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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Using the Stix finite element RF code to investigate operation optimization of the ICRF antenna on Alcator C-Mod

Abstract As the Ion Cyclotron Radio Frequency range (ICRF) heating becomes more favorable in fusion devices, the urgency of predicting and mitigating impurity generation that arises from it becomes more pressing. In the ICRF regime, rectified Radio Frequency (RF) sheaths are known to form at antenna and material edges that influence negative effects like sputtering and a decrease in heating efficiency. Methods to mitigate the formation of these RF sheaths through RF image currents cancellation have been experimentally studied. A power-phasing scan done on Alcator C-Mod in which the amount of power on the two inner straps ( P in ) versus the total 4 straps ( P tot ) was varied showed a minimization of enhanced potentials between P in / P tot ∼ 0.7–0.9 while impurities were minimized for P in / P tot ∼ 0.5–0.8. New capabilities in the realm of representing the RF sheath numerically now allow for these experiments to be simulated. Given the size of the sheath relative to the scale of the device, it can be approximated as a Boundary Condition (BC). A new parallelized cold-plasma wave equation solver called Stix implements a non-linear sheath impedance model BC formulated by Myra et al (2015 Phys. Plasmas 22 062507) through the method of finite elements using the MFEM library [ http://mfem.org ]. It is seen that Stix shows qualitative agreement with the measured C-Mod enhanced potentials.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Studies of laser stimulated photodetachment from nanoparticles for particle charge measurements

Determining nanoparticle charge is more challenging than that for microparticles due to change in the particle size during the synthesis substantial plasma property variations, and difficulties in visualizing individual particles, rendering conventional microparticle charge diagnostics ineffective in dusty plasma. In this work, we utilized laser-stimulated photodetachment (LSPD) to deduce the mean charge of nanoparticles. Nanoparticles were grown in an Ar/C 2 H 2 mixture using a capacitively coupled RF discharge and the LSPD induced changes in the electron current monitored by a cylindrical Langmuir probe. LSPD signals were obtained and analyzed across different dust growth phases. The prolonged decay of electron current pulses was attributed to the presence of residual negative ions, caused by the effective electrostatic trapping of these ions and the potential post—LSPD re-formation of new ones. The particle charge was estimated by combining the laser-stimulated photodetachment signal from the probe with the dust density obtained from laser-light extinction using the measured nanoparticle size distribution. For a nanoparticles size range of approximately 100–250 nm and mean diameter of $d$ p ∼154.37 nm, the effective mean charge was estimated to be $\langle$$Q$$\rangle$ d $≈$ 37 elementary charge units. The measured charge values are lower than those predicted by orbital motion limited theory, which may be attributed to significant electron depletion in the nanodusty plasma. LSPD results in Ar/C 2 H 2 nano-dusty plasma confirm the applicability of this method for estimating individual nanoparticle charges. However, it has also been demonstrated that electron detachment from residual background negative ions can influence the detachment current decay and must be carefully considered.

dust particle charge↗
DOE OSTI2025

Integrated modeling of RF-induced tungsten erosion at ICRH antenna structures in the WEST tokamak *

This paper introduces STRIPE (Simulated Transport of RF Impurity Production and Emission), an advanced modeling framework developed to analyze material erosion and the global transport of eroded impurities originating from radio-frequency (RF) antenna structures in magnetic confinement fusion devices. STRIPE integrates multiple physics modules: SolEdge3x for scrape-off-layer plasma profiles, COMSOL for 3D RF rectified sheath potentials, RustBCA for erosion yields and surface interactions, and global impurity transport for 3D ion energy-angle distributions and impurity transport. The framework is applied to an ion cyclotron RF-heated L-mode discharge (#57877) in the WEST tokamak, where it predicts a thirty-fold increase in gross tungsten erosion at antenna limiters during the transition from ohmic to ICRH operation. Additionally, under ICRH conditions, a tenfold enhancement in erosion is observed when comparing RF sheath effects to purely thermal sheath conditions. High-charge-state oxygen ions ($\mathrm{O}$ 6+ and above) are identified as the dominant contributors to tungsten sputtering. To validate the model, a synthetic diagnostic tool based on inverse photon efficiency (S/XB coefficients) from the ColRadPy collisional-radiative model enables direct comparison with spectroscopic measurements. Model predictions using a plasma composition of 1% oxygen and 99% deuterium show good agreement with observed W − I (400.9 nm) emission for discharge #57877, supporting the accuracy of the STRIPE framework. This study focuses specifically on gross erosion calculations to demonstrate STRIPE’s capabilities. Future extensions of this work will incorporate net erosion, re-deposition, self-sputtering effects, and whole-device modeling of sputtered tungsten impurity transport. STRIPE is also being applied to other RF-heated linear and toroidal devices, offering valuable insights for antenna design, impurity control, and performance optimization in next-generation fusion reactors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Climate cooling benefits of cellulosic bioenergy crops from elevated albedo

Abstract Changes in land surface albedo can alter ecosystem energy balance and potentially influence climate. We examined the albedo of six bioenergy cropping systems in southwest Michigan USA: monocultures of energy sorghum ( Sorghum bicolor ), switchgrass ( Panicum virgatum L.), and giant miscanthus ( Miscanthus × giganteus) , and polycultures of native grasses, early successional vegetation, and restored prairie. Direct field measurements of surface albedo ( α s ) from May 2018 through December 2020 at half‐hourly intervals in each system quantified the magnitudes and seasonal differences in albedo (∆ α ) and albedo‐induced radiative forcing (RF ∆ α ). We used a nearby forest as a historical native cover type to estimate reference albedo and RF ∆ α change upon original land use conversion, and a continuous no‐till maize ( Zea mays L .) system as a contemporary reference to estimate change upon conversion from annual row crops. Annually, α s differed significantly ( p < 0.05) among crops in the order: early successional (0.288 ± 0.012SE) >> miscanthus (0.271 ± 0.009) ≈ energy sorghum (0.270 ± 0.010) ≥ switchgrass (0.265 ± 0.009) ≈ restored prairie (0.264 ± 0.012) > native grasses (0.259 ± 0.010) > maize (0.247 ± 0.010). Reference forest had the lowest annual α s (0.134 ± 0.003). Albedo differences among crops during the growing season were also statistically significant, with growing season α s in perennial crops and energy sorghum on average ~20% higher (0.206 ± 0.003) than in no‐till maize (0.184 ± 0.002). Average non‐growing season (NGS) α s (0.370 ± 0.020) was much higher than growing season α s (0.203 ± 0.003) but these NGS differences were not significant. Overall, the original conversion of reference forest and maize landscapes to perennials provided a cooling effect on the local climate (RF αMAIZE : −3.83 ± 1.00 W m −2 ; RF αFOREST : −16.75 ± 3.01 W m −2 ). Significant differences among cropping systems suggest an additional management intervention for maximizing the positive climate benefit of bioenergy crops, with cellulosic crops on average ~9.1% more reflective than no‐till maize, which itself was about twice as reflective as the reference forest.

Lei, Cheyenne↗
DOE OSTI2023

Machine Learning Downscaling of SoilMERGE in the United States Southern Great Plains

SoilMERGE (SMERGE) is a root-zone soil moisture (RZSM) product that covers the entire continental United States and spans 1978 to 2019. Machine learning techniques, Random Forest (RF), eXtreme Gradient Boosting (XGBoost), and Gradient Boost (GBoost) downscaled SMERGE to spatial resolutions straddling the field scale domain (100 to 3000 m). Study area was northern Oklahoma and southern Kansas. The coarse resolution of SMERGE (0.125 degree) limits this product’s utility. To validate downscaled results in situ data from four sources were used that included: United States Department of Energy Atmospheric Radiation Measurement (ARM) observatory, United States Climate Reference Network (USCRN), Soil Climate Analysis Network (SCAN), and Soil moisture Sensing Controller and oPtimal Estimator (SoilSCAPE). In addition, RZSM retrievals from NASA’s Airborne Microwave Observatory of Subcanopy and Surface (AirMOSS) campaign provided a nearly spatially continuous comparison. Three periods were examined: era 1 (2016 to 2019), era 2 (2012 to 2015), and era 3 (2003 to 2007). During eras 1 and 2, RF outperformed XGBoost and GBoost, whereas during era 3 no model dominated. Performance was better during eras 1 and 2 as opposed to the pre-L band era 3. Improvements across all eras, regions, and models realized from downscaling included an increase in correlation from 0.03 to 0.42 and a decrease in ub RMSE from -0.0005 to -0.0118 m 3 /m 3 . This study demonstrates the feasibility of SMERGE downscaling opening the prospect for the development of a long-term RZSM dataset at a more desirable field-scale resolution with the potential to support diverse hydrometeorological and agricultural applications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Advances in the long-pulse steady-state high beta H-mode scenario with active controls of divertor heat and particle fluxes in EAST

Since the last IAEA-Fusion Energy Conference, the Experimental Advanced Superconducting Tokamak (EAST) research program has been, in support of ITER and CFETR, focused on development in terms of the long-pulse steady-state (fully noninductive) high beta H-mode scenario with active controls of the stationary and transient divertor heat and particle fluxes. The operational domain of the steady-state H-mode plasma scenario has been significantly extended with ITER-like tungsten mono-block divertor, plasma control and heating schemes. EAST has achieved several important milestones in the development of high β p H-mode scenario and its key physics and technologies. A 60 s-scale long-pulse steady-state high β p H-mode discharge with the major normalized plasma parameters similar to the designed performance of the CFETR 1GW fusion power operation scenario has been successfully established and sustained by pure RF heating and current drive. Several feedback control schemes have been developed for a sustained detachment with good core confinement. This includes control of the total radiation power, target electron temperature, and particle flux measured using divertor Langmuir probes or a combination of the control of target electron temperature and AXUV radiation near the X point. The detachment feedback control schemes have been integrated with small-ELM regimes and high β p scenario via neon seeding, enabling a core and edge compatible integrated high-beta scenario applicable to long-pulse operations. ELM suppression has been achieved using various methods, including resonant magnetic perturbations and impurity seeding. Full suppression of ELMs by using n=4 RMPs has been demonstrated for ITER for the first time in low input torque plasmas in EAST. Finally, EAST has been operated with helium to support the ITER research requirements for the first time. For a long-pulse, high bootstrap current fraction operation, a new lower tungsten divertor with active water-cooling has been installed, along with improvements in the heating and current drive capability.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

LLRF System for the Fermilab Mu2e Project – AC Dipole Extinction

The Mu2e experiment measures the conversion rate of muons into electrons. The experiments requires 53 MHz batches of 8 GeV protons to be re-bunched into 150 ns, 2.5 MHz pulses for extraction to a single RF cavity running at 2.36 MHz. To meet stringent limits on the amount of beam between pulses, an Extinction System is used comprising of 2 AC dipole magnets (4.4MHz, 296Khz) and a collimator.

Guran, M. [Fermilab] (ORCID:0009000235538559)↗
DOE OSTI2022

Effect of successive heat treatment on the performance of superconducting radio frequency niobium cavities

One of the primary sources of radio frequency residual losses leading to lower quality factor is trapped residual magnetic field during the cooldown of superconducting radio frequency cavities. It has been reported that non-uniform recrystallization of niobium cavities after the post fabrication heat treatment leads to higher flux trapping during the cooldown, and hence the lower quality factor. Here, we fabricated two 1.3 GHz single cell cavities from high purity fine grain niobium and processed with successive heat treatments in the range 800-1000 ?C to measure the flux expulsion and flux trapping sensitivity. The results show the improved flux expulsion with increase in heat treatment temperature and flux trapping sensitivity depends on the final surface preparation prior to the rf test.

Khanal, Bashu↗
DOE OSTI2020

High precision 5 MeV Mott polarimeter

We report on the design and performance of a Mott polarimeter optimized for a nominal 5-MeV electron beam from the Continuous Electron Beam Accelerator Facility (CEBAF) injector. The rf time structure of this beam allows the use of time of flight in the scattered electron detection, making it possible to cleanly isolate those detected electrons that originate from the scattering foil, and resulting in measured scattering asymmetries which are exceptionally stable over a broad range of beam conditions, beam currents, and foil thicknesses. In two separate series of measurements from two different photocathode electron sources, we have measured the Mott scattering asymmetries produced by an approximately 86% transversely polarized electron beam incident on ten gold foils with nominal thicknesses between 50 and 1000 nm. The statistical uncertainty of the measured asymmetry from each foil is below 0.25%. Within this statistical precision, the measured asymmetry was unaffected by ±1-mm shifts in the beam position on the target foil, and by beam current changes and dead-time effects over a wide range of beam currents. The overall uncertainty of our beam polarization measurement, arising from the uncertainty in the value of the scattering asymmetry at zero foil thickness as determined from our fits to the measured asymmetries versus scattering foil thicknesses, the estimated systematic effects, and the (dominant) uncertainty from the calculation of the theoretical Sherman function, is 0.61%. A simulation of the polarimeter using geant4 has confirmed that double scattering in the target foil is the sole source of the dependence of the measured asymmetry on foil thickness, and gives a result for the asymmetry versus foil thickness in good agreement with both our measurements and a simple calculation. Future measurements at different beam energies and with target foils of different atomic numbers will seek to bound uncertainties from small effects such as radiative corrections to the calculation of the polarimeter analyzing power. A simultaneous high-precision measurement of the beam polarization with a different polarimeter, AESOP (Accurate Electron Spin Optical Polarimeter), under development at the University of Nebraska, clearly possible at the CEBAF accelerator, will allow a high-precision comparison of our measured asymmetries with theoretical calculations of the Mott analyzing power. Finally, the improved precision of the current Mott polarimeter along with similar improvements to other Jefferson Lab polarimeters warrants another precision comparison of all of these polarimeters when measuring a beam of the same polarization.

Grames, J. M. (ORCID:0000000193908752)↗
DOE OSTI2025

The Frequency Shift and $Q$ of Disordered Superconducting RF Cavities

Niobium superconducting radio-frequency (SRF) cavities for high-energy accelerator applications have been greatly improved in terms of the quality factor $Q$ by techniques such as Nitrogen doping. However, the mechanisms leading to improvement in $Q$ are still not fully understood. Quite recently the SRF group at Fermilab measured anomalies in the frequency shift of N-doped SRF Niobium cavities near the transition temperature. Here we report our theoretical analysis of these results based on the microscopic theory of superconductivity that incorporates anisotropy of the superconducting gap and inhomogeneous disorder in the screening region of the SRF cavities. We are able to account for frequency shift anomalies very close to $T_c$ on the order of fractions of 1 kHz. Our results for the frequency shift and Q are in good agreement with the experimental data reported for all four N-doped Nb SRF cavities by Bafia et al. We also compare our theory with an earlier report on a Nb sample measured at 60 GHz. In addition, we show that the quality factor calculated theoretically has a peak of upper convexity with the largest $Q$ at intermediate levels of disorder. For strong disorder, i.e. the dirty limit, pair breaking in the presence of disorder and screening currents limits the $Q$.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

A Random Forest Approach to Identifying Young Stellar Object Candidates in the Lupus Star-forming Region

The identification and characterization of stellar members within a star-forming region are critical to many aspects of star formation, including formalization of the initial mass function, circumstellar disk evolution, and star formation history. Previous surveys of the Lupus star-forming region have identified members through infrared excess and accretion signatures. We use machine learning to identify new candidate members of Lupus based on surveys from two space-based observatories: ESA’s Gaia and NASA’s Spitzer. Astrometric measurements from Gaia's Data Release 2 and astrometric and photometric data from the Infrared Array Camera on the Spitzer Space Telescope, as well as from other surveys, are compiled into a catalog for the random forest (RF) classifier. The RF classifiers are tested to find the best features, membership list, non-membership identification scheme, imputation method, training set class weighting, and method of dealing with class imbalance within the data. We list 27 candidate members of the Lupus star-forming region for spectroscopic follow-up. Most of the candidates lie in Clouds V and VI, where only one confirmed member of Lupus was previously known. These clouds likely represent a slightly older population of star formation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Qualifying AL-800 Garnet For The Fermilab Booster Perpendicular Biased 2nd Harmonic RF Cavity

Al-800 garnet was evaluated for the perpendicular biased 2nd harmonic cavity for the Fermilab Booster accelerator. A test apparatus was designed to evaluate the magnetic permeability and batch consistency of small witness samples of Al-800. Fully assembled AL-800 garnet rings were tested on the garnet ring test stand to measure the resonant frequency and quality factor of each ring. The garnet witness samples and assembled garnet rings showed acceptable consistency within the parameters set by the cavity design team. Based on the test results, AL-800 garnet was deemed suitable for use in the perpendicular biased 2nd harmonic cavity.

Kuharik, John C.↗
DOE OSTI2024

Machine Learning Correlation of Electron Micrographs and ToF-SIMS for the Analysis of Organic Biomarkers in Mudstone

The spatial distribution of organics in geological samples can be used to determine when and how these organics were incorporated into the host rock. Mass spectrometry (MS) imaging can rapidly collect a large amount of data, but ions produced are mixed without discrimination, resulting in complex mass spectra that can be difficult to interpret. Here, we apply unsupervised and supervised machine learning (ML) to help interpret spectra from time-of-flight-secondary ion mass spectrometry (ToF-SIMS) of an organic-carbon-rich mudstone of the Middle Jurassic of England (UK). It was previously shown that the presence of sterane molecular biomarkers in this sample can be detected via ToF-SIMS (Pasterski, M. J. et al., Astrobiology 2023, 23, 936). We use unsupervised ML on scanning electron microscopy–electron dispersive spectroscopy (SEM-EDS) measurements to define compositional categories based on differences in elemental abundances. We then test the ability of four ML algorithms─k-nearest neighbors (KNN), recursive partitioning and regressive trees (RPART), eXtreme gradient boost (XGBoost), and random forest (RF)─to classify the ToF-SIM spectra using (1) the categories assigned via SEM-EDS, (2) organic and inorganic labels assigned via SEM-EDS, and (3) the presence or absence of detectable steranes in ToF-SIMS spectra. In terms of predictive accuracy and balanced accuracy, KNN was the best performing model and RPART the worst. The feature importance, or the specific features of the ToF-SIM spectra used by the models to make classifications, cannot be determined for KNN, preventing posthoc model interpretation. Nevertheless, the feature importance extracted from the other models was useful for interpreting spectra. In conclusion, we determined that some of the organic ions used to classify biomarker containing spectra may be fragment ions derived from kerogen which is abundant in this mudstone sample.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Effects of Heat Treatment on Microstructure, Thermal Transport and Stability in SRF Niobium

Efficient heat transfer and thermal stability are critical for preventing thermal quench and ensuring the high performance and reliability of superconducting radiofrequency (SRF) cavities, especially under high RF fields. In this article, we investigate thermal conductivity and heat capacity of high-purity cold-worked niobium used in SRF applications, with a particular focus on the effects of high-temperature heat treatments. Our measurements reveal a pronounced sensitivity of thermal transport and thermodynamic properties to the underlying microstructure such as grain size and dislocation density. The results show the critical role of controlled heat treatment processes in optimizing the thermal performance of SRF niobium, providing valuable insights for improving cavity fabrication and processing.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Combined Optical and Radio-Frequency Measurements of a Lightning Megaflash by the FORTE Satellite

The optical and VHF instrumentation on the Fast On-Orbit Recording of Transient Events (FORTE) satellite is used to document the combined phenomenology evolution of a lightning “megaflash” – mesoscale lightning that propagates laterally over exceptional distances. We identify a FORTE flash whose maximum extent was 82 km and inferred length over multiple distinct branches exceeded 100 km. This flash lasted 1.2 s and produced 250 optical and 591 RF events. We find that the channel development mapped by FORTE’s pixelated lightning imager (LLS) occurred at a typical speed of 2.6x10 5 m s -1 and was accompanied by sustained periods of VHF emission that could individually exceed 100 ms in duration. The impulsive IC events generated by the flash indicate that this development occurred at altitudes between 3 and 8 km. Four +CG strokes were identified in the VHF waveform data that are responsible for two of the three highly-radiant LLS groups (two of the +CGs were not as optically bright as the others). These strokes occurred at different locations throughout the flash footprint with the most distant strokes separated by approximately 50 km. These space-based observations match previous observations of megaflashes as well as ground-based measurements of negative leader development during “spider” lightning, suggesting that FORTE is sensing the same phenomena.

Peterson, Michael Jay↗
DOE OSTI2022

Experimental realization of linearly polarized x-ray detected ferromagnetic resonance

We present the first theoretical and experimental evidence of time-resolved dynamic x-ray magnetic linear dichroism (XMLD) measurements of GHz magnetic precessions driven by ferromagnetic resonance in both metallic and insulating thin films. Our findings show a dynamic XMLD in both ferromagnetic Ni 80 Fe 20 and ferrimagnetic Ni 0.65 Zn 0.35 Al 0.8 Fe 1.2 O 4 for different measurement geometries and linear polarizations. A detailed analysis of the observed signals reveals the importance of separating different harmonic components in the dynamic signal in order to identify the XMLD response without the influence of competing contributions. In particular, RF magnetic resonance elicits a large dynamic XMLD response at the fundamental frequency under experimental geometries with oblique x-ray polarization. The geometric range and experimental sensitivity can be improved by isolating the 2ω Fourier component of the dynamic response. These results illustrate the potential of dynamic XMLD and represent a milestone accomplishment toward the study of GHz spin dynamics in systems beyond ferromagnetic order.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Characterization of an RF-driven argon plasma at atmospheric pressure using broadband absorption and optical emission spectroscopy

Atmospheric pressure plasmas in argon are of particular interest due to the production of highly excited and reactive species enabling numerous plasma-aided applications. In this contribution, we report on absolute optical emission and absorption spectroscopy of a radio frequency (RF) driven capacitively coupled argon glow discharge operated in a parallel-plate configuration. This enabled the study of all key parameters including electron density and temperature, gas temperature, and absolute densities of atoms in highly electronically excited states. The space and time-averaged electron density and temperature were determined from the measurement of the absolute intensity of the electron-atom bremsstrahlung in the visible range. Considering the non-Maxwellian electron energy distribution function, an electron temperature (T e ) of 2.1 eV and an electron density (n e ) of 1.1 × 10 19 m –3 were obtained. The time-averaged and spatially resolved absolute densities of atoms in the metastable (1s 5 and 1s 3 ) and resonant (1s 4 and 1s 2 ) states of argon in pure Ar and Ar/He mixture were obtained by broadband absorption spectroscopy. The 1s 5 metastable atoms had the largest density near the sheath region with a maximum value of 8 × 10 17 m –3 , while all other 1s states had densities of at most 2 × 10 17 m –3 . Here, the dominant production and loss mechanisms of these atoms were discussed, in particular, the role of radiation trapping. We conclude with a comparison of the plasma properties of the argon RF glow discharges with the more common He equivalent and highlight their differences.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Autoencoder Based Analysis of RF Parameters in the Fermilab Low Energy Linac

Machine learning (ML) has the potential for significant impact on the modeling, operation, and control of particle accelerators due to its ability to model nonlinear behavior, interpolate on complicated surfaces, and adapt to system changes over time. Anomaly detection in particular has been highlighted as an area where ML can significantly impact the operation of accelerators. These algorithms work by identifying subtle behaviors of key variables prior to negative events. Efforts to apply ML to anomaly detection have largely focused on subsystems such as RF cavities, superconducting magnets, and losses in rings. However, dedicated efforts to understand how to apply ML for anomaly detection in linear accelerators have been limited. In this paper the use of autoencoders is explored to identify anomalous behavior in measured data from the Fermilab low-energy linear accelerator.

Edelen, Jonathan P. (ORCID:0000000215180652)↗