2004Unpublished venueOpen access

Statistical simulations to inspect and predict data retention and program disturbs in flash memories

Luca Larcher, Paolo Pavan

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Abstract

A new statistical model of stress-induced leakage current (SILC) is implemented and used to predict data retention and program disturbs of state-of-the-art flash memories, and to correlate oxide characterization outputs (density, cross section, energy level of defects) to flash memory reliability. Physical mechanisms inducing the largest threshold voltage (V/sub T/) degradation are explained, and tunnel oxide scaling effects on flash reliability are predicted.

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What this paper is about

A new statistical model of stress-induced leakage current (SILC) is implemented and used to predict data retention and program disturbs of state-of-the-art flash memories, and to correlate oxide characterization outputs (density, cross section, energy level of defects) to flash memory reliability. Physical mechanisms inducing the largest threshold voltage (V/sub T/) degradation are explained, and tunnel oxide scaling effects on flash reliability are predicted.

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Available abstract

A new statistical model of stress-induced leakage current (SILC) is implemented and used to predict data retention and program disturbs of state-of-the-art flash memories, and to correlate oxide characterization outputs (density, cross section, energy level of defects) to flash memory reliability. Physical mechanisms inducing the largest threshold voltage (V/sub T/) degradation are explained, and tunnel oxide scaling effects on flash reliability are predicted.

Key concepts: SILC, Data retention, Flash memory, Flash (photography), Reliability (semiconductor), Non-volatile memory, Scaling, Computer science

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