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of annotated, domain-specific data; and (iii) complex architectures with tightly coupled components hinder modular adaptation. To address these limitations, we research a physics-guided machine learning
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design of metamaterials for complex loading conditions. The overall objective is to develop an AI-enhanced framework for the rapid design and optimization of next-generation metamaterials, targeting
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