Self-rectifying resistive memory in passive crossbar arrays

Kanghyeok Jeon, Jeeson Kim, Jin Joo Ryu, Seung Jong Yoo, Choongseok Song, Min Kyu Yang, Doo Seok Jeong, Gun Hwan Kim

Research output: Contribution to journalArticlepeer-review


Conventional computing architectures are poor suited to the unique workload demands of deep learning, which has led to a surge in interest in memory-centric computing. Herein, a trilayer (Hf0.8Si0.2O2/Al2O3/Hf0.5Si0.5O2)-based self-rectifying resistive memory cell (SRMC) that exhibits (i) large selectivity (ca. 104), (ii) two-bit operation, (iii) low read power (4 and 0.8 nW for low and high resistance states, respectively), (iv) read latency (<10 μs), (v) excellent non-volatility (data retention >104 s at 85 °C), and (vi) complementary metal-oxide-semiconductor compatibility (maximum supply voltage ≤5 V) is introduced, which outperforms previously reported SRMCs. These characteristics render the SRMC highly suitable for the main memory for memory-centric computing which can improve deep learning acceleration. Furthermore, the low programming power (ca. 18 nW), latency (100 μs), and endurance (>106) highlight the energy-efficiency and highly reliable random-access memory of our SRMC. The feasible operation of individual SRMCs in passive crossbar arrays of different sizes (30 × 30, 160 × 160, and 320 × 320) is attributed to the large asymmetry and nonlinearity in the current-voltage behavior of the proposed SRMC, verifying its potential for application in large-scale and high-density non-volatile memory for memory-centric computing.

Original languageEnglish
Article number2968
JournalNature communications
Issue number1
Publication statusPublished - 2021 Dec 1

Bibliographical note

Funding Information:
G.H.K. would like to acknowledge a Korea Research Institute of Chemical Technology grant (Grant no. SS2021-20; Development of smart chemical materials for IoT devices). This work was partly supported by a research grant from the National Research Foundation of Korea under Grant no. NRF-2019R1C1C1009810. This research was also supported by the Ministry of Trade, Industry & Energy (grant number 20012002) and Korea Semiconductor Research Consortium program for the development of future semiconductor devices.

Publisher Copyright:
© 2021, The Author(s).

All Science Journal Classification (ASJC) codes

  • Chemistry(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • General
  • Physics and Astronomy(all)


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