Issue 2, 2021

Ferroelectric polymer-based artificial synapse for neuromorphic computing

Abstract

Recently, various efforts have been made to implement synaptic characteristics with a ferroelectric field-effect transistor (FeFET), but in-depth physical analyses have not been reported thus far. Here, we investigated the effects by (i) the formation temperature of the ferroelectric material, poly(vinylidene fluoride-trifluoroethylene) P(VDF-TrFE) and (ii) the nature of the contact metals (Ti, Cr, Pd) of the FeFET on the operating performance of a FeFET-based artificial synapse in terms of various synaptic performance indices. Excellent ferroelectric properties were induced by maximizing the size and coverage ratio of the β-phase domains by annealing the P(VDF-TrFE) film at 140 °C. A metal that forms a relatively high barrier improved the dynamic range and nonlinearity by suppressing the contribution of the tunneling current to the post-synaptic current. Subsequently, we studied the influence of the synaptic characteristics on the training and recognition tasks by using two MNIST datasets (fashion and handwritten digits) and the multi-layer perceptron concept of neural networks.

Graphical abstract: Ferroelectric polymer-based artificial synapse for neuromorphic computing

Supplementary files

Article information

Article type
Communication
Submitted
23 Sept. 2020
Accepted
18 Nov. 2020
First published
24 Dec. 2020

Nanoscale Horiz., 2021,6, 139-147

Ferroelectric polymer-based artificial synapse for neuromorphic computing

S. Kim, K. Heo, S. Lee, S. Seo, H. Kim, J. Cho, H. Lee, K. Lee and J. Park, Nanoscale Horiz., 2021, 6, 139 DOI: 10.1039/D0NH00559B

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