Next Generation Space Instrument Modeling and Simulations for the X-Ray and Particle Sensing Project [Slides]
Abstract not provided.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
SEARCH · Engineering Papers
Results for “Particle generation”
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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Deuterated polyethylene nanowire arrays for high-energy density physics
Abstract The interaction of intense, ultrashort laser pulses with ordered nanostructure arrays offers a path to the efficient creation of ultra-high-energy density (UHED) matter and the generation of high-energy particles with compact lasers. Irradiation of deuterated nanowires arrays results in a near-solid density environment with extremely high temperatures and large electromagnetic fields in which deuterons are accelerated to multi-megaelectronvolt energies, resulting in deuterium–deuterium (D–D) fusion. Here we focus on the method of fabrication and the characteristics of ordered arrays of deuterated polyethylene nanowires. The irradiation of these array targets with femtosecond pulses of relativistic intensity and joule-level energy creates a micro-scale fusion environment that produced $2\times {10}^6$ neutrons per joule, an increase of about 500 times with respect to flat solid CD 2 targets irradiated with the same laser pulses. Irradiation with 8 J laser pulses was measured to generate up to 1.2 × 10 7 D–D fusion neutrons per shot.
Optics↗
Isotopic analysis of Nd nanoparticles using single particle MC-ICP-MS: A comparative study with single particle-ICP-TOF-MS
Single particle - inductively coupled plasma - mass spectrometry (SP-ICP-MS) is a powerful technique for characterization of the elemental and isotopic composition of individual particles. In this work, the capabilities of the newest generation of MC-ICP-MS with acquisition rates down to 50 ms were evaluated for single particle analysis, with a focus on isotopic precision achievable on a single-particle level. Nd (NdVO 4 ) nanoparticles (~120 nm in diameter) were used as case study and were first characterized in terms of mass (respective size) and particle number concentration by SP-ICP-TOF-MS and then by SP-MC-ICP-MS for isotopic precision. For the isotopic ratio measurements, the MC-ICP-MS performance was compared to the ICP-TOF-MS and it was found that the isotope ratio precision was increased (R 2 between 0.98 and 0.99) compared to ICP-TOF-MS (R 2 between 0.88 and 0.97). The accuracy attained on a single particle level, was compared to bulk digestion followed by MC-ICP-MS analysis, and the SP-MC-ICP-MS technique was able to determine the particle population average to be <4 %, percent relative differences for the 142 Nd/ 144 Nd, 143 Nd/ 144 Nd, 145 Nd/ 144 Nd, 146 Nd/ 144 Nd, and 148 Nd/ 144 Nd ratios The detection limit for the SP-MC-ICP-MS approach was also assessed. Here, when utilizing an all Faraday-cup based detection scheme the determined LOD for the measurements was 0.2fg for Nd, per particle. Based on these results, the newest generation of MC-ICP-MS has demonstrated its utility for performing SP measurement, particularly when high precision isotopic determination is warranted.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Super-resolving microscopy images of Li-ion electrodes for fine-feature quantification using generative adversarial networks
Abstract For a deeper understanding of the functional behavior of energy materials, it is necessary to investigate their microstructure, e.g., via imaging techniques like scanning electron microscopy (SEM). However, active materials are often heterogeneous, necessitating quantification of features over large volumes to achieve representativity which often requires reduced resolution for large fields of view. Cracks within Li-ion electrode particles are an example of fine features, representative quantification of which requires large volumes of tens of particles. To overcome the trade-off between the imaged volume of the material and the resolution achieved, we deploy generative adversarial networks (GAN), namely SRGANs, to super-resolve SEM images of cracked cathode materials. A quantitative analysis indicates that SRGANs outperform various other networks for crack detection within aged cathode particles. This makes GANs viable for performing super-resolution on microscopy images for mitigating the trade-off between resolution and field of view, thus enabling representative quantification of fine features.
30 DIRECT ENERGY CONVERSION↗
Efficient Hot Electron Transfer from Small Au Nanoparticles
Many important chemical transformations enabled by plasmonic hot carrier photocatalysis have been reported, although their efficiencies are often too low for practical applications. Here, we examine how the efficiency of plasmon-induced hot electron transfer depends on the Au particle size in Au-tipped CdS nanorods. We show that with decreasing Au size, the plasmon width increases due to enhanced surface damping contributions. The excitation of Au nanoparticles leads to an instrument response time-limited ultrafast hot electron transfer process to CdS ($\ll$140 fs). The quantum efficiency of this process increases from ~1% to ~18% as the particle size decreases from 5.5 ± 1.1 to 1.6 ± 0.5 nm due to both enhanced hot electron generation and transfer efficiencies in small Au particles. Our finding suggests that decreasing plasmonic particle size is an effective approach for improving plasmon-induced hot carrier transfer efficiency and provides important insight for the rational improvement of plasmonic hot carrier-based devices.
77 NANOSCIENCE AND NANOTECHNOLOGY↗
A better way to define dark matter haloes
ABSTRACT Dark matter haloes have long been recognized as one of the fundamental building blocks of large-scale structure formation models. Despite their importance – or perhaps because of it! – halo definitions continue to evolve towards more physically motivated criteria. Here, we propose a new definition that is physically motivated, effectively unique, and parameter-free: ‘A dark matter halo is comprised of the collection of particles orbiting in their own self-generated potential’. This definition is enabled by the fact that, even with as few as ≈300 particles per halo, nearly every particle in the vicinity of a halo can be uniquely classified as either orbiting or infalling based on its dynamical history. For brevity, we refer to haloes selected in this way as physical haloes. We demonstrate that (1) the mass function of physical haloes is Press–Schechter, provided the critical threshold for collapse is allowed to vary slowly with peak height; and (2) the peak-background split prediction of the clustering amplitude of physical haloes is statistically consistent with the simulation data, with accuracy no worse than ≈5 per cent.
Astronomy & Astrophysics↗
Investigation of Solid Particle Reactors for Nonoxidative Dehydrogenation of Ethane: Toward Solar Thermal Ethylene Production
Concentrating solar power plants can generate renewable heat at temperatures well above those of most industrial processes. Ceramic particles irradiated with concentrated sunlight can store high-quality sensible heat and transfer this to power generation systems. These concepts and materials hold great potential to also enable thermal processes in the chemical industry, but effective strategies for transferring heat from thermal energy storage media into chemical reactors are still under development. This present work evaluated the thermal and chemical compatibility of various solid particle media (including quartz, bauxite, and alumina particles) integrated directly into tube reactors and the subsequent effects on reactor performance for the nonoxidative dehydrogenation of ethane reaction. Empty tube reactors without loaded particles (representing conventional ethane cracking coils) showed significant heat transfer limitations as the tube diameter was scaled. The incorporation of media into the reactor significantly aided heat transfer to the gaseous ethane reactant and increased its conversion by as much as 10% at similar space velocities. Despite direct contact with hydrocarbon gases, alumina and quartz media showed negligible coke formation. Even during reaction in 100% ethane feed gas at 825 °C, the average selectivity of the coke product was only 0.57% when using the quartz media. These materials further demonstrated excellent thermal stability during subsequent reoxidation in air at 800 °C, which simulated the reheating of particles in a circulating particle solar receiver. Conversely, high rates of coke formation, with a product selectivity of 27.5%, were observed on sintered bauxite particles during the reaction, likely promoted by transition metal constituents. These particles fractured upon reoxidation due to exotherms generated from coke combustion. In conclusion, while the use of cofed steam could mitigate attrition of redox-active particles, the ability of inert metal oxide particles to efficiently transfer heat to concentrated ethane reactant gas while suppressing side reactions or degradation suggests that these media could effectively couple solar thermal plants to reactors for next-generation production of ethylene and other critical chemicals.
Hydrocarbons↗
A standard convention for particle-level Monte Carlo event-variation weights
Streams of event weights in particle-level Monte Carlo event generators are a convenient and immensely CPU-efficient approach to express systematic uncertainties in phenomenology calculations, providing systematic variations on the nominal prediction within a single event sample. But the lack of a common standard for labelling these variation streams across different tools has proven to be a major limitation for event-processing tools and analysers alike. Here we propose a well-defined, extensible community standard for the naming, ordering, and interpretation of weight streams that will serve as the basis for semantically correct parsing and combination of such variations in both theoretical and experimental studies.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
An Efficient Bayesian Approach to Learning Droplet Collision Kernels: Proof of Concept Using “Cloudy,” a New n -Moment Bulk Microphysics Scheme
The small-scale microphysical processes governing the formation of precipitation particles cannot be resolved explicitly by cloud resolving and climate models. Instead, they are represented by microphysics schemes that are based on a combination of theoretical knowledge, statistical assumptions, and fitting to data (“tuning”). Historically, tuning was done in an ad hoc fashion, leading to parameter choices that are not explainable or repeatable. Recent work has treated it as an inverse problem that can be solved by Bayesian inference. The posterior distribution of the parameters given the data—the solution of Bayesian inference—is found through computationally expensive sampling methods, which require over $\mathcal{O}$(10 5 ) evaluations of the forward model; this is prohibitive for many models. We present a proof of concept of Bayesian learning applied to a new bulk microphysics scheme named “Cloudy,” using the recently developed Calibrate-Emulate-Sample (CES) algorithm. Cloudy models collision-coalescence and collisional breakup of cloud droplets with an adjustable number of prognostic moments and with easily modifiable assumptions for the cloud droplet mass distribution and the collision kernel. The CES algorithm uses machine learning tools to accelerate Bayesian inference by reducing the number of forward evaluations needed to $\mathcal{O}$(10 2 ). It also exhibits a smoothing effect when forward evaluations are polluted by noise. In a suite of perfect-model experiments, we show that CES enables computationally efficient Bayesian inference of parameters in Cloudy from noisy observations of moments of the droplet mass distribution. In an additional imperfect-model experiment, a collision kernel parameter is successfully learned from output generated by a Lagrangian particle-based microphysics model.
54 ENVIRONMENTAL SCIENCES↗
Micro-Transfer Printing of Repeaters on Passive Interposer
Silicon-based sensors are central to particle physics experiments and particle tracking detectors. New-generation Large Focal Plane Arrays (LFPAs) cover areas that extend beyond several square meters. Distributing power and transporting data across such areas while maintaining good signal integrity is a complicated challenge. Tiling the detector on an organic interposer would be far too expensive and take too much space while offering little to no advantage regarding signal integrity. Passive silicon interposers are much less expensive and more integrable but would worsen signal integrity because of their inherent higher dielectric constant. Active interposers are a good compromise from the economic and signal integrity standpoint; unfortunately, their yield trends to zero for areas greater than a reticle size, making this technology incompatible with our application. NHanced proposes to duplicate the behavior of a high-yield, low-cost active interposer by printing active microcomponents on a passive interposer with our die-to-wafer micro-transfer printing (MTP) technology. This resolves the signal integrity and power distribution limitations. In Phase I, we designed and simulated analog and digital repeaters to be MTPed onto a passive silicon interposer test wafer.
2.5D↗
Flow structures of the cross-flow over a five-layer helically coiled steam generator geometry
The helically-coiled heat exchanger (HCSG) offers advantages over straight tubes such as compactness in geometry, increased heat transfer coefficients, and capability to absorb thermal expansion. In this study, the time-resolved velocity field data of shell-side crossflow over a five-layer helically coiled steam generator geometry was obtained using Particle Image Velocimetry (PIV) between adjacent rods in four regions with up to 5000 frames per second (5 kHz) at approximately Re u = 3600. The slant rod bundle created different flow patterns in different regions. Proper Orthogonal Decomposition (POD) revealed high-energy-mode flow structures. Due to the confined flow channel geometry, the large flow structures were not advected resulting in no strong POD mode paring. Continuous Wavelet Transform (CWT) visualized the characteristics of flow fluctuation in time and frequency domain simultaneously, which ranged in Strouhal number, S u , between 0.03 and 1.17. In the wake regions of the rods, flows changed in both pattern and magnitude over time. Once a pattern formed, it continued for relatively shorter than straight tube arrays, before changing the pattern again. The histograms of the POD time coefficients presented this multimodal flow characteristics. The current study focuses more on whole flow field analyses in the selected regions rather than local point-wise analyses. Finally, this study revealed that various Strouhal numbers can exist in the helically coiled heat exchanger geometry, which was not observed in straight tube arrays. In particular, Strouhal numbers smaller than 0.1 do not seem to be caused by vortex shedding but seem to be the result of the combination of complex geometry and possible multimodal trends. Based on the current observation, further works would involve intensive instantaneous point-wise analyses on the interactions between important locations such as separation points, stagnation points, shear layers, etc.
42 ENGINEERING↗
Insights into Mechanisms of Screw Feeder Plugging by Heated Pine Forestry Residues Using in-situ and Correlative Microscopy
Increasing concerns about global carbon emissions due to fossil fuel use has created interest in renewable fuel alternatives, such as lignocellulosic biomass. With an estimated global biomass production probability ten-fold higher than projected need, functionalizing and scaling biomass conversion processes, like pyrolysis, is a promising component of a diverse sustainable energy program (Kan, Strezov, & Evans, 2016). Pyrolysis reactors employed in biomass conversion often encounter the known problem of screw feeder plugging, halting work and reducing efficiency of biorefineries. Although the screw feeder is not heated directly, conductive heat transfer from the fluidized bed pyrolysis reactor creates a temperature gradient, where particles experience temperatures between 22°C and 500°C from the time they enter the feeder to being emptied into the reactor (Digman, Joo, & Kim, 2009; Nieminen & Folke, 1982). The impact of unintentional heating on this highly variable feedstock may result in particle morphology modification, surface texture transformation, and the evolution of viscous compounds and may contribute to screw feeder plugging (Haas, Nimlos, & Donohoe, 2009; Ingram et al., 2008). We hypothesized that particles of various anatomical fractions (including needles, branches, bark, cambium, and whitewood) will experience dramatic changes during this heating regime, which will be characterized by decreased particle size, increased surface roughness, degradation of key structural macromolecules, and generation of viscous compounds that would result in increased particle friction and cohesion, contributing to screw feeder plugging.
biofuels↗
LHC hadronic jet generation using convolutional variational autoencoders with normalizing flows
Abstract In high energy physics, one of the most important processes for collider data analysis is the comparison of collected and simulated data. Nowadays the state-of-the-art for data generation is in the form of Monte Carlo (MC) generators. However, because of the upcoming high-luminosity upgrade of the Large Hadron Collider (LHC), there will not be enough computational power or time to match the amount of needed simulated data using MC methods. An alternative approach under study is the usage of machine learning generative methods to fulfill that task. Since the most common final-state objects of high-energy proton collisions are hadronic jets, which are collections of particles collimated in a given region of space, this work aims to develop a convolutional variational autoencoder (ConVAE) for the generation of particle-based LHC hadronic jets. Given the ConVAE’s limitations, a normalizing flow (NF) network is coupled to it in a two-step training process, which shows improvements on the results for the generated jets. The ConVAE+NF network is capable of generating a jet in 18.30 ± 0.04 μ s , making it one of the fastest methods for this task up to now.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Testing strong-field QED with the avalanche precursor
A two-beam high-power laser facility is essential for the study of one of the most captivating phenomena predicted by strong-field quantum electrodynamics (QED) and yet unobserved experimentally: the avalanche-type cascade. In such a cascade, the energy of intense laser light can be efficiently transformed into high-energy radiation and electron–positron pairs. The future 50-petawatt-scale laser facility NSF OPAL will provide unique opportunities for studying such strong-field QED effects, as it is designed to deliver two ultra-intense, tightly focused laser pulses onto the interaction point. In this work, we investigate the potential of such a facility for studying elementary particle and plasma dynamics deeply in the quantum radiation-dominated (RD) regime, and the generation of QED avalanches. With three-dimensional particle-in-cell simulations, we demonstrate that QED avalanche precursors can be reliably triggered under realistic laser parameters and layout (namely, focusing f/2, tilted optical axes, and non-ideal co-pointing) with the anticipated capabilities of NSF OPAL. We demonstrate that seed electrons can be efficiently injected into the laser focus by using targets of three types: a gas of heavy atoms, an overcritical plasma, and a thin foil. A strong positron and high-energy photon signal is generated in all cases. The cascade properties can be identified from the final particle distributions, which have a clear directional pattern. At increasing laser field intensity, such distributions provide signatures of the transition, first, to the RD interaction regime, and then to a QED avalanche. Our findings can also be used for designing related future experiments.
Lasers↗
Methods development towards automated, physics-informed, quantitative quality control of TRISO-SiC
Tristructural-isotropic (TRISO) fuel particles have been developed as a high-performance fuel for use in high-temperature gas-cooled reactor (HTGR) systems due to their high efficiency and stability under both normal and off-normal conditions. Broader deployment of this technology in advanced nuclear applications may benefit from quantitative quality assurance and quality control (QA/QC) methods that directly link TRISO properties to downstream performance. A key TRISO property is the SiC layer microstructure, which influences fission product retention during irradiation. However, existing QA/QC for the TRISO-SiC microstructure comprises only a qualitative visual inspection; therefore, there is a clear opportunity for the development of quantitative methods for TRISO QA/QC. Here, to this end, previous work has demonstrated an image processing approach to grain boundary (GB) identification and subsequent extraction of microstructural metrics; however, extensive twinning within the SiC layer complicates such analyses because twin GBs significantly influence microstructural metrics but are not expected to contribute to fission product transport. This study presents the initial development, training, and testing of an ML-based image segmentation algorithm designed to identify and remove twin GBs from standard backscattered electron micrographs, providing an industrially applicable, quantitative, and physically meaningful QA/QC approach for the TRISO-SiC microstructure. Although pixel-wise performance metrics for the twin predictions are low, the change in grain area and the number of GB pixels after twin removal predicted by the ML workflow are within 1% of the true values calculated using crystallographic data. This suggests that the model is well capable of predicting overall twin boundary structures and grain morphology, and continued advancement of this approach could enable automated, scalable, and physics-informed QA/QC for TRISO-SiC microstructures, supporting the reliable qualification of coated particle fuels for next-generation reactor systems.
Computer vision↗
Directed flow from parton spin-orbit coupling in $pp$ and $pA$ collisions
We point out a novel mechanism to generate cos φ two-particle azimuthal correlation (‘directed flow’) in unpolarized proton-proton and proton-nucleus collisions in the forward rapidity region of the projectile proton. This is a direct consequence of the recently discovered strong spin-orbit coupling in gluons at small-x. The observable simultaneously serves as a unique probe into the double helicity parton distribution functions of the proton.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Simulation of the radiological impact during selected space travel scenarios using the Monte Carlo code FLUKA
Radiation is one of the major challenges of space exploration and can negatively impact both biological and electronic systems, particularly in the case of long-term journeys or if the spaceship features inadequate shielding. Here, in this work, the cumulative dose levels from prompt radiation in the spacecraft are quantified alongside the residual dose contributions arising from activation of vessel components. The radiological impact was assessed for various space exploration scenarios, considering the same spaceship model featuring three shielding design variants. In each scenario, the radiation environment was generated with the Monte Carlo particle transport and interaction code FLUKA. These results can be used to quantify the contribution of prompt and residual dose in spacefaring ventures and help determine optimal radiation shielding needed to mitigate the overall radiological impact on both astronauts and equipment.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Advancing the physics basis for quasi-helically symmetric stellarators
A new optimized quasi-helically symmetric configuration is described that has the desirable properties of improved energetic particle confinement, reduced turbulent transport by three-dimensional shaping and non-resonant divertor capabilities. The configuration presented in this paper is explicitly optimized for quasi-helical symmetry, energetic particle confinement, neoclassical confinement and stability near the axis. Post optimization, the configuration was evaluated for its performance with regard to energetic particle transport, ideal magnetohydrodynamic stability at various values of plasma pressure and ion temperature gradient instability induced turbulent transport. The effects of discrete coils on various confinement figures of merit, including energetic particle confinement, are determined by generating single-filament coils for the configuration. Preliminary divertor analysis shows that coils can be created that do not interfere with expansion of the vessel volume near the regions of outgoing heat flux, thus demonstrating the possibility of operating a non-resonant divertor.
Physics↗