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Advanced Materials
Article . 2021 . Peer-reviewed
License: CC BY
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Advanced Materials
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License: CC BY
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Giant Ferroelectric Resistance Switching Controlled by a Modulatory Terminal for Low‐Power Neuromorphic In‐Memory Computing

Authors: Fei Xue; Xin He; Zhenyu Wang; José Ramón Durán Retamal; Zheng Chai; Lingling Jing; Chenhui Zhang; +9 Authors

Giant Ferroelectric Resistance Switching Controlled by a Modulatory Terminal for Low‐Power Neuromorphic In‐Memory Computing

Abstract

AbstractFerroelectrics have been demonstrated as excellent building blocks for high‐performance nonvolatile memories, including memristors, which play critical roles in the hardware implementation of artificial synapses and in‐memory computing. Here, it is reported that the emerging van der Waals ferroelectric α‐In2Se3 can be used to successfully implement heterosynaptic plasticity (a fundamental but rarely emulated synaptic form) and achieve a resistance‐switching ratio of heterosynaptic memristors above 103, which is two orders of magnitude larger than that in other similar devices. The polarization change of ferroelectric α‐In2Se3 channel is responsible for the resistance switching at various paired terminals. The third terminal of α‐In2Se3 memristors exhibits nonvolatile control over channel current at a picoampere level, endowing the devices with picojoule read‐energy consumption to emulate the associative heterosynaptic learning. The simulation proves that both supervised and unsupervised learning manners can be implemented in α‐In2Se3 neutral networks with high image recognition accuracy. Moreover, these heterosynaptic devices can naturally realize Boolean logic without an additional circuit component. The results suggest that van der Waals ferroelectrics hold great potential for applications in complex, energy‐efficient, brain‐inspired computing systems and logic‐in‐memory computers.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
109
Top 1%
Top 10%
Top 1%
hybrid