Controlling Cu Migration on Resistive Switching, Artificial Synapse, and Glucose/Saliva Detection by Using an Optimized AlO x Interfacial Layer in a-CO x-Based Conductive Bridge Random Access Memory

Sreekanth Ginnaram, Jiantai Timothy Qiu, Siddheswar Maikap

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)

Abstract

The Cu migration is controlled by using an optimized AlOx interfacial layer, and effects on resistive switching performance, artificial synapse, and human saliva detection in an amorphous-oxygenated-carbon (a-COx)-based CBRAM platform have been investigated for the first time. The 4 nm-thick AlOx layer in the Cu/AlOx/a-COx/TiNxOy/TiN structure shows consecutive >2000 DC switching, tight distribution of SET/RESET voltages, a long program/erase (P/E) endurance of >109 cycles at a low operation current of 300 μA, and artificial synaptic characteristics under a small pulse width of 100 ns. After a P/E endurance of >108 cycles, the Cu migration is observed by both ex situ high-resolution transmission electron microscopy and energy-dispersive X-ray spectroscopy mapping images. Furthermore, the optimized Cu/AlOx/a-COx/TiNxOy/TiN CBRAM detects glucose with a low concentration of 1 pM, and real-time measurement of human saliva with a small sample volume of 1 μL is also detected repeatedly in vitro. This is owing to oxidation-reduction of Cu electrode, and the switching mechanism is explored. Therefore, this CBRAM device is beneficial for future artificial intelligence application.

Original languageEnglish
Pages (from-to)7032-7043
Number of pages12
JournalACS Omega
Volume5
Issue number12
DOIs
Publication statusAccepted/In press - 2020
Externally publishedYes

ASJC Scopus subject areas

  • Chemistry(all)
  • Chemical Engineering(all)

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