The linear growth and nonlinear energy transfer of the electron drift instability (EDI) are experimentally measured in the plume of a low-temperature, Hall effect discharge. A frequency-based bispectral analysis technique applied to fast ion density fluctuation measurements shows a growth rate function that is qualitatively similar to predictions from the linear instability dispersion relation, but an order of magnitude smaller. Calculation of the nonlinear transfer function indicates multiple three-wave interactions between high-frequency resonances of the instability in addition to an inverse energy cascade toward lower-frequency modes. These results are discussed in the context of recent theoretical, numerical, and experimental efforts on the EDI in Hall effect discharges and how the EDI may impact anomalous cross field transport.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1103/PhysRevLett.130.115101 | DOI Listing |
Sensors (Basel)
December 2024
Dipartimento di Fisica G. Occhialini, Università Degli Studi di Milano-Bicocca, 20126 Milano, Italy.
The ASPECT-BET project, or An sdd-SPECTrometer for BETa decay studies, aims to develop a novel technique for the precise measurement of forbidden beta spectra in the 10 keV-1 MeV range. This technique employs a Silicon Drift Detector (SDD) as the main spectrometer with the option of a veto system to reject events exhibiting only partial energy deposition in the SDD. A precise understanding of the spectrometer's response to electrons is crucial for accurately reconstructing the theoretical shape of the beta spectrum.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Freiburg Materials Research Center, Albert-Ludwigs-Universität Freiburg, 79104 Freiburg im Breisgau, Germany.
Nuclear power plant decommissioning requires the rapid and accurate classification of radioactive waste in narrow spaces and under time constraints. Photon-counting detector technology offers an effective solution for the quick classification and detection of radioactive hotspots in a decommissioning environment. This paper characterizes a 5 mm CdTe Timepix3 detector and evaluates its feasibility as a single-layer Compton camera.
View Article and Find Full Text PDFTalanta
January 2025
National Institutes for Quantum Science and Technology, 4-9-1 Anagawa, Chiba, Chiba, 263-8555, Japan; Department of Physics, Faculty of Science, Toho University, 2-2-1 Miyama, Funabashi, Chiba, 274-8510, Japan.
Natural uranium isotopes have extremely long half-lives; therefore, analytical methods based on the number of atoms, such as X-ray fluorescence (XRF) analysis, are suitable for uranium detection. However, XRF measurements cannot be used to detect the major isotopes of americium when present in amounts barely detectable using radiation measurements, owing to their relatively short half-lives. Because of α-decay-induced internal conversion, where orbital electrons are emitted instead of γ-rays, these nuclides emit characteristic X-rays.
View Article and Find Full Text PDFRev Sci Instrum
December 2024
X-ray Astrophysics Laboratory, NASA Goddard Space Flight Center, Greenbelt, Maryland 20771, USA.
This paper presents progress made toward the overarching goal to adapt single-photon-counting microcalorimeters to magnetic fusion energy research and demonstrate the value of such measurements for fusion. Microcalorimeter spectrometers combine the best characteristics of x-ray instrumentation currently available on fusion devices: high spectral resolution similar to an x-ray crystal spectrometer and broad spectral coverage sufficient to measure impurity species from Be to W. As a proof-of-principle experiment, a NASA-built x-ray microcalorimeter spectrometer has been installed on the Madison Symmetric Torus (MST) at the Wisconsin Plasma Physics Laboratory.
View Article and Find Full Text PDFChem Rev
December 2024
Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, California 90089, United States.
Conventional artificial intelligence (AI) systems are facing bottlenecks due to the fundamental mismatches between AI models, which rely on parallel, in-memory, and dynamic computation, and traditional transistors, which have been designed and optimized for sequential logic operations. This calls for the development of novel computing units beyond transistors. Inspired by the high efficiency and adaptability of biological neural networks, computing systems mimicking the capabilities of biological structures are gaining more attention.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!