Prediction and Reinforcement of Fracture-Prone Regions in Disordered Mechanical Metamaterials

Disordered metamaterials have gained prominence in engineering applications owing to their exceptional strength-to-weight ratios and tunable mechanical behaviors. However, the inherent structural heterogeneity of these metamaterials often induces stress localization, creating fracture-prone regions that compromise structural reliability. To address this challenge, a self-organized generation algorithm is proposed beyond conventional unit-cell-based architectures, enabling the customization of disordered mechanical metamaterials. Fracture-prone regions are evaluated by geodesic edge betweenness centrality (GEBC) metrics, and are optimized by node connectivity adjustment and preferential short-bond redistribution. Remarkably, increasing short-bond frequency resulted in simultaneous enhancement of fracture toughness and ultimate strength while maintaining constant mass density. This study provides new insights into the design of amorphous architected materials, establishing a computational framework for designing disorder metamaterials with damage-tolerant characteristics.