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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Review of the application piezoelectric actuators for SRF cavity tuners

Modern particle accelerators and high-energy physics experiments that deployed up to several hundred of accelerating superconducting RF cavities require accurate frequency control. This is achieved by using cavity tuners typically actuated with the piezoelectric ceramic actuators. Piezoelectric ceramic actuators have become “standard” components of the SRF cavity tuner and depending on the application could be operated in different environments: in air, at cryogenic temperature, in vacuum, and submerged in liquid helium. Different applications place different requirements on the piezo actuators, but the important parameters common to all applications are the lifetime and reliability of the actuators. Several programs targeting the development of reliable piezo actuators are presented in this contribution.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Machine Learning for Mapping Multipactor Susceptibility in RF Systems: Capabilities and Generalization Constraints

Multipactor is a surface-driven electron avalanche phenomenon that degrades the performance and reliability of radio-frequency (RF) systems in particle accelerator and vacuum electronics applications. Multipactor behavior in a given device structure is conventionally assessed through susceptibility charts, which provide a parameter-space characterization of the instability. In this work, we assess the capabilities of machine-learning (ML) models to learn and predict such susceptibility charts and analyze the constraints governing their generalization across materials. Using a simulation-derived dataset spanning six distinct secondary-electron-yield material profiles in a canonical two-surface planar geometry, we train supervised regression models and artificial neural networks to predict the time-averaged electron growth rate, δavg, across the relevant parameter space. Model performance is evaluated using metrics that explicitly probe the structure of susceptibility charts, including Intersection over Union, Structural Similarity Index, and correlation analysis. Tree-based ensemble models outperform neural-network models in reconstructing susceptibility regions and in generalizing across material domains. Principal-component analysis reveals disjoint material feature distributions, indicating that the piecewise mode structure of multipactor susceptibility is difficult to represent with a single global model and that generalization is constrained by data coverage rather than by model complexity. An exhaustive reduced-coverage study further shows that sparse material-space coverage can yield mean performance in the same general range but producing large variability in the susceptibility-region overlap. These results clarify the capabilities of ML-based surrogate models for parameter-space characterization of multipactor discharge. They also provide guidance for their appropriate use in RF system design.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Uranium particle age dating, aggregation, and model age best estimators

We present important aspects of uranium particle age dating by Large-Geometry Secondary Ion Mass Spectrometry (LG-SIMS) that can introduce bias and increase model age uncertainties, especially for small, young, and/or low-enriched particles. This metrology is important for applications related to International Nuclear Safeguards. We explore influential factors related to model age estimation, including the effects of evolving surface chemistry on inter-element measurements of particles (e.g., Th and U), detector background, and aggregation methods using simulated and actual particle samples. We introduce a new model age estimator, called “mid68”, that supplements 95% confidence intervals, providing a “best estimate” and uncertainty about the most likely age. The mid68 estimator can be calculated using the Feldman and Cousins method or Bayesian methods and provides a value with a symmetric uncertainty that can be used for calculations and approximate aggregation of processed model age values when the raw data and correction factors are not available. For particles yielding low 230 Th counts amidst nonzero detector background, their underlying model age probability distributions are asymmetric, so the mid68 estimator provides additional robust information regarding the underlying model age likelihood. This study provides a comprehensive and timely examination of critical aspects of uranium particle age dating as more laboratories establish particle chronometry capabilities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Intercomparison of Aerosol Instrumental Responses Using AEROTRAK, SMPS, and APS in a Simulated Building

In this work, three aerosol instruments were intercompared by using data collected from field campaigns in a simulated building environment during the last quarter of 2020 from October to December at Oak Ridge National Laboratory. The three aerosol instruments—AeroTrak Model 9110, Scanning Mobility Particle Spectrometer (SMPS) 3080L + 3025A, and Aerodynamic Particle Sizer (APS) 3320—were manufactured by TSI Inc. to perform in situ measurements of particle number concentration in the air. These instruments were co-located in one room in which an aerosol generator was used to produce a defined aerosol population for the instruments to sample and detect in each campaign. The SMPS measured aerosol particles with diameters from 0.01 to 0.7 µm, APS measured aerosol particles with diameters from 0.5 to 20 µm, and AeroTrak measured aerosol particles with diameters from 0.1 to 10 µm. The results suggest that although AeroTrak is fast and easy to use, it does not provide measurements comparable with those obtained by SMPS and APS. The differences in particle counts were orders of magnitude in size (i.e., the AeroTrak data were unreasonably small in the tested scenarios). The results clearly indicate that AeroTrak should not be used in ambient applications in which the level of particle concentration is expected to be high. This would cause difficulty to a campaign in which the dilution factor is unknow a priori. The high particle concentration could also lead to an erroneous aerosol size distribution (e.g., a bimodal size distribution was measured as opposed to a single-mode one). The number concentration limit that AeroTrak is expected to run reliably (i.e., with a counting coincidence error less than ±10%) is approximately three to four per cubic centimeter. This suggests that the instrument is best used in a clean room environment, not in an ambient or indoor application, such as the Flexible Research Platform campaigns.

47 OTHER INSTRUMENTATION↗
NASA NTRS1971

Fog dispersal technology.

The state-of-the-art in fog dispersal technology is briefly discussed. Fog is categorized as supercooled fog, occurring in air temperatures below freezing, and warm fog, occurring at above-freezing temperatures. Operational techniques are available to disperse supercooled fog in the airport area. It is much more difficult to cope with warm fog. Various known concepts to disperse warm fog are evaluated as to their operational merits. The most effective concept for immediate use involves heating the air to cause fog evaporation. Use of helicopter downwash has some application, possibly complementing the promising concept of seeding with sized hygroscopic particles. These latter two concepts appear to have future application, pending further research. The concept using polyelectrolytes is of uncertain value, lacking both a scientific explanation and a substantive evaluation of reported operational successes.

Mcgowan, W. A.↗
NASA NTRS1993

Generation of monodisperse droplets by spontaneous condensation of flow in nozzles

Submicron size monodisperse particles are of interest in many industrial and scientific applications. These include the manufacture of ceramic parts using fine ceramic particles, the production of thin films by deposition of ionized clusters, monodisperse seed particles for laser anemometry, and the study of size dependence of cluster chemical and physical properties. An inexpensive and relatively easy way to generate such particles is by utilizing the phenomenon of spontaneous condensation. The phenomenon occurs when the vapor or a mixture of a vapor and a noncondensing gas is expanded at a high expansion rate. The saturation line is crossed with the supercooled vapor behaving like a gas, until all of a sudden at the so called Wilson point, condensation occurs, resulting in a large number of relatively monodisperse droplets. The droplet size is a function of the expansion rate, inlet conditions, mass fraction of vapor, gas properties, etc. Spontaneous condensation of steam and water vapor and air mixture in a one dimensional nozzle was modeled and the resulting equations solved numerically. The droplet size distribution at the exit of various one dimensional nozzles and the flow characteristics such as pressure ratio, mean droplet radius, vapor and droplet temperatures, nucleation flux, supercooling, wetness, etc., along the axial distance were obtained. The numerical results compared very well with the available experimental data. The effect of inlet conditions, nozzle expansion rates, and vapor mass fractions on droplet mean radius, droplet size distribution, and pressure ratio were examined.

Lai, Der-Shaiun↗
DOE OSTI2021

Automating Bayesian inference and design to quantify acoustic particle levitation

Self-propulsion of micro- and nanoparticles powered by ultrasound provides an attractive strategy for the remote manipulation of colloidal matter using biocompatible energy inputs. Quantitative understanding of particle motion and its dependence on size, shape, and composition requires accurate characterization of the acoustic field, which depends sensitively on the experimental setup. Here, we show how automated experiments based on Bayesian inference and design can accurately and efficiently characterize the acoustic field within resonant chambers used to propel acoustic nanomotors. Repeated cycles of observation, inference, and design (OID) are guided by a physical model that describes the rate at which levitating particles approach the nodal plane. Using video microscopy, we observe the relaxation of tracer particles to this plane following the application of the acoustic field. We use sequential Monte Carlo methods to infer model parameters such as the amplitude and frequency of the resonant chamber while accounting for particle-level measurement noise and population-level heterogeneity in the field. Guided by simulated outcomes, we select the optimal design for the next experiment as to maximize the information gain in the relevant parameters. We show how this iterative process serves to discriminate between competing hypotheses and efficiently converges to accurate parameter estimates using only few automated experiments. We discuss the need for model criticism to ensure the validity of the guiding model throughout automated cycles of observation, inference, and design. Furthermore, this work demonstrates how Bayesian methods can learn the parameters of nonlinear, hierarchical models used to describe video microscopy data of active colloids.

42 ENGINEERING↗
DOE OSTI2021

Avoiding surface instability and slurry jamming in simultaneous multilayer coating of structured particulate films

Simultaneous multilayer coating techniques are widely known, but their industrial application remains limited to narrow market sectors. One barrier to adoption may be the mismatch between industries that are familiar with such processes but have no need, and industries that have need but are not familiar. Moreover, there are application-specific technical challenges to developing multilayer-coating processes. In this article, we describe our resolution of two specific issues in simultaneous multilayer coating of all aqueous highly loaded slurries for new and emerging energy applications. The first issue is particle jamming (associated with Shear-thickening) of the highly loaded slurries in the die internals, which we alleviated by adding small amounts of viscosity modifiers without reducing the solid loading. The second issue is a Marangoni-driven surface instability that resembles top layer de-wetting, which we solved by carefully selecting surfactants to tune the dynamic surface tensions of each slurry. Both issues were resolved early in a step-wise development, saving significant development cost which in our case was driven by expensive materials.

08 HYDROGEN↗
DOE OSTI2021

Validation of the TOPAS Monte Carlo toolkit for HDR brachytherapy simulations

The goal of this work is to validate the user-friendly Geant4-based Monte Carlo toolkit TOol for PArticle Simulation (TOPAS) for brachytherapy applications. Brachytherapy simulations performed with TOPAS were systematically compared with published TG-186 reference data. The photon emission energy spectrum, the air-kerma strength, and the dose-rate constant of the model-based dose calculation algorithm (MBDCA)-WG generic Ir-192 source were extracted. For dose calculations, a track-length estimator was implemented. Additionally, the four Joint AAPM/ESTRO/ABG MBDCA-WG test cases were evaluated through histograms of the local and global dose difference volumes. A prostate, a palliative lung, and a breast case were simulated. For each case, the dose ratio map, the histogram of the global dose difference volume, and cumulative dose-volume histograms were calculated. The air-kerma strength was (9.772 ± 0.001) × 10 -8 U Bq -1 (within 0.3% of the reference value). The dose-rate constant was 1.1107 ± 0.0005 cGy h -1 U -1 (within 0.01% of the reference value). For all cases, at least 96.9% of voxels had a local dose difference within [-1%, 1%] and at least 99.9% of voxels had a global dose difference within [-0.1%, 0.1%]. The implemented track-length estimator scorer was more efficient than the default analog dose scorer by a factor of 237. For all clinical cases, at least 97.5% of voxels had a global dose difference within [-1%, 1%]. Dose-volume histograms were consistent with the reference data. TOPAS was validated for high-dose-rate brachytherapy simulations following the TG-186 recommended approach for MBDCAs. Built on top of Geant4, TOPAS provides broad access to a state-of-the-art Monte Carlo code for brachytherapy simulations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Magnus method for electronic structure calculations at extreme conditions

We present the application of Magnus based methods to the solution of first order coupled ordinary differential equations in High Energy Density (HED) physics applications. Our focus is on the application to quantum mechanical methods, specifically on the solution of the radial Dirac equation for real and complex energies. HED applications require accurate solutions across a wide range of spatial and energy domains, including regimes where the solutions exhibit pronounced oscillatory behavior. Such cases pose significant computational challenges. We demonstrate that Magnus-based integrators can efficiently and accurately address these challenges. We discuss the implementation of the Magnus method for the solution of the radial Dirac equation, including practical considerations such as the evaluation of matrix exponentials, numerical integration, error estimation, and adaptive step size control. We also discuss the application of these methods to complex energy Green’s function techniques and the efficient approximation of integrals of the solutions relevant to HED electronic structure calculations. Here, we demonstrate the accuracy and robustness of the resulting method in applications to the free-particle case, for which analytic solutions are available for comparison, as well as the challenging case of gold at HED conditions.

general physics↗
DOE OSTI2020

Effect of copper content on the tensile elongation of Al–Cu–Mn–Zr alloys: Experiments and finite element simulations

Microstructures of cast aluminum alloys used in automotive engine applications often consist of intermetallic particles that can impact the tensile elongation of these alloys. Here in this paper, we investigate the effect of intermetallic grain boundary particles on tensile elongation by fabricating a series of alloys with Cu content varying between 6.0 - 9.0 wt% in cast Al–Cu–Mn–Zr (ACMZ) type compositions. The tensile elongation of as-aged ACMZ alloys decreases monotonically with increase in Cu content. While the microstructure within the grains and yield stress of the alloy remains invariant with Cu content, the decrease in tensile elongation correlates well with increase in the size and volume fraction of grain boundary particles. Microstructural observations are combined with finite element simulations to explain the trend in tensile elongation with changing Cu content. Crack initiation is found to occur by brittle fracture of the grain boundary particles. Increase in particle size promotes crack initiation by reduction in size dependent particle fracture strength. Lower inter-particle spacing at higher particle volume fraction further facilitates crack initiation by increasing stress within the particles caused by the interaction between stress fields of neighboring particles. Increase in particle volume fraction also accelerates crack propagation through the formation of macro shear zones in the microstructure. The increase in Cu content of cast ACMZ alloys, therefore, decreases tensile elongation by promoting both crack initiation and crack propagation.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Hermetically sealed porous-wall hollow microspheres enabled by monolithic glass coatings: Potential for thermal insulation applications

Thermal insulation materials are crucial to improve the energy performance of buildings and industrial applications. We report an approach to create hermetically vacuum-sealed silica-based hollow microspheres that can lower the thermal conductivity of closed-cell insulation materials. The wall structure of these hollow microspheres includes a reticulated network of pores or channels that extend through the thickness of the wall. When a thin layer of glass material is applied to the wall exterior, followed by a vacuum-assisted thermal treatment process, the coated microsphere surfaces display a highly dense conformal coverage and near-complete elimination of surface porosity. The sealing efficiency of these microspheres is verified by trapping argon within their cavities as well as through evacuating their hollow cores. Notably, incorporating the evacuated microspheres into a polymer matrix resulted in ~27% enhancement in its thermal insulation performance and no notable loss of performance was observed following three months of exposure to ambient conditions. Thus, we believe that the present study offers a commercially viable strategy that opens the door to applications of such inorganic hollow particles in areas ranging from vacuum-based thermal insulation systems to catalysis, separation technologies, and medical fields.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Edge mode percolation and equilibration in the topological insulator cadmium arsenide

Two-dimensional topological insulators can feature one-dimensional charge transport via edge modes, which offer a rich ground for studying exotic quasi-particles and for quantum materials applications. In this work, we use lateral junction devices, defined by nanoscale finger gates, to study edge mode transport in the two-dimensional topological insulator Cd 3 As 2 . The finger gate can be tuned to transmit an integer number of quantum Hall edge modes and exhibits full equilibration in the bipolar regime. When the Fermi level of the channel crosses a Landau level, reflected modes percolate through the channel, resulting in an anomalous conductance peak. The device does not fully pinch off when the channel is tuned into the topological gap, which is a sign of remnant modes in the channel. These modes are expected from band inversion, while residual bulk conduction associated with the disorder potential may also play a role.

36 MATERIALS SCIENCE↗
DOE OSTI2022

From predicting to learning dissipation from pair correlations of active liquids

Active systems, which are driven out of equilibrium by local non-conservative forces, can adopt unique behaviors and configurations. Towards designing such materials, an important challenge is to precisely connect the static structure of active systems to the dissipation of energy induced by the local driving. Here, we use tools from liquid-state theories and machine learning to take on these challenges. We first demonstrate analytically for an isotropic active matter system that dissipation and pair correlations are closely related when driving forces behave like an active temperature. We then extend a nonequilibrium mean-field framework for predicting these pair correlations which, unlike most existing approaches, is applicable even for strongly interacting particles and far from equilibrium, to predict dissipation in these systems. Based on this theory, we reveal analytically a robust relation between dissipation and structure which holds even as the system approaches a nonequilibrium phase transition. Finally, we construct a neural network which maps static configurations of particles to their dissipation rate without any prior knowledge of the underlying dynamics. Furthermore, our results open novel perspectives on the interplay between dissipation and organization out-of-equilibrium.

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

Super-Fermi acceleration in multiscale MHD reconnection

We investigate the Fermi acceleration of charged particles in 2D MHD anti-parallel plasmoid reconnection, finding a drastic enhancement in energization rate ε ˙ over a standard Fermi model of ε ˙ ~ ε. The shrinking particle orbit width around a magnetic island due to E → × B → drift produces a ε ˙ ∥ ~ ε ∥ 1 + 1 / 2 χ power law with χ ~ 0.75. The increase in the maximum possible energy gain of a particle within a plasmoid due to the enhanced efficiency increases with the plasmoid size and is by multiple factors of 10 in the case of solar flares and much more for larger plasmas. Including the effects of the non-constant E → × B → drift rates leads to further variation in power law indices from ≳ 2 to ≲ 1, decreasing with plasmoid size at the time of injection. The implications for energetic particle spectra are discussed alongside applications to 3D plasmoid reconnection and the effects of a guide field.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Modeling the co-assembly of binary nanoparticles

Abstract In this work, we present a binary assembly model that can predict the co-assembly structure and spatial frequency spectra of monodispersed nanoparticles with two different particle sizes. The approach relies on an iterative algorithm based on geometric constraints, which can simulate the assembly patterns of particles with two distinct diameters, size distributions, and at various mixture ratios on a planar surface. The two-dimensional spatial-frequency spectra of the modeled assembles can be analyzed using fast Fourier transform analysis to examine their frequency content. The simulated co-assembly structures and spectra are compared with assembled nanoparticles fabricated using transfer coating method are in qualitative agreement with the experimental results. The co-assembly model can also be used to predict the peak spatial frequency and the full-width at half-maximum bandwidth, which can lead to the design of the structure spectra by selection of different monodispersed particles. This work can find applications in fabrication of non-periodic nanostructures for functional surfaces, light extraction structures, and broadband nanophotonics.

Mohanty, Saurav (ORCID:0009000302592855)↗
DOE OSTI2024

Superconducting quasiparticle-amplifying transmon: A qubit-based sensor for meV-scale phonons and single terahertz photons

With great interest from the quantum computing community, an immense amount of R&D effort has been invested into improving superconducting qubits. The technologies developed for the design and fabrication of these qubits can be directly applied to applications for ultralow-threshold particle detectors, e.g., low-mass dark matter and far-infrared photon sensing. We propose a novel energy-resolving sensor based on the transmon qubit architecture combined with a signal-enhancing superconducting quasiparticle amplification stage. We refer to these sensors as SQUATs: superconducting quasiparticle-amplifying transmons. We detail the operating principle and design of this new sensor and predict that, with minimal R&D effort, solid-state-based detectors patterned with these sensors can achieve sensitivity to single terahertz photons, and sensitivity to 1 meV phonons in the detector absorber substrate on the microsecond timescale. Published by the American Physical Society 2024

47 OTHER INSTRUMENTATION↗