Graphite-based selectorless RRAM: Improvable intrinsic nonlinearity for array applications

  • Ying Chen Chen
  • , Szu Tung Hu
  • , Chih Yang Lin
  • , Burt Fowler
  • , Hui Chun Huang
  • , Chao Cheng Lin
  • , Sungjun Kim
  • , Yao Feng Chang
  • , Jack C. Lee

Research output: Contribution to journalArticlepeer-review

31 Scopus citations

Abstract

Selectorless graphite-based resistive random-access memory (RRAM) has been demonstrated by utilizing the intrinsic nonlinear resistive switching (RS) characteristics, without an additional selector or transistor for low-power RRAM array application. The low effective dielectric constant value (k) layer of graphite or graphite oxide is utilized, which is beneficial in suppressing sneak-path currents in the crossbar RRAM array. The tail-bits with low nonlinearity can be manipulated by the positive voltage pulse, which in turn can alleviate variability and reliability issues. Our results provide additional insights for built-in nonlinearity in 1R-only selectorless RRAMs, which are applicable to the low-power memory array, ultrahigh density storage, and in-memory neuromorphic computational configurations.

Original languageEnglish
Pages (from-to)15608-15614
Number of pages7
JournalNanoscale
Volume10
Issue number33
DOIs
StatePublished - 7 Sep 2018

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