二氧化硅/氟化镁基超低能耗相变集成光子器件

连晓娟; 蒋纪元; 万相; 肖宛昂; 王磊

doi:10.12263/DZXB.20230948

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二氧化硅/氟化镁基超低能耗相变集成光子器件

学术论文 | 更新时间：2025-12-11

- 二氧化硅/氟化镁基超低能耗相变集成光子器件
- Ultralow Energy Phase-Change Integrated Photonics Devices with the Silicon Dioxide/Magnesium Fluoride Platform
- 电子学报 2024年52卷第11期页码：3886-3898
- 作者机构：
  
  1.南京邮电大学集成电路科学与工程学院（产教融合学院），江苏南京 210023
  2.中国科学院半导体研究所，北京 100083
  3.中国科学院大学材料与光电研究中心&集成电路学院，北京 100083
  4.江苏集萃智能集成电路设计技术研究所有限公司，江苏无锡 214028
  5.南京邮电大学南通研究院，江苏南通 226021
- 作者简介：
  
  [ "连晓娟女，1985年4月出生，山西交城人.分别于2008年和2011年在西安电子科技大学获得工学学士和工学硕士学位，于2014年在西班牙巴塞罗那自治大学获得工学博士学位.目前任南京邮电大学集成电路科学与工程学院副教授、硕士生导师.主要研究方向为阻变存储器、相变存储器、忆阻神经形态器件的制备工艺、物理机制以及性能优化.E-mail: xjlian@njupt.edu.cn" ]
  [ "蒋纪元男，2000年7月出生，广西桂林人.2022年毕业于武汉纺织大学光电信息科学与工程专业，2022年进入南京邮电大学电子信息专业攻读硕士学位.主要研究方向为相变集成光子器件.E-mail: 1222228504@njupt.edu.cn" ]
  [ "肖宛昂男，1970年4月出生，江西樟树人.研究员.1992年本科毕业于中国农业大学（东校区）电子电力工程系，2003年硕士毕业于华东交通大学交通信息工程及控制专业，2006年博士毕业于中国科学院半导体研究所微电子学与固体电子学专业.2006年7月至今，在中国科学院半导体研究所工作.主要研究方向为声音信号处理和无线通信算法及芯片实现、人工智能硬件加速.E-mail: waxiao@semi.ac.cn" ]
  [ "王磊男，1980年10月出生，江西南昌人.2003年、2004年和2009年分别在北京科技大学、曼彻斯特大学和埃克塞特大学获得工学学士、工学硕士和工学博士学位.现为南京邮电大学集成电路科学与工程学院教授硕士生导师.IEEE会员.主要研究方向为基于非易失性器件的类脑光电存储器及神经网络.E-mail: leiwang1980@njupt.edu.cn" ]
- 基金信息：
  
  国家自然科学基金(61964012)
- DOI：10.12263/DZXB.20230948
  中图分类号： TN385;
- 收稿：2023-10-13，
  
  修回：2024-06-25，
  
  纸质出版：2024-11-25
- 稿件说明：
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连晓娟, 蒋纪元, 万相, 等. 二氧化硅/氟化镁基超低能耗相变集成光子器件[J]. 电子学报, 2024, 52(11): 3886-3898.

LIAN Xiao-juan, JIANG Ji-yuan, WAN Xiang, et al. Ultralow Energy Phase-Change Integrated Photonics Devices with the Silicon Dioxide/Magnesium Fluoride Platform[J]. Acta Electronica Sinica, 2024, 52(11): 3886-3898.
连晓娟, 蒋纪元, 万相, 等. 二氧化硅/氟化镁基超低能耗相变集成光子器件[J]. 电子学报, 2024, 52(11): 3886-3898. DOI：10.12263/DZXB.20230948

LIAN Xiao-juan, JIANG Ji-yuan, WAN Xiang, et al. Ultralow Energy Phase-Change Integrated Photonics Devices with the Silicon Dioxide/Magnesium Fluoride Platform[J]. Acta Electronica Sinica, 2024, 52(11): 3886-3898. DOI：10.12263/DZXB.20230948

摘要

相变集成光子器件具有带宽大、延迟低、多路复用和抗干扰性好等性能优势，因此被广泛视作传统电子器件的有力竞争者.然而，当前相变光子器件编程所需的能耗较高，从而对其商业应用前景造成了严重的损害.为了解决这一问题，本文创造性地提出了一种非常有前景的二氧化硅（SiO

）/氟化镁（MgF

）基光子架构以取代当前主流的硅基器件.该器件采用目前已得到广泛应用的相变材料Ge

（GST）和氧化铟锡（ITO）合金分别作为功能层和片上加热器材料，并通过自主开发的电热和相场耦合模型实现其数据编程和读取过程的模拟.仿真结果表明该器件在晶化和非晶化过程中所产生的能耗分别为78 aj/nm

和90 aj/nm

，远低于其他大多数硅基器件.同时其在近红外波段（如1 550 nm）也保持了良好的光学传输特性，并展现出超过5个中间态的多值存储特性和50 ns的短脉宽编程时间.除此之外，进一步研究表明使用该器件所搭建的光学神经网络可用于鸢尾花数据集识别，其准确率高达90%，接近于传统人工神经网络的识别准确率（约为94.7%）.上述工作为具有低功耗、存内计算和神经形态计算功能的新兴相变光子器件开发提供了新的研究思路，对于实现一种兼具电子和全光信息器件性能优势的通用非冯诺依曼计算体系有着重大的意义.

Abstract

Phase-change integrated photonic devices are widely considered as a strong competitor to conventional electronic devices due to their large bandwidth

short delay

multiplexing and great anti-interference. However

current phase-change integrated photonic devices require high energy consumption

thus severely exacerbating its commercial application prospect. To address this issue

this paper innovatively proposed a promising silicon dioxide (SiO

) / magnesium fluoride (MgF

) based photonic architecture to replace the mainstream silicon based devices. Such device made use of the Ge

(GST) and indium tin oxide (ITO) as the functional and microheater materials

respectively

which have received widespread applications today

and simulated its programming and readout process according to an independently developed model that coupled electro-thermal and phase-change field processes. Results indicated that the energy consumption for crystallization and amorph

ization were 78 aj/nm

and 90 aj/nm

much lower than majority of other silicon-based devices. It also exhibited good light propagation trait at near-infrared band (1 550 nm)

as well as multilevel characteristic with more than 5 intermediate states and short pulse width with 50 ns. Additionally

further research suggested that the photonic neural networks constructed from the proposed device can be used to recognize the iris dataset

and its accuracy can reach 90%

close to that of conventional neural networks (~94.7%). Aforementioned work provided for the new strategy for developing emerging phase-change photonic devices with low power

in-memory computing and neuromorphic computing functionalities

and exhibited its extremely important significance to the general non von-Neumann regime that has both electronic and photonic performance superiorities.

关键词

Keywords

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