Highly Controllable and Silicon-Compatible Ferroelectric Photovoltaic Synapses for Neuromorphic Computing
| Autor: | Minghui Qin, Ruiqiang Tao, Zhipeng Hou, Zhen Fan, Qicheng Huang, Xubing Lu, Jun-Ming Liu, Guofu Zhou, Shengliang Cheng, Xingsen Gao, Min Zeng, Jingjing Rao, Lanqing Hong, Guoliang Yuan |
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| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
0301 basic medicine
Materials science Semiconductor Manufacturing Materials Science 02 engineering and technology Noise (electronics) Article 03 medical and health sciences Synaptic weight Circuit Systems Devices Polarization (electrochemistry) lcsh:Science Photocurrent Multidisciplinary business.industry 021001 nanoscience & nanotechnology Ferroelectricity Controllability 030104 developmental biology Neuromorphic engineering Modulation Optoelectronics lcsh:Q 0210 nano-technology business Electrical Engineering |
| Zdroj: | iScience, Vol 23, Iss 12, Pp 101874-(2020) iScience |
| ISSN: | 2589-0042 |
| Popis: | Summary 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. Graphical Abstract Highlights • 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 |
| Databáze: | OpenAIRE |
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