Molecular mechanism of h-BN enhancing the thermal conductivity of PEEK

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Molecular mechanism of h-BN enhancing the thermal conductivity of PEEK | 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 Molecular mechanism of h-BN enhancing the thermal conductivity of PEEK Juan Du, Kaiyin Xiao, Dongyu Li, Kaifan Du, Zebei Mao, Tong Li, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7415087/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 As electronic devices rapidly evolve towards higher power density and integration, the importance of efficient thermal management grows significantly. In the context of nano-reinforced thermoplastic composites, establishing effective thermal path through the filler network is crucial. In this study, by optimizing the ratios of two sizes of hexagonal boron nitride (h-BN) nanosheets in the poly (ether ether ketone) (PEEK) matrix, a significant enhancement of the thermal conductivity of PEEK/h-BN composites was achieved. The thermal conductivity of a PEEK/h-BN composite containing a 3:7 weight ratio of the two sizes of h-BN(with 15wt% overall h-BN content) achieved the highest thermal conductivity of 0.87 W/mK due to the formation of more complete thermal paths. Additionally, based on the structural distribution of boron nitride nanosheets (BNNSs) observed in scanning electron microscopy (SEM), the influence of heat transfer direction along single-layer BNNSs, as well as the interlayer relative displacement and torsional angle of bilayer BNNSs, on the thermal conductivity of BNNSs/PEEK composites was investigated through molecular dynamics simulations. The results show that when heat flow is transmitted along the armchair direction of BNNSs, the BNNSs/PEEK composites exhibit higher thermal conductivity. Furthermore, by regulating the microstructure of BNNSs, the interface scattering in BNNSs/PEEK composites can be effectively reduced, and the interfacial coupling of BNNSs/PEEK composites can be improved, leading to an enhancement in thermal conductivity. This study provides experimental data and theoretical support for the further development of high-performance thermal management materials. Hexagonal boron nitride Poly (ether ether ketone) Size effect Molecular dynamics Microstructure 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. 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-7415087","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":506600141,"identity":"8d0d7334-f88e-411d-bcaf-37e7d1b97cd8","order_by":0,"name":"Juan 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