Advances in 2D Linear‐Polarization‐Sensitive Optoelectronic Synapses: From Anisotropic Carrier Dynamics to Neuromorphic Polarized Vision
Boyu Ye, Xiao Liu, Lang Pei, Xusheng Wang, Wensheng Yan, Xiaodong Pi
Hangzhou Dianzi University Zhejiang Sci-Tech University Zhejiang University of Science and Technology State Key Laboratory of Silicon Materials
阅读操作
确认中在文库中上传 PDF 后可生成中文音频讲解。
摘要与影响
Integrating polarization discrimination directly into optoelectronic synapses enables the fusion of polarization perception, memory, and preprocessing at the device level, thereby enhancing information density and computational efficiency. This architecture overcomes the limitations of conventional polarization detection schemes that rely on bulky optical components and external data processing. Two‐dimensional (2D) materials provide a versatile platform for such on‐chip linear‐polarization‐sensitive optoelectronic synapses (LPOSs), owing to their tunable anisotropy and heterointegration compatibility. This review systematically surveys recent advances in 2D LPOSs through three material design strategies: intrinsic low‐symmetry crystals, heterostructure engineering, and artificially induced anisotropy. We establish a comparative framework correlating crystal symmetry, polarization‐selective absorption, carrier dynamics, and synaptic plasticity via four key mechanisms: defect‐dominated carrier trapping, strain‐bulk photovoltaic (strain‐BPV)‐assisted carrier separation, intrinsic slow carrier relaxation, and heterojunction‐mediated charge storage. We further highlight emerging applications in polarization‐encoded optical communication, bioinspired navigation, and in‐sensor imaging. Finally, we discuss critical challenges and outline future directions toward strongly anisotropic materials, actively tunable polarization sensitivity, and wafer‐scale integration, offering a roadmap for high‐performance LPOSs and compact neuromorphic polarized visual systems.
逐年被引趋势
暂无年度引用数据
关键指标
同类平均 = 1
同领域 · 同年份 · 同类型
Google Scholar 与 OpenAlex 的被引统计范围不同,数值存在差异属正常。
AI 辅助阅读
依据:摘要
可就本文提问;依据不足时会说明。
学术脉络
学科主题
工程Advanced Memory and Neural Computing
2D Materials and Applications · Neural Networks and Reservoir Computing
参考文献 93
此处列出前 3 条