Highly Controllable and Silicon-Compatible Ferroelectric Photovoltaic Synapses for Neuromorphic Computing.
Highly Controllable and Silicon-Compatible Ferroelectric Photovoltaic Synapses for Neuromorphic Computing.
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用于神经形态计算的高度可控且硅兼容的铁电光伏突触
DOI:
10.1016/j.isci.2020.101874
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发表时间:
2020-12-18
期刊:
影响因子:
5.8
通讯作者:
Liu JM
中科院分区:
文献类型:
--
作者:
Cheng S;Fan Z;Rao J;Hong L;Huang Q;Tao R;Hou Z;Qin M;Zeng M;Lu X;Zhou G;Yuan G;Gao X;Liu JM
Ferroelectric 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/LaNiO3 FePV 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. 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 substrates Circuit Systems; Electrical Engineering; Semiconductor Manufacturing; Materials Science; Devices
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