Abstract
Ferroelectrics 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-In2 Se3 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-In2 Se3 channel is responsible for the resistance switching at various paired terminals. The third terminal of α-In2 Se3 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-In2 Se3 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.
Highlights
Device scaling in Si-based integrated circuits has slowed due to the approaching physical limit, leading to difficulties in the extension of Moore’s Law.[1]
Integrating in-memory computing with the multiterminal design of heterosynaptic devices could be one approach to realize the Boolean logic with a single logic cycle
It is worth mentioning that our multiterminal ferroelectric memristors can operate at picoampere-range current, less than 4 V poling bias, and femtojoule read-energy consumption, which is promising for energy-efficient neuromorphic inmemory computing systems.[23]
Summary
Device scaling in Si-based integrated circuits has slowed due to the approaching physical limit, leading to difficulties in the extension of Moore’s Law.[1]. Integrating in-memory computing with the multiterminal design of heterosynaptic devices could be one approach to realize the Boolean logic with a single logic cycle. Toward this aim, ferroelectric materials are considered excellent building blocks for nonvolatile resistance switching memories that could be adopted for neuromorphic in-memory computing systems. He Department of Materials Science and Engineering City University of Hong Kong Kowloon, Hong Kong, China network (CNN) and spiking neural network can be simulated to fulfill supervised and unsupervised learning, respectively. The demonstrated logic operations for OR and NOR gates in the α-In2Se3 memristors only require a single logic cycle, providing a route for devising high-efficient neuromorphic in-memory devices
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
