Physical Correlation Between Stochasticity and Process-Induced Damage in Ferroelectric Memory Devices

Physical Correlation Between Stochasticity and Process-Induced Damage in Ferroelectric Memory Devices | 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 Physical Correlation Between Stochasticity and Process-Induced Damage in Ferroelectric Memory Devices Ryun-Han Koo, Seungwhan Kim, Jiseong Im, Sangwoo Ryu, Kangwook Choi, and 10 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6642967/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 29 Aug, 2025 Read the published version in Nano Convergence → Version 1 posted 4 You are reading this latest preprint version Abstract This study investigates the influence of sputtering plasma-induced damage on stochastic characteristics in HfZrO₂ (HZO)-based ferroelectric tunnel junctions (FTJs), with an emphasis on memory and neuromorphic device optimization. Variation of the sputtering plasma power during top electrode deposition introduces distinct levels of trap within the HZO layer. Low-frequency noise (LFN) spectroscopy and temperature-dependent electrical measurements confirm that higher plasma power generates additional shallow-level traps, thereby promoting Poole-Frenkel conduction while simultaneously increasing current noise magnitude. Although the resulting enhancements in on-current density and ferroelectric tunnel electroresistance (TER) ratio are beneficial for high-density memory integration, these conditions also elevate stochastic fluctuations, potentially degrading read margins and long-term endurance. Furthermore, the observed increase in stochasticity negatively affects neuromorphic inference accuracy, particularly after endurance cycling stress. These results demonstrate the critical interplay among plasma process conditions, trap density, and LFN in FTJs. By systematically engineering sputtering process parameters, we optimize the electrical performance with minimized stochastic noise. This approach provides guidelines for the development of next-generation ferroelectric-based memories and neuromorphic systems with consideration of stochasticity, where robust performance and reliability are imperative for large-scale integration. Stochasticity Ferroelectric tunnel junction Low-frequency noise (LFN) Trap formation Plasma-induced damage Full Text Supplementary Files NanoConvergenceGA.png Graphical Abstract Cite Share Download PDF Status: Published Journal Publication published 29 Aug, 2025 Read the published version in Nano Convergence → Version 1 posted Reviewers agreed at journal 30 May, 2025 Reviewers invited by journal 30 May, 2025 Editor assigned by journal 20 May, 2025 First submitted to journal 19 May, 2025 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-6642967","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":463971696,"identity":"0d13249a-16ba-4f76-bdb4-3194cf268d00","order_by":0,"name":"Ryun-Han Koo","email":"","orcid":"","institution":"Seoul National University Department of Electrical and Computer Engineering","correspondingAuthor":false,"prefix":"","firstName":"Ryun-Han","middleName":"","lastName":"Koo","suffix":""},{"id":463971697,"identity":"07c771d4-c7bd-49e7-bb87-6c04d2ba82b7","order_by":1,"name":"Seungwhan Kim","email":"","orcid":"","institution":"Seoul National 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