Learning through ferroelectric domain dynamics in solid-state synapses
Abstract
In the brain, learning is achieved through the ability of synapses to reconfigure the strength by which they connect neurons (synaptic plasticity). In promising solid-state synapses called memristors, conductance can be finely tuned by voltage pulses and set to evolve according to a biological learning rule called spike-timing-dependent plasticity (STDP). Future neuromorphic architectures will comprise billions of such nanosynapses, which require a clear understanding of the physical mechanisms responsible for plasticity. Here we report on synapses based on ferroelectric tunnel junctions and show that STDP can be harnessed from inhomogeneous polarization switching. Through combined scanning probe imaging, electrical transport and atomic-scale molecular dynamics, we demonstrate that conductance variations can be modelled by the nucleation-dominated reversal of domains. Finally, based on this physical model, our simulations show that arrays of ferroelectric nanosynapses can autonomously learn to recognize patterns in a predictable way, opening the path towards unsupervised learning in spiking neural networks.
- Authors:
-
[4];
[5];
- Univ. Paris-Saclay, Palaiseau (France); ETH Zurich, Zurich (Switzerland)
- Univ. Paris-Saclay, Palaiseau (France)
- Univ. of Bordeaux, Talence (France)
- Univ. of Arkansas, Fayetteville, AR (United States)
- Univ. Paris-Saclay, Orsay Cedex (France)
- Univ. Paris-Saclay, Palaiseau (France); Luxembourg Institute of Science and Technology (LIST), Belvaux (Luxembourg)
- Campus de l'Ecole Polytechnique, Palaiseau (France)
- Publication Date:
- Research Org.:
- Univ. of Arkansas, Fayetteville, AR (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), Basic Energy Sciences (BES); Defense Advanced Research Projects Agency (DARPA); European Union (EU); European Research Council (ERC)
- OSTI Identifier:
- 1367544
- Grant/Contract Number:
- SC0002220; HR0011-15-2- 0038
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Nature Communications
- Additional Journal Information:
- Journal Volume: 8; Journal ID: ISSN 2041-1723
- Publisher:
- Nature Publishing Group
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 60 APPLIED LIFE SCIENCES; electronic devices; ferroelectrics and multiferroics
Citation Formats
Boyn, Soren, Grollier, Julie, Lecerf, Gwendal, Xu, Bin, Locatelli, Nicolas, Fusil, Stephane, Girod, Stephanie, Carretero, Cecile, Garcia, Karin, Xavier, Stephane, Tomas, Jean, Bellaiche, Laurent, Bibes, Manuel, Barthelemy, Agnes, Saighi, Sylvain, and Garcia, Vincent. Learning through ferroelectric domain dynamics in solid-state synapses. United States: N. p., 2017.
Web. doi:10.1038/ncomms14736.
Boyn, Soren, Grollier, Julie, Lecerf, Gwendal, Xu, Bin, Locatelli, Nicolas, Fusil, Stephane, Girod, Stephanie, Carretero, Cecile, Garcia, Karin, Xavier, Stephane, Tomas, Jean, Bellaiche, Laurent, Bibes, Manuel, Barthelemy, Agnes, Saighi, Sylvain, & Garcia, Vincent. Learning through ferroelectric domain dynamics in solid-state synapses. United States. https://doi.org/10.1038/ncomms14736
Boyn, Soren, Grollier, Julie, Lecerf, Gwendal, Xu, Bin, Locatelli, Nicolas, Fusil, Stephane, Girod, Stephanie, Carretero, Cecile, Garcia, Karin, Xavier, Stephane, Tomas, Jean, Bellaiche, Laurent, Bibes, Manuel, Barthelemy, Agnes, Saighi, Sylvain, and Garcia, Vincent. Mon .
"Learning through ferroelectric domain dynamics in solid-state synapses". United States. https://doi.org/10.1038/ncomms14736. https://www.osti.gov/servlets/purl/1367544.
@article{osti_1367544,
title = {Learning through ferroelectric domain dynamics in solid-state synapses},
author = {Boyn, Soren and Grollier, Julie and Lecerf, Gwendal and Xu, Bin and Locatelli, Nicolas and Fusil, Stephane and Girod, Stephanie and Carretero, Cecile and Garcia, Karin and Xavier, Stephane and Tomas, Jean and Bellaiche, Laurent and Bibes, Manuel and Barthelemy, Agnes and Saighi, Sylvain and Garcia, Vincent},
abstractNote = {In the brain, learning is achieved through the ability of synapses to reconfigure the strength by which they connect neurons (synaptic plasticity). In promising solid-state synapses called memristors, conductance can be finely tuned by voltage pulses and set to evolve according to a biological learning rule called spike-timing-dependent plasticity (STDP). Future neuromorphic architectures will comprise billions of such nanosynapses, which require a clear understanding of the physical mechanisms responsible for plasticity. Here we report on synapses based on ferroelectric tunnel junctions and show that STDP can be harnessed from inhomogeneous polarization switching. Through combined scanning probe imaging, electrical transport and atomic-scale molecular dynamics, we demonstrate that conductance variations can be modelled by the nucleation-dominated reversal of domains. Finally, based on this physical model, our simulations show that arrays of ferroelectric nanosynapses can autonomously learn to recognize patterns in a predictable way, opening the path towards unsupervised learning in spiking neural networks.},
doi = {10.1038/ncomms14736},
journal = {Nature Communications},
number = ,
volume = 8,
place = {United States},
year = {Mon Apr 03 00:00:00 EDT 2017},
month = {Mon Apr 03 00:00:00 EDT 2017}
}
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- Liddle, J. A.; Hoskins, B. D.; Vladár, A. E.
- APL Materials, Vol. 6, Issue 7
Memristive behavior of field-driven domain-wall motion in a width-modulated structure with multiple Hall crosses
journal, November 2018
- Hwang, H. -K.; Kwon, J.; Lee, K. -S.
- Journal of Applied Physics, Vol. 124, Issue 19
An epitaxial synaptic device made by a band-offset BaTiO 3 /Sr 2 IrO 4 bilayer with high endurance and long retention
journal, March 2019
- Xu, Hui; Zhai, Xiaofang; Wang, Zhicheng
- Applied Physics Letters, Vol. 114, Issue 10
Memcomputing and Nondestructive Reading in Functional Ferroelectric Heterostructures
journal, August 2019
- Boni, Georgia A.; Filip, Lucian D.; Chirila, Cristina
- Physical Review Applied, Vol. 12, Issue 2
Gate‐Tunable and Multidirection‐Switchable Memristive Phenomena in a Van Der Waals Ferroelectric
journal, May 2019
- Xue, Fei; He, Xin; Retamal, José Ramón Durán
- Advanced Materials, Vol. 31, Issue 29
Efficient two-terminal artificial synapse based on a network of functionalized conducting polymer nanowires
journal, January 2019
- Jiang, Chunli; Zhang, Yu; Tian, Bobo
- Journal of Materials Chemistry C, Vol. 7, Issue 32
Neuromorphic computing with multi-memristive synapses
text, January 2017
- Boybat, Irem; Gallo, Manuel Le; Nandakumar, S. R.
- arXiv
Electric Field Driven Memristive Behavior at the Schottky Interface of Nb doped SrTiO3
text, January 2018
- Goossens, A. S.; Das, A.; Banerjee, T.
- arXiv
Tuning a binary ferromagnet into a multi-state synapse with spin-orbit torque induced plasticity
text, January 2018
- Cao, Yi; Rushforth, Andrew; Sheng, Yu
- arXiv