Animal-skin-pattern-inspired multifunctional composites by generative AI

M Masrouri and AV Jadhav and Z Qin, CELL REPORTS PHYSICAL SCIENCE, 6, 102428 (2025).

DOI: 10.1016/j.xcrp.2025.102428

Bioinspired composite materials offer several advantages by mimicking the structure of natural counterparts. However, their complex hierarchical structure, compared to the limited number of observations, makes it difficult to extract all the structural features and vary the structure to optimize the materials' functions without losing their natural features. We applied generative artificial intelligence (GenAI) to design composites inspired by animal skin patterns, leveraging a small dataset to generate diverse configurations that closely emulate natural designs. Our computational simulations investigated the structure-mechanics relationship in these materials, revealing significant variations in mechanical functions and identifying patterns that exhibited superior mechanical properties. We validated these outstanding configurations' performance through tensile tests on specimens produced by a multimaterial printer. We showcase GenAI's role in structural augmentation that can yield rational bioinspired designs, complemented by an educational web page with interactive games for public access.

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