Bending Resistant Multibit Memristor for Flexible Precision Inference Engine Application

Parthasarathi Pal, Ke Jing Lee, Sunanda Thunder, Sourav De, Po Tsang Huang, Thomas Kampfe, Yeong Her Wang

Research output: Contribution to journalArticlepeer-review

Abstract

This work reports 2-bits/cell hafnium oxide-based stacked resistive random access memory devices fabricated on flexible polyimide substrates for neuromorphic applications considering the high thermal budget. The ratio of low-resistance state current (ION) to high-resistance state current (IOFF) or ION/IOFF for the fabricated devices was above 1.4×103 with a low device-to-device variation at 100 μA current compliance. The mechanical stability over 104 bending cycles at a 5 mm bending radius and endurance over 106 WRITE cycles makes these devices suitable for online neural network training. The data retention capability over 104s at 125°C also infuses these devices' long-term inference capability. Furthermore, the performance of the devices has been verified for neuromorphic applications by system-level simulations with experimentally calibrated data. The system-level simulation reveals only a 2% loss in inference accuracy over ten years from the baseline.

Original languageEnglish
Pages (from-to)4737-4743
Number of pages7
JournalIEEE Transactions on Electron Devices
Volume69
Issue number8
DOIs
Publication statusPublished - 2022 Aug 1

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Electrical and Electronic Engineering

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