Rate prediction for single event effects-a critique

Petersen, E.L.; Pickel, J.C.; Adams, J. H.; Smith, Edward C.

doi:10.1109/23.211340

Cited by 248 publications

(72 citation statements)

References 50 publications

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“…Figure 4 also plots the heavy ion test results for the SRAM cells reported in [12] fabricated in 0.15 mm UNIBOND SOI process, together with the Weibull fit. The Weibull function is shown in [19]. The heavy ion test in [12] was carried out at Lawrence Berkeley National Laboratory using the 88 in.…”

Section: The Physical Basis For Predicting the Cross Section Of 6t Somentioning

confidence: 99%

Proton induced single event upset cross section prediction for 0.15 μm six-transistor (6T) silicon-on-insulator static random access memories

Li¹,

Zhou²,

Liu³

2012

Journal of Nuclear Science and Technology

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In this paper, an efficient physics-based method to estimate the saturated proton upset cross section for six-transistor (6T) silicon-on-insulator (SOI) static random access memory (SRAM) cells using layout and technology parameters is proposed. This method calculates the effects of radiation based on device physics. The simple method handles the problem with ease by SPICE simulations, which can be divided into two stages. At first, it uses a standard SPICE program to predict the cross section for recoiling heavy ions with linear energy transfer (LET) of 14 MeV-cm 2 /mg. Then, the predicted cross section for recoiling heavy ions with LET of 14 MeV-cm 2 /mg is used to estimate the saturated proton upset cross section for 6T SOI SRAM cells with a simple model. The calculated proton induced upset cross section based on this method is in good agreement with the test results of 6T SOI SRAM cells processed using 0.15 mm technology.

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Section: The Physical Basis For Predicting the Cross Section Of 6t Somentioning

confidence: 99%

Proton induced single event upset cross section prediction for 0.15 μm six-transistor (6T) silicon-on-insulator static random access memories

Li¹,

Zhou²,

Liu³

2012

Journal of Nuclear Science and Technology

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“…Author defined the mining operation and sensor data processing so that the distributed network processing and the technological improvement will be done. E. L. Petersen [9] presented a work on even specific handling on crique dataset under rate level analysis. Author processed the sample set for the estimation of rates and generates the critical information with low level prediction and recommendation based on standard information analysis.…”

Section: Existing Workmentioning

confidence: 99%

A Neuro-Fuzzy Integrated Clustering for Weather Knowledge Analysis

Dahiya¹,

Gigras²

2015

IJCA

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Weather Information processing and knowledge extraction is one of the challenging applications of data mining. This process area requires authenticated and intelligent processing to obtain accurate information from the knowledge set. In this work, an intelligent clustering mechanism is defined to acquire such information. This neuro-fuzzy based model is applied on raw dataset defined with various weather characteristics including humidity, temperature, rainfall etc. The work is divided in three main stages. In first stage, the filtration over the dataset is performed to get more relevant information set. In second stage, the clustering is performed to divide the information set in knowledge groups. In final stage, the filtration over the knowledge set is performed to acquire the most effective knowledge. The results show the effective information analysis is obtained from the work.

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“…Five general explanations have been proposed in the literature: 1) energy loss of the ion before arriving at the surface of the device, changing its LET [25], 2) the device has significant collection depth so that the cos(θ) correction to the cross section doesn't hold [33] Germanium introduced [12]. Introducing an alloy of SiGe in the base of a bipolar transistor provides a valence band offset in the base (Fig.…”

Section: Event Effect (See)mentioning

confidence: 99%

“…The sensitive volume is used to determine how much energy is deposited from an ion event in a region of interest in a semiconductor device. The methods of obtaining the dimensions of the RPP have been refined and debated since its inception [25][26][27][28][29][30][31], but are typically defined by a combination of theory, technology process information, and experimental analysis. The charge collected from the energy deposited in the SV must be greater or equal to the critical charge of the device for a SEU to be recorded.…”

Section: Event Effect (See)mentioning

confidence: 99%