On-chip analogue signal processing using molybdenum disulfide reservoir computing

On-chip analogue signal processing using molybdenum disulfide reservoir computing | 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 On-chip analogue signal processing using molybdenum disulfide reservoir computing Guohua Hu, Yingyi Wen, Songwei Liu, Jingfang Pei, Zewen Kong, and 9 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8634485/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 In the era where edge intelligence powers robotics, autonomous systems, and various IoT sensors, real-time processing of the signals is vital yet challenging to achieve with the current digital systems, particularly when latency, reliability, and privacy are concerned. Here, we present a groundbreaking analogue reservoir computing prototype for on-chip parallel signal processing using solution-processed molybdenum disulfide (MoS2) fading memory. By harnessing the intrinsic nonlinearity and fading memory relaxation processes of the MoS2 memory, the prototype performs reservoir activation with rich dynamics while, notably, requiring no periphery circuits for virtual-node-coupling or recurrent connections. Benchmarked on chaotic system prediction, e.g. Lorenz-63 with NRMSE of 0.01, the prototype manifests the potential in enabling robust on-chip analogue signal processing in edge intelligence, e.g. assistive driving. The prototype proves successful human electrophysiological and vehicular signal processing on chip, with an accuracy of 80-95% achieved in the tasks, promising to enhance the driving safety. This analogue reservoir computing, with the compact hardware design along with the scalability of solution-processed electronics, is positioned to become a transformative signal processing technology for embedded edge intelligence systems. Physical sciences/Nanoscience and technology/Nanoscale materials/Two-dimensional materials Physical sciences/Engineering/Electrical and electronic engineering Molybdenum disulfide (MoS2) fading memory nonlinearity analogue reservoir computing edge intelligence Full Text Additional Declarations There is NO Competing Interest. Supplementary Files SI.pdf Supplementary Information 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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