Brain‐inspired Multimodal Synaptic Memory via Mechano‐photonic Plasticized Asymmetric Ferroelectric Heterostructure

作者：Jie Gong, Yichen Wei, Yifei Wang, Zhenyu Feng, Jinran Yu, Liuqi Cheng, Mingxia Chen, Lin Li, Zhong Lin Wang, Qijun Sun · 发表于：Advanced Functional Materials · 年份：2024 · DOI：10.1002/adfm.202408435 · 被引用次数：37 · 研究领域：Advanced Memory and Neural Computing、Photoreceptor and optogenetics research、Neuroscience and Neural Engineering

Abstract Neuromorphic devices capable of emulating biological synaptic behaviors are crucial for implementing brain‐like information processing and computing. Emerging 2D ferroelectric neuromorphic devices provide an effective means of updating synaptic weight aside from conventional electrical/optical modulations. Here, by further synergizing with an energy‐efficient synaptic plasticity strategy, a multimodal mechano‐photonic synaptic memory device based on 2D asymmetric ferroelectric heterostructure is presented, which can be modulated by external mechanical behavior and light illumination. By integrating the asymmetric ferroelectric heterostructured field‐effect transistor and a triboelectric nanogenerator, the mechanical displacement‐derived triboelectric potential is ready for gating, programming, and plasticizing the synaptic device, resulting in superior electrical properties of high on/off ratios (> 10 7 ), large storage windows (equivalent to ≈95 V), excellent charge retention capability (> 10 4 s), good endurance (> 10 3 cycles), and primary synaptic behaviors. Besides, optical illumination can effectively synergize with mechanoplasticity to implement multimodal spatiotemporally correlated dynamic logic. The demonstrated multimodal memory synapse provides a facile and promising strategy for multifunctional sensory memory, interactive neuromorphic devices, and future brain‐like electronics embodying artificial intelligence.