In this paper we propose a compact model of Random Telegraph Noise in HfOx-based Resistive Random Access Memory devices. Starting from the physics of charge transport, we first focus on the RTN phenomenon in the two different resistive states (HRS and LRS). We separately explore the microscopic mechanisms responsible for Random Telegraph Noise (RTN) current fluctuations in HfOx RRAM devices in HRS and LRS, exploiting a self-consistent physics-based simulation framework accounting for many charge transport mechanisms and their alterations. Then, we develop a simple yet effective compact model of RTN valid in both states, which can be easily integrated in state-of-the-art compact RRAM device models. The compact model predictions are validated by comparison with both a large experimental dataset obtained by measuring RRAM devices in different conditions, and data found in the literature.
Random telegraph noise in HfOx Resistive Random Access Memory: From physics to compact modeling / Puglisi, Francesco Maria; Pavan, Paolo; Larcher, Luca. - 2016:(2016), pp. MY81-MY85. (Intervento presentato al convegno 2016 International Reliability Physics Symposium, IRPS 2016 tenutosi a Pasadena (CA) - USA nel 2016) [10.1109/IRPS.2016.7574624].
Random telegraph noise in HfOx Resistive Random Access Memory: From physics to compact modeling
PUGLISI, Francesco Maria;PAVAN, Paolo;LARCHER, Luca
2016
Abstract
In this paper we propose a compact model of Random Telegraph Noise in HfOx-based Resistive Random Access Memory devices. Starting from the physics of charge transport, we first focus on the RTN phenomenon in the two different resistive states (HRS and LRS). We separately explore the microscopic mechanisms responsible for Random Telegraph Noise (RTN) current fluctuations in HfOx RRAM devices in HRS and LRS, exploiting a self-consistent physics-based simulation framework accounting for many charge transport mechanisms and their alterations. Then, we develop a simple yet effective compact model of RTN valid in both states, which can be easily integrated in state-of-the-art compact RRAM device models. The compact model predictions are validated by comparison with both a large experimental dataset obtained by measuring RRAM devices in different conditions, and data found in the literature.Pubblicazioni consigliate
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