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Title: Atomically Thin CBRAM Enabled by 2-D Materials: Scaling Behaviors and Performance Limits

Abstract

Reducing the energy and power dissipation of conductive bridge random access memory (CBRAM) cells is of critical importance for their applications in future Internet of Things (IoT) device and neuromorphic computing platforms. Atomically thin CBRAMs enabled by 2-D materials are studied theoretically by using 3-D kinetic Monte Carlo simulations together with experimental characterization. The results indicate the performance potential of attoJoule energy dissipation for intrinsic filament formation and a filament size of a single atomistic chain in such a CBRAM cell. The atomically thin CBRAM cells also show qualitatively different features from conventional CBRAM cells, including complete rupture of the filament in the reset stage and comparable forming and set voltages. The scaling and variability of the CBRAM cells down to sub-nanometer size of the switching layer as realized in the experiment are systematically studied, which indicates performance improvement and increased relative variability as the switching layer scales down. Finally, the results establish the ultimate limits of the size and energy scaling for CBRAM cells and illustrate the unique application of 2-D materials in ultralow power memory devices.

Authors:
ORCiD logo [1]; ORCiD logo [2];  [3];  [4];  [4];  [3];  [2]; ORCiD logo [1]
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  1. Univ. of Florida, Gainesville, FL (United States). Dept. of Electrical and Computer Engineering
  2. Univ. of Southern California, Los Angeles, CA (United States). Ming Hsieh Dept. of Electrical Engineering
  3. NG Next, Northrop Grumman Corporation, Redondo Beach, CA (United States)
  4. Brookhaven National Lab. (BNL), Upton, NY (United States)
Publication Date:
Research Org.:
Brookhaven National Lab. (BNL), Upton, NY (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES)
OSTI Identifier:
1477961
Report Number(s):
BNL-209193-2018-JAAM
Journal ID: ISSN 0018-9383
Grant/Contract Number:  
SC0012704
Resource Type:
Accepted Manuscript
Journal Name:
IEEE Transactions on Electron Devices
Additional Journal Information:
Journal Volume: 65; Journal Issue: 10; Journal ID: ISSN 0018-9383
Publisher:
IEEE
Country of Publication:
United States
Language:
English
Subject:
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND SUPERFLUIDITY

Citation Formats

Dong, Zhipeng, Zhao, Huan, DiMarzio, Don, Han, Myung-Geun, Zhang, Lihua, Tice, Jesse, Wang, Han, and Guo, Jing. Atomically Thin CBRAM Enabled by 2-D Materials: Scaling Behaviors and Performance Limits. United States: N. p., 2018. Web. doi:10.1109/TED.2018.2830328.
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Dong, Zhipeng, Zhao, Huan, DiMarzio, Don, Han, Myung-Geun, Zhang, Lihua, Tice, Jesse, Wang, Han, & Guo, Jing. Atomically Thin CBRAM Enabled by 2-D Materials: Scaling Behaviors and Performance Limits. United States. https://doi.org/10.1109/TED.2018.2830328
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Dong, Zhipeng, Zhao, Huan, DiMarzio, Don, Han, Myung-Geun, Zhang, Lihua, Tice, Jesse, Wang, Han, and Guo, Jing. Tue . "Atomically Thin CBRAM Enabled by 2-D Materials: Scaling Behaviors and Performance Limits". United States. https://doi.org/10.1109/TED.2018.2830328. https://www.osti.gov/servlets/purl/1477961.
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@article{osti_1477961,
title = {Atomically Thin CBRAM Enabled by 2-D Materials: Scaling Behaviors and Performance Limits},
author = {Dong, Zhipeng and Zhao, Huan and DiMarzio, Don and Han, Myung-Geun and Zhang, Lihua and Tice, Jesse and Wang, Han and Guo, Jing},
abstractNote = {Reducing the energy and power dissipation of conductive bridge random access memory (CBRAM) cells is of critical importance for their applications in future Internet of Things (IoT) device and neuromorphic computing platforms. Atomically thin CBRAMs enabled by 2-D materials are studied theoretically by using 3-D kinetic Monte Carlo simulations together with experimental characterization. The results indicate the performance potential of attoJoule energy dissipation for intrinsic filament formation and a filament size of a single atomistic chain in such a CBRAM cell. The atomically thin CBRAM cells also show qualitatively different features from conventional CBRAM cells, including complete rupture of the filament in the reset stage and comparable forming and set voltages. The scaling and variability of the CBRAM cells down to sub-nanometer size of the switching layer as realized in the experiment are systematically studied, which indicates performance improvement and increased relative variability as the switching layer scales down. Finally, the results establish the ultimate limits of the size and energy scaling for CBRAM cells and illustrate the unique application of 2-D materials in ultralow power memory devices.},
doi = {10.1109/TED.2018.2830328},
journal = {IEEE Transactions on Electron Devices},
number = 10,
volume = 65,
place = {United States},
year = {Tue May 08 00:00:00 EDT 2018},
month = {Tue May 08 00:00:00 EDT 2018}
}
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Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record
https://doi.org/10.1109/TED.2018.2830328
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Cited by: 15 works
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Figures / Tables:

Figure 1 Figure 1: (a) Schematic plot of the atomically thin CBRAM. Here the active electrode is Ag (Silver) and the inert electrode is graphene. An atomically thin BNOx layer with a thickness down to tBNO~0.9 nm, which is formed from partially oxidizing h-BN bilayer, is used as the switching layer. (b)more » Raman plot of bilayer h-BN and BNOx layer. (c) The AFM image (right panel) with its height profile (left panel) and (d) STEM image of a fabricated device, which shows a measured thickness of ~0.9 nm of the BNOx layer between the Ag and graphene electrodes.« less
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Works referencing / citing this record:

Emerging Artificial Synaptic Devices for Neuromorphic Computing
journal, February 2019

  • Wan, Qingzhou; Sharbati, Mohammad T.; Erickson, John R.
  • Advanced Materials Technologies, Vol. 4, Issue 4
  • DOI: 10.1002/admt.201900037

Quantized Conduction Device with 6‐Bit Storage Based on Electrically Controllable Break Junctions
journal, September 2019

  • Banerjee, Writam; Hwang, Hyunsang
  • Advanced Electronic Materials, Vol. 5, Issue 12
  • DOI: 10.1002/aelm.201900744

Ultra compact electrochemical metallization cells offering reproducible atomic scale memristive switching
journal, March 2019

Efficient learning and crossbar operations with atomically-thin 2-D material compound synapses
journal, October 2018

  • Sanchez Esqueda, Ivan; Zhao, Huan; Wang, Han
  • Journal of Applied Physics, Vol. 124, Issue 15
  • DOI: 10.1063/1.5042468

High on/off ratio black phosphorus based memristor with ultra-thin phosphorus oxide layer
journal, November 2019

  • Wang, Yudan; Wu, Facai; Liu, Xingqiang
  • Applied Physics Letters, Vol. 115, Issue 19
  • DOI: 10.1063/1.5115531

Ultra compact electrochemical metallization cells offering reproducible atomic scale memristive switching
text, January 2019

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