Details

Autor(en) / Beteiligte

• Kim, Sungjun
• Heo, Keun
• Lee, Sunghun
• Seo, Seunghwan
• Kim, Hyeongjun
• Cho, Jeongick
• Lee, Hyunkyu
• Lee, Kyeong-Bae
• Park, Jin-Hong

Titel

Ferroelectric polymer-based artificial synapse for neuromorphic computing

Ist Teil von

• Nanoscale horizons, 2021-02, Vol.6 (2), p.139-147

Ort / Verlag

England: Royal Society of Chemistry

Erscheinungsjahr

2021

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• 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. 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.