Polarization-Encoded Neuromorphic Vision in Infrared via Gate-Programmable 2D Anisotropic Semiconductors

Polarization-Encoded Neuromorphic Vision in Infrared via Gate-Programmable 2D Anisotropic Semiconductors | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Polarization-Encoded Neuromorphic Vision in Infrared via Gate-Programmable 2D Anisotropic Semiconductors Libo Zhang, Shi Zhang, Shuguan Zhu, Shijian Tian, Kening Xiao, and 16 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6218819/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Polarization-sensitive neuromorphic vision sensing excels in distinguishing light polarization states, offering intrinsic advantages in reducing glare and enhancing visual clarity in complex lighting environments, enabling advanced applications in autonomous driving, optical communication, and bioinspired imaging across the visible to infrared spectrum. Here, we present a polarization-sensitive neuromorphic phototransistor based on a high-quality, intrinsically anisotropic two-dimensional black arsenic-phosphorus (b-As0.2P0.8) nanosheets, which exhibits exceptional optoelectronic performances with a peak responsivity up to 2.88 A/W, a polarization ratio of 4.7 and a dynamic range of 40 dB within the near-infrared communication band. Through multidimensional input control, including polarization and gate voltage, the phototransistor successfully simulates synaptic behaviors analogous to human neural responses to visual stimuli, with paired-pulse facilitation (PPF) values reaching 201%. Critically, the device demonstrates gate-tunable short-term plasticity, with optical persistence triggering stable long-term plasticity states that underpin memory consolidation. The neuromorphic properties enable the development of a hybrid optical-electronic neural network (HOENN) which achieves a classification accuracy of over 90% on the Fashion-MNIST dataset and a reconstruction accuracy of 71.38% using data from the Yale Face Database under linear polarization at 0 degrees. We demonstrate a polarization-resolved imaging approach utilizing the b-As0.2P0.8 phototransistor to reconstruct hidden targets with high fidelity through Stokes parameter extraction and degree of linear polarization (DoLP) mapping, revealing intricate polarization features invisible to conventional imaging systems. Our work establishes a foundational platform for high-performance neuromorphic vision systems with integrated polarization imaging, polarization computation, and polarization communication functionalities, addressing critical challenges in scalable brain-inspired optoelectronic technologies. Physical sciences/Optics and photonics/Other photonics/Micro-optics Physical sciences/Materials science/Materials for devices/Electronic devices Full Text Additional Declarations There is NO Competing Interest. Supplementary Files SupplementaryInformation.docx Polarization-Encoded Neuromorphic Vision in Infrared via Gate-Programmable 2D Anisotropic Semiconductors Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6218819","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":433831074,"identity":"549c7522-8eaf-49b5-b707-dc975eea07c1","order_by":0,"name":"Libo 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