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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

RF Sources for Electron Accelerators With a focus on high-duty-factor, low-to-moderate energy architectures

A charged particle, such as an electron or a proton, is accelerated through its interaction with either a static (DC) or time-varying (RF) electric field. The magnitude of the accelerating field, or gradient, is typically given in units of volts per meter; in charged-particle accelerators, fields are usually expressed as kV/m or MV/m. The energy of the accelerated particle is usually expressed in terms of electron volts, or eV. An electron starting at rest at ground potential, and accelerated to an electrode with a potential of 1 kV, will have an energy of 1 keV.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Concept of circular-linear energy recovery accelerator to probe the energy frontier

Energy-frontier accelerators provide powerful tools performing high precision measurements confirming the fundamentals of the physics and broadening new research horizons. Such machines are either driven by circular or linear accelerators. The circular machines, having the centre-of-mass (CM) energy values reaching 200 GeV (for leptons) and above, experience beam energy loss and quality dilution, for example, due to synchrotron radiation, limiting the overall CM energy achievable and requiring a constant energy top-up to compensate the loss and the beam quality dilution. Linear colliders overcome these limitations, while the finite capabilities of generating high average current beams limits the luminosity. This is partially compensated by the quality of the colliding beams. In this work, we suggest a novel design of circular-linear accelerator based on the merging of the “non-emitting”, low-energy storage rings and energy recovery linear accelerators. We suggest using the recently considered dual-axis asymmetric cavities to enable the operation of such a system, and in particular the energy recovery from spent, high-intensity beams. The machine considered, under the scope of the SNOWMASS-2021 initiative, can be potentially used to reach ultimate energy frontiers in high-energy physics as well as to drive next generation light sources. The merging of circular and linear systems, and applications of dual axes cavities, should allow the maintaining of high beam quality, high luminosity, and high energy efficiency, while offering a flexible energy management and opening clear opportunity for reducing the running cost. We note that the numbers shown in the paper are for illustration purpose and can be improved further.

43 PARTICLE ACCELERATORS↗
DOE OSTI2018

Advances in high gradient normal conducting accelerator structures

Here, this paper reviews the current state-of-the-art in understanding the phenomena of ultra-high vacuum radio-frequency (rf) breakdown in accelerating structures and the efforts to improve stable operation of the structures at accelerating gradients above 100 MV/m. Numerous studies have been conducted recently with the goal of understanding the dependence of the achievable accelerating gradients and breakdown rates on the frequency of operations, the geometry of the structure, material and method of fabrication, and operational temperature. Tests have been conducted with single standing wave accelerator cells as well as with the multi-cell traveling wave structures. Notable theoretical effort was directed at understanding the physical mechanisms of the rf breakdown and its statistical behavior. Finally, the achievements presented in this paper are the result of the large continuous self-sustaining collaboration of multiple research institutions in the United States and worldwide.

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

Explainable physics-based constraints on reinforcement learning for accelerator optimization

We present a reinforcement learning (RL) framework for optimizing particle accelerator experiments that builds explainable physics-based constraints on agent behavior. The goal is to increase transparency and trust by letting users verify that the agent’s decision-making process incorporates suitable physics. Our algorithm uses a learnable surrogate function for physical observables, such as energy, and uses them to fine-tune how actions are chosen. This surrogate can be represented by a neural network or by an interpretable sparse dictionary model. We test our algorithm on a range of particle accelerator optimization environments designed to emulate the Continuous Electron Beam Accelerator Facility at Jefferson Lab. By examining the mathematical form of the learned constraint function, we are able to confirm the agent has learned to use the established physics of each environment. In addition, we find that the introduction of a physics-based surrogate enables our RL algorithms to reliably converge for difficult high-dimensional accelerator optimization environments.

explainability↗
DOE OSTI2023

Stability of the modulator in a plasma-modulated plasma accelerator

We explore the regime of operation of the modulator stage of a recently proposed laser-plasma accelerator scheme [Phys. Rev. Lett. 127, 184801 (2021)], dubbed the plasma-modulated plasma accelerator (P-MoPA). The P-MoPA scheme offers a potential route to high-repetition-rate, GeV-scale plasma accelerators driven by picosecond-duration laser pulses from, for example, kilohertz thin-disk lasers. The first stage of the P-MoPA scheme is a plasma modulator in which a long, high-energy “drive” pulse is spectrally modulated by copropagating in a plasma channel with the low-amplitude plasma wave driven by a short, low-energy “seed” pulse. The spectrally modulated drive pulse is converted to a train of short pulses, by introducing dispersion, which can resonantly drive a large wakefield in a subsequent accelerator stage with the same on-axis plasma density as the modulator. In this paper we derive the 3D analytic theory for the evolution of the drive pulse in the plasma modulator and show that the spectral modulation is independent of transverse coordinate, which is ideal for compression into a pulse train. We then identify a transverse mode instability (TMI), similar to the TMI observed in optical fiber lasers, which sets limits on the energy of the drive pulse for a given set of laser-plasma parameters. We compare this analytic theory with particle-in-cell (PIC) simulations and find that even higher energy drive pulses can be modulated than those demonstrated in the original proposal.

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

Machine learning at the Spallation Neutron Source accelerator and target

We describe the ongoing efforts to apply Machine Learning techniques to improve the performance of our accelerator and target. Specially, we are looking to minimize halo beam losses in the absence of a proper physics model, automatically detect and log anomalies in the target support systems such as cooling, and detect and prevent errant beam pulses in the linac. We also describe the infrastructure we use to acquire and stream data to the GPU cluster for training, our code development cycle, and edge computing for model inference. To minimize halo beam losses, we use a Reinforcement Learning technique tested on a virtual accelerator. The target anomaly detection is trained on archived data using incomplete physics models and is made part of the existing target reporting system. The errant beam prevention analyzes beam current and beam phase waveforms as well as accelerator configuration data to predict errant pulses. We also develop continual learning to adapt to changes in the accelerator.

Accelerator Physics↗
DOE OSTI2021

Quantum dynamics of a nucleon in the Fermi accelerator

Highlights: • In nuclear physics, the Fermi accelerator is a coherent open quantum system. • There is not a true equilibrium for a nucleon‘s mean-energy in the Fermi accelerator. • Occupation of higher energy eigen-states remains even after the mean-energy plateaus. • This work paves the way for work on quantum tunnelling in the Fermi accelerator. The quantum dynamics of a particle in a one-dimensional box with an oscillating wall (the Fermi accelerator) is investigated. The model is applied to the motion of a single nucleon in the mean-field potential of a heavy atomic nucleus whose surface vibrates. By directly solving the time-dependent Schrödinger equation, both the state of the particle and its mean-energy are studied. The effects of the frequency of the wall oscillation on the nucleon’s energy are addressed. Its energy oscillates in phase with the moving wall for all frequencies, showing no chaotic behaviour. There is a large initial peak of the nucleon’s energy as the particle adjusts to the sudden change in the size of the box and a varying relaxation time as it plateaus towards lower energy and a partial equilibrium. Small oscillations in energy continue, since there cannot be a true equilibrium while the wall is moving. The quantum coherence between the different parts of the nucleon’s wave-function in real space is very much preserved. This research lays the foundation for future investigations into quantum tunnelling in the Fermi accelerator.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Accelerated tert -butyloxycarbonyl deprotection of amines in microdroplets produced by a pneumatic spray

Protection and deprotection of organic compounds in multistep reactions using functional groups such as tert-butoxycarbonyl (Boc), is widely performed in synthetic organic chemistry. Reaction rate acceleration studies in spray-based ionization methods (electrosonic spray, paper spray, nanospray) have become increasingly common. In this report, we demonstrate reaction rate acceleration of Boc deprotection using easy ambient sonic-spray ionization (EASI), a pneumatic technique which does not involve an applied voltage, in a teaching laboratory setting. The goal of this laboratory exercise was to explore acceleration in a previously unexplored spray-based reaction, while emphasizing in a pedagogic setting the importance of protecting groups for multistep synthesis. Rate acceleration factors of more than an order of magnitude were observed in the uncharged micron-sized droplets generated by EASI. The effect of reaction conditions on reaction acceleration was examined including changes in the type of acid, reagent concentration ratios and syringe pump flow rates. Student knowledge was assessed by pre-laboratory assignments, post-laboratory reports and oral interviews.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Simulation study of high-current 7 Li 3+ beam acceleration with laser ion source and RFQ linac using direct plasma injection

Accelerator-based neutron sources (ABNS) utilizing the 7 Li(p,n) 7 Be reaction in inverse kinematics offer strong forward-directed neutron emission, making them attractive for compact and clean neutron source with low background neutrons and unwanted radiation. However, practical use of such systems requires lithium ion beam currents that exceed the capability of conventional ion accelerators by two orders of magnitude. In this study, we numerically designed and evaluated a high-current acceleration system based on a direct plasma injection scheme (DPIS), combining a laser ion source (LIS) and a radio-frequency quadrupole (RFQ) linac. The ion extraction optics and RFQ entrance were optimized using IGUN, OPERA, and GPT, demonstrating that over 1.2 A-class beam current can be injected into the RFQ. The RFQ structure was designed under realistic engineering constraints including surface field strength (Kilpatrick factor) and RF power. GPT simulations showed that a 370 mA 7 Li 3+ beam can be successfully accelerated within a ±10 % energy spread. To validate downstream compatibility, we also designed a simplified medium-energy beam transport (MEBT) section and an interdigital H-type (IH) linac, confirming successful acceleration of a 320 mA beam to the total energy of 14 MeV. These results support the feasibility of the DPIS and RFQ approach as a promising solution for compact neutron sources and other high-intensity ion beam applications.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Accelerated oxidation of epoxy thermosets with increased O 2 pressure

Polymer oxidation is usually accelerated with temperature, which is therefore applied in nearly every experimental approach dealing with predictive materials aging. Because of this simple approach, we may tend to neglect that the effective concentration of oxygen also acts as a rate multiplier for oxidation. Increasing the oxygen partial pressure in an aging environment accelerates oxidation, and while there is often a near proportional increase initially, the effect of additional oxygen usually transitions to a saturation level at some elevated pressure. This has been theoretically described in the general autoxidation scheme and is well recognized. However, for many materials the exact rate behavior under moderately increased oxygen concentration remains to be established. We therefore review epoxy oxidation and offer a broader overview of its behavior under increased O 2 partial pressure. Experimental data are given for a few thermoset materials demonstrating their rate behavior under O 2 partial pressure up to 4 atm, meaning approximately 20 times more than under standard atmospheric conditions. Confirmative evidence suggests that epoxy materials will reach saturation oxidation rates only at significantly higher O 2 partial pressure. In such a high-pressure regime it is theoretically possible to not only accelerate oxidation, but to transition into a condition where O 2 diffusion can be increased without further accelerating the oxidation rate. Finally, this can reduce diffusion limited oxidation effects under specific accelerated aging conditions as a combination of temperature and O 2 partial pressure.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Interpreting accelerated tests on perovskite modules using photooxidation of MAPbI 3 as an example

Solar panels (modules) based on metal halide perovskites are following a fast track to commercialization. Unlike more established solar cell materials, there are not yet decades-long field observations to increase consumer confidence. The "physics and chemistry of failure" approach is used in other industries and estimates product degradation based on laboratory accelerated tests integrated with an understanding of degradation mechanisms. This work uses that approach to quantify the relationship between accelerated tests and projected product behavior for metal halide perovskite modules. Degradation involving photooxidation of methylammonium lead iodide is used to illustrate the method. Acceleration factors in common accelerated tests are found to be low. Conclusions emphasize that the accelerated tests on photovoltaics should not be interpreted as equivalent across module types or as a green light for commercialization unless supported by the appropriate field data or physics and chemistry of failure analysis.

14 SOLAR ENERGY↗
DOE OSTI2021

Turn-key constrained parameter space exploration for particle accelerators using Bayesian active learning

Abstract Particle accelerators are invaluable discovery engines in the chemical, biological and physical sciences. Characterization of the accelerated beam response to accelerator input parameters is often the first step when conducting accelerator-based experiments. Currently used techniques for characterization, such as grid-like parameter sampling scans, become impractical when extended to higher dimensional input spaces, when complicated measurement constraints are present, or prior information known about the beam response is scarce. Here in this work, we describe an adaptation of the popular Bayesian optimization algorithm, which enables a turn-key exploration of input parameter spaces. Our algorithm replaces the need for parameter scans while minimizing prior information needed about the measurement’s behavior and associated measurement constraints. We experimentally demonstrate that our algorithm autonomously conducts an adaptive, multi-parameter exploration of input parameter space, potentially orders of magnitude faster than conventional grid-like parameter scans, while making highly constrained, single-shot beam phase-space measurements and accounts for costs associated with changing input parameters. In addition to applications in accelerator-based scientific experiments, this algorithm addresses challenges shared by many scientific disciplines, and is thus applicable to autonomously conducting experiments over a broad range of research topics.

43 PARTICLE ACCELERATORS↗
DOE OSTI2019

Ionization injection of highly-charged copper ions for laser driven acceleration from ultra-thin foils

Laser-driven ion acceleration is often analyzed assuming that ionization reaches a steady state early in the interaction of the laser pulse with the target. This assumption breaks down for materials of high atomic number for which the ionization occurs concurrently with the acceleration process. Using particle-in-cell simulations, we have examined acceleration and simultaneous field ionization of copper ions in ultra-thin targets (20-150 nm thick) irradiated by a laser pulse with intensity 1 × 10 21 W/cm 2 . At this intensity, the laser pulse drives strong electric fields at the rear side of the target that can ionize Cu to charge states with valence L-shell or full K-shell. The highly-charged ions are produced only in a very localized region due to a significant gap between the M- and L-shells' ionization potentials and can be accelerated by strong, forward-directed sections of the field. Such an "ionization injection" leads to well-pronounced bunches of energetic, highly-charged ions. We also find that for the thinnest target (20 nm) a push by the laser further increases the ion energy gain. Thus, the field ionization, concurrent with the acceleration, offers a promising mechanism for the production of energetic, high-charge ion bunches.

43 PARTICLE ACCELERATORS↗
DOE OSTI2018

Modeling of thermalization phenomena in coaxial plasma accelerators

Coaxial plasma accelerators are electromagnetic acceleration devices that employ a self-induced Lorentz force to produce collimated plasma jets with velocities ~50 km s -1 . The accelerator operation is characterized by the formation of an ionization/thermalization zone near gas inlet of the device that continually processes the incoming neutral gas into a highly ionized thermal plasma. In this paper, we present a 1D non-equilibrium plasma model to resolve the plasma formation and the electron-heavy species thermalization phenomena that take place in the thermalization zone. The non-equilibrium model is based on a self-consistent multi-species continuum description of the plasma with finite-rate chemistry. The thermalization zone is modelled by tracking a 1D gas-bit as it convects down the device with an initial gas pressure of 1 atm. The thermalization process occurs in two stages. The first is a plasma production stage, associated with a rapid increase in the charged species number densities facilitated by cathode surface electron emission and volumetric production processes. The production stage results in the formation of a two-temperature plasma with electron energies of ~2.5 eV in a low temperature background gas of ~300 K. The second, a temperature equilibration stage, is characterized by the energy transfer between the electrons and heavy species. In conclusion, the characteristic length scale for thermalization is found to be comparable to axial length of the accelerator thus putting into question the equilibrium magnetohydrodynamics assumption used in modeling coaxial accelerators.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

First demonstration of a cryocooler conduction cooled superconducting radiofrequency cavity operating at practical cw accelerating gradients

Abstract We demonstrate practical accelerating gradients on a superconducting radiofrequency (SRF) accelerator cavity with cryocooler conduction cooling, a cooling technique that does not involve the complexities of the conventional liquid helium bath. A design is first presented that enables conduction cooling an elliptical-cell SRF cavity. Implementing this design, a single cell 650 MHz Nb 3 Sn cavity coupled using high purity aluminum thermal links to a 4 K pulse tube cryocooler generated accelerating gradients up to 6.6 MV m −1 at 100% duty cycle. The experiments were carried out with the cavity-cryocooler assembly in a simple vacuum vessel, completely free of circulating liquid cryogens. We anticipate that this cryocooling technique will make the SRF technology accessible to interested accelerator researchers who lack access to full-stack helium cryogenic systems. Furthermore, the technique can lead to SRF based compact sources of high average power electron beams for environmental protection and industrial applications. A concept of such an SRF compact accelerator is presented.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Multi-beam operation of LANSCE accelerator facility

The Los Alamos Neutron Science Center (LANSCE) accelerator facility has been in operation for 50 years performing important scientific support for national security. The unique feature of the LANSCE accelerator facility is multi-beam operation, delivering beams to five experimental areas. The near-term plans are to replace obsolete and almost end-of-life systems of the LANSCE linear accelerator with a modern 100-MeV Front End with significant improvement in beam quality. This paper summarizes experimental results obtained during the operation of the LANSCE accelerator facility and considers plans to expand the performance of the accelerator for near- and long-term operations.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Multipoint-BAX: a new approach for efficiently tuning particle accelerator emittance via virtual objectives

Abstract Although beam emittance is critical for the performance of high-brightness accelerators, optimization is often time limited as emittance calculations, commonly done via quadrupole scans, are typically slow. Such calculations are a type of multipoint query , i.e. each query requires multiple secondary measurements. Traditional black-box optimizers such as Bayesian optimization are slow and inefficient when dealing with such objectives as they must acquire the full series of measurements, but return only the emittance, with each query. We propose a new information-theoretic algorithm, Multipoint-BAX , for black-box optimization on multipoint queries, which queries and models individual beam-size measurements using techniques from Bayesian Algorithm Execution (BAX). Our method avoids the slow multipoint query on the accelerator by acquiring points through a virtual objective , i.e. calculating the emittance objective from a fast learned model rather than directly from the accelerator. We use Multipoint-BAX to minimize emittance at the Linac Coherent Light Source (LCLS) and the Facility for Advanced Accelerator Experimental Tests II (FACET-II). In simulation, our method is 20× faster and more robust to noise compared to existing methods. In live tests, it matched the hand-tuned emittance at FACET-II and achieved a 24% lower emittance than hand-tuning at LCLS. Our method represents a conceptual shift for optimizing multipoint queries, and we anticipate that it can be readily adapted to similar problems in particle accelerators and other scientific instruments.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Uncertainty quantification for deep learning in particle accelerator applications

With the advent of increased computational resources and improved algorithms, machine learning-based models are being increasingly applied to complex problems in particle accelerators. However, such data-driven models may provide overly confident predictions with unknown errors and uncertainties. For reliable deployment of machine learning models in high-regret and safety-critical systems such as particle accelerators, estimates of prediction uncertainty are needed along with accurate point predictions. In this investigation, we evaluate Bayesian neural networks (BNN) as an approach that can provide accurate predictions along with reliably quantified uncertainties for particle accelerator problems, and compare their performance with bootstrapped ensembles of neural networks. We select three accelerator setups for this evaluation: a storage ring, a photoinjector, and a linac. The problems span different data volumes and dimensionalities (e.g., scalar predictions as well as image outputs). It is found that BNN provide accurate predictions of the mean along with reliable estimates of predictive uncertainty across the test cases. In this vein, BNN may offer an attractive alternative to deterministic deep learning tools to generate accurate predictions with quantified uncertainties in particle accelerator applications.

43 PARTICLE ACCELERATORS↗