Analysis of Ion-Induced SEFI and SEL Phenomena in 90 nm NOR Flash Memory

Ju, Anan; Guo, Hao; Ding, Lili; Zhang, Fengqi; Zhong, Xiangli; Pan, Xiaoyu; Zhang, Hong; Bi, Jinshun

doi:10.1109/tns.2021.3105998

Cited by 3 publications

(2 citation statements)

References 33 publications

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“…Two options are available to meet the 4 Gb requirement on the nonvolatile memory, NOR and NAND Flash memory chips. Radiation reliability concerns are detailed in papers such as [18], but the main takeaway is that NOR Flash is more reliable owing primarily to the lack of bad blocks present in the chips and singular nature of the memory cells reducing failure modes. This is balanced against the storage density achievable with NAND Flash, but chipmakers such as Micron produce NOR Flash with up to 2 Gb of memory, and the AI Accelerator SoC is capable of "stacking" two of these chips together, meeting the 4 Gb requirement.…”

Section: Nonvolatile Memorymentioning

confidence: 99%

On-orbit rule-based and deep learning image segmentation strategies

Kacker

Meredith

Kusters

et al. 2022

AIAA SCITECH 2022 Forum

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We discuss image segmentation algorithms and additional space considerations for BeaverCube-2, a project under development between the MIT Space Telecommunications, Astronomy, Radiation (STAR) Lab and the Northrop Grumman Corporation that aims to demonstrate the use of an Artificial Intelligence (AI) Computational Accelerator System-on-a-Chip (SoC) on a 3U CubeSat in Low-Earth Orbit (LEO). The processing power afforded by the SoC will allow the use of modern artificial intelligence techniques as part of an Earth observation mission to obtain and process visible and infrared imagery of coastal features.We focus on three algorithms used for cloud segmentation in satellite imagery. These are a luminosity-thresholding method, a random forest method, and an autoencoder-based deep learning method. Our luminosity thresholding method classifies each pixel based on its luminosity and achieved 84% accuracy using 2 MB of memory. Our random forest method contextualizes pixels within a 3 × 3 kernel and classifies them based on the luminosity of each pixel in the kernel -it achieved 90% accuracy, with a memory usage of 700 MB. Finally, our U-Net-based deep learning method achieved 92% accuracy with 1500 MB memory usage, demonstrating modest gains over the two simpler methods, with higher accuracy in snow scenes.

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Section: Nonvolatile Memorymentioning

confidence: 99%

On-orbit rule-based and deep learning image segmentation strategies

Kacker

Meredith

Kusters

et al. 2022

AIAA SCITECH 2022 Forum

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“…SEFI is a multifaceted failure phenomenon that arises when high-energy particles collide with sensitive regions, such as control registers and circuits within devices, leading to abnormal operational states such as test mode activation, reset mode engagement, or temporary functional failures [1][2][3][4]. As technology progresses, integrated circuits are growing increasingly intricate, encompassing diverse storage units, control circuits, and other complex circuitry, making them more vulnerable to SEFI [5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Experiment Study of Single Event Functional Interrupt in Analog-to-Digital Converters Using a Pulsed Laser

Mai

Zhu

et al. 2023

Electronics

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Single Event Functional Interrupt (SEFI) poses a severe threat to the normal operation of spacecraft. This paper investigates SEFI in Analog-to-Digital Converters (ADCs) with storage units using precision positioning of pulsed lasers. Based on the experiment, it was discovered that a bit flip in the configuration registers in ADCs results in changes in parameters such as digital filter frequency, operating mode, and gain, leading to an upward or downward offset of ADC output codes. Similarly, a bit flip in the calibration registers also causes ADC output codes to shift upwards or downwards, or even output a value of zero. Furthermore, it was observed that SEFI phenomena can occur due to current latch-up in ADC input pins, causing the inability to read or write data in ADC storage units. This current latch-up can be resolved through power cycling or configuring the pins into a high-impedance state. This work highlights the significance of SEFI phenomena in ADCs, emphasizing the serious threat posed by storage unit flipping-induced SEFI to the proper functioning of ADCs. Moreover, the SEFI phenomenon caused by current latch-up in input pins is difficult to detect in practice, making it highly elusive. Once it occurs, it severely impacts the functionality of ADCs.

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Fast development and validation of a Sensing Suite system for CubeSats

Bollattino,

Stesina

2024

Acta Astronautica

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Analysis of Ion-Induced SEFI and SEL Phenomena in 90 nm NOR Flash Memory

Cited by 3 publications

References 33 publications

On-orbit rule-based and deep learning image segmentation strategies

On-orbit rule-based and deep learning image segmentation strategies

Experiment Study of Single Event Functional Interrupt in Analog-to-Digital Converters Using a Pulsed Laser

Fast development and validation of a Sensing Suite system for CubeSats

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