Binary superlattices enable programmable tensile strength and ductility in magneto-elastic granular architectures (MEGAs) | 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 Binary superlattices enable programmable tensile strength and ductility in magneto-elastic granular architectures (MEGAs) Sinan Keten, Xinyan Yang, Junqing Leng, Yitong Chen, Bolin Chen, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9511359/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 Magneto-elastic Granular Architectures (MEGAs) consisting of 3D-printed star-shaped units and magnetic branch termini offer modularity and reversibility not seen in conventional monolithic materials. Tailoring magnetic strength and star topology leads to ordered structures with distinct mechanical responses. However, single-component MEGAs typically exhibit limited tensile extensibility. Here we show that binary superlattices, introduced by combining two-branch (Bar) and three-branch (Y) units, enable programmable tensile strength and ductility and yield architectures with extensibility far exceeding that of single-component systems. By tuning unit sizes, we uncover hierarchical dual networks in which subnetwork units provide hidden length released via sacrificial magnetic bond detachment during deformation. We construct a phase diagram, a performance map, and a predictive framework to reveal design rules linking unit geometry, deformation pathways, and macroscopic response. Our work opens opportunities for easy-to-assemble and reconfigurable architected metamaterials with controllable brittle–ductile transitions, with implications for adaptive load-bearing, impact mitigation, and robotic systems. Physical sciences/Engineering/Mechanical engineering Physical sciences/Materials science/Structural materials/Mechanical properties Physical sciences/Physics/Condensed-matter physics/Magnetic properties and materials magneto-elastic granular architectures binary superlattices programmable tensile response data-driven predictive modeling Full Text Additional Declarations There is NO Competing Interest. Supplementary Files 2SimulatedTensileDeformationTrajectoryForSystemBar1.9Y2.3.mp4 Supplementary Video 2 | Simulated uniaxial tensile deformation of system ( L 0,Bar , L 0,Y ) = (1.9, 2.3) 1SimulatedTensileDeformationTrajectoryForSystemBar1.3Y1.3.mp4 Supplementary Video 1 | Simulated uniaxial tensile deformation of system ( L 0,Bar , L 0,Y ) = (1.3, 1.3) 4SimulatedTensileDeformationTrajectoryForSystemBar1.0Y1.9.mp4 Supplementary Video 4 | Simulated uniaxial tensile deformation of system ( L 0,Bar , L 0,Y ) = (1.0, 1.9) MEGAsupplementary.pdf Supplementary Information 5SimulatedTensileDeformationTrajectoryForSystemBar1.4Y1.8.mp4 Supplementary Video 5 | Simulated uniaxial tensile deformation of system ( L 0,Bar , L 0,Y ) = (1.4, 1.8) 3SimulatedTensileDeformationTrajectoryForSystemBar1.4Y1.0.mp4 Supplementary Video 3 | Simulated uniaxial tensile deformation of system ( L 0,Bar , L 0,Y ) = (1.4, 1.0) 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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