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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Numerical studies of collinear laser-assisted injection from a foil for plasma wakefield accelerators

We present a laser-assisted electron injection scheme for beam-driven plasma wakefield acceleration. The laser is collinear with the driver and triggers the injection of hot electrons into the plasma wake by interaction with a thin solid target. We present a baseline case using the AWAKE Run 2 parameters and then perform variations on key parameters to explore the scheme. It is found that the trapped witness electron charge may be tuned by altering laser parameters, with a strong dependence on the phase of the wake upon injection. Normalized emittance settles at the order of micrometres and varies with witness charge. The scheme is robust to misalignment, with a 1/10th plasma skin-depth offset ( 20 μ m for the AWAKE case) having a negligible effect on the final beam. The final beam quality is better than similar existing schemes, and several avenues for further optimization are indicated. The constraints on the AWAKE experiment are very specific, but the general principles of this mechanism can be applied to future beam-driven plasma wakefield accelerator experiments. Published by the American Physical Society 2024

Physics↗
DOE OSTI2024

Benchmarking of hydrodynamic plasma waveguides for multi-GeV laser-driven electron acceleration

Hydrodynamic plasma waveguides initiated by optical field ionization have recently become a key component of multi-GeV laser wakefield accelerators. Here, we present the most complete and accurate experimental and simulation-based characterization to date, applicable to current multi-GeV experiments and future 100 GeV-scale laser plasma accelerators. Crucial to the simulations is the correct modeling of intense Bessel beam interaction with meter-scale gas targets, the results of which are used as initial conditions for hydrodynamic simulations. The simulations are in good agreement with our experiments measuring evolving plasma and neutral hydrogen density profiles using two-color short pulse interferometry, enabling realistic determination of the guided mode structure for application to laser-driven plasma accelerator design. Published by the American Physical Society 2024

Physics↗
DOE OSTI2024

Toward the Discovery of New Elements: Production of Livermorium (𝑍 = 116) with 50 Ti

The 244 Pu ⁢(50 Ti ,𝑥⁢𝑛)⁢ 294−𝑥 Lv reaction was investigated at Lawrence Berkeley National Laboratory’s 88-Inch Cyclotron. The experiment was aimed at the production of a superheavy element with 𝑍 ≥114 by irradiating an actinide target with a beam heavier than 48 Ca. Produced Lv ions were separated from the unwanted beam and nuclear reaction products using the Berkeley Gas-filled Separator and implanted into a newly commissioned focal-plane detector system. Two decay chains were observed and assigned to the decay of 290 Lv . The production cross section was measured to be 𝜎 prod = 0.44($^{+0.58}_{−0.28}$) pb at a center-of-target center-of-mass energy of 220(3) MeV. Furthermore, this represents the first published measurement of the production of a superheavy element near the “island of stability,” with a beam of 50 Ti and is an essential precursor in the pursuit of searching for new elements beyond 𝑍 =118.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Measurement of Atmospheric Neutrino Oscillation Parameters Using Convolutional Neural Networks with 9.3 Years of Data in IceCube DeepCore

The DeepCore subdetector of the IceCube Neutrino Observatory provides access to neutrinos with energies above approximately 5 GeV. Data taken between 2012 and 2021 (3387 days) are utilized for an atmospheric ν μ disappearance analysis that studied 150 257 neutrino-candidate events with reconstructed energies between 5 and 100 GeV. An advanced reconstruction based on a convolutional neural network is applied, providing increased signal efficiency and background suppression, resulting in a measurement with both significantly increased statistics compared to previous DeepCore oscillation results and high neutrino purity. For the normal neutrino mass ordering, the atmospheric neutrino oscillation parameters and their 1 σ errors are measured to be Δ m 32 2 = 2.40 − 0.04 + 0.05 × 10 − 3 eV 2 and sin 2 θ 23 = 0.54 − 0.03 + 0.04 . The results are the most precise to date using atmospheric neutrinos, and are compatible with measurements from other neutrino detectors including long-baseline accelerator experiments. Published by the American Physical Society 2025

Abbasi, R.↗
DOE OSTI2025

Ultra-Fast 4H-SiC LGAD With Etched Termination and Field Plate

The design, fabrication, and demonstration of a novel Silicon Carbide Low Gain Avalanche Detector (4HSiC LGAD), exhibiting an ultra-fast time response and excellent time resolution, are reported. Here, the use of field plates is proposed to suppress the high electric field caused by the negative bevel-etched angle in 4H-SiC LGADs based on TCAD simulations. Experimental measurements confirm that the field plate significantly increases the breakdown voltage of the 4H-SiC LGADs. Gain and time resolution are measured by using the ultraviolet transient current technique (UV-TCT) showing that 4H-SiC LGADs possess excellent timing performance, with a time resolution better than 35 ps for the injected laser signal with single minimum ionizing particle (MIP) charges generation at room temperature. Additionally, the gain suppression effect in a 4H-SiC LGAD is observed for the first time.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Data-Driven Analysis of Multipactor Dynamics via Dynamic Mode Decomposition

Multipactor effect is a performance-limiting kinetic plasma effect that can occur in high-power microwave and radio frequency (RF) devices. Multipactor effect is of special concern in vacuum or near-vacuum conditions such as those in particle accelerators and spaceborne devices. In this work, we present a data-driven reduced-order model (ROM) based on dynamic mode decomposition (DMD) for modeling of multipactor effects. We study multipactor effects and the resulting nonlinear harmonic generation by processing high-fidelity data generated from electromagnetic particle-in-cell (EMPIC) simulations using the DMD algorithm. We also investigate time-delay embedding extensions of DMD with improved generalizability and accuracy for modeling the electron plasma current density behavior. Here, the results show that DMD provides valuable insights into multipactor phenomena by extracting relevant modal spatiotemporal patterns and frequencies. In addition, DMD offers the potential to time extrapolate EMPIC simulations at a minimal cost, thereby reducing overall simulation time.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Probabilistic data fusion and physics-informed machine learning: A new paradigm for modeling under uncertainty, and its application to accelerating the discovery of new materials

In this report we summarize the work conducted by PI Perdikaris and his group under this Early Career project DE–SC0019116 during the period of 09/01/2018 – 08/31/2023. The central aim of the work was to introduce a new paradigm for scientific data analysis that can seamlessly synthesize rigorous mathematical modeling with data of variable fidelity (e.g., measurements at multiple scales/resolutions or predictions of variable fidelity models) and multiple modalities (e.g., images, time–series, or scattered measurements). The setting we are interested in involves complex systems that are partially observed and whose dynamical behavior could be hard to model or totally unknown. The inherent uncertainty associated with this setting necessitates a departure from the classical deterministic realm of modeling and scientific computation, and, consequently, our main building blocks can no longer be crisp deterministic numbers and governing laws, but instead we must operate with probabilistic models.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Status of the Muon Neutrino Charged-Current Mesonless Cross Section Measurement in the NOvA Near Detector

NOvA is a long-baseline accelerator neutrino experiment at Fermilab whose physics goals include precision neutrino oscillation as well as cross-section measurements. We present the status of the measurement of a muon neutrino charged-current cross section with zero mesons in the final state at the NOvA near detector. This measurement is being made with respect to the kinematics of the final state muon. The chosen interaction channel is especially sensitive to quasielastic and meson exchange current interactions and aims to provide experimental constraints for the development of models of neutrino interactions. It will also provide a handle for constraining cross section systematic uncertainties in oscillation analyses in current and future experiments. For particle identification, we use a convolutional neural network (CNN) trained on individual particles simulated in the NOvA near detector that allows us to select the desired signal while reducing the potential bias from neutrino interaction modeling. Charged pion background constraining is further improved via Michel electron tagging.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Status of the Muon Neutrino Charged-Current Zero Mesons Cross Section at the NOvA Near Detector

NOvA is a long-baseline accelerator neutrino experiment at Fermilab whose physics goals include precision neutrino oscillation as well as cross-section measurements. We present the status of the measurement of a muon neutrino charged-current cross section with zero mesons in the final state at the NOvA near detector. This measurement is being made with respect to the kinematics of the final state muon. The chosen interaction channel is especially sensitive to quasielastic and meson exchange current interactions and aims to provide experimental constraints for the development of models of neutrino interactions. It will also provide a handle for constraining cross section systematic uncertainties in oscillation analyses in current and future experiments. For particle identification, we use a convolutional neural network (CNN) trained on individual particles simulated in the NOvA near detector that allows us to select the desired signal while reducing the potential bias from neutrino interaction modeling. Charged pion background constraining is further improved via Michel electron tagging.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

LaserNetUS: A Proposal to Advance North America’s First High Intensity Laser Research Network Final Report

LaserNetUS Collaborative Network established in 2018 is a network of high-power laser facilities supported by the Department of Energy (DOE) Office of Fusion Energy Sciences (FES) and operating effectively as a user facility. Its mission is to advance and promote intense laser science and applications by providing scientists and students with broad access to unique facilities and enabling technologies, advancing the frontiers of laser-science research, and fostering collaboration among researchers and networks from around the world. Users who submit proposals through an annual call are selected by an external and independent proposal review panel (PRP) not involving personnel from any of the facilities.

36 MATERIALS SCIENCE↗
DOE OSTI2024

MEMS RF accelerators for nuclear energy and advanced manufacturing

Energetic ions are widely used to develop radiation hard structural materials and fuels for advanced nuclear energy. Ion beams are also used to generate neutrons for nuclear materials testing, as well as in a series of high impact, high value adding manufacturing processes (ranging from doping of semiconductors to hardening of materials against wear and to increase bio-compatibility of materials). But to date, high power beams of high energy ions are simply too expensive because they are delivered from large single beam accelerators. We have recently demonstrated that MEMS technology enables massively parallel, low cost batch fabrication of ion beams. We propose to scale intense ion accelerators based on MEMS (micro-electro mechanical systems) to high beam power (>10 kW). With our approach, hundreds to thousands of ion beamlets will be densely packed on silicon wafers. Ions are injected and accelerated across gaps formed in stacks of wafers, leading to uniquely high current densities for intense ion accelerators with variable kinetic energy (0.1 to 10 MeV) and variable ion species. Our team brings together experts in high power ion accelerators from Lawrence Berkeley National Laboratory and leading experts in MEMS technology from Cornell University. We will deliver a disruptive technology of low cost, flexible and massively scalable ion accelerators that will enable the rapid development of radiation hard nuclear materials for advanced nuclear energy and enable new applications in manufacturing.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Fast Adaptive Neural Control of Resonant Extraction at Fermilab

We present the development of a machine learning (ML) based regulation system for third-order resonant beam extraction in the Mu2e experiment at Fermilab. Classical and ML-based controllers have been optimized using semi-analytic simulations and evaluated in terms of regulation performance and training efficiency. We compare several controller architectures and discuss the integration of neural control into an adaptive framework. We also present progress on surrogate models that predict the controller response given a spill intensity and controller action history. To enable real-time deployment, we report progress on implementing low-latency, edge-based inference suitable for hardware-constrained environments. Our results demonstrate the feasibility and advantages of ML-based control in managing complex, time-varying physical systems, with broader implications for accelerator operations and other domains requiring fast, adaptive regulation.

Berlioz, Jose Rene [Fermilab]↗
DOE OSTI2026

Testing the Common Platform LLRF with a 197 MHz NCRF Cavity

The Common Platform is the hardware that will support the new LLRF platform to be used for the Electron-Ion Collider. The Common Platform features a carrier board that is used to interface with a variety of daughter for different applications. This paper details the testing that was done using the Common Platform and an RF Digitizer Daugther Board. Firstly, the firmware and software development is discussed followed by a description of the controls algorithms used in the testing. Then, testing and verification of the platform with a 197 MHz NCRF cavity is discussed. The paper concludes with results from the testing and the path forward.

42 ENGINEERING↗
NASA NTRS1968

Physics of Electric Propulsion.

Book on physics of electric propulsion covering gas acceleration principles, flow heating and space thrustor design

Jahn, R. G.↗
NASA NTRS1980

Review of hot plasma composition near geosynchronous altitude

The information available on the hot plasma composition at and near the geostationary satellite orbit has increased dramatically during the past four years. At energies below 32 keV, ions of terrestrial origin, 0(+) and He(+) are frequently observed to be significant contributors to the hot plasma density and energy density, and during geomagnetically disturbed periods, 0(+) ions are typically the dominant hot plasma ions. Evidence for a solar cycle dependence to the 0(+) hot plasma densities at the geostationary orbit has been found. Our understanding of the details of the physical processes involved in the entry, acceleration, transport, and loss of the plasma ions, and thus our ability to model them, is still quite limited.

Johnson, R. G.↗
NASA NTRS1991

Passive dynamic controllers for non-linear mechanical systems

The objective is to develop active model-independent controllers for slewing and vibration control of nonlinear multibody flexible systems, including flexible robots. The topics are presented in viewgraph form and include: passive stabilization; work-energy rate principle; Liapunov theory; displacement feedback; dynamic controller; displacement and acceleration feedback; velocity feedback; displacement feedback; physical interaction; a 6-DOF robot; and simulation results.

Jer-Nan Juang↗