A data-driven framework for structure-property correlation in ordered and disordered cellular metamaterials
Shengzhi Luan, Enze Chen, Joel John, Stavros Gaitanaros

TL;DR
This paper introduces a data-driven framework that systematically links microstructural features of cellular metamaterials to their mechanical properties, enabling better design and understanding of complex lightweight materials.
Contribution
It develops an integrated approach combining virtual microstructure generation, quantification, and interpretable models to analyze structure-property relationships in cellular metamaterials.
Findings
Microstructural features like nodal connectivity and strut orientation significantly influence stiffness.
The framework reveals microstructures that challenge classical Maxwell's criteria.
Effective stiffness varies with microstructural disorder and topology.
Abstract
Cellular solids and micro-lattices are a class of lightweight architected materials that have been established for their unique mechanical, thermal, and acoustic properties. It has been shown that by tuning material architecture, a combination of topology and solid(s) distribution, one can design new material systems, also known as metamaterials, with superior performance compared to conventional monolithic solids. Despite the continuously growing complexity of synthesized microstructures, mainly enabled by developments in additive manufacturing, correlating their morphological characteristics to the resulting material properties has not advanced equally. This work aims to develop a systematic data-driven framework that is capable of identifying all key microstructural characteristics and evaluating their effect on a target material property. The framework relies on integrating virtual…
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Taxonomy
TopicsCellular and Composite Structures
