Layer-by-Layer Shear Densification for Multiscale Hierarchical Alignment in Bulk Hydrogels | 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 Layer-by-Layer Shear Densification for Multiscale Hierarchical Alignment in Bulk Hydrogels Ronghui Wu, Sen Wang, Senxuan Tang, Tianqi Fu, Yirong Jiang, Yun Lin, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8184208/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 Natural structural tissues achieve exceptional performance through precisely aligned hierarchical architectures that extend across multiple length scales. However, realizing such multiscale long-range alignment in synthetic bulk hydrogels remains challenging because of the difficulty in constructing a uniformly dense and highly oriented structure that extends throughout the full bulk matrix. Here, we introduce a scalable and versatile Layer-by-Layer Shear Densification (LBSD) strategy that integrates flocculation-induced aggregation with shear-driven progressive alignment, precisely driving the architectural evolution toward compact and uniformly ordered lamellar structures across multiscales. The produced poly(vinyl alcohol) (PVA) hydrogels with hierarchical network exhibit a Herman orientation factor of 0.91, surpassing all previously reported bulk hydrogels. The structural orientation enables the hydrogel with outstanding mechanical properties, including a tensile strength of 41.29 ± 2.10 MPa and toughness of 159.37 ± 28.15 MJ·m⁻³. To demonstrate the versatility, this strategy was further used to fabricate gelatin hydrogel, resulting in a 32-fold enhancement in mechanical strength. Anisotropic thermal conductivity, another representative physical property originating from molecular-level alignment, was also demonstrated. This work establishes a generalizable technology in developing high-performance bulk polymeric materials through molecular level engineering, offering substantial potential for creating new materials for superior load-bearing components, bioelectronic devices, and thermal management systems, etc. Physical sciences/Materials science/Structural materials/Mechanical properties Physical sciences/Engineering/Mechanical engineering Physical sciences/Nanoscience and technology/Nanoscale materials/Structural properties Full Text Additional Declarations There is NO Competing Interest. Supplementary Files Supportinformation.docx 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. 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-8184208","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":552354334,"identity":"4333919a-5cc5-4aea-af5f-26bf1c9b18b0","order_by":0,"name":"Ronghui 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