1999
DOI: 10.1109/55.761013
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A new extrapolation law for data-retention time-to-failure of nonvolatile memories

Abstract: In this letter, we demonstrate that the commonly assumed Arrhenius law is inconsistent with extrapolation of data-retention time-to-failure of nonvolatile memories in highly accelerated life-tests. We argue that the retention time, namely log(tR), varies linearly with temperature T rather than with 1=T as commonly assumed, yielding an important reduction in the extrapolated time-to-failure. Extensive experimental results demonstrate the physical consistency of the new model. In particular, data-retention of EP… Show more

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Cited by 18 publications
(7 citation statements)
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“…7a,b and c, respectively. Here the retention time model with linear variations according to the temperature, which employs a T extrapolation model by Salvo et al ., was considered 35, 36 . The inset figures in Fig.…”
Section: Resultsmentioning
confidence: 99%
“…7a,b and c, respectively. Here the retention time model with linear variations according to the temperature, which employs a T extrapolation model by Salvo et al ., was considered 35, 36 . The inset figures in Fig.…”
Section: Resultsmentioning
confidence: 99%
“…It has even been proposed that a T extrapolation law should rather be used [4], based on retention tests on floating gate devices with ONO stacks.…”
Section: Resultsmentioning
confidence: 99%
“…In order to estimate the device lifetime using the Arrhenius model, E aa should be a constant. However, real experimental data shows E aa roll-off characteristics [6][7][8]. Figure 1(f) shows a comparison of the results for the extracted E aa with the E a of each mechanism according to the baking temperature.…”
Section: Modeling Of Apparent Activation Energymentioning
confidence: 99%
“…This Arrhenius model is used under the assumption that the E aa is constant with temperature. However, it has been continuously reported that the Arrhenius plot shows not a straight line but the E aa roll-off behavior mainly due to the coexistence of various failure mechanisms [6][7][8]. In order to predict the accurate lifetime of the device, physical mechanisms on the abnormal E aa behavior should be understood.…”
Section: Introductionmentioning
confidence: 99%