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CMOS-Integrated Synaptic Photoreceptor Chip Inspired by Insect Visual Processing.

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Τίτλος: CMOS-Integrated Synaptic Photoreceptor Chip Inspired by Insect Visual Processing.
Συγγραφείς: Chai J; College of Integrated Circuits, State Key Laboratory of Silicon and Advanced Semiconductor Materials, ZJU-HIC, Center of CMOS IC Manufacturing Process and Design, Zhejiang University, Hangzhou, China., Xu X; College of Integrated Circuits, State Key Laboratory of Silicon and Advanced Semiconductor Materials, ZJU-HIC, Center of CMOS IC Manufacturing Process and Design, Zhejiang University, Hangzhou, China., Wang Y; State Key Laboratory of Silicon and Advanced Semiconductor Materials & School of Materials Science and Engineering, Zhejiang University, Hangzhou, Zhejiang, China., Wang X; College of Integrated Circuits, State Key Laboratory of Silicon and Advanced Semiconductor Materials, ZJU-HIC, Center of CMOS IC Manufacturing Process and Design, Zhejiang University, Hangzhou, China., Wang H; College of Integrated Circuits, State Key Laboratory of Silicon and Advanced Semiconductor Materials, ZJU-HIC, Center of CMOS IC Manufacturing Process and Design, Zhejiang University, Hangzhou, China., Xie Y; College of Integrated Circuits, State Key Laboratory of Silicon and Advanced Semiconductor Materials, ZJU-HIC, Center of CMOS IC Manufacturing Process and Design, Zhejiang University, Hangzhou, China., Zhang X; College of Integrated Circuits, State Key Laboratory of Silicon and Advanced Semiconductor Materials, ZJU-HIC, Center of CMOS IC Manufacturing Process and Design, Zhejiang University, Hangzhou, China., Wang H; College of Integrated Circuits, State Key Laboratory of Silicon and Advanced Semiconductor Materials, ZJU-HIC, Center of CMOS IC Manufacturing Process and Design, Zhejiang University, Hangzhou, China., Ning H; College of Integrated Circuits, State Key Laboratory of Silicon and Advanced Semiconductor Materials, ZJU-HIC, Center of CMOS IC Manufacturing Process and Design, Zhejiang University, Hangzhou, China., Lin J; College of Integrated Circuits, State Key Laboratory of Silicon and Advanced Semiconductor Materials, ZJU-HIC, Center of CMOS IC Manufacturing Process and Design, Zhejiang University, Hangzhou, China., Xie Y; College of Integrated Circuits, State Key Laboratory of Silicon and Advanced Semiconductor Materials, ZJU-HIC, Center of CMOS IC Manufacturing Process and Design, Zhejiang University, Hangzhou, China., Jiang Q; ZJU-UIUC Institute, International Campus, Zhejiang University, Haining, China., Qiao B; ZJU-UIUC Institute, International Campus, Zhejiang University, Haining, China., Ding X; ZJU-UIUC Institute, International Campus, Zhejiang University, Haining, China., Ma L; College of Artificial Intelligence, Southwest University, Chongqing, China., Duan S; College of Artificial Intelligence, Southwest University, Chongqing, China., Ni Z; State Key Laboratory of Silicon and Advanced Semiconductor Materials & School of Materials Science and Engineering, Zhejiang University, Hangzhou, Zhejiang, China., Hu H; ZJU-UIUC Institute, International Campus, Zhejiang University, Haining, China., He X; ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou, China., Xue F; ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou, China.; Center for Quantum Matter, School of Physics, Zhejiang University, Hangzhou, China., Zhou F; School of Microelectronics, Southern University of Science and Technology, Shenzhen, China., Li L; College of Integrated Circuits, State Key Laboratory of Silicon and Advanced Semiconductor Materials, ZJU-HIC, Center of CMOS IC Manufacturing Process and Design, Zhejiang University, Hangzhou, China., Bodepudi SC; College of Integrated Circuits, State Key Laboratory of Silicon and Advanced Semiconductor Materials, ZJU-HIC, Center of CMOS IC Manufacturing Process and Design, Zhejiang University, Hangzhou, China., Yuan R; ZJU-UIUC Institute, International Campus, Zhejiang University, Haining, China., Yu B; College of Integrated Circuits, State Key Laboratory of Silicon and Advanced Semiconductor Materials, ZJU-HIC, Center of CMOS IC Manufacturing Process and Design, Zhejiang University, Hangzhou, China., Xu Y; College of Integrated Circuits, State Key Laboratory of Silicon and Advanced Semiconductor Materials, ZJU-HIC, Center of CMOS IC Manufacturing Process and Design, Zhejiang University, Hangzhou, China.
Πηγή: Advanced science (Weinheim, Baden-Wurttemberg, Germany) [Adv Sci (Weinh)] 2026 Jul; Vol. 13 (40), pp. e75388. Date of Electronic Publication: 2026 Apr 21.
Τύπος έκδοσης: Journal Article
Γλώσσα: English
Στοιχεία περιοδικού: Publisher: WILEY-VCH Country of Publication: Germany NLM ID: 101664569 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2198-3844 (Electronic) Linking ISSN: 21983844 NLM ISO Abbreviation: Adv Sci (Weinh) Subsets: MEDLINE
Imprint Name(s): Original Publication: Weinheim : WILEY-VCH, [2014]-
Ιατρικοί όροι (MeSH): Insecta*/physiology , Visual Perception*/physiology , Bionics*/methods , Bionics*/instrumentation , Biomimetics*/methods , Biomimetics*/instrumentation, Photoreceptor Cells, Invertebrate/physiology ; Animals ; Equipment Design
Περίληψη: Bionic visual processing hardware serves as the core technology for mimicking the efficient information processing of biological vision systems and forms the foundation for perceiving and recognizing both static and dynamic scenes. However, most current bionic visual hardware remains at the level of individual devices and simple arrays. Full hardware implementation of bionic vision chips, as well as comprehensive demonstrations in practical application scenarios, is still scarce. This work proposes a complete optoelectronic insect-inspired visual sensor. We realize a Si QDs/ReS2 heterogeneous integrated neuromorphic chip fabricated using a 180-nm CMOS process technology and demonstrate its capabilities on both static and dynamic visual tasks. Based on the wavelength-dependent synaptic properties of ReS2, this neuromorphic photoreceptor chip exhibits high-fidelity discrimination between purple and red features. Through light pulse sequence modulation, it achieves temporal encoding of dynamic visual information and can precisely identify leaf movement trajectories in eight directions. We further achieved 3D perception capabilities, attaining 99.4% accuracy in classification tasks. This work establishes a novel 1D/2D/3D heterogeneously integrated material platform and a CMOS-compatible integration strategy for a low-power, multifunctional brain-inspired neuromorphic sensor chip, advancing the application of optoelectronic devices in artificial intelligence and machine vision.
(© 2026 The Author(s). Advanced Science published by Wiley‐VCH GmbH.)
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Grant Information: 2022YFA1204304 National Key Research and Development Program of China; 62406260 National Natural Science Foundation of China; ZCLQN25F0401 Zhejiang Provincial Natural Science Foundation of China; LDT23F04013F04 NSFC of Zhejiang Province; LDT23F0401 NSFC of Zhejiang Province
Contributed Indexing: Keywords: Depth perception; SiQDs/ReS2 neuromorphic image sensor chip; dynamic trajectory tracking; static feature recognition
Entry Date(s): Date Created: 20260421 Date Completed: 20260717 Latest Revision: 20260726
Update Code: 20260726
PubMed Central ID: PMC13335448
DOI: 10.1002/advs.75388
PMID: 42011902
Βάση Δεδομένων: MEDLINE
Περιγραφή
ISSN:2198-3844
DOI:10.1002/advs.75388