Large-scale iontronic skins with neural-hierarchical processing architecture

Large-scale iontronic skins with neural-hierarchical processing architecture | 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 Large-scale iontronic skins with neural-hierarchical processing architecture Chuan Fei Guo, Zhibin Li, Binxu Da, Junli Shi, Taihong Wang, Wenlong Si, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8887464/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract The human skin can encode and gather signals from over 200,000 afferents, providing high spatiotemporal-resolution sensations to enable fine touch and to prevent skin injury. Existing robotic skins typically employ a serial architecture to readout multichannel signals, while such an architecture becomes incapable when a skin has thousands of receptors, resulting in readout latency, signal crosstalk, and bandwidth consumption. Here, we introduce a large-scale neural-hierarchical iontronic skin (NI-skin) with >10,000 sensors that mimics the hierarchical processing architecture of the tactile nervous system, transmitting tactile information in layers via signal encoding, convergence, and cognitive modeling. The position-encoding of the frequency-dependent iontronic receptors enable parallel transmission with ultralow latency and suppressed crosstalk, while the backend convergent compression minimizes bandwidth, achieving an 800 µm spatial resolution and a 10.6 ms temporal resolution. We demonstrate that robots equipped with our system can perform challenging tasks, including fine tactile interactions and the perception of pain-related mechanical stimuli for proactive injury avoidance. This technology provides a large-scale tactile system with high spatiotemporal resolution, paving the way for humanoid robots to achieve human-level perception and manipulation. Physical sciences/Engineering/Electrical and electronic engineering Physical sciences/Materials science/Materials for devices/Sensors and biosensors Iontronic skin tactile sensing neuromimetic sensory system spatiotemporal-resolution robot interaction Full Text Additional Declarations There is NO Competing Interest. Supplementary Files SupplementaryMovie8.mp4 Demonstration of self-protection triggered by external noxious stimuli. SupplementaryMovie2.mp4 Dynamic tactile sensing recordings of NI-skin integrated on the robotic body. SupplementaryMovie7.mp4 Demonstration of adaptive and safe grasping of a spiny chestnut. SupplementaryMovie6.mp4 Demonstration of stable grasping of a soft 0.2-mm solder wire. SupplementaryMovie5.mp4 Demonstration of stable grasping of a 0.5-mm pencil lead. SupplementaryMovie1.mp4 Demonstration of fine surface tactile perception using NI-skin integrated on the robotic body. Supplementarymaterials.docx Supplementary Materials SupplementaryMovie3.mp4 NI-skin on the robotic palm perceiving contact contours and sharp stimuli. SupplementaryMovie4.mp4 Demonstration of high spatiotemporal-resolution tactile perception of NI-skin. Cite Share Download PDF Status: Under Review 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. 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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-8887464","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":592591334,"identity":"15d1afc4-54a3-49bf-8136-1d07e1258db4","order_by":0,"name":"Chuan Fei 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