SEARCH · Search NASA

Results for “RF”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 163 records · Page 9

All sources NASA NTRS DOE OSTI

DOE OSTI2026

AMAROK: A Radio Frequency Development Platform for High-Power, Full-Scale Positive Ion Sources for DIII-D Neutral Beam Injectors

Next-generation neutral beam injection (NBI) systems demand RF ion sources capable of efficiently coupling >120 kW at 2–4-MHz frequencies, yet existing designs face voltage standoff and impedance-matching challenges. To address this, the advanced multicoil antenna for RF operations at kilowatts (AMAROK) was developed as a high-power RF inductively coupled plasma (ICP) source delivering up to 200 kW in the 2–4-MHz range via four phase-controlled generators for flexible power sharing. Two antenna designs—a single-strap multiturn (MT) and a multistrap single-turn (ST) design—were evaluated to optimize resonance, impedance matching, and power coupling across plasma loads. Here, a semi-analytical self-resonant frequency (SRF) model, validated experimentally, predicts resonance trends for arbitrary turn counts and tubing diameters, enabling rapid antenna optimization. Strap-to-strap mutual inductance in the ST configuration showed strong spatial dependence, guiding generator operation and total load inductance. These insights informed a custom π -topology matching network, achieving stable impedance matching over a wide range of plasma-driven loads. Collectively, these results position AMAROK as a versatile testbed for advancing high-power RF source technology in fusion NBI applications.

DIII-D↗

DOE OSTI2026

Rapid RASER MRI

Conventional Magnetic Resonance Imaging (MRI) relies on high-power Radio-Frequency (RF) pulses to excite nuclear spins and in turn generate NMR signals. These pulses require large high-power RF-amplifiers and cause heat deposition in the tissue, which must be minimized for safety, presenting a growing problem when moving toward ever-higher field MRI. An alternative to RF-pulse excitation is self-excitation of nuclear spins using Radiofrequency Amplification by Stimulated Emission of Radiation (RASER), where the nuclear spins undergo spontaneous transition, without RF excitation, from an over-populated state to a ground state. Here, the feasibility of recording rapid proton RASER MRI images of pyrazine at low concentration (120 mM) with large matrix (128x128 pixels) in as little as 78 ms is demonstrated at 500 MHz (11.7 T). We also recorded a time-series of images using a single bolus hyperpolarized pyrazine highlighting the feasibility of dynamic tracking. Here, the demonstrated approach allows recording MRI scans without transmit-receive electronics of the MRI scanner, which is highly desirable for portable MRI as well as the emerging field of hyperpolarized MRI using, e.g., HP protons, 129 Xe gas or HP 13 C labeled biomolecules as molecular tracers and imaging agents.

MRI↗

DOE OSTI2026

Uncertainty-Aware Machine Learning for Small-Angle X-ray Scattering Analysis in Autonomous Experimentation

Small-angle X-ray scattering (SAXS) is a powerful high-throughput characterization tool for probing nanoscale structure in native sample environments, providing real-time morphological information such as nanoparticle size and shape during synthesis. However, automated SAXS data analysis for extracting meaningful structural parameters is non-trivial and remains a bottleneck in closed-loop experimentation towards autonomous materials discovery, which demands fast, reliable, and uncertainty-aware data analysis. Here, we develop a machine-learning approach for automated SAXS analysis tailored to closed-loop nanoparticle synthesis. A Random Forest (RF) regression model is trained on 100,000 synthetic SAXS curves generated from polydisperse spherical nanoparticles with realistic background contributions. Using normalized one-dimensional SAXS intensity profiles as input, the RF model directly predicts nanoparticle radius, size polydispersity, and background parameters, while the ensemble standard deviation across trees provides built-in uncertainty quantification (UQ). On synthetic data, we show that combining fit-quality metrics (R 2 , MAE) with thresholds on prediction uncertainty reliably identifies accurate parameter estimates without access to ground truth. We then apply the trained model to 365 experimental SAXS profiles of citrate-reduced gold nanoparticles synthesized using an automated droplet-flow microreactor with in situ SAXS at a synchrotron beamline, classifying the results into high- and low-confidence subsets based on UQ metrics. Finally, we integrate RF-based SAXS analysis into a simulated closed-loop optimization campaign using Gaussian process Bayesian optimization to minimize nanoparticle polydispersity, benchmarking against conventional automated Levenberg–Marquardt fitting. The RF-guided campaign exhibits substantially faster convergence and lower relative opportunity cost (∼0.07 vs ∼0.3), demonstrating that uncertainty-aware machine-learning SAXS analysis significantly enhances the efficiency and robustness of autonomous nanomaterials synthesis workflows.

Bayesian optimization↗

DOE OSTI2025

Enhanced Boundary Layer Height Detection Using Ceilometer, Surface Meteorology, and Radiation Products With a Random Forest Ensemble Method

This study develops and evaluates a Random Forest (RF) model for estimating planetary boundary layer height (PBLH) using 9 years of data from the Atmospheric Radiation Measurement Southern Great Plains (ARM SGP) user facility, with potential application in the NOAA Surface Radiation (SURFRAD) Network. The model integrates ceilometer, surface meteorology, and radiation measurements, and is trained using thermodynamic PBLH estimates derived from radiosondes. This approach aims to bridge gaps between aerosol-based and thermodynamic-based PBLH estimates. The RF model outperformed traditional methods during daytime and better captured transition periods, demonstrating improved accuracy and robustness. At ARM SGP, it showed a substantial reduction in both bias and RMSE, with a bias near zero (−4.9 m) compared with traditional Haar Wavelet (HW) (70.9 m) and Vaisala BL-View software (124.1 m), and an RMSE of 303.2 m, lower than both BL-View (566.9 m) and HW (404.6 m). During daytime hours, RF consistently outperformed both alternatives, maintaining lower bias and RMSE across all periods. At a second evaluation site, RF achieved the lowest overall RMSE (323.7 m), similar to HW (326.4 m) and significantly better than BL-View (738.3 m). However, all models showed reduced accuracy under stable nighttime conditions, limiting the reliability of PBLH estimates. Key predictors for the model included the lifting condensation level height (LCLH), aerosol gradients, and month for seasonal variability. The study underscores the potential of integrating machine learning with multiple data sets such as surface energy and thermodynamic data to advance PBLH estimation.

boundary layer height↗

DOE OSTI2026

The effect of high-power transient events on tungsten and tungsten coatings used for radio frequency launcher applications

High-temperature plasma-facing material coatings used for radio frequency (RF) launchers need to be robust enough to survive RF breakdown arcing or other transient events from the plasma (e.g., an edge localized mode) without causing a catastrophic failure of the coating. High-power transient effects are being explored by using an RF-induced vacuum arc to determine the robustness of tungsten coatings made by a variety of manufacturing methods. A 1/4-wavelength resonant section of vacuum transmission line terminated with an open circuit electrode structure with a well-defined electric field (30-60 kV/mm) produces repeatable arcing conditions. The initial focus is on tungsten as a plasma-facing material, including sintered tungsten, tungsten coatings on steel produced via physical vapor deposition (PVD), and functionally graded tungsten/steel coatings deposited by low-pressure plasma-spraying (LPPS). Thin PVD coatings (1-2 microns) fail catastrophically from an arc and result in severe delamination of the coating. The arc-induced damage of thicker coatings, such as those made via LPPS, tend to be restricted to the top few microns of the surface. Arcing often initiates on sharp surface microstructures and causes localized melting of tungsten at the surface of all the materials studied and results in resolidified melt pools with surface cracks. The resolidified surface results in a reduction in overall deuterium retention when exposed to typical RF plasma sheath conditions.

Caughman, John [ORNL] (ORCID:0000000206091164)↗

DOE OSTI2025

Design and Engineering of LUPIN: A Test-Bed Radio-Frequency Ion Source for Enhanced Neutral Beam Injection on DIII-D

The Large, Uniform Plasma for Ionizing Neutrals (LUPIN) is a radio-frequency (RF) inductively coupled plasma (ICP) chamber for demonstrating plasma performance of an RF ICP positive ion source upgrade for the DIII-D neutral beam injection (NBI) system. LUPIN will be used to investigate ion source physics, including neutral gas dynamics, plasma density uniformity, interactions with Faraday shields, and power coupling to novel RF antenna designs. LUPIN has an RF generator capable of delivering 20 kW of power at 2 MHz, which is coupled into a cylindrical quartz vessel measuring 20 cm in length and 10 cm in radius. This configuration matches the power density requirements for a full-scale ion source. Target hydrogen and deuterium plasma densities exceeding 10 18 m -3 would relate to extracted ion current densities of 2100 A/m 2 for 10s. Vacuum conductance and gas flow calculations predict a maximum achievable neutral gas flow rate of 1675 Pa ⋅ L/s at 5 Pa of He, which mimics the gas flow of the DIII-D NBI system. Designs have been developed for an internal Faraday shield to mitigate heat flux and ion sputtering on the dielectric vessel. Thermomechanical finite element simulations demonstrated the Faraday shield design to be capable of withstanding anticipated heat loads from worst-case operation scenarios. Finally, results of upcoming experimental investigations on LUPIN will guide the design of a full-scale prototype for DIII-D integration.

Faraday shield↗

DOE OSTI2025

Design and Study of Inductively Coupled Plasma Chamber Components Using the SupRISE Test Device at DIII-D

The DIII-D National Fusion Facility aims to increase the auxiliary heating power for the tokamak by upgrading the Neutral Beam Injection (NBI) system. In collaboration with North Carolina State University, the conventional ‘arc and filament’ NBI ion sources will be converted to inductively coupled plasma (ICP) sources which utilize radio frequency (RF) coupling to maximize reliability for high power operation. In support of this initiative, a full scale test device (SupRISE, Superior Radiofrequency Ion Source Experiment) is currently under construction at the DIII-D Facility. In preparation for the construction of a full scale prototype that can be installed on the DIII-D NBI system, experiments on SupRISE will be conducted to determine the optimal RF frequency for high power coupling, Faraday shield slit configuration, and ICP chamber length. SupRISE is comprised of an approximately 30 x 70 cm quartz dielectric vessel with an internal Faraday shield enclosed in a secondary vacuum chamber to ensure structural stability of the dielectric. Actively cooled front and back plates are designed to reduce the thermal stresses on the plasma facing components and mate with the existing accelerator used by the NBI system at DIII-D. 50 kW of RF power will be coupled to the plasma through the quartz over a variable frequency range of 4-8 MHz to sustain a plasma density of ∼ 10 18 m −3 for a 10 s ON, 210 s OFF duty cycle. Various modelling efforts have been employed to simulate the thermal and stress profiles over the primary components of the SupRISE device as well as the inductance behavior of the RF antenna. These simulation results and the final design for SupRISE will be presented. An additional reduced-scale predecessor ICP source (called RISE) has been used to develop a predictive match model that will be applied to frequency optimization studies on SupRISE. Furthermore, the outcomes of this research and complementary efforts at North Carolina State University are essential for the incorporation of ICP NBI positive ion sources at the DIII-D facility.

DIII-D↗

DOE OSTI2026

Fluid-kinetic modeling of a high power density radio frequency inductively coupled positive hydrogen ion source

High power density radio-frequency (RF) inductively coupled positive ion sources are attractive candidates for next-generation neutral beam injection (NBI) systems, where higher injected power and longer pulse lengths are desired without sacrificing source reliability. Operating at absorbed power densities of order $\gt 1~\mathrm{W\,cm}^{-3}$ places these sources in a regime with stronger gas heating, higher dissociation, and non-Maxwellian electron energy distributions. The Large Uniform Plasma for Ionizing Neutrals (LUPIN) is an RF inductively coupled plasma source designed to explore this high power density regime and to provide guidance for a positive ion source upgrade for the DIII-D NBI system. LUPIN is designed to operate at up to 20 kW of RF power at 2 MHz, coupling energy through a cylindrical quartz vessel to achieve target ion current densities of $2100\,\mathrm{A\,m}^{-2}$ . This paper presents fluid-kinetic modeling of LUPIN using the hybrid plasma equipment model where electrons are treated kinetically, and the simulations reveal that electron energy distribution function transitions from nearly Maxwellian in the core to bi-Maxwellian towards the edge. Parametric simulations investigate the effects of RF power, gas pressure, and frequency on plasma density, ion flux, and uniformity. Parametric sweeps reveal that increasing power shifts the primary ionization channel from molecular to atomic with diminishing flux gains due to skin-depth contraction and gas rarefaction. Higher frequency localizes heating and increases $\mathrm{H}_2^+$ and $\mathrm{H}_3^+$ delivery to the grid, while elevated pressure boosts ionization yet hinders ion transport due to increase in collisionality.

inductively coupled plasma↗

DOE OSTI2024

Bilayer Ion Trap Design for 2D Arrays

Junctions are fundamental elements that support qubit locomotion in two-dimensional ion trap arrays and enhance connectivity in emerging trapped-ion quantum computers. In surface ion traps they have typically been implemented by shaping radio frequency (RF) electrodes in a single plane to minimize the disturbance to the pseudopotential. However, this method introduces issues related to RF lead routing that can increase power dissipation and the likelihood of voltage breakdown. Here, we propose and simulate a novel two-layer junction design incorporating two perpendicularly rotoreflected (rotated, then reflected) linear ion traps. The traps are vertically separated, and create a trapping potential between their respective planes. The orthogonal orientation of the RF electrodes of each trap relative to the other provides perpendicular axes of confinement that can be used to realize transport in two dimensions. While this design introduces manufacturing and operating challenges, as now two separate structures have to be precisely positioned relative to each other in the vertical direction and optical access from the top is obscured, it obviates the need to route RF leads below the top surface of the trap and eliminates the pseudopotential bumps that occur in typical junctions. Here in this paper the stability of idealized ion transfer in the new configuration is demonstrated, both by solving the Mathieu equation analytically to identify the stable regions and by numerically modeling ion dynamics. Our novel junction layout has the potential to enhance the flexibility of microfabricated ion trap control to enable large-scale trapped-ion quantum computing.

42 ENGINEERING↗

DOE OSTI2026

Nb 3 Sn coating of SRF cavity by cosputtering from a composite target

Here, we deposited an Nb 3 Sn film on the inner surface of a 2.6 GHz Nb superconducting radio frequency cavity by cosputtering using a composite of Nb and Sn tube targets in a DC cylindrical magnetron sputtering system, followed by the thermal annealing of the coated cavity. An aluminum mockup cavity, replicating a 2.6 GHz Nb SRF cavity geometry, was utilized to optimize deposition parameters, resulting in cosputtered Nb–Sn films with an Sn content of 32–42 at. % on the beam tubes and equator positions. Several annealing conditions were investigated to improve the surface homogeneity of the Nb 3 Sn film. The best cosputtered Nb–Sn film was achieved after annealing at 600 °C for 6 h, followed by annealing at 950 °C for 1 h. The best process was applied to a Nb cavity, which was RF tested in a cryogenic dewar. RF testing of the Nb 3 Sn-coated cavity demonstrated a superconducting transition temperature of 17.78 K. The Nb 3 Sn cavity underwent light Sn recoating, followed by additional RF testing, resulting in the enhancement of the RF performance, primarily due to the improved surface homogeneity of the Nb 3 Sn coating.

Nb3Sn film↗

DOE OSTI2025

High-resolution leaf area index maps generated from unoccupied aerial system, Teller Mile 27, Seward Peninsula, Alaska

Leaf area index (LAI), a measure of the amount of one-side leaf area per ground unit, is an important indicator of plant carbon, energy, and water cycle. In the heterogeneous Arctic landscapes, it has been challenging to accurately measure LAI across species and space needed for Earth system model validation. Here, we use multispectral unoccupied aerial systems (UASs) to scale up and map leaf area index (LAI) , in a low-Arctic tundra landscape on the Seward Peninsula, Alaska. We linked previous published LAI measurements with high-resolution, UAS-collected multispectral data collected over the region of Next Generation Ecosystem Experiments in the Arctic (NGEE Arctic)’s Teller Mile Maker 27 site in 2022 to develop random forest (RF) machine learning models to predict and map LAI. 100 RF models were developed to account for uncertainties in ground LAI plot measurements and process scaling. This dataset includes a raster (*.tif) map of the mean LAI value of the 100 RF models, a raster (*.tif) map of the standard deviation of the RF-modeled LAI data, and a user guide (*.pdf).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Fermilab's controls development with virtual accelerator

Control Systems development is often the last thing considered when designing and building new equipment, e.g. a new detector or superconducting RF LINAC; however when the new equipment is installed, it is the first thing desired to be operational for testing. Due to frequent delays in building new equipment and project deadlines, control system development and testing is often curtailed. A way to alleviate this problem is to simulate the control system, though this will be challenging for complex systems.The Fermilab PIP-II (proton improvement plan - II) project is being constructed at Fermilab to deliver $800\,MeV$ protons of $>1\,MW$ beam power to replace the present LINAC for the remainder of the existing accelerator complex. The new LINAC consists of a warm front end (WFE), 23 superconducting RF cryomodules (of 5 types), and a beam transfer line (BTL) to the existing complex.The accelerator physics group has a parallel project to create a digital twin (DT) of the PIP-II accelerator. We have coupled the EPICS controls to this DT and are developing both the DT and EPICS software in parallel. This will allow us to develop the EPICS software framework, the HMIs, sequences, high level physics applications, and other services for use in a fully functional control system.This presentation will detail the work that we have performed to date and show demonstrations of controlling and monitoring the status of the accelerator, as well as future plans for this work.

Hanlet, Pierrick [Fermilab]↗

DOE OSTI2024

TRANSFER LEARNING FOR FIELD EMISSION MITIGATION IN CEBAF SRF CAVITIES

The Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab operates hundreds of super-conducting radio frequency (SRF) cavities in its two linear accelerators (linacs). Field emission (FE) is an ongoing operational challenge in higher gradient SRF cavities. FE generates high levels of neutron and gamma radiation leading to damaged accelerator hardware and a radiation hazard environment. During machine development periods, we performed gradient scans to record data capturing the relationship between cavity gradients and radiation levels measured throughout the linacs. However, the field emission environment at CEBAF varies considerably over time as the configuration of the radio frequency (RF) gradients changes and due to the changing behaviour of field emitters. An artificial intelligence/machine learning (AI/ML) approach with transfer learning could be a valuable tool to mitigate FE and lower the radiation levels. In this work, we mainly focus on leveraging the RF trip data gathered during CEBAF operations. We develop a transfer learning-based surrogate model for radiation detector readings given RF cavity gradients to track the CEBAF?s changing configuration and environment. Then, we could use the developed model as an optimization process for redistributing the RF gradients within a linac to minimize radiation levels.

Ahammed, K.↗

DOE OSTI2024

Microscopic understanding of the effects of impurities in low RRR SRF cavities

The SRF community has shown that introducing certain impurities into high-purity niobium can improve quality factors and accelerating gradients. We question why some impurities improve RF performance while others hinder it. The purpose of this study is to characterize the impurities of niobium coupons with a low residual resistance ratio (RRR) and correlate these impurities with the RF performance of low RRR cavities so that the mechanism of impurity-based improvements can be better understood and improved upon. The combination of RF testing, temperature mapping, frequency vs temperature analysis, and materials studies reveals a microscopic picture of why low RRR cavities experience low BCS resistance behavior more prominently than their high RRR counterparts. We evaluate how differences in the mean free path, grain structure, and impurity profile affect RF performance. The results of this study have the potential to unlock a new understanding on SRF materials and enable the next generation of high Q/high gradient surface treatments.

43 PARTICLE ACCELERATORS↗

DOE OSTI2026

Predicting initial trans-membrane pressure across cycles in the ultrafiltration process using random forest

With growing freshwater scarcity, direct potable reuse (DPR) systems that reclaim wastewater for drinking are becoming increasingly important for sustainable water supply. Reliable operation requires minimizing downtime in ultrafiltration (UF) units, where membrane fouling leads to elevated trans-membrane pressure (TMP). This study develops data-driven regression models based on random forest (RF) and autoregressive (AR) approaches to forecast the initial TMP at the start of each UF filtration cycle in a pilot-scale DPR system. The RF model consistently outperforms baseline methods, including historical mean, last observation carried forward, and AR models, across multiple forecast horizons, achieving the lowest root mean square error. To evaluate how different classes of process variables contribute to TMP dynamics over time, we examine the feature importance of independent input variables across multiple forecast horizons. This analysis provides insight into the temporal relevance of operational and sensor-derived features, guiding control and monitoring strategies. Additionally, the impact of hyperparameter tuning on TMP prediction performance is assessed for both direct and recursive RF modelling approaches. The proposed RF framework establishes a robust foundation for predictive monitoring and real-time optimization of UF operations, supporting sustainable and reliable water reuse.

direct potable reuse↗

DOE OSTI2024

Ultrasound preliminary cyber-physical evaluation

In this assessment, we focused on identifying unwanted RF emissions from the subject devices. This consisted of two major approaches: 1) Monitor for emitted RF during operation and ensure it is within expected bounds. 2) Inspect circuit board construction for any geometry or design patterns that could lead to RF emissions, whether intentional or unintentional. These patterns include: a) Single-ended PCB traces that could operate as an antenna. b) Insufficient shielding around typically “noisy” components such as switching power supplies. c) Free-hanging high-speed signal wires with no shielding that could emit RF. Suspicious components and design patterns were given a plausible reason to be included in the design. Any suspicious components or patterns warranted reason for deeper investigation. After more in-depth analysis no components were found to be intentionally malicious or had unexpected functionality.

42 ENGINEERING↗

DOE OSTI2024

TRANSFER LEARNING FOR FIELD EMISSION MITIGATION IN CEBAF SRF CAVITIES

Ahammed, K.↗

DOE OSTI2024

Microscopic Understanding of the Effects of Impurities in Low RRR SRF Cavities

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗