Hybrid CMOS (hCMOS) x-ray framing cameras are a new and powerful detector option for experiments in the fields of Inertial Confinement Fusion (ICF) and High Energy Density Physics (HEDP). These digital cameras capture multiple images along a single line-of-sight with a time resolution as short as 1.5 ns and with high quantum efficiency. To manage the high data rate, an image sequence is acquired in a short burst of time and subsequently read out on a much longer time scale. The technology is well suited for operating in high radiation environments, including fusion ignition experiments. Diagnostics using hCMOS cameras are now deployed in experiments on major laser and pulsed-power ICF facilities around the world. Continued advances in microelectronics technologies will enable faster and more capable detectors well into the future. This paper reviews this detector technology with a focus on application to ICF and HEDP experiments.
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http://dx.doi.org/10.1063/5.0138264 | DOI Listing |
Nature
January 2025
imec, Leuven, Belgium.
Silicon photonics is a rapidly developing technology that promises to revolutionize the way we communicate, compute and sense the world. However, the lack of highly scalable, native complementary metal-oxide-semiconductor (CMOS)-integrated light sources is one of the main factors hampering its widespread adoption. Despite considerable progress in hybrid and heterogeneous integration of III-V light sources on silicon, monolithic integration by direct epitaxy of III-V materials remains the pinnacle of cost-effective on-chip light sources.
View Article and Find Full Text PDFFront Neurosci
December 2024
CIMAINA and Dipartimento di Fisica "A. Pontremoli", Università degli Studi di Milano, Milan, Italy.
The brain's ability to perform efficient and fault-tolerant data processing is strongly related to its peculiar interconnected adaptive architecture, based on redundant neural circuits interacting at different scales. By emulating the brain's processing and learning mechanisms, computing technologies strive to achieve higher levels of energy efficiency and computational performance. Although efforts to address neuromorphic solutions through hardware based on top-down CMOS-based technologies have obtained interesting results in terms of energetic efficiency improvement, the replication of brain's self-assembled and redundant architectures is not considered in the roadmaps of data processing electronics.
View Article and Find Full Text PDFNanophotonics
July 2024
School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan 430074, China.
Nanophotonics
March 2024
School of Electrical Engineering and Computer Science, Department of Semiconductor Engineering, and Artificial Intelligence (AI) Graduate School, Gwangju Institute of Science and Technology (GIST), Cheomdangwagi-ro 123, Buk-gu, Gwangju 61005, Republic of Korea.
ACS Appl Mater Interfaces
December 2024
Centre for Nano Science and Engineering, Indian Institute of Science, Bengaluru 560012, India.
Resistive switching elements have introduced a paradigm shift in emerging computation, offering energy- and space-efficient logic operations. A single-resistive threshold switch can enable applications that require tens of standard CMOS transistors. They can also be used to design hybrid-phase-FETs with a steep subthreshold slope.
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