Statistical nature of hard breakdown recovery in high-κ dielectric stacks studied using ramped voltage stress

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

1 Scopus Citations
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Author(s)

  • X. Feng
  • N. Raghavan
  • S. Mei
  • S. Dong
  • K.L. Pey

Related Research Unit(s)

Detail(s)

Original languageEnglish
Pages (from-to)164-168
Journal / PublicationMicroelectronics Reliability
Volume88-90
Online published30 Sep 2018
Publication statusPublished - Sep 2018

Abstract

In replacing the conventional SiO2 gate dielectric with high-κ materials, new challenges emerge on understanding the kinetics of dielectric breakdown due to the different properties of the new bulk oxide and the interfacial layers at the substrate and gate electrode interface as well. Among several complexities, dielectric relaxation and recovery have received a lot of attention due to their promising applications in resistive random access memory (RRAM). In this study, we explore the stochastic nature of hard breakdown recovery in HfO2, taking advantage of ramped voltage stress (RVS) measurements, which are theoretically equivalent to the widely used constant voltage stress (CVS), while being significantly less time-consuming. We found that the possibility of recovery is largely dependent on the ramp rate during RVS as the dielectric needs adequate time and sufficient thermal budget to recover. The clustering model is found to be a good fit to the RVS data sets for post-recovery subsequent breakdown events and the extent of defect clustering is found to be more intense after increasing number of recovery events. The breakdown mechanism in the stack is confirmed by measuring the resistance change trends with temperature.

Research Area(s)

  • Clustering model, Hard breakdown recovery, High-κ dielectric, Ramped voltage stress, Weibull distribution, Weibull slope

Citation Format(s)