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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Low RF loss DC conductive ceramic for RF windows

Charging of RF windows has historically been problematic, frequently resulting in damage to the window severe enough that the window needs to be replaced. Many attempts have been made to prevent charging and therefore improve window lifetime, the most successful and common of which is coating the window with titanium nitride (TiN). Surface coatings such as TiN rely on the secondary electron yield of the coating material being lower than that of the ceramic window material, reducing the number of electrons emitted from a variety of mechanisms. An alternative approach is to introduce a small amount of DC conductivity to the ceramic itself, turning the traditionally insulating window into a mildly conductive one. This allows any charge on the surface of the window to drain rather than build until a discharge happens. A magnesium titanate ceramic has been developed with a small DC conductivity and used to make RF windows. Several window assemblies have been produced and tested, including 1.3 GHz waveguide and 650 MHz coaxial designs. The results of the conductive ceramic window test program will be presented.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

High Average Power RF Window with Improved Multipactor Coating

Multipactor emission can be a serious issue for vacuum electron devices operating at megawatt power levels. It can lead to catastrophic failure from surface arcs or excessive heating of ceramic windows. Titanium nitride is effective at suppressing multipactor emission; however, sputter coating is not strongly bonded to surfaces and issue related to lifetime have arisen. It’s difficult to ensure a uniform coating over large surfaces. This research investigated atomic layer deposition (ALD) as an improved alternative to sputtered coatings. Test windows were fabricated and coated with TiN using ALD, then tested for RF loss and secondary emission. All ALD samples showed RF loss less than 0.01dB with secondary emission yield equal to or better than reported measurements with sputter coated windows. The program also designed a preliminary ALD system capable of coating windows up to 24 inches in diameter.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Multipacting analysis of the SNS drift tube linac (DTL) RF vacuum window using Spark3d

An ongoing study at the Spallation Neutron Source (SNS) seeks to better understand and address potential multipacting issues associated with the Drift Tube Linac (DTL) RF vacuum windows. An analysis of several failed operational windows showed indications of excessive RF heating on the TiN-coated alumina ceramics. Coupled with vacuum bursts and arcing during conditioning and/or operational periods, these problems have been attributed to electron activity likely caused by multipacting. The status of the study, 3-D electromagnetic simulation results, mitigating techniques and a future experimental plan for studying multipacting in the SNS DTL vacuum windows are presented.

Toby, George↗
DOE OSTI2023

Resonant dynamics of one-side multipactor on dielectric

Breakdown of dielectric radio frequency (RF) windows is an important issue for particle accelerators and high-power RF sources. One of the common reasons for RF window failure is the multipactor on a dielectric surface. The multipactor may be responsible for excessive heating of the dielectric and discharge of charges that accumulated in the ceramic due to secondary emission. In this study, comprehensive self-consistent particle-in-cell simulations with space charge effect were performed. This was to better understand the dynamic of one-side multipactor development and floating potential on the dielectric induced by the emission. The important correlations between the multipactor parameters at saturation, the secondary emission properties of dielectric, and the applied RF field parameters have been found, which led to the conclusion that the dynamics of one-side multipactor on dielectric is a resonant phenomenon.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Low RF loss conductive ceramic for high power input coupler windows for SRF cavities

High power RF couplers connect transmission lines to cavities, providing power used to accelerate particle beam • Coupler also provides vacuum barrier for beam vacuum via RF windows • RF windows experience breakdown at much lower voltages than comparable insulators in DC fields • For large voltages, electron emission from “triple junction” and multipacting lead to window failure due to arching and/or thermal runaway.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

DC bulk conductive ceramic with low RF and microwave loss

A DC conductive, low RF/microwave loss titanium oxide ceramic provides, at room temperature, a bulk DC resistivity of less than 1×10 11 ohm-meters and an RF loss tangent of less than 2×10 −4 at 7.5 GHz and less than 2×10 −5 at 650 MHz. The resistivity is reduced by oxygen vacancies and associated Ti 3+ and/or Ti 4+ centers created by sintering in an atmosphere containing only between 0.01% and 0.1% oxygen. The reduced resistivity prevents DC charge buildup, while the low loss tangent provides good RF/microwave transparency and low losses. The ceramic is suitable for forming RF windows, electron gun cathode insulators, dielectrics, and other components. An exemplary Mg 2 TiO 4 —MgTiO 3 embodiment includes mixing, grinding, pre-sintering in air, and pressing 99.95% pure MgO and TiO 2 powders, re-sintering in air at 1400° C.-1500° C. to reduce porosity, and sintering at 1350° C.-1450° C. for 4 hours in an 0.05% oxygen and 99.05% nitrogen atmosphere.

Kanareykin, Alexei↗
DOE OSTI2024

Impurity transport in PISCES-RF

Linear plasma devices (LPD) utilizing a helicon plasma source, a high density light ion source, can generate impurities due to progressive erosion of the radio frequency (RF) transmission window caused by rectified sheath voltage. These source-born impurities can entrain and be transported by the plasma toward a target, affecting plasma-material interaction studies. Earlier work on material testing in Prototype-Materials Plasma Exposure eXperiment at ORNL revealed significant source impurity deposition on downstream targets. However, using a similar RF source, no target impurity deposition is observed in Plasma Interaction Surface Component Experimental Station (PISCES)-RF despite evidence of RF window erosion in the source region, thereby motivating the present work. Experimentally, using various magnetic field configurations upstream of the PISCES-RF plasma source and seeding titanium (Ti) impurities at various axial locations, impurity transport and deposition along the machine axis were investigated. It was found that Ti deposition was localized to the side of the plasma source where the Ti impurity was seeded. In contrast, aluminum (Al) deposition, originating from the sputtering of the helicon window, occurred predominantly upstream of the plasma source, suggesting an asymmetry in the axial transport of eroded RF window material. These observations suggest a stagnation of the parallel plasma flow immediately downstream of the plasma source, with impurity ions remaining unmagnetized near the source upstream. Al deposition in magnetic field-free regions in PISCES-RF indicates that sputtered Al impurities likely remained neutral due to their large ionization mean-free path under PISCES-RF conditions. Plasma modeling and simulation supported this, indicating that Al-neutrals transport toward the helicon source upstream for low electron density cases. It was found that the Larmor radius of the Al ions was greater than the plasma radius towards the source upstream and remained weakly magnetized in PISCES-RF, meaning that plasma source-born impurities are not efficiently entrained in the plasma flow. These findings provide critical insights into impurity transport in helicon plasma-based LPDs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Low RF Loss DC Conductive Ceramic for High Power Input Coupler Windows for SRF Cavities

Euclid Techlabs, LLC is developing a low RF loss/DC conductive MgTi ceramics for high power input coupler windows for SRF cavities, under DOE SBIR phase II grant DE-SC0017150. JLab was subcontracted to: fabricate two 500 kW capable pre-stressed coaxial windows; provide an RF testing fixture, and test the window with low power and high power RF. This collaboration helped to develop a better material for high power RF windows, with low RF loss and less prone to arcing, with the potential to improve the state of the art high power RF window performance.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Erosion of high-Z refractory coatings for helicon plasma source window

Proto-MPEX (Materials Plasma Exposure eXperiment), a linear plasma device (LPD), using a high power radio frequency (RF) (⩾100 kW, 13.56 MHz) helicon plasma source, has suffered RF sheath-induced window erosion. The sputtered impurities from the window surface transport toward the downstream target affecting plasma-material interaction studies. The rectified sheath voltage formed was high enough to cause window erosion by light ions due to its low-Z components (e.g. Si 3 N 4 and AlN). Hence, we are proposing impurity mitigation strategies, which involve the application of a Faraday screen to lower the rectified sheath voltage and the application of high-Z refractory coatings on the existing window plasma-facing surface. In this work, we report the erosion of two different coatings, i.e., tantalum oxide (Ta 2 O 5 ) and hafnium oxide (HfO 2 ) on a silicon nitride (Si 3 N 4 ) window material under conditions of low-energy deuterium (D) ion impact, well below the Ta 2 O 5 sputtering energy threshold (i.e. 250 eV). The test samples were RF-biased and exposed to a high D-ion fluence (∼10 26 m −2 ) in Plasma Interaction with Surface Component Experimental Station (PISCES-A) LPD. The experimentally measured sputtering yields of the high-Z refractory coatings below the sputtering energy threshold of Ta 2 O 5 indicate an increased erosion due to the plasma impurities, especially due to oxygen. Improving the vacuum level could reduce the oxygen impurities and increase the lifespan of the coated helicon window for plasma operation. Post-surface analysis indicates no preferential erosion of oxygen or enrichment of the high-Z surface component. This is likely due to an effective energy transfer from the impurity ion for sputtering of the high-Z component in the coating. With the reduced rectified sheath voltage at the window surface and improved vacuum conditions, the proposed high-Z refractory coatings offer a promising solution for reducing window erosion in future MPEX plasma operations at ORNL.

RF bias↗
DOE OSTI2024

Empowering Machine Learning Forecasting of Labquake Using Event‐Based Features and Clustering Characteristics

Abstract Following recent advances of machine learning (ML), we present a novel approach to extract spatiotemporal seismo‐mechanical features from Acoustic Emission (AE) catalogs to empower ML‐based forecasting. The AE data were recorded during laboratory stick‐slip experiments on granite samples cut by rough faults. Based on the features computed for a past time window, a random forest (RF) classifier is used to forecast the occurrence of a large magnitude event ( M AE > 3.5) in the next time window. Event‐based features allow us to associate informative time‐space characteristics to each feature and nearest‐neighbor clustering analysis enables us to separate background and clustered seismicity and train individual models. The results show that the separation of AEs enhances the forecasting accuracy from 73.2% for the entire catalog up to 82.1% and 89.0% if background and clustered events are used separately. The presented new approach may be upscaled for applications to forecast tectonic earthquakes.

Karimpouli, Sadegh↗
DOE OSTI2026

Python-EPICS RF Conditioning Automatic Control System at the Spallation Neutron Source

The RF Test Facility (RFTF) at the Spallation Neutron Source (SNS) is used for the conditioning of RF compo-nents such as ceramic vacuum windows and power cou-plers prior to their installation in the H- ion linear accel-erator. This process exposes components to high-power RF fields and thermal cycling to improve performance and remove surface impurities. To automate and optimize this process, a Python-based EPICS control system was developed alongside targeted hardware upgrades. The system enables real-time monitoring and control of RF power levels, temperature, and vacuum pressure. A user-friendly graphical interface was implemented using CS-Studio (Phoebus), allowing operators to adjust parameters and collect data efficiently. The system integrates a High-Power Protection Module (HPM) for interlocks based on vacuum and arc detection, ensuring safe operation. These upgrades have significantly improved the efficiency, accuracy, and safety of RF conditioning at the SNS RFTF. This paper describes the updated RF conditioning sys-tem, highlighting the software and hardware develop-ments and their application in support of the Proton Pow-er Upgrade (PPU) project.

Lee, Sung-Woo [ORNL] (ORCID:000000030915835X)↗
DOE OSTI2022

INITIAL STUDIES OF CAVITY FAULT PREDICTION AT JEFFERSON LABORATORY

The Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Laboratory is a CW recirculating linac that utilizes over 400 superconducting radio-frequency (SRF) cavities to accelerate electrons up to 12 GeV through 5-passes. Recent work has shown that, given RF signals from a cavity during a fault as input, machine learning approaches can accurately classify the fault type. In this paper we report on initial results of predicting a fault onset using only data prior to the failure event. A data set was constructed using time-series data immediately before a fault (’unstable’) and 1.5 seconds prior to a fault (’stable’) gathered from over 5,000 saved fault events. The data was used to train a binary classifier. The results gave key insights into the behavior of several fault types and provided motivation to investigate whether data prior to a failure event could also predict the type of fault. We discuss our method using a sliding window approach and report on initial results. Recent modifications to the low-level RF control system will provide access to streaming signals and we outline a path forward for leveraging deep learning on streaming data

Vidyaratne, Lasitha↗
DOE OSTI2022

Development of a direct-sampling RF receiver for precision beam charge measurements in the MOLLER experiment

Here, we have developed and tested a direct-sampling RF receiver capable of measuring the amplitude of a 1497 MHz sinusoidal beam signal in 0.5 ms integration windows with a relative uncertainty of better than 10 parts per million. The receiver is intended for measuring signals from beam current monitoring cavities on the beamline of the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab. The beam signal strength, frequency, and integration window fulfill the thus far unmet requirements of the upcoming MOLLER experiment to measure the beam charge for different helicity states.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Accelerating cavity fault prediction using deep learning at Jefferson Laboratory

Abstract Accelerating cavities are an integral part of the continuous electron beam accelerator facility (CEBAF) at Jefferson Laboratory. When any of the over 400 cavities in CEBAF experiences a fault, it disrupts beam delivery to experimental user halls. In this study, we propose the use of a deep learning model to predict slowly developing cavity faults. By utilizing pre-fault signals, we train a long short-term memory-convolutional neural network binary classifier to distinguish between radio-frequency (RF) signals during normal operation and RF signals indicative of impending faults. We optimize the model by adjusting the fault confidence threshold and implementing a multiple consecutive window criterion to identify fault events, ensuring a low false positive rate. Results obtained from analysis of a real dataset collected from the accelerating cavities simulating a deployed scenario demonstrate the model’s ability to identify normal signals with 99.99% accuracy and correctly predict 80% of slowly developing faults. Notably, these achievements were achieved in the context of a highly imbalanced dataset, and fault predictions were made several hundred milliseconds before the onset of the fault. Anticipating faults enables preemptive measures to improve operational efficiency by preventing or mitigating their occurrence.

43 PARTICLE ACCELERATORS↗