This paper presents statistical characterization of Random Telegraph Noise (RTN) in hafnium-oxide-based Resistive Random Access Memories (RRAMs) in High Resistive State (HRS). Complex RTN signals are analyzed exploiting a Factorial Hidden Markov Model (FHMM) approach, allowing to derive the statistical properties of traps responsible of the multi-level RTN measured in these devices. Noise characteristics in different reset conditions are explored to prove the existence of a direct relation between the reset voltage, the volume of the dielectric barrier created during the reset operation and the number of active traps contributing to the RTN.
Random Telegraph Noise analysis to investigate the properties of active traps of HfO2-Based RRAM in HRS / Puglisi, Francesco Maria; Pavan, Paolo; Padovani, Andrea; Larcher, Luca. - ELETTRONICO. - (2013), pp. 166-169. (Intervento presentato al convegno European Solid-State Device Research Conference (ESSDERC) tenutosi a Bucharest, Romania nel September 16-20) [10.1109/ESSDERC.2013.6818845].
Random Telegraph Noise analysis to investigate the properties of active traps of HfO2-Based RRAM in HRS
PUGLISI, Francesco Maria;PAVAN, Paolo;PADOVANI, ANDREA;LARCHER, Luca
2013
Abstract
This paper presents statistical characterization of Random Telegraph Noise (RTN) in hafnium-oxide-based Resistive Random Access Memories (RRAMs) in High Resistive State (HRS). Complex RTN signals are analyzed exploiting a Factorial Hidden Markov Model (FHMM) approach, allowing to derive the statistical properties of traps responsible of the multi-level RTN measured in these devices. Noise characteristics in different reset conditions are explored to prove the existence of a direct relation between the reset voltage, the volume of the dielectric barrier created during the reset operation and the number of active traps contributing to the RTN.
Pubblicazioni consigliate
I metadati presenti in IRIS UNIMORE sono rilasciati con licenza Creative Commons CC0 1.0 Universal, mentre i file delle pubblicazioni sono rilasciati con licenza Attribuzione 4.0 Internazionale (CC BY 4.0), salvo diversa indicazione.
In caso di violazione di copyright, contattare Supporto Iris
