{"title":"用于深度传感和实时手势识别的自适应近红外光电探测器","authors":"Mohit Kumar , Hyunmin Dang , Hyungtak Seo","doi":"10.1016/j.mssp.2025.109734","DOIUrl":null,"url":null,"abstract":"<div><div>The rapid evolution of real-time, energy-efficient sensing technologies is paramount for innovations in fields such as 3D imaging, gesture recognition, and human-machine interaction. However, conventional photodetectors are limited by their slow response to sudden changes in light and high-power consumption during continuous monitoring, while event sensors excel in detecting instantaneous changes but are ineffective at capturing gradual intensity shifts. To address these critical limitations, we present a ‘<em>hybrid’</em> near-infrared (NIR) Au/Ga<sub>2</sub>O<sub>3</sub>/<em>n</em>-Si/Au photodetector, designed to simultaneously detect both instantaneous events and gradual light intensity variations. Our single-pixel NIR photodetector leverages capacitance changes for rapid event detection and photocurrent generation at the junction to monitor continuous light variations. This dual-functionality architecture allows for real-time adaptability in dynamic and static environments. We further demonstrate its capability in real-time z-distance sensing, integrating a deep neural network for precise depth measurements. Additionally, the hybrid single-pixel photodetector facilitates real-time sign language recognition, translating gestures into word, thereby offering a new paradigm in human-machine interaction. By bridging the gap between traditional and event-based sensors, this hybrid NIR device not only meets the demands of next-generation sensing technologies but also redefines the potential for innovation in the fields, such as in object classification, gesture recognition, and beyond.</div></div>","PeriodicalId":18240,"journal":{"name":"Materials Science in Semiconductor Processing","volume":"198 ","pages":"Article 109734"},"PeriodicalIF":4.6000,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An adaptive near-infrared photodetector for depth sensing and real-time gesture recognition\",\"authors\":\"Mohit Kumar , Hyunmin Dang , Hyungtak Seo\",\"doi\":\"10.1016/j.mssp.2025.109734\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The rapid evolution of real-time, energy-efficient sensing technologies is paramount for innovations in fields such as 3D imaging, gesture recognition, and human-machine interaction. However, conventional photodetectors are limited by their slow response to sudden changes in light and high-power consumption during continuous monitoring, while event sensors excel in detecting instantaneous changes but are ineffective at capturing gradual intensity shifts. To address these critical limitations, we present a ‘<em>hybrid’</em> near-infrared (NIR) Au/Ga<sub>2</sub>O<sub>3</sub>/<em>n</em>-Si/Au photodetector, designed to simultaneously detect both instantaneous events and gradual light intensity variations. Our single-pixel NIR photodetector leverages capacitance changes for rapid event detection and photocurrent generation at the junction to monitor continuous light variations. This dual-functionality architecture allows for real-time adaptability in dynamic and static environments. We further demonstrate its capability in real-time z-distance sensing, integrating a deep neural network for precise depth measurements. Additionally, the hybrid single-pixel photodetector facilitates real-time sign language recognition, translating gestures into word, thereby offering a new paradigm in human-machine interaction. By bridging the gap between traditional and event-based sensors, this hybrid NIR device not only meets the demands of next-generation sensing technologies but also redefines the potential for innovation in the fields, such as in object classification, gesture recognition, and beyond.</div></div>\",\"PeriodicalId\":18240,\"journal\":{\"name\":\"Materials Science in Semiconductor Processing\",\"volume\":\"198 \",\"pages\":\"Article 109734\"},\"PeriodicalIF\":4.6000,\"publicationDate\":\"2025-06-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Materials Science in Semiconductor Processing\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1369800125004718\",\"RegionNum\":3,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Materials Science in Semiconductor Processing","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1369800125004718","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
An adaptive near-infrared photodetector for depth sensing and real-time gesture recognition
The rapid evolution of real-time, energy-efficient sensing technologies is paramount for innovations in fields such as 3D imaging, gesture recognition, and human-machine interaction. However, conventional photodetectors are limited by their slow response to sudden changes in light and high-power consumption during continuous monitoring, while event sensors excel in detecting instantaneous changes but are ineffective at capturing gradual intensity shifts. To address these critical limitations, we present a ‘hybrid’ near-infrared (NIR) Au/Ga2O3/n-Si/Au photodetector, designed to simultaneously detect both instantaneous events and gradual light intensity variations. Our single-pixel NIR photodetector leverages capacitance changes for rapid event detection and photocurrent generation at the junction to monitor continuous light variations. This dual-functionality architecture allows for real-time adaptability in dynamic and static environments. We further demonstrate its capability in real-time z-distance sensing, integrating a deep neural network for precise depth measurements. Additionally, the hybrid single-pixel photodetector facilitates real-time sign language recognition, translating gestures into word, thereby offering a new paradigm in human-machine interaction. By bridging the gap between traditional and event-based sensors, this hybrid NIR device not only meets the demands of next-generation sensing technologies but also redefines the potential for innovation in the fields, such as in object classification, gesture recognition, and beyond.
期刊介绍:
Materials Science in Semiconductor Processing provides a unique forum for the discussion of novel processing, applications and theoretical studies of functional materials and devices for (opto)electronics, sensors, detectors, biotechnology and green energy.
Each issue will aim to provide a snapshot of current insights, new achievements, breakthroughs and future trends in such diverse fields as microelectronics, energy conversion and storage, communications, biotechnology, (photo)catalysis, nano- and thin-film technology, hybrid and composite materials, chemical processing, vapor-phase deposition, device fabrication, and modelling, which are the backbone of advanced semiconductor processing and applications.
Coverage will include: advanced lithography for submicron devices; etching and related topics; ion implantation; damage evolution and related issues; plasma and thermal CVD; rapid thermal processing; advanced metallization and interconnect schemes; thin dielectric layers, oxidation; sol-gel processing; chemical bath and (electro)chemical deposition; compound semiconductor processing; new non-oxide materials and their applications; (macro)molecular and hybrid materials; molecular dynamics, ab-initio methods, Monte Carlo, etc.; new materials and processes for discrete and integrated circuits; magnetic materials and spintronics; heterostructures and quantum devices; engineering of the electrical and optical properties of semiconductors; crystal growth mechanisms; reliability, defect density, intrinsic impurities and defects.