Implementation of Leaky Integrate and Fire neuron using Trench gate vertical FBFET (TG-V-FBFET) exploiting its Steep Subthreshold slope

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Abstract In this work, we have proposed a Trench gate vertical feedback field-effect transistor (TG-V-FBFET) utilizing the positive feedback mechanism. Simulation and result extraction of the device is done using computer aided TCAD tool (ATLAS-SILVACO). Proposed device exhibits Subthreshold swing (SS) of 0.013mV/dec and on state current (Ion) of 0.1mA/µm with overall Ion/Ioff = 1010. Overall on chip area can be reduce up to 66% compared to lateral FBFET counter-part. Further-more, steep subthreshold slope characteristic of the device is exploited for the producing of Leaky Integrate and Fire neuron like spiking behavior. Circuit level simulations consisting proper resetting as well, is also done to properly implement single LIF neuron. Proposed LIF neuron shows a spiking frequency of 0.86GHz/spike and energy of 0.13pJ/spike for input current and threshold potential of 0.9mA and 1.3V respectively.
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Implementation of Leaky Integrate and Fire neuron using Trench gate vertical FBFET (TG-V-FBFET) exploiting its Steep Subthreshold slope | 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 Research Article Implementation of Leaky Integrate and Fire neuron using Trench gate vertical FBFET (TG-V-FBFET) exploiting its Steep Subthreshold slope Zuber Rasool, S. Amin, Dinesh Prasad, Naveen Kumar This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4365737/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 In this work, we have proposed a Trench gate vertical feedback field-effect transistor (TG-V-FBFET) utilizing the positive feedback mechanism. Simulation and result extraction of the device is done using computer aided TCAD tool (ATLAS-SILVACO). Proposed device exhibits Subthreshold swing (SS) of 0.013mV/dec and on state current (I on ) of 0.1mA/µm with overall I on /I off = 10 10 . Overall on chip area can be reduce up to 66% compared to lateral FBFET counter-part. Further-more, steep subthreshold slope characteristic of the device is exploited for the producing of Leaky Integrate and Fire neuron like spiking behavior. Circuit level simulations consisting proper resetting as well, is also done to properly implement single LIF neuron. Proposed LIF neuron shows a spiking frequency of 0.86GHz/spike and energy of 0.13pJ/spike for input current and threshold potential of 0.9mA and 1.3V respectively. FBFET Positive Feedback LIF-neuron SNN Reset circuit Steep-switching Steep Subthreshold swing Full Text Additional Declarations No competing interests reported. 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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