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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

Analysis of multipacting threshold sensitivity to the random distributions of the secondary electron yield parameters

The way multipacting develops, depends strongly on the secondary emission property of the surface material. The knowledge of secondary electron yield is crucial for accurate prediction of the multipacting threshold. Variations in secondary electron yield parameters from experimental measurements create uncertainty, stemming from handling and surface preparation, and these uncertainties significantly affect multipacting threshold predictions. Despite their significance, the previous studies on the multipacting phenomenon did not adequately address the effect of an assumed random distribution of the secondary emission parameters on the multipacting threshold. Therefore, this paper aims to provide a comprehensive statistical study on how the different random distributions of the secondary emission parameters and, as a result, the uncertainty in the secondary electron yield affect multipacting thresholds. We focus on three commonly used distributions, namely uniform, normal, and truncated normal distributions, to define the uncertainty of random inputs. We use the chaos polynomial expansion method to determine how much each of the random parameters contributes to the multipacting threshold uncertainty. Additionally, we calculate Sobol sensitivity indices to evaluate the impact of the individual parameters or groups of parameters on the model outputs and study how different random distributions of these parameters affected the Sobol index results.

physics↗
DOE OSTI2023

The influence of secondary electron yield uncertainty on the single-sided multipacting in dielectrics

Multipacting is an electrical discharge caused by the emission of secondary electrons which can occur in vacuum radio frequency systems. Generally multipacting is highly undesirable obstacle, which increases the noise level as well as the return loss of radio frequency systems. Therefore, a prediction of multipacting is necessary to avoid it during radio frequency system design. In this regard, the accurate evaluation of the factors that affect multipacting is required. One of the critical factors determining the multipacting development is the secondary electron yield of the material. In practice the emission properties of materials are not known very accurately. There are uncertainties in the measured values of this yield. In this paper, the generalized Polynomial Chaos (gPC) method is used to quantify uncertainty of the secondary electron yield. This method is verified by Monte Carlo simulation. The effect of uncertainty for two secondary electron yield parameters is then investigated on the multipacting using gPC method.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

NOVEL METHODS FOR IN SITU HIGH DENSITY SURFACE CLEANING SCRUBBING OF ULTRAHIGH VAC LONG NARROW TUBES TO REDUCE SECONDARY ELECTRON YIELD AND OUT GASSING

This project developed new methods for cleaning the inside surfaces of very long, narrow vacuum tubes used in particle accelerators. Traditional cleaning approaches are expensive, slow, or difficult to implement in accelerator tunnels. We designed and tested a portable plasma discharge cleaning system that uses lower-cost microwave and magnetron technologies to reduce outgassing and secondary electron emission from stainless steel and copper surfaces. The system, called the Plasma Discharge Test System (PDTS), allows accelerator components to be scrubbed more efficiently, which can improve performance and reduce maintenance costs for research and industrial applications.

POOLE, JOE HENRY [PRESIDENT]↗
DOE OSTI2023

Impact of photoexcitation on secondary electron emission: A Monte Carlo study

Understanding the transport of photogenerated charge carriers in semiconductors is crucial for applications in photovoltaics, optoelectronics, and photo-detectors. While recent experimental studies using scanning ultrafast electron microscopy (SUEM) have demonstrated that the local change in the secondary electron emission induced by photoexcitation enables direct visualization of the photocarrier dynamics in space and time, the origin of the corresponding image contrast still remains unclear. Here, we investigate the impact of photoexcitation on secondary electron emissions from semiconductors using a Monte Carlo simulation aided by time-dependent density functional theory. Particularly, we examine two photoinduced effects: the generation of photocarriers in the sample bulk and the surface photovoltage (SPV) effect. Using doped silicon as a model system and focusing on primary electron energies below 1 keV, we found that both the hot photocarrier effect immediately after photoexcitation and the SPV effect play dominant roles in changing the secondary electron yield (SEY), while the distribution of photocarriers in the bulk leads to a negligible change in SEY. Our work provides insights into electron–matter interaction under photo-illumination and paves the way toward a quantitative interpretation of the SUEM contrasts.

Physics↗
DOE OSTI2025

General kinetic ion-induced electron emission model for metallic walls applied to biased Z-pinch electrodes

A kinetic ion-induced electron emission (IIEE) model for general applications is developed to obtain the emitted electron energy spectrum for a distribution of ion impacts on a metallic surface. We assume an ionization cascade mechanism and use empirical models for the ion and electron stopping powers. The emission spectrum and the secondary electron yield (SEY) are validated for a variety of materials. The IIEE model is used to study the effect of IIEE on the plasma-material interactions of Z-pinch electrodes. Un-magnetized Boltzmann-Poisson simulations are performed for a Z-pinch plasma doubly bounded by two biased copper electrodes with and without IIEE at bias potentials from 0 to 9 kV. At the anode, the SEY decreases from 0 to 1 kV, but then increases at higher bias potentials. At the cathode, the SEY is much larger due to higher energy ion bombardment and grows with bias potential. As the bias potential increases, the emitted cathode electrons are accelerated to higher energies into the domain, collisionally heating the plasma. Above 1 kV, the heating is strong enough to increase the plasma potential. Despite SEY greater than 1, only a classical sheath forms as opposed to a space-charge limited or inverse sheath due to the emitted electron flux not reaching the space charge current saturation limits. Furthermore, the current in the emissionless cases saturates to a value lower than experiment. With IIEE, the current does not saturate and continues to increase with the 4 kV case, matching most closely with the experiment.

Carbon based materials↗
DOE OSTI2026

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

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

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Electron cloud simulations in the Fermilab booster

As part of Fermilab's Proton Improvement Plan-II (PIP-II),the Fermilab Booster synchrotron will operate at a higherintensity, increasing from 4.5 x 10^12 to 6.7 x 10^12 protons per pulse (ppp). A potential challenge for achievinghigh intensity performance arises from rapid transverse instabilities induced by electron cloud (EC). This researchpresents EC simulations using PyECLOUD, which is anadvanced computational tool that incorporates measurements of the secondary electron yield (SEY) from theBooster's combined function magnet material. By systematically varying beam parameters in PyECLOUD, such asbunch structure, SEY, bunch length, and intensity, it becomes possible to forecast the impact of EC effects on thebeam stability of the PIP-II era Booster.

43 PARTICLE ACCELERATORS↗
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

Advanced Diagnostics of Broad Spectrum Multipactor

Multipactor is a resonance event between electron emission and RF fields causing exponential secondary electron re-emission growth when the secondary electron yield of the primary electron impact energy exceeds unity. Multipactor is a serious problem in vacuum electron devices (VEDs) such as particle accelerators, radars, electronic warfare systems, directed energy devices, and even Hall effect thrusters. It also poses an even greater threat to space communication systems where high power, multi-channel links are required. The UC Davis and SLAC team will conduct basic research to advance the fundamental understanding of multipactor physics by developing and carrying out full spectrum, radio frequency (RF) laboratory tests aimed at understanding both single and two-surface multipactor phenomena and at evaluating novel multipactor mitigation approaches for accelerator, space-based RF systems, as well as high power microwave (HPM) applications.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Thermal analysis of RHIC arc dipole magnet cold mass with EIC beam screen

The existing RHIC storage rings – including their superconducting magnet arcs – will be used for the hadron storage ring of the Electron-Ion Collider (EIC). The vacuum chamber of these magnets was not designed for the EIC hadron beams, with shorter bunches and of higher average current than the RHIC beams. With the current stainless steel beam pipe, the resistive-wall (RW) heating will exceed the dynamic heat load budget. Limiting the RW heating is important to prevent the superconducting magnets from quenching and to maintain a low screen temperature necessary to impede the rise of RW heating (higher resistance at higher temperature) as well as to achieve desired ultra-high vacuum. In addition, simulations predict the formation of electron cloud which would further contribute to the dynamic heat load and could compromise the quality and stability of the beam. To reduce the resistive-wall heating and suppress electron cloud, a beam screen will be installed in the vacuum chamber of the RHIC SC magnets. The screen will have a high RRR copper layer at its inner face – useful to reduce the resistive-wall impedance thanks to its high conductivity especially at cryogenic temperatures – and will be coated with a thin layer of amorphous carbon, a material with low secondary electron yield to suppress the formation of electron clouds. The baseline solution envisages a screen that will be cooled by thermal contact to the 4.55 K beam pipe. Detailed thermal analysis have been conducted in ANSYS 2020 for an arc dipole cold mass equipped with a beam screen in order to study the feasibility of a passively-cooled screen and guide its design. Temperature-dependent thermal conductivity properties of all materials in the operating (cryogenic) temperature range are considered. Suitable assumptions and simplifications are made to model the magnet coil and calculate its homogenized thermal conductivity. Sensitivity studies with respect to layer thicknesses and area of contact are carried out and results are presented.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Electron Cloud Simulations in the Fermilab Booster

As part of Fermilab's Proton Improvement Plan-II (PIP-II), the Fermilab Booster synchrotron will operate at a higher intensity, increasing from 4.5×1012 to 6.7×1012 protons per pulse [ppp]. A potential challenge for achieving high-intensity performance arises from rapid transverse instabilities induced by electron cloud (EC). This research presents EC simulations using PyECLOUD, which is an advanced computational tool that incorporates measurements of the secondary electron yield (SEY) from the Booster's combined function magnet material. By systematically varying beam parameters in PyECLOUD, such as bunch structure, bunch length, and intensity, the EC effects on beam stability and overall performance of Booster can be predicted.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Spacecraft surface charging as a function of material properties

Spacecraft material behavior plays a very important role in space missions. Spacecraft immersed in plasma get charged by absorbing plasma particles and by emitting electrons from spacecraft surfaces via photoelectron and secondary electron emission. Spacecraft charging depends heavily on material properties such as work function, secondary electron yield, dielectric constant, and electric conductivity among other. Material properties are typically assumed to be static in charging models. However, it is well known that this is not the case in space. This makes spacecraft charging predictions very challenging. Material properties are well characterized before the spacecraft is put in orbit through characterization in the lab under clean conditions. However, once in space, material properties change due to the harsh and very dynamic space environment. We present a new capability to predict material behavior in space from first-principles modeling. The ongoing effort seeks to couple material models, density functional theory (DFT) and molecular dynamic (MD) codes, with environment models, plasma kinetic codes. This preliminary study will show results of surface charging as a function of material work function, dielectric constant, and conductivity.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Beam-Impedance Considerations for the EIC HSR Screen

The hadron storage ring (HSR) of the Electron-Ion Collider (EIC) will use the superconducting magnets from the Relativistic Heavy Ion Collider (RHIC). However, the beam pipes of these magnets show too large resistive-wall impedance and secondary electron yield to the HSR beams. The planned solution is to install beam screens that feature a thin film of amorphous carbon with low SEY on top of a high RRR copper layer for reduced impedance. This note discusses beam-impedance considerations that impact the EIC HSR beam screen design.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Project FELICIA - A probe to survey the RHIC magnet beampipe diameter for EIC beam screen insertion

The Electron Ion Collider (EIC) Hadron Storage Ring (HSR) will reuse many of the existing superconducting (SC) magnets of the RHIC storage rings. To comply with the beamline vacuum requirements in more demanding operational scenarios, the beampipe of the RHIC SC magnets will be equipped with low surface impedance, low secondary electron yield (SEY) beam screens. The installation of these beam screens will be done with the SC magnets as installed today, thus making it a critical operation for a timely EIC installation. The beam screen inner dimensions must be maximized to retain enough aperture to the beam. On the other hand, keeping enough clearance between the screen and the beampipe is critical to ensure a smooth beam screen installation. A survey probe was designed and built to measure the inner diameter of several RHIC SC magnets in-situ and provide critical data for the beam screen design optimization. This paper reports on the design of the probe and the results from the survey campaign.

43 PARTICLE ACCELERATORS↗
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↗