2016
DOI: 10.1109/ted.2016.2617890
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Cycling-Induced Charge Trapping/Detrapping in Flash Memories—Part II: Modeling

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Cited by 13 publications
(18 citation statements)
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“…The reduction in the nonuniformities in channel electrostatics with temperature arises both from the reduction in trap occupancy at the grain boundaries [12] and to a less severe constraint of thermionic emission. All of these points must be carefully considered when addressing the variety of phenomena affected by percolative channel conduction, such as RTN [7,13,19,[34][35][36] and charge detrapping [37][38][39][40], when performing spectroscopic analyses of oxide traps based on local tunneling currents [41][42][43][44] and when addressing the impact of localized electron storage in charge trap layers on nonuniform channel inversion [45].…”
Section: Current Variabilitymentioning
confidence: 99%
“…The reduction in the nonuniformities in channel electrostatics with temperature arises both from the reduction in trap occupancy at the grain boundaries [12] and to a less severe constraint of thermionic emission. All of these points must be carefully considered when addressing the variety of phenomena affected by percolative channel conduction, such as RTN [7,13,19,[34][35][36] and charge detrapping [37][38][39][40], when performing spectroscopic analyses of oxide traps based on local tunneling currents [41][42][43][44] and when addressing the impact of localized electron storage in charge trap layers on nonuniform channel inversion [45].…”
Section: Current Variabilitymentioning
confidence: 99%
“…The concept of distributed cycling conditions was then proposed in [221] as a way to better emulate the real array behavior by performing either a uniform cycling over a longer time or several groups of fast cycles preceded by bake times, usually at high temperature to accelerate the charge loss. However, the previous model shows its limitations when dealing with highly non-uniform cycling patterns, calling for a more comprehensive interpretation of the trapping/detrapping physics, that was pursued in [223][224][225]227,233]. Such a model was built upon a few phenomenological assumptions: a Poisson distribution for the number of trapped electrons n t and a uniform distribution over a log-time axis of their detrapping time constant τ d .…”
Section: Modelsmentioning
confidence: 99%
“…In particular, it was noted that charge detrapping is enhanced with the oxide electric field and that little or no detrapping takes place during bake phases performed with cells in the erased state [227,237], suggesting that holes may play a non-negligible role in what is usually described as an electron-only detrapping process [238]. These developments led to a recent refinement of the above-mentioned model [225,233] that goes beyond the classical vision of pure charge detrapping, considering multiple-state defects related to structural relaxation of the oxide network. A pictorial view of the proposed defect states can be seen in Figure 27, where the lower states D2 and N2 represent the usual trapping/detrapping phenomena, for which the model discussed so far still holds (besides a minor modification to account for trapping).…”
Section: Modelsmentioning
confidence: 99%
See 1 more Smart Citation
“…Most of them focus on the single memory cell [5]- [7], and the comprehensively analysis of different physical failure mechanisms [5], [6] and the influence of states of adjacent cells [7] are presented. Some works study on the effects of data retention times, operation temperatures, and P/E cycles on retention characteristics [8]- [11] of NAND flash memory, and the universal retention V th degradation formula is developed. Besides, several modeling approaches have been proposed to predict the retention V th distributions based on array statistical behavior, such as: assuming the retention V th distributions as a mixture of Gaussian [12], [13] and other distribution functions, or fitting the V th distributions by parameter estimation algorithms [14]- [16], or using the experimental results to interpolation or extrapolation [17], and these modeling approaches nicely represent the retention V th distributions.…”
Section: Introductionmentioning
confidence: 99%