectors of coherent elastic neutrino-nucleus scattering (CEvNS) by neutrinos produced at nuclear reactors.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Simulation of Transport Phenomena in Bubble Column Reactors

The production of carbon and hydrogen from methane is a viable pathway for monetizing the vast reserves of US natural gas. Liquid (metals and/or salts) bubble column reactors operating at temperatures greater than 1000° C allow the conversion of methane into hydrogen without CO 2 emission. The low-density carbon floats on top of the liquid surface, allowing an easier removal, compared to other reactor concepts for methane pyrolysis. In this current report, we present results from simulations of transport phenomena in a liquid bubble column reactor. The goal is to investigate and understand parameters that are crucial for bubble column reactor design and scale up. The report presents the formulation and numerical methods used in the multiphase direct numerical simulation software, Quilt. This software was validated for the bubbly flow using numerical and physics based test problems. Quilt was then used to perform simulations of the bubble column reactor as a parametric study, varying the bubble injection parameters. The simulations were visualized for qualitative analysis and followed up with a quantitative analysis. The effect of injection parameters on various quantitative measures of the bubble residence time, interfacial area and motion through the column are presented.

03 NATURAL GAS↗
DOE OSTI2026

Probing and Tuning Strain‐Localized Exciton Emission in 2D Material Bubbles at Room Temperature

In monolayer transition metal dichalcogenides bubbles-nanoscale deformations typically exhibiting a dome-like shape-Excitons are confined by the strain effect, which exhibits extraordinary emission properties, such as single photon generation, enhanced light emission, and spectrally tunable excitonic states. While the strain profiles of these bubbles are extensively studied, this work provides an approach 1) to directly visualize the associated exciton properties in bubbles formed in WSe2 monolayer, revealing an intrinsic emission wavelength shift of ≈40 nm, and 2) actively modify local strain, enabling further exciton emission tuning over a range of 50 nm. These are achieved by emission mapping and nanoindentation using a dielectric near-field probe, which enables the detection of local emission spectra and emission lifetimes within individual bubbles. Statistical analysis of 67 bubbles uncovers an emission wavelength distribution centered around 780 nm. Furthermore, saturation behavior in the power-dependent studies and the associated lifetime change reveal the localized nature of the strain-induced states. These findings provide direct insights into the strain-localized emission dynamics in bubbles and establish a robust framework for non-destructive, reversible, and predictable nanoscale emission control, presenting a potential avenue for developing next-generation tunable quantum optical sources.

2D materials bubbles↗
DOE OSTI2024

Plasma Bubble Column Reactor: A High Throughput Reactor Design for Water Treatment

Plasma-based water treatment (PWT) is a promising technology that can degrade various emerging contaminants. However, PWT application on an industrially viable scale is hindered by the lack of an efficient reactor design that combines enhanced plasma-liquid contact with high liquid throughput. This work investigates the applicability of a bubble column gas-liquid contactor to PWT. A pulsed plasma bubble column reactor (PBCR) with a concentric rod-cylinder electrode configuration was used to correlate contaminant removal performance with the gas-liquid contact parameters of the bubble column. A surfactant, rhodamine B dye, and a nonsurfactant, caffeine, were used as model contaminants at µM concentration levels. The bubble column characteristics, i.e., gas holdup, bubble size distribution, and gas-liquid area, were measured as a function of superficial gas velocity using image-based methods. Degradation rates of both contaminants increased with gas flowrate. For caffeine, the increase was attributed to intensified bulk liquid mixing, while dye degradation increased due to the increased gas-liquid area. Ultimately, we show that bubble column contactors significantly improve the utilization of plasma-generated reactive species toward contaminant degradation by distributing them over a large contact area. As a result, a better match between the plasma species interfacial flux and the interfacial contaminant concentration leads to improved treatment energy efficiency. Furthermore, typical degradation energy efficiencies were ~10 g/kWh for caffeine and ~60 g/kWh for rhodamine B.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Application of a deep learning semantic segmentation model to helium bubbles and voids in nuclear materials

Imaging nanoscale radiation-induced defects using the transmission electron microscope (TEM) is a key factor in the successful implementation of materials for nuclear energy structural applications. Analyzing each defect in a TEM micrograph is currently a manual task. To identify the defects in a single image can take anywhere from 15 min to an hour and a project can require the analysis of anywhere from tens to ≥ 100 images. Here, we use artificial intelligence (AI) models to automate this task. For simplification, we evaluated images with only a single type of defect; helium bubbles. Additionally, we performed semantic segmentation of these helium bubble defects in electron microscopy images of irradiated FeCrAl alloys using a deep learning DefectSegNet model. This model, which was previously used to classify crystal defects, is inspired by the classic DenseNet and U-Net image segmentation models. It claims high spatial resolution, but has poor performance at object boundaries. Our paper improves the DefectSegNet model’s application by adding two new features. First, the DefectSegNet model is applied not only to perform calculation pixel-wise but also object (or feature) wise. Because object-wise metrics are directly relevant to our final goal of detecting bubbles, whereas pixel-wise classification is only an intermediate step, it is an important part of our study. Second, a distance map loss (DML) function has been added to increase its performance at object boundaries. It is crucial to accurately represent defects boundaries, especially bubbles, in order to track the bubble-induced swelling caused by irradiation. The boundary-focused DML function is also compared to other loss functions like Cross-entropy, Weighted Binary Cross Entropy (WBCE), Dice and Intersection over Union (IOU). Finally, by incorporating new features, we found a marked improvement on segmentation quality and better shape preservation at the boundaries and areas of the bubbles.

42 ENGINEERING↗
DOE OSTI2023

Evidence of Xe-incorporation in the bubble superlattice in irradiated U-Mo fuel

For years, researchers have reported competing ideas on the formation of fission gas bubble super lattices in metallic fuels, which was postulated to be comprised of elemental xenon (Xe) atoms. However, the chemical and physical arrangement of these elements within this gas bubble superlattice has not been verified. In this contribution, Xe was chemically profiled using atomic resolution scanning transmission electron microscopy (STEM) and atom probe tomography (APT) techniques in irradiated uranium-molybdenum (U-Mo) fuels. These complementary techniques provide conclusive evidence of Xe presence in bubble superlattice up to fission densities of 4.5×10 21 fissions/cm 3 and provide quantitative assessment of Xe content within the bubble superlattice. Based on the results of simultaneous imaging and spectroscopy using STEM, the chemical composition of the Xe bubble superlattice present in fission densities less than 4.5x10 21 fissions/cm 3 in U-Mo fuel was measured and found to be up to 8±1.3 atomic %. APT data complements STEM findings on Xe distribution in irradiated U-Mo fuel sample. APT showed a chemical composition of 0.7±0.1 atomic%. Finally, this study concludes by providing conclusive evidence that Xe is not only present within an atomically arranged bubble superlattice but provides fundamental insight the physical state of Xe in low enriched U-Mo monolithic fuel.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Operator learning for predicting multiscale bubble growth dynamics

We report simulating and predicting multiscale problems that couple multiple physics and dynamics across many orders of spatiotemporal scales is a great challenge that has not been investigated systematically by deep neural networks (DNNs). Herein, we develop a framework based on operator regression, the so-called deep operator network (DeepONet), with the long-term objective to simplify multiscale modeling by avoiding the fragile and time-consuming “hand-shaking” interface algorithms for stitching together heterogeneous descriptions of multiscale phenomena. To this end, as a first step, we investigate if a DeepONet can learn the dynamics of different scale regimes, one at the deterministic macroscale and the other at the stochastic microscale regime with inherent thermal fluctuations. Specifically, we test the effectiveness and accuracy of the DeepONet in predicting multirate bubble growth dynamics, which is described by a Rayleigh–Plesset (R–P) equation at the macroscale and modeled as a stochastic nucleation and cavitation process at the microscale by dissipative particle dynamics (DPD). First, we generate data using the R–P equation for multirate bubble growth dynamics caused by randomly time-varying liquid pressures drawn from Gaussian random fields (GRFs). Our results show that properly trained DeepONets can accurately predict the macroscale bubble growth dynamics and can outperform long short-term memory networks. We also demonstrate that the DeepONet can extrapolate accurately outside the input distribution using only very few new measurements. Subsequently, we train the DeepONet with DPD data corresponding to stochastic bubble growth dynamics. Although the DPD data are noisy and we only collect sparse data points on the trajectories, the trained DeepONet model is able to predict accurately the mean bubble dynamics for time-varying GRF pressures. Taken together, our findings demonstrate that DeepONets can be employed to unify the macroscale and microscale models of the multirate bubble growth problem, hence providing new insight into the role of operator regression via DNNs in tackling realistic multiscale problems and in simplifying modeling with heterogeneous descriptions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Two-Phase Turbulent Kinetic Energy Budget Computation in Co-Current Taylor Bubble Flow

Simulation of two-phase flows is relevant for reactor design and safety at normal operation or during accident scenarios. Often, the two-phase flow is in a regime in which slugs are formed or where the flow stratifies. Modeling such situations using standard single-phase Reynolds-averaged Navier-Stokes (RANS) turbulence models fails due to an overestimation of the eddy viscosity at the resolved two-phase interface. To solve this, an ad hoc turbulence damping term has been proposed in the literature that reduces the turbulence production locally at a two-phase interface, analogously to turbulence wall functions. However, this approach must be tailored to the specific setting and does not consider physical contributions such as surface tension or flow topology. Therefore, the problem of two-phase interfacial turbulence must be studied more in-depth. In this work, we consider co-current turbulent Taylor bubble flow using high-fidelity numerical simulation. The Basilisk code is used to simulate a Taylor bubble rising in a vertical pipe. By simulating the bubble in a moving frame of reference, we may study the turbulent kinetic energy (TKE) budgets ahead of the bubble, in its wake, and across the interface. The implementation of the TKE budget computation and the underlying averaging techniques are validated for the single-phase region ahead of the Taylor bubble using reference direct numerical simulation data. The analysis of the TKE budgets in the setting of Taylor bubble flow allows for the study of how turbulence behaves due to the presence of a two-phase interface and, in turn, supports the improvement of two-phase RANS models.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Helium bubble formation in aged plutonium metal at ambient conditions

A model of helium bubble formation is developed that assumes the initial nascent bubbles are generated when two diffusing helium atoms come within a distance of about the interatomic spacing of the plutonium atoms. These nascent bubbles are assumed to be locked in place and grow as additional helium atoms diffuse across their surfaces. Calculations of the helium-bubble number density and sizes as a function of age are compared to experiment. This leads to an inferred helium diffusion coefficient of-the-order of 10 -20 m 2 /s, supports the idea that most of the helium from alpha-decay end up in bubbles, and that previous transmission electron microscopy size estimates are biased low. The energy that helium can transfer to 40-year-old plutonium, upon expansion, is determined to be <0.1 Joules per gram of metal. The model predicts differences between the bubble properties in naturally and accelerated aged plutonium.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Motion of Air Bubbles in a Cement Slurry

The dynamics of air (gas) bubbles in a column of cement slurry is examined numerically. The air injected at the bottom of a laboratory-scale column through a porous distributor plate spatially distributes and migrates as a swarm of bubbles throughout the slurry toward the freeboard. The two-phase system of the cement slurry and the air bubbles is modeled using the conservation equations of mass and linear momentum in the framework of the volume-of-fluid (VOF) approach. The cement slurry is modeled using the Herschel–Bulkley and Bingham fluid models. Results show that the mean Sauter diameter and the mean rise velocity of the bubbles decrease with the gas flow rate. Meanwhile, it is found that the rising of the bubbles is controlled by breakup events, along with relatively weak path instabilities of the bubbles resulting in relatively straight trajectories, independent of the gas flow rate. The extent of the yielded region appears larger for the Herschel–Bulkley model compared to the Bingham fluid model (by approximately 10%).

36 MATERIALS SCIENCE↗
DOE OSTI2023

Quantitative Insight to Fission Gas Bubble Distribution in Irradiated Annular U-10Zr Metallic Fuel Using Deep Learning

U-10Zr Metal fuel is a promising nuclear fuel candidate for next-generation sodium-cooled fast spectrum reactors. Porosity is one of the key facts to impact the performance of metallic fuel. Additionally, a mechanical understanding of fission gas bubbles evolution behavior is a prerequisite for fuel development and qualification. Previous study of fission gas bubbles relied on a simple threshold method working on low resolution optical microscopy images, which has challenges in recognizing bubble boundaries, and caused inaccurate statistics of bubble properties. In this paper, a pre-trained deep learning model on Scanning Electron Microscopy (SEM) images from an annular U-10Zr fuel (AF1), was applied to another U-10Zr annular fuel (AF2). More accurate fission gas bubble segmentation results were generated, which leads to more precise qualitative analysis on the morphology, size, density, and orientation of bubbles. Furthermore, we investigated the lanthanide movement along the radial temperature gradient and obtained conclusive findings.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A improved equation of state for Xe gas bubbles in gamma U-Mo fuels

A monolithic fuel design based on a U-Mo alloy has been selected as the fuel type for conversion of the United States High-Performance Research Reactors (HPRRs). An issue with U-Mo monolithic fuel is the large amount of swelling that takes place during operation. The accurate prediction of fuel evolution under irradiation requires implementation of correct thermodynamic properties into mesoscale and continuum level fuel performance modeling codes. However, the thermodynamic properties of the fission gas bubbles (such as the relationship among bubble size, equilibrium Xe concentration, and bubble pressure) are not well known. This work studies Xe bubbles in ?U-Mo from a diameter of 3 nm up to 8.5 nm and from 400 K up to 700 K. The energetic relationship of Xe bubbles with regard to voids and Xe substitutional atoms is described. The transition is also determined for when a bubble becomes over-pressurized. Finally, an equation of state is fit to the pressure as a function of molar volume and temperature.

Beeler, Benjamin↗
DOE OSTI2022

Development of machine learning framework for interface force closures based on bubble tracking data

Interfacial force closures in the two-fluid model play a critical role for the predictive capabilities of void fraction distribution. However, the practices of interfacial force modeling have long been challenged by the inherent physical complexity of the two-phase flows. The rapidly expanding computational capabilities in the recent years have made high-fidelity data from the interface-captured direct numerical simulation become more available, and hence potential for data-driven interfacial force modeling has prevailed. In this work, we established a data-driven modeling framework integrated to the HZDR multiphase Eulerian-Eulerian framework for computational fluid dynamics simulations. The data-driven framework is verified in a benchmark problem, where a feedforward neural network managed to capture the non-linear mapping between bubble Reynolds number and drag coefficient and reproduce the void distribution resulting from the baseline model in the test case. The second focus is on utilizing the bubble tracking data set to form a closure for the bubble drag in the turbulent bubbly flow, in which the drag coefficient is set to be correlated with the bubble Reynolds number and the Eötvös number. Pseudo-steady state filtering in the Frenet Frame was carried out to obtain the drag coefficient from the turbulent bubbly flow data. The performance of the data-driven drag model is also examined through a case study, where improvement of model’s prediction near-wall is regarded necessary. In conclusion, discussion and further plans of investigation are provided.

42 ENGINEERING↗
DOE OSTI2023

Effects of transition metal carbide dispersoids on helium bubble formation in dispersion-strengthened tungsten

Abstract The formation of helium bubbles and subsequent property degradation poses a significant challenge to tungsten as a plasma-facing material in future long-pulse plasma-burning fusion reactors. In this study, we investigated helium bubble formation in dispersion-strengthened tungsten doped with transition metal carbides, including TaC, ZrC, and TiC. Of the three dispersoids, TaC exhibited the highest resistance to helium bubble formation, possibly due to the low vacancy mobility in the Group VB metal carbide and oxide phases. Under identical irradiation conditions, large helium bubbles formed at grain boundaries in tungsten, while no bubbles were observed at the interfaces between the carbide dispersoid and tungsten matrix. Moreover, our results showed the interfaces could suppress helium bubble formation in the nearby tungsten matrix, suggesting that the interfaces are more effective in trapping helium as tiny clusters. Our research provided new insights into optimizing the microstructure of dispersion-strengthened tungsten alloys to enhance their performance.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Optical and electrochemical effects of H 2 and O 2 bubbles at upward-facing Si photoelectrodes

The effects of the size, contact-angle, and coverage of gas bubbles on solar fuels devices were characterized at cm-scale, upward-facing planar and microwire-array Si photoelectrodes in stagnant electrolytes. Experimental measurements were supported by ray-tracing simulations of surface attached gas bubble films. A dilute, redox-active tracer allowed for the quantification of the mass-transport effects of bubble coverage during photoanodic O 2 (g) evolution at upward-facing photoanodes in 1.0 M KOH(aq.). Measurements of the gas coverage at upward-facing p-Si photocathodes in 0.50 M H 2 SO 4 (aq.) allowed for the nucleation rate and contact angle of H 2 (g) bubbles to be evaluated for systems having various surface free energies. Under simulated solar illumination, the rapid departure of small O 2 (g) bubbles produced stable photocurrents at upward-facing oxygen-evolving Si photoanodes and yielded increased mass-transport velocities relative to a stagnant electrolyte, indicating that bubbles can provide a net benefit to the photoelectrochemical performance of an upward-facing photoanode in solar fuels devices.

14 SOLAR ENERGY↗
DOE OSTI2020

Void-interface wetting to crossing transition owing to bubble to void transformation

Understanding cavity-interface interaction is crucial in designing high-strength, radiation-tolerant nanocomposites. In this work, bubbles near the Cu–Nb interface in Nb could be absorbed by Cu voids wetting the interface due to the high system energy difference produced by the huge pressure difference between the bubbles and voids and high mobility of bubbles, and no bubble-denuded zone forms owing to fast Brownian motion of bubbles, which keeps bubbles distributed homogeneously. However, owing to the low system energy difference generated by the low internal pressure difference and low mobility, voids near the Cu–Nb interface in Nb would simply coalesce with Cu voids wetting the interface, leading to the void-interface wetting to crossing transition and the formation of void-denuded zones due to the negligible migration of internal Nb voids.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Material migration in W and Mo during bubble growth and fuzz formation

Growth of helium (He) induced bubbles and fuzz in tungsten (W) and molybdenum (Mo) is investigated using samples of W films on Mo substrates and Mo films on W substrates exposed to He-containing plasma in the temperature range of 340 to 1075 K, fluence range of 1.0–14 × 10 25 He·m -2 , and incident ion energy of <50 eV. No fuzz (only up to 2 nm diameter bubbles) and no material transport occur in W films at ≤750 K, while precursors-of or fully-developed fuzz and material mixing occur in W and Mo films at ≥800 K. This suggests that fuzz forms in multi-material systems as long as one material meets the conditions for fuzz formation, namely T s / T m ~ 0.27–0.5 where T s and T m are the sample exposure and material melting temperatures, respectively. Larger He bubbles, more material mixing, and further-developed fuzz occur at higher temperature due to increased mobility of He atoms and small He clusters. Accumulation of substrate material at the surface of fuzzy W and Mo thin-film (<80 nm) samples suggests fuzz growth by material transport from the bubble layer in the bulk up to the fiber tip, likely by a two-step process: (i) diffusion of punched dislocation loops in the bulk toward the fuzz base and (ii) diffusion of adatoms along the fuzz base and fiber surface (with effective transport of adatoms upwards due to trapping of adatoms at curved surfaces of fiber tips and/or due to the continuous generation of adatoms at the fuzz base). While the bubble size and fuzz thickness increase with reduced W concentration in Mo thin-film samples at 838 K likely due to an increase in trap mutation and dislocation loop punching in Mo compared to W, the fuzz thickness decreases with reduced W concentration at 1075 K despite an increase in the bubble size likely due to slower diffusion of interstitial loops in Mo.

Physics↗
DOE OSTI2022

Emission from hadronic and leptonic processes in galactic jet-driven bubbles

ABSTRACT We investigate the multiwavelength emission from hadronic and leptonic cosmic rays (CRs) in bubbles around galaxies, analogous to the Fermi bubbles of the Milky Way. The bubbles are modelled using 3D magnetohydrodynamical simulations, and are driven by a 0.3 Myr intense explosive outburst from the nucleus of Milky Way-like galaxies. We compute their non-thermal emission properties at different stages throughout their evolution, up to 7 Myr, by post-processing the simulations. We compare the spectral and spatial signatures of bubbles with hadronic, leptonic, and hybrid hadro-leptonic CR compositions. These each show broadly similar emission spectra, comprised of radio synchrotron, inverse Compton, and non-thermal bremsstrahlung components. However, hadronic and hybrid bubbles were found to be brighter than leptonic bubbles in X-rays, and marginally less bright at radio frequencies, and in γ-rays between ∼0.1 and a few 10s of GeV, with a large part of their emission being driven by secondary electrons formed in hadronic interactions. Hadronic systems were also found to be slightly brighter in high-energy γ-rays than their leptonic counterparts, owing to the π0 decay emission that dominates their emission between energies of 100s of GeV and a few TeV.

Owen, Ellis R. (ORCID:0000000310526439)↗