{"title":"Deep multiband photodetectors enabled by reconfigurable band alignment in van der Waals heterostructures","authors":"Jinjin Wang, Xiao Fu, Xiaolong Chen, Guanyu Liu, Qixiao Zhao, Hangyu Xu, Fansheng Chen, Jianbin Xu, Sang-Hoon Bae, Jiadong Zhou, Lixin Dong, Wenzhong Bao, Zengfeng Di, Jinshui Miao, Weida Hu","doi":"10.1364/optica.519888","DOIUrl":null,"url":null,"abstract":"Multiband recognition technology is being extensively investigated because of the increasing demand for on-chip, multifunctional, and sensitive devices that can distinguish coincident spectral information. Most existing multiband imagers use large arrays of photodetectors to capture different spectral components, from which their spectrum is reconstructed. A single device embedded with a convolutional neural network (CNN) capable of recognizing multiband photons allows the footprints of multiband recognition chips to be scaled down while achieving spectral resolution approaching that of benchtop systems. Here, we report a multiple and broadband photodetector based on 2D/3D van der Waals p/n/p heterostructures [p-germanium (Ge)/n-molybdenum disulfide (MoS<jats:sub>2</jats:sub>)/p-black phosphorus (bP)] with an electrically tunable transport-mediated spectral photoresponse. The devices show bias-tunable multiband photodetection (visible, short-wave infrared, and mid-wave infrared photoresponse). Further combination with the CNN algorithm enables crosstalk suppression of photoresponse to different wavelengths and high-accuracy blackbody radiation temperature recognition. The deep multiband photodetection strategies demonstrated in this work may open pathways towards the integration of multiband vision for application in on-chip neural network perception.","PeriodicalId":19515,"journal":{"name":"Optica","volume":"26 1","pages":""},"PeriodicalIF":8.4000,"publicationDate":"2024-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Optica","FirstCategoryId":"101","ListUrlMain":"https://doi.org/10.1364/optica.519888","RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"OPTICS","Score":null,"Total":0}
引用次数: 0
Abstract
Multiband recognition technology is being extensively investigated because of the increasing demand for on-chip, multifunctional, and sensitive devices that can distinguish coincident spectral information. Most existing multiband imagers use large arrays of photodetectors to capture different spectral components, from which their spectrum is reconstructed. A single device embedded with a convolutional neural network (CNN) capable of recognizing multiband photons allows the footprints of multiband recognition chips to be scaled down while achieving spectral resolution approaching that of benchtop systems. Here, we report a multiple and broadband photodetector based on 2D/3D van der Waals p/n/p heterostructures [p-germanium (Ge)/n-molybdenum disulfide (MoS2)/p-black phosphorus (bP)] with an electrically tunable transport-mediated spectral photoresponse. The devices show bias-tunable multiband photodetection (visible, short-wave infrared, and mid-wave infrared photoresponse). Further combination with the CNN algorithm enables crosstalk suppression of photoresponse to different wavelengths and high-accuracy blackbody radiation temperature recognition. The deep multiband photodetection strategies demonstrated in this work may open pathways towards the integration of multiband vision for application in on-chip neural network perception.
期刊介绍:
Optica is an open access, online-only journal published monthly by Optica Publishing Group. It is dedicated to the rapid dissemination of high-impact peer-reviewed research in the field of optics and photonics. The journal provides a forum for theoretical or experimental, fundamental or applied research to be swiftly accessed by the international community. Optica is abstracted and indexed in Chemical Abstracts Service, Current Contents/Physical, Chemical & Earth Sciences, and Science Citation Index Expanded.