光子学
神经形态工程学
材料科学
光电子学
相变存储器
超短脉冲
纳米光子学
计算机科学
光开关
光子晶体
光子集成电路
硫系化合物
硅光子学
纳米技术
硫系玻璃
光子超材料
量子点
非易失性存储器
光学计算
纳米电子学
调制(音乐)
信号处理
电子工程
硅
光通信
光调制器
堆栈(抽象数据类型)
光电探测器
集成电路
作者
Xiaozhang Chen,Yuan Xue,Yibo Sun,Jiabin Shen,Sannian Song,Min Zhu,Zhitang Song,Zengguang Cheng,Peng Zhou
标识
DOI:10.1002/adma.202203909
摘要
Abstract The search for ultrafast photonic memory devices is inspired by the ever‐increasing number of cloud‐computing, supercomputing, and artificial‐intelligence applications, together with the unique advantages of signal processing in the optical domain such as high speed, large bandwidth, and low energy consumption. By embracing silicon photonics with chalcogenide phase‐change materials (PCMs), non‐volatile integrated photonic memory is developed with promising potential in photonic integrated circuits and nanophotonic applications. While conventional PCMs suffer from slow crystallization speed, scandium‐doped antimony telluride (SST) has been recently developed for ultrafast phase‐change random‐access memory applications. An ultrafast non‐volatile photonic memory based on an SST thin film with a 2 ns write/erase speed is demonstrated, which is the fastest write/erase speed ever reported in integrated phase‐change photonic devices. SST‐based photonic memories exhibit multilevel capabilities and good stability at room temperature. By mapping the memory level to the biological synapse weight, an artificial neural network based on photonic memory devices is successfully established for image classification. Additionally, a reflective nanodisplay application using SST with optoelectronic modulation capabilities is demonstrated. Both the optical and electrical changes in SST during the phase transition and the fast‐switching speed demonstrate their potential for use in photonic computing, neuromorphic computing, nanophotonics, and optoelectronic applications.
科研通智能强力驱动
Strongly Powered by AbleSci AI