Giant ferroelectric resistance switching controlled by a modulatory terminal for low-power neuromorphic in-memory computing
Duran Retamal, Jose Ramon
Alshareef, Husam N.
KAUST DepartmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Electrical Engineering Program
Functional Nanomaterials and Devices Research Group
KAUST Solar Center (KSC)
Material Science and Engineering Program
Nano Energy Lab
Physical Science and Engineering (PSE) Division
Embargo End Date2022-03-02
Permanent link to this recordhttp://hdl.handle.net/10754/667793
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AbstractFerroelectrics have been demonstrated as excellent building blocks for high-performance non-volatile memories, including memristors, which play critical roles in the hardware implementation of artificial synapses and in-memory computing. Here, we report 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 order 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. Our 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. Our 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.
CitationXue, F., He, X., Wang, Z., Retamal, J. R. D., Chai, Z., Jing, L., … Zhang, X. (2021). Giant Ferroelectric Resistance Switching Controlled by a Modulatory Terminal for Low-Power Neuromorphic In-Memory Computing. Advanced Materials, 2008709. doi:10.1002/adma.202008709
SponsorsThe research presented here was supported by the King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR) under Award No: CRF-2015- 2634-CRG4 and CRF-2016- 2996 -CRG5. Y. C. thanks the financial support from the Research Grant Council of Hong Kong (152053/18E). We thank Prof. Tuo-Hung Hou for helpful suggestions. J. -H. H. thanks the financial support from the startup fund of City University of Hong Kong.
JournalAccepted by Advanced Materials