Abstract

Data retention and its statistics are the key issues for the development of next generation phase-change memory (PCM) arrays. For this reason, the understanding and modeling of cell-to-cell and cycle-to-cycle variabilities of retention time are essential. This paper provides an extensive experimental characterization of retention statistics in 45-nm PCM technology and presents a Monte Carlo model for variability based on a Gaussian spread in the activation energy for crystallization. Results show that both cell-to-cell and cycle-to-cycle variabilities are well explained by a Gaussian spread in the activation energy for crystallization, due to local composition/structure changes in PCM active volume.

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