Optimized mechano-fluidic metamaterials inspired by deep-sea sponges.
作者
Authors
Meier Timon, Litvinov Sergey, Li Runxuan, Blankenship Brian W, Kokubun Andrew, Hahn David, Mavrikos Stefanos, Vangelatos Zacharias, Yildizdag M Erden, Mäkiharju Simo A, Zheng Xiaoyu, Koumoutsakos Petros, Grigoropoulos Costas P
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年份
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2026
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-
DOI
10.1038/s41467-026-72612-4
📝 摘要
Abstract
Multifunctional materials that balance mechanical resilience and fluid dynamic efficiency are critical in engineering applications, yet their synergistic optimization remains challenging due to inherent trade-offs, computational expense, and high-dimensional design spaces. Inspired by the skeleton of the deep-sea sponge Euplectella aspergillum, this work presents an automated framework integrating Finite Element Analysis for mechanics, Computational Fluid Dynamics for flow behavior, and multi-objective Bayesian optimization. Leveraging high-performance computing, the framework efficiently explores complex design spaces to identify Pareto-optimal solutions. Optimized lattices achieve an average 140% increase in critical buckling load across a range of volume fractions relative to baseline designs, while simultaneously reducing drag, lift, and vortex shedding at porosities as low as 5%. We fabricate selected designs via stereolithography and validate them through compression experiments and particle image velocimetry, showing agreement with simulations. By jointly optimizing mechanics and fluidics, this work establishes a scalable methodology for designing lightweight, high-performance architected materials.
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