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  • 标题:Highly Controllable and Silicon-Compatible Ferroelectric Photovoltaic Synapses for Neuromorphic Computing
  • 本地全文:下载
  • 作者:Shengliang Cheng ; Zhen Fan ; Jingjing Rao
  • 期刊名称:iScience
  • 印刷版ISSN:2589-0042
  • 出版年度:2020
  • 卷号:23
  • 期号:12
  • 页码:1-52
  • DOI:10.1016/j.isci.2020.101874
  • 语种:English
  • 出版社:Elsevier
  • 摘要:SummaryFerroelectric synapses using polarization switching (a purely electronic switching process) to induce analog conductance change have attracted considerable interest. Here, we propose ferroelectric photovoltaic (FePV) synapses that use polarization-controlled photocurrent as the readout and thus have no limitations on the forms and thicknesses of the constituent ferroelectric and electrode materials. This not only makes FePV synapses easy to fabricate but also reduces the depolarization effect and hence enhances the polarization controllability. As a proof-of-concept implementation, a Pt/Pb(Zr0.2Ti0.8)O3/LaNiO3FePV synapse is facilely grown on a silicon substrate, which demonstrates continuous photovoltaic response modulation with good controllability (small nonlinearity and write noise) enabled by gradual polarization switching. Using photovoltaic response as synaptic weight, this device exhibits versatile synaptic functions including long-term potentiation/depression and spike-timing-dependent plasticity. A simulated FePV synapse-based neural network achieves high accuracies (>93%) for image recognition. This study paves a new way toward highly controllable and silicon-compatible synapses for neuromorphic computing.Graphical AbstractDisplay OmittedHighlights•Switchable ferroelectric photovoltaic (FePV) effect is used for synaptic application•Tunable photovoltaic response is enabled by gradual polarization switching•Versatile synaptic functions and high image recognition accuracy are achieved•The FePV synapses are facilely grown on silicon substratesCircuit Systems; Electrical Engineering; Semiconductor Manufacturing; Materials Science; Devices
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