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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Generating and Sustaining Microplasma with Microwaves (Final Report)

Plasma can be generated in spaces ranging in size from astronomical down to the microscopic. The physics that describes the gas breakdown is different at each size scale. The dominant physical phenomenon also depends on the type of electromagnetic field that drives the breakdown – static, AC, RF, microwave, visible. This project, staffed by undergraduate researchers and their mentor, focused on plasma generated in the size range of 10 to 500 micrometers using microwave energy. This project was motivated by the prior observation that plasma can only be generated in microgaps when the gas is above a certain gap-dependent pressure, here called the transition pressure. A microwave-driven microgap was designed and constructed in this project and then used to measure the electric field required to initiate plasma over a wide range of pressures from 0.1 Torr to 760 Torr (1 atmosphere).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Field Emission Mitigation in CEBAF SRF Cavities Using Deep Learning

The Continuous Electron Beam Accelerator Facility (CEBAF) operates hundreds of superconducting radio frequency (SRF) cavities in its two main linear accelerators. Field emission can occur when the cavities are set to high operating RF gradients and is an ongoing operational challenge. This is especially true in newer, higher gradient SRF cavities. Field emission results in damage to accelerator hardware, generates high levels of neutron and gamma radiation, and has deleterious effects on CEBAF operations. So, field emission reduction is imperative for the reliable, high gradient operation of CEBAF that is required by experimenters. Here we explore the use of deep learning architectures via multilayer perceptron to simultaneously model radiation measurements at multiple detectors in response to arbitrary gradient distributions. These models are trained on collected data and could be used to minimize the radiation production through gradient redistribution. This work builds on previous efforts in developing machine learning (ML) models, and is able to produce similar model performance as our previous ML model without requiring knowledge of the field emission onset for each cavity.

Ahammed, K.↗
DOE OSTI2026

Online LIBS–ML Framework for Dynamic Characterization of Heterogeneous Waste-Derived Gasification Feedstocks

LIBS−ML framework for real time feedstock characterization during continuous conveyor transport Heterogeneous waste derived feedstocks (e.g., waste coal, biomass and blends) introduce rapid variability in heating value and ash chemistry that affect gasifier operation, yet conventional laboratory characterization techniques are too slow to support proactive control. To address this gap, this study reports on an online, in situ, dynamic characterization framework that couple’s laser-induced breakdown spectroscopy (LIBS) with leakage safe machine learning (ML) regression to deliver real time, decision quality predictions of gasifier relevant properties. A controlled sample matrix spanning two different waste coals, two different biomasses, and engineered blends under two particle size conditions were constructed and benchmarked using standardized laboratory analyses for proximate/ultimate properties and ash composition. LIBS spectra were acquired dynamically as material flowed on a conveyor belt, using high energy 1064 nm laser ablation and shot averaging to improve repeatability and precision. Supervised regression models (multi layer perceptron (MLP) /artificial neural network (ANN), random forest (RF), and support vector regression (SVR)) and an optimized weighted ensemble were trained on emission line feature sets using nested cross validation with Bayesian hyperparameter tuning and validated against an independent hold out set. The proposed LIBS−ML workflow achieves near laboratory predictive fidelity across parametric targets (including higher heating value (HHV), ash content, fixed carbon, sulfur, major ash forming oxides, and initial deformation temperature (IDT)), with the weighted ensemble providing a robust default predictor under dynamic measurement conditions. These results demonstrate a practical pathway for real time feedstock characterization that can enable feedforward adjustments and more resilient gasifier operation for variable quality waste derived fuels.

Biomass↗
DOE OSTI2025

First on-line commissioning experiments at the St. Benedict facility

Nuclear beta decays provide an excellent probe of fundamental symmetries due to their mediation by the weak interaction. In particular, precise measurements of these decays provide constraints on the unitarity of the Cabbibo-Kobayashi-Maskawa (CKM) quark-mixing matrix. While superallowed pure Fermi decays currently set the most precise limits, the alternative suite of superallowed mixed mirror decays has been ill-studied. These nuclei can provide an important consistency check of calculation and measurement methods employed for the pure Fermi decays, more critically needed now in the wake of a 2.4σ deviation from unitarity of the CKM matrix. In order to remedy the gap in data for mirror decays, the Superallowed Transition Beta-Neutrino Decay Ion Coincidence Trap (St. Benedict) facility is being commissioned at the University of Notre Dame’s Nuclear Science Laboratory (NSL). In this paper, we present first results of the commissioning of the St. Benedict facility on-line at the TwinSol radioactive beam facility. The results of initial commissioning experiments involving the St. Benedict gas catcher, RF carpet, RFQ ion guide and RFQ cooler-buncher will be presented.

beta decay↗
DOE OSTI2020

Electron Bernstein wave conversion of high-field side injected X-modes in QUEST

This paper presents a detailed design of the Q-shu University experimental steady state spherical tokamak's (QUEST's) high-field side (HFS) injection system for electron Bernstein wave (EBW) excitation and the results of an experimental comparison of the HFS eXtraordinary X-mode and low-field side (LFS) ordinary O-mode injection of 8.2 GHz radio frequency (RF) power. Waveguides, as an alternative to mirror polarizers for transmitting RF X-mode power from LFS to HFS for EBW conversion, were used instead of the installation of an RF mirror. Testing of LFS-to-HFS RF power transmission at 8.2 GHz, using an RG-50-type vacuum waveguide in a bench-scale device filled with SF6 gas at 0.03 Mpa, revealed that an RF power of 10.8 kW could traverse the fundamental electron cyclotron resonance layer for 60 s without breakdown. The short-length, open-ended waveguide antenna used in the HFS injection-induced wave diffraction reduced the efficiency of power delivery to the upper hybrid resonance (UHR) by approximately 7% at an electron temperature of 50 eV. The HFS injection was able to produce brighter camera images than the standard LFS injection. The location of the UHR, as estimated by measuring the density with an interferometer, agreed with its location as measured by plasma radiation low-field, side-edge positions shown by fast camera imaging. This indicates that the plasma was produced by mode-converted EBW. The HFS injection had an absorption efficiency of 96%, compared to 40% for LFS. A greater fluctuation of floating potential adjustable to the lower hybrid wave (LHW) was observed in the HFS case by installing a Langmuir probe, confirming that EBW conversion efficiency was higher in the HFS case. Moreover, after setting the poloidal field to B PF = 7.6 mT, plasma current (I P ) in the HFS peaked at 1.3 kA, as opposed to 0.3 kA for LFS, despite LFS injection having a total power of 55 kW, compared to 40 kW for HFS. However, as the impurity level was comparatively high, it is believed that this I P is dominated by pressure-drive, which makes it difficult to analyze EBWCD. Finally, the line-integrated density in the HFS injection peaked at 1.6 × 10 18 m -2 , compared to 8 × 10 17 m -2 in the LFS one.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Modeling of Thermal Quench in Superconducting RF Cavities

Superconducting radio frequency (SRF) cavities are often limited by thermal quench, which is an excessive electromagnetic heating that occurs in the high magnetic field area and expands thereafter forcing the cavity to lose its superconducting state. In this paper, we demonstrate how the quench phenomena can be modeled using a coupled electromagnetic thermal analysis. The proposed model takes into account the nonlinearity of the material properties at cryogenic temperature and the effect of Kapitza resistance. The proposed approach is used to compute the thermal quench field of a 3.9 GHz 9-cell accelerating cavity, a 2.815 GHz deflecting cavity, and a 1.3GHz 9-cell accelerating cavity. Here, the computed values of quenchfield are in good agreement with the measured ones observedduring vertical testing at 2 K. Without loss of generality, theproposed methodology can be applied to other cavity geometries.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Experimental Investigation of the Effects of Magnetic Mirrors on Plasma Transport in the Prototype Material Plasma Exposure Experiment

The Prototype Material Plasma Exposure eXperiment (Proto-MPEX) at Oak Ridge National Laboratory is developing a helicon radio frequency (RF) source for plasma production along with microwave electron heating and RF ion heating. Proto-MPEX has several magnetic mirrors that affect plasma transport. The magnetic field near the helicon source is ~ 0.05 T, and the peak magnetic field in Proto-MPEX is ~ 1.8 T, which results in a large magnetic well for particles sourced at the helicon transporting toward the target region. Keeping the helicon source field and the target field constant, experiments have been conducted by methodically changing the magnetic field, at a local axial location, within the source and the target. Plasma flow measurements using Mach probes have shown a decrease in the flow as a function of the magnetic mirror ratio. Plasma flows were further investigated with ion cyclotron resonant heating (ICH). Results with the addition of ICH measured upstream of the antenna have shown a decrease in Mach number as a function of mirror ratio when compared to helicon discharges. Such flow behavior demonstrated slowing down of the plasma due to the increased reverse plasma flow toward the helicon plasma source. However, in high magnetic fields, when the resonant magnetic field moved away from the ICH antenna, no effects on the plasma flow due to ICH were observed.

Kafle, Nischal↗
DOE OSTI2025

Experiments to validate Thermodynamics and Transport models of Strongly Coupled Dusty Plasma Matter (Final Technical Report for DE-SC0023416)

The goal of this two-year grant is to provide access to the PI to dusty plasma experimental facilities at the DOE-funded Collaborative Research Facility Magnetized Plasma Research Laboratory, Auburn University to become a user of that facility, to obtain experimental data to support another ongoing grant DE-SC0021146 (an Early Career Award to the PI that is focused on modeling of dusty plasma thermodynamics and transport processes), to generate experimental data for funding proposals, and to provide exposure to University of Memphis students to advanced experimental techniques. The following technical accomplishments were made: 1. Development of a novel Bidirectional Electrode Control Arms Assembly (BECAA) for producing perfect 2D grain layers for complex plasma experimentation. BECAA uses movable electrode arms to tilt or move the electrode in a RF discharge from outside the chamber, allowing for the manipulation of grain clouds without needing to change the plasma parameters or gas pressure. This work addresses a longstanding gap in the literature for a method to produce clusters of selectable number of grains and that are perfectly two dimensional as opposed to being only quasi-2D. 2. Experimental investigation of the structural properties of finite-N clusters with N=2 to 50. Individual particle behavior in clusters could vary from grain to grain and this study measured systematically produced clusters for two different grain sizes. Analysis (funded by another grant DE-SC0021146) is currently underway to quantify the differences between grains that are found on the surface vs. the interior of clusters, the shell structure, and the decay of correlations in position, velocity, and kinetic energy. 3. An experimental method to measure the structural entropy of clusters was developed by observing the self-induced structural transitions between various possible arrangements. In a series of heating and cooling cycles, the number of times each possible arrangement was attained was experimentally observed and used to compute the probability of existence of that arrangement, and subsequently the configurational entropy of the cluster. Analysis (funded by another grant DE-SC0021146) is currently underway to produce the entropy of clusters as a function of the number of grains and use the same to compute thermodynamic state variables for 2D complex plasma/grain clusters. 4. A preliminary experimental study of multibody collisions between N grains (N=2 – 10) was conducted. The clusters were produced using the BECAA technique and velocities were imparted to the grains using manipulation laser pulses. Analysis (funded by another grant DE-SC0021146) is currently underway to develop a theoretical framework to describe multibody collisions analogous to classical two-body interactions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Machine Learning for Predicting Multipactor Susceptibility in Planar RF Structures

Multipactor discharge is a persistent challenge in high-power microwave (HPM) and accelerator systems, where secondary electron avalanches can cause heating, vacuum degradation, and failure. This work presents the first supervised machine learning (ML) framework for multipactor prediction, trained on high-fidelity 3D Particle-in-Cell (PIC) simulation data in planar geometries. The model maps operational, geometric, and material-dependent secondary electron yield (SEY) parameters to the time-averaged electron growth rate, enabling rapid reconstruction of susceptibility charts. Among the models evaluated, tree-based ensemble methods such as Random Forest and Extra Trees demonstrate superior generalization to unseen materials compared to neural networks such as multilayer perceptron (MLP). Performance metrics, including Intersection over Union (IoU), Structural Similarity Index Measure (SSIM), and Pearson correlation, show close agreement with simulation benchmarks. Principal Component Analysis attributes generalization limits to material feature-space disjointedness.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

LINAC Longitudinal Simulation and Measurement of Output Energy

The Fermilab Linac, a pivotal and historic accelerator at Fermilab, is crucial to the laboratory's operations, supplying a 400 MeV beam to various acceleration facilities. Due to daily variations in the Linac's output energy, precise monitoring and machine tuning are important to ensure the exiting energy meets the Booster's acceptance criteria. To address this, Beam Position Monitors (BPMs) are employed to assess and adjust the beam's energy, providing essential data on both the transverse position and longitudinal phase of the beam. We also aim to regulate the longitudinal phase profile to match our simulation predictions. By utilizing a Python-based simulation and beam data from three BPMs, we can determine the optimal phasing correction required for the final RF stage to achieve the desired energy. Currently, the calculations of longitudinal phase profile are based on simulations, so additional research is needed to verify if the predicted longitudinal phase distribution aligns with actual real-world data.

Safaryan, Milena↗
DOE OSTI2022

Nanoscale laser flash measurements of diffuson transport in amorphous Ge and Si

The thermal properties of amorphous materials have attracted significant attention due to their technological importance in electronic devices. In addition, the disorder-induced breakdown of the phonon gas model makes vibrational transport in amorphous materials a topic of fundamental interest. In the past few decades, theoretical concepts, such as propagons, diffusons, and locons, have emerged to describe different types of vibrational modes in disordered solids. However, experiments can struggle to accurately determine which types of vibrational states carry the majority of the heat. In this study, we use nanoscale laser flash measurements (front/back time-domain thermoreflectance) to investigate thermal transport mechanisms in amorphous Ge and amorphous Si thin-films. We observe a nearly linear relationship between the amorphous film’s thermal resistance and the film’s thickness. The slope of the film’s thermal resistance vs thickness corresponds to a thickness-independent thermal conductivity of 0.4 and 0.6 W/(m K) for a-Ge and a-Si, respectively. This result reveals that the majority of heat currents in amorphous Si and Ge thin films prepared via RF sputtering at room temperature are carried by diffusons and/or propagons with mean free paths less than a few nanometers.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Demonstration of nitrogen-incorporated ultrananocrystalline diamond photocathodes in a RF gun environment

Quantum efficiency (QE), intrinsic emittance, and robustness are the three most important figures of merit for photocathodes, the first two determine the ultimate achievable brightness of an electron beam, and the third one directly correlates with the complications of a beamline design. Nitrogen-incorporated ultrananocrystalline diamond [(N)UNCD] materials are promising candidates for photocathode applications due to their remarkable electron emission performance as well as the moderate vacuum requirement. Two (N)UNCD photocathodes have been characterized in a realistic RF gun environment with the nicely balanced performance of all three figures of merit. In this work, the QE of the first (N)UNCD cathode (stored in air for two years before the test) was found to be 3.8 x 10 –4 using a 262 nm UV laser and a cathode surface field of 30MV/m. It was found that the QE of the second (N)UNCD sample (grown days before the test) was nearly the same and, therefore, demonstrates the exceptional environmental tolerance of the material. The intrinsic emittance of (N)UNCD was measured to be 1.00 μm/mm.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Spurious regulatory connections dictate the expression-fitness landscape of translation factors

During steady-state cell growth, individual enzymatic fluxes can be directly inferred from growth rate by mass conservation, but the inverse problem remains unsolved. Perturbing the flux and expression of a single enzyme could have pleiotropic effects that may or may not dominate the impact on cell fitness. Here, we quantitatively dissect the molecular and global responses to varied expression of translation termination factors (peptide release factors, RFs) in the bacterium Bacillus subtilis. While endogenous RF expression maximizes proliferation, deviations in expression lead to unexpected distal regulatory responses that dictate fitness reduction. Molecularly, RF depletion causes expression imbalance at specific operons, which activates master regulators and detrimentally overrides the transcriptome. Through these spurious connections, RF abundances are thus entrenched by focal points within the regulatory network, in one case located at a single stop codon. Such regulatory entrenchment suggests that predictive bottom-up models of expression-fitness landscapes will require near-exhaustive characterization of parts.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Thermocouples in Resistive and Induction Furnaces Operated in Strong Magnetic Fields

The thermomagnetic processing methods require an understanding of the in situ temperatures experienced by the workpieces. When commonly used thermocouples (TCs) are employed in induction furnaces, RF fields can contribute additional temperature uncertainties to the ones arising from the use of strong magnetic fields. Focusing on temperatures between 300 ° C and 1000 ° C produced by induction and resistive furnaces, the readings generated by Type-K TCs were contrasted to the ones produced by Type-S and Type-N sensors for magnetic fields up to 9 T. Overall, when comparing Type-K response to temperatures above 700 ° C in both zero field and high field ( ≤9 T), the differences amounted to less than 1% and when continuously measured has a linear relationship to the strength of the applied field. The relative invariance of Type-N and Type-S TCs was confirmed. In conclusion, these findings suggest that the use of TCs in high magnetic fields remains a viable option for applications, although the precision depends on the type used.

Tener, Zachary P. [Oak Ridge National Laboratory (↗
DOE OSTI2024

SRF CAVITY FAULT PREDICTION USING DEEP LEARNING AT JEFFERSON LAB

In this study, we present a deep learning-based pipeline for predicting superconducting radio-frequency (SRF) cavity faults in the Continuous Electron Beam Accelera-tor Facility (CEBAF) at Jefferson Lab. We leverage pre-fault RF signals from C100-type cavities and employ deep learning to predict faults in advance of their onset. We train a binary classifier model to distinguish between stable and impending fault signals. Test results show accuracies exceeding 99% for distinguishing between normal signals and pre-fault signals from a class of more slowly developing fault types, such as microphonics. We describe results from a proof-of-principle demonstration on a realistic, imbalanced data set and report performance metrics. Encouraging results suggest that future SRF systems could leverage this framework and implement measures to mitigate the onset in more slowly developing fault types.

Rahman, M.↗
DOE OSTI2024

The ion-gas-neutral interactions with surfaces-2 (IGNIS-2) facility for the study of plasma–material interactions

The Ion-Gas-Neutral Interactions with Surfaces-2 (IGNIS-2) surface science facility has been designed at the Pennsylvania State University with the specific purpose of enabling experiments to study plasma–material interactions. This in situ surface modification and characterization facility consists of multiple reconfigurable substations that are connected through a central transfer chamber. This fully connected vacuum system ensures that the physical and chemical properties of samples are not altered between surface modification and analysis. The modification techniques in IGNIS-2 include a low-energy (<300 eV), high-flux (up to 1016 cm−2 s−1) broad-beam ion source, a liquid metal dropper, a lithium injection system, an RF sputter source, and an evaporator. Its characterization techniques include charged particle-based techniques, such as low-energy ion scattering (enabled by two <5 keV ion sources) and x-ray photoelectron spectroscopy, and photon and light-based techniques, such as x-ray fluorescence, multi-beam optical stress sensors, and optical cameras. All of these techniques can be utilized up to mTorr pressures, allowing both in situ and in operando studies to be conducted. Results are presented on lithium wetting experiments of argon-irradiated tungsten-based composites, surface stress measurements of tungsten films during deuterium ion irradiation, and temperature-programmed desorption of deuterium-irradiated graphite to demonstrate the in situ capabilities of this new facility.

Instruments & Instrumentation↗
DOE OSTI2023

Flux Expulsion and Material Properties of Niobium Explored in 644-650 MHz Cavities

Upcoming projects requiring high-Q ~650 MHz medium-to-high-${\beta}$ elliptical cavities drive a need to understand magnetic RF loss mechanisms and mitigations in greater detail. High-temperature annealing and fast-cooldowns have proven effective techniques for promoting magnetic flux expulsion in cavities, however the extent of their effectiveness has been observed to vary between niobium material lot and vendor. We explore the fast-cooldown method, and high-temperature annealing (900{\deg}C) in 644-650 MHz cavities fabricated from two different niobium vendors: Tokyo-Denkai, and Ningxia. which promote flux-expulsion efficiency. Using EBSD and PPMS methods, we aim to trace cavity flux expulsion efficiency to specific, measurable properties of the bulk niobium material, which, if identified, can lead to methods by which the flux expulsion properties of Nb material can be predicted prior to cavity fabrication, and can enable fine-tuning of cavity temperature treatments.

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

Diagnosing Ghost Bunches with the Upstream Extinction Monitor in the Mu2e Experiment

The Mu2e experiment has a stringent requirement for extinction of the pulsed proton beam, referring to the elimination of particles between proton bunches to a relative level of 10$^-10$, which means a single out-of-time particle in the inter-pulse gaps for every 250 complete proton pulses. As the construction of the Mu2e experiment nears completion, it is crucially important to make an early measurement of the beam extinction in its current condition. Hence the upstream extinction monitor was constructed and operated to probe for problems in the proton pulse structure or a higher than expected incidence rate of out-of-time particles. The analysis in this work comes from data taken in March 2026. The long data run showed a significant presence of out-of-time particles from ghost bunches in the Delivery Ring approximately 388 ns after the centers of the main proton pulses. These are hypothesized to be the result of a combination of a RF frequency mismatch, particle space charge, and machine impedance during the rebunching sequence in the Recycler Ring, which can lead to particles leaking into adjacent buckets, but further studies and simulations are needed to confirm this

Hensley, R. [UC, Davis] (ORCID:0000000216064485)↗