RTN analysis with FHMM as a tool for multi-trap characterization in HfO<inf>X</inf> RRAM

Abstract

This paper presents a new technique to analyze the characteristics of multi-level random telegraph noise (RTN) in HfO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">X</sub> RRAM. RTN is characterized by abrupt switching of either the current or the voltage between discrete values as a result of trapping/de-trapping activity while reading the RRAM cell. RTN statistical properties are deduced exploiting a factorial hidden Markov model (FHMM). The proposed method considers the measured multi-level RTN as a superposition of many two-levels RTN, each represented by a Markov chain and associated to a single trap, and it is used to retrieve the statistical properties of each chain. These properties (i.e. dwell times and amplitude) are directly related to physical properties of each trap.