A Three-Dimensional Neuromorphic Photosensor Array for Nonvolatile In-Sensor Computing

被引:32
作者
Wang, Yanrong [1 ,2 ]
Cai, Yuchen [1 ,2 ]
Wang, Feng [1 ,2 ]
Yang, Jia [1 ,2 ]
Yan, Tao [1 ]
Li, Shuhui [1 ,2 ]
Wu, Zilong [1 ,2 ]
Zhan, Xueying [1 ]
Xu, Kai [3 ,4 ]
He, Jun [2 ,5 ]
Wang, Zhenxing [1 ,2 ]
机构
[1] Natl Ctr Nanosci & Technol, CAS Key Lab Nanosyst & Hierarch Fabricat, Beijing 100190, Peoples R China
[2] Univ Chinese Acad Sci, Ctr Mat Sci & Optoelect Engn, Beijing 100049, Peoples R China
[3] ZJU Hangzhou Global Sci & Technol Innovat Ctr, Hangzhou 310027, Peoples R China
[4] Zhejiang Univ, Sch Micronano Elect, Hangzhou 310027, Peoples R China
[5] Wuhan Univ, Sch Phys & Technol, Key Lab Artificial Micro & Nanostruct, Minist Educ, Wuhan 430072, Peoples R China
基金
国家重点研发计划; 中国国家自然科学基金;
关键词
in-sensor computing; 3D integration; reconfigurablephotovoltaic effect; ion migration;
D O I
10.1021/acs.nanolett.3c00899
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
In-sensorcomputing hardware based on emerging reconfigurable photosensorscan effectively reduce redundant data and decrease power consumption,which can greatly promote the evolution of machine vision. However,because of the complex device structures and low integration abilities,the common architectures mainly lie in two dimensions, resulting inlow time and area efficiencies. Here we propose a three-dimensional(3D) neuromorphic photosensor array for parallel in-sensor image processing.It is constructed on a vertical Graphite/CuInP2S6/Graphite photosensor unit, where the directional Cu+ ionmigrations after voltage pulse programming enable a reconfigurablephotovoltaic effect and an in-sensor computing capability. With amemristor-like device structure, van der Waals interfaces, and a highuniformity with a low crosstalk problem, a 10 x 10 array is fabricatedfor intelligent image recognition. Furthermore, using a verticallystacked 3D 3 x 3 x 3 array, we demonstrate an in-sensorconvolution strategy with high time and area efficiencies.
引用
收藏
页码:4524 / 4532
页数:9
相关论文
共 44 条
[1]   3-D Stacked Image Sensor With Deep Neural Network Computation [J].
Amir, Mohammad Faisal ;
Ko, Jong Hwan ;
Na, Taesik ;
Kim, Duckhwan ;
Mukhopadhyay, Saibal .
IEEE SENSORS JOURNAL, 2018, 18 (10) :4187-4199
[2]   Locally Controlled Cu-Ion Transport in Layered Ferroelectric CuInP2S6 [J].
Balke, Nina ;
Neumayer, Sabine M. ;
Brehm, John A. ;
Susner, Michael A. ;
Rodriguez, Brian J. ;
Jesse, Stephen ;
Kalinin, Sergei V. ;
Pantelides, Sokrates T. ;
McGuire, Michael A. ;
Maksymovych, Petro .
ACS APPLIED MATERIALS & INTERFACES, 2018, 10 (32) :27188-27194
[3]  
Baugher BWH, 2014, NAT NANOTECHNOL, V9, P262, DOI [10.1038/nnano.2014.25, 10.1038/NNANO.2014.25]
[4]   In-sensor computing for machine vision [J].
Chai, Yang .
NATURE, 2020, 579 (7797) :32-33
[5]   Large-Scale Domain Engineering in Two-Dimensional FerroelectricCuInP2S6 via Giant Flexoelectric Effect [J].
Chen, Chen ;
Liu, Heng ;
Lai, Qinglin ;
Mao, Xiaoyu ;
Fu, Jun ;
Fu, Zhaoming ;
Zeng, Hualing .
NANO LETTERS, 2022, 22 (08) :3275-3282
[6]   Human eye-inspired soft optoelectronic device using high-density MoS2-graphene curved image sensor array [J].
Choi, Changsoon ;
Choi, Moon Kee ;
Liu, Siyi ;
Kim, Min Sung ;
Park, Ok Kyu ;
Im, Changkyun ;
Kim, Jaemin ;
Qin, Xiaoliang ;
Lee, Gil Ju ;
Cho, Kyoung Won ;
Kim, Myungbin ;
Joh, Eehyung ;
Lee, Jongha ;
Son, Donghee ;
Kwon, Seung-Hae ;
Jeon, Noo Li ;
Song, Young Min ;
Lu, Nanshu ;
Kim, Dae-Hyeong .
NATURE COMMUNICATIONS, 2017, 8
[7]   Ferroelectric photosensor network: an advanced hardware solution to real-time machine vision [J].
Cui, Boyuan ;
Fan, Zhen ;
Li, Wenjie ;
Chen, Yihong ;
Dong, Shuai ;
Tan, Zhengwei ;
Cheng, Shengliang ;
Tian, Bobo ;
Tao, Ruiqiang ;
Tian, Guo ;
Chen, Deyang ;
Hou, Zhipeng ;
Qin, Minghui ;
Zeng, Min ;
Lu, Xubing ;
Zhou, Guofu ;
Gao, Xingsen ;
Liu, Jun-Ming .
NATURE COMMUNICATIONS, 2022, 13 (01)
[8]   Neuromorphic electronics based on copying and pasting the brain [J].
Ham, Donhee ;
Park, Hongkun ;
Hwang, Sungwoo ;
Kim, Kinam .
NATURE ELECTRONICS, 2021, 4 (09) :635-644
[9]   In-sensor optoelectronic computing using electrostatically doped silicon [J].
Jang, Houk ;
Hinton, Henry ;
Jung, Woo-Bin ;
Lee, Min-Hyun ;
Kim, Changhyun ;
Park, Min ;
Lee, Seoung-Ki ;
Park, Seongjun ;
Ham, Donhee .
NATURE ELECTRONICS, 2022, 5 (08) :519-525
[10]   An Atomically Thin Optoelectronic Machine Vision Processor [J].
Jang, Houk ;
Liu, Chengye ;
Hinton, Henry ;
Lee, Min-Hyun ;
Kim, Haeryong ;
Seol, Minsu ;
Shin, Hyeon-Jin ;
Park, Seongjun ;
Ham, Donhee .
ADVANCED MATERIALS, 2020, 32 (36)