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Updated: Jan 17, 2026

Scalable Quantum Integrated Circuits on Superconducting Two-Dimensional Electron Gas Platform
Published on: August 2, 2019
Two-dimensional ferroelectric synaptic devices enabled by diverse coupling mechanisms
Youna Huang1,2,3, Wei Wang2, Yang Li2
1Department of Materials Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong 518105, China. licj@sustech.edu.cn.
Abstract:
Two-dimensional (2D) van der Waals (vdW) ferroelectric (FE) materials have recently emerged as promising candidates for advanced synaptic devices in brain-inspired neuromorphic computing systems. These materials retain ferroelectricity down to a few atomic layers, including the monolayer limit. Their unique properties-such as atomically clean surface/interface, mechanical flexibility, and LEGO®-like stacking capability-offer significant advantages for complementary metal-oxide-semiconductor (CMOS)-compatible fabrication, enabling high integration density, energy-efficient operation, and fast switching speed. Importantly, the intrinsic polarization in 2D ferroelectrics can couple with various physical phenomena, enabling the emulation of complex biological synaptic behaviors. This review provides a comprehensive overview of recent advances in 2D ferroelectric-based synaptic devices, with a particular focus on the role of coupling mechanisms within these materials. Firstly, we introduce the principles of neuromorphic computing, and advantages of 2D ferroelectric materials. Next, we classify 2D ferroelectric materials according to five key types of coupling mechanisms. We then review representative studies on 2D FE-based synaptic devices by analyzing how each coupling mechanism is utilized to achieve synaptic functionality. Finally, we discuss current challenges and prospects for leveraging these coupling mechanisms in synaptic applications. The purpose of this review is to provide a structured understanding of how intrinsic coupling in 2D ferroelectric materials can be utilized for the design of high-performance and biologically inspired synaptic devices.
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