skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Parallel programming of an ionic floating-gate memory array for scalable neuromorphic computing

Abstract

Neuromorphic computers could overcome efficiency bottlenecks inherent to conventional computing through parallel programming and readout of artificial neural network weights in a crossbar memory array. However, selective and linear weight updates and <10-nanoampere read currents are required for learning that surpasses conventional computing efficiency. We introduce an ionic floating-gate memory array based on a polymer redox transistor connected to a conductive-bridge memory (CBM). Selective and linear programming of a redox transistor array is executed in parallel by overcoming the bridging threshold voltage of the CBMs. Synaptic weight readout with currents <10 nanoamperes is achieved by diluting the conductive polymer with an insulator to decrease the conductance. The redox transistors endure >1 billion write-read operations and support >1-megahertz write-read frequencies.

Authors:
; ORCiD logo; ORCiD logo; ORCiD logo; ORCiD logo; ; ; ORCiD logo; ; ORCiD logo; ORCiD logo; ORCiD logo
Publication Date:
Research Org.:
Energy Frontier Research Centers (EFRC) (United States). Nanostructures for Electrical Energy Storage (NEES); Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Univ. of Maryland, College Park, MD (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES) (SC-22); USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1566723
DOE Contract Number:  
NA0003525; SC0001160
Resource Type:
Journal Article
Journal Name:
Science
Additional Journal Information:
Journal Volume: 364; Journal Issue: 6440; Journal ID: ISSN 0036-8075
Publisher:
AAAS
Country of Publication:
United States
Language:
English
Subject:
bio-inspired, energy storage (including batteries and capacitors), defects, charge transport, synthesis (novel materials), synthesis (self-assembly), synthesis (scalable processing)

Citation Formats

Fuller, Elliot J., Keene, Scott T., Melianas, Armantas, Wang, Zhongrui, Agarwal, Sapan, Li, Yiyang, Tuchman, Yaakov, James, Conrad D., Marinella, Matthew J., Yang, J. Joshua, Salleo, Alberto, and Talin, A. Alec. Parallel programming of an ionic floating-gate memory array for scalable neuromorphic computing. United States: N. p., 2019. Web. doi:10.1126/science.aaw5581.
Fuller, Elliot J., Keene, Scott T., Melianas, Armantas, Wang, Zhongrui, Agarwal, Sapan, Li, Yiyang, Tuchman, Yaakov, James, Conrad D., Marinella, Matthew J., Yang, J. Joshua, Salleo, Alberto, & Talin, A. Alec. Parallel programming of an ionic floating-gate memory array for scalable neuromorphic computing. United States. doi:10.1126/science.aaw5581.
Fuller, Elliot J., Keene, Scott T., Melianas, Armantas, Wang, Zhongrui, Agarwal, Sapan, Li, Yiyang, Tuchman, Yaakov, James, Conrad D., Marinella, Matthew J., Yang, J. Joshua, Salleo, Alberto, and Talin, A. Alec. Thu . "Parallel programming of an ionic floating-gate memory array for scalable neuromorphic computing". United States. doi:10.1126/science.aaw5581.
@article{osti_1566723,
title = {Parallel programming of an ionic floating-gate memory array for scalable neuromorphic computing},
author = {Fuller, Elliot J. and Keene, Scott T. and Melianas, Armantas and Wang, Zhongrui and Agarwal, Sapan and Li, Yiyang and Tuchman, Yaakov and James, Conrad D. and Marinella, Matthew J. and Yang, J. Joshua and Salleo, Alberto and Talin, A. Alec},
abstractNote = {Neuromorphic computers could overcome efficiency bottlenecks inherent to conventional computing through parallel programming and readout of artificial neural network weights in a crossbar memory array. However, selective and linear weight updates and <10-nanoampere read currents are required for learning that surpasses conventional computing efficiency. We introduce an ionic floating-gate memory array based on a polymer redox transistor connected to a conductive-bridge memory (CBM). Selective and linear programming of a redox transistor array is executed in parallel by overcoming the bridging threshold voltage of the CBMs. Synaptic weight readout with currents <10 nanoamperes is achieved by diluting the conductive polymer with an insulator to decrease the conductance. The redox transistors endure >1 billion write-read operations and support >1-megahertz write-read frequencies.},
doi = {10.1126/science.aaw5581},
journal = {Science},
issn = {0036-8075},
number = 6440,
volume = 364,
place = {United States},
year = {2019},
month = {4}
}

Works referenced in this record:

Deep learning
journal, May 2015

  • LeCun, Yann; Bengio, Yoshua; Hinton, Geoffrey
  • Nature, Vol. 521, Issue 7553
  • DOI: 10.1038/nature14539

Scaling for edge inference of deep neural networks
journal, April 2018


Multiscale Co-Design Analysis of Energy, Latency, Area, and Accuracy of a ReRAM Analog Neural Training Accelerator
journal, March 2018

  • Marinella, Matthew J.; Agarwal, Sapan; Hsia, Alexander
  • IEEE Journal on Emerging and Selected Topics in Circuits and Systems, Vol. 8, Issue 1
  • DOI: 10.1109/JETCAS.2018.2796379

Experimental Demonstration and Tolerancing of a Large-Scale Neural Network (165 000 Synapses) Using Phase-Change Memory as the Synaptic Weight Element
journal, November 2015

  • Burr, Geoffrey W.; Shelby, Robert M.; Sidler, Severin
  • IEEE Transactions on Electron Devices, Vol. 62, Issue 11
  • DOI: 10.1109/TED.2015.2439635

The missing memristor found
journal, May 2008

  • Strukov, Dmitri B.; Snider, Gregory S.; Stewart, Duncan R.
  • Nature, Vol. 453, Issue 7191
  • DOI: 10.1038/nature06932

Efficient and self-adaptive in-situ learning in multilayer memristor neural networks
journal, June 2018


Analogue signal and image processing with large memristor crossbars
journal, December 2017


Li-Ion Synaptic Transistor for Low Power Analog Computing
journal, November 2016

  • Fuller, Elliot J.; Gabaly, Farid El; Léonard, François
  • Advanced Materials, Vol. 29, Issue 4
  • DOI: 10.1002/adma.201604310

A non-volatile organic electrochemical device as a low-voltage artificial synapse for neuromorphic computing
journal, February 2017

  • van de Burgt, Yoeri; Lubberman, Ewout; Fuller, Elliot J.
  • Nature Materials, Vol. 16, Issue 4
  • DOI: 10.1038/nmat4856

Low-Power, Electrochemically Tunable Graphene Synapses for Neuromorphic Computing
journal, July 2018

  • Sharbati, Mohammad Taghi; Du, Yanhao; Torres, Jorge
  • Advanced Materials, Vol. 30, Issue 36
  • DOI: 10.1002/adma.201802353

All-Solid-State Synaptic Transistor with Ultralow Conductance for Neuromorphic Computing
journal, September 2018

  • Yang, Chuan-Sen; Shang, Da-Shan; Liu, Nan
  • Advanced Functional Materials, Vol. 28, Issue 42
  • DOI: 10.1002/adfm.201804170

Memristors with diffusive dynamics as synaptic emulators for neuromorphic computing
journal, September 2016

  • Wang, Zhongrui; Joshi, Saumil; Savel’ev, Sergey E.
  • Nature Materials, Vol. 16, Issue 1
  • DOI: 10.1038/nmat4756

Optimized pulsed write schemes improve linearity and write speed for low-power organic neuromorphic devices
journal, May 2018

  • Keene, Scott T.; Melianas, Armantas; Fuller, Elliot J.
  • Journal of Physics D: Applied Physics, Vol. 51, Issue 22
  • DOI: 10.1088/1361-6463/aabe70

Mechanisms for Enhanced State Retention and Stability in Redox-Gated Organic Neuromorphic Devices
journal, November 2018

  • Keene, Scott Tom; Melianas, Armantas; van de Burgt, Yoeri
  • Advanced Electronic Materials, Vol. 5, Issue 2
  • DOI: 10.1002/aelm.201800686

Energy Scaling Advantages of Resistive Memory Crossbar Based Computation and Its Application to Sparse Coding
journal, January 2016


Anatomy of Ag/Hafnia-Based Selectors with 10 10 Nonlinearity
journal, January 2017

  • Midya, Rivu; Wang, Zhongrui; Zhang, Jiaming
  • Advanced Materials, Vol. 29, Issue 12
  • DOI: 10.1002/adma.201604457

Resistance-dependent amplitude of random telegraph-signal noise in resistive switching memories
journal, February 2010

  • Ielmini, Daniele; Nardi, Federico; Cagli, Carlo
  • Applied Physics Letters, Vol. 96, Issue 5
  • DOI: 10.1063/1.3304167

Direct Measurement of Ion Mobility in a Conducting Polymer
journal, June 2013

  • Stavrinidou, Eleni; Leleux, Pierre; Rajaona, Harizo
  • Advanced Materials, Vol. 25, Issue 32
  • DOI: 10.1002/adma.201301240

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


Origin of Outstanding Stability in the Lithium Solid Electrolyte Materials: Insights from Thermodynamic Analyses Based on First-Principles Calculations
journal, October 2015

  • Zhu, Yizhou; He, Xingfeng; Mo, Yifei
  • ACS Applied Materials & Interfaces, Vol. 7, Issue 42
  • DOI: 10.1021/acsami.5b07517

Flash memory cells-an overview
journal, January 1997

  • Pavan, P.; Bez, R.; Olivo, P.
  • Proceedings of the IEEE, Vol. 85, Issue 8
  • DOI: 10.1109/5.622505

Training and operation of an integrated neuromorphic network based on metal-oxide memristors
journal, May 2015

  • Prezioso, M.; Merrikh-Bayat, F.; Hoskins, B. D.
  • Nature, Vol. 521, Issue 7550
  • DOI: 10.1038/nature14441

SiGe epitaxial memory for neuromorphic computing with reproducible high performance based on engineered dislocations
journal, January 2018


Organic electrochemical transistors
journal, January 2018


State of Understanding of Nafion
journal, October 2004

  • Mauritz, Kenneth A.; Moore, Robert B.
  • Chemical Reviews, Vol. 104, Issue 10
  • DOI: 10.1021/cr0207123

Investigation of the through-plane impedance technique for evaluation of anisotropy of proton conducting polymer membranes
journal, October 2008