The inherent brittleness of artificial metamaterials often leads to catastrophic failures due to uncontrolled crack propagation. In contrast, natural materials like bone and ceramics exhibit remarkable crack resistance due to their complex microstructures, which allow for spatially controlled crack paths and enhanced toughness. This research addresses the challenge of designing metamaterials with programmable fracture behavior to prevent catastrophic failure. Current methods mainly focus on deflecting cracks using pre-designed vacancies or localized weakening, or enhancing overall fracture energy using nanolattices or multi-material designs. However, a systematic design method for precise spatial damage programming in metamaterials and a comprehensive understanding of effective crack-resisting mechanisms are lacking. This study aims to bridge this gap by developing a design methodology that mimics nature's strengthening mechanisms to create damage-programmable (DP) metamaterials. The anticipated outcome is to produce lightweight materials with superior fracture resistance and the ability to precisely control and arrest damage propagation, thus expanding the potential applications of metamaterials in high-value industries such as biomedical engineering, aerospace, and civil engineering.

Existing research on mechanical metamaterials has focused on achieving extraordinary properties like ultrahigh stiffness-to-weight ratios, energy absorption, and negative Poisson's ratios. Advances in manufacturing have enabled the creation of complex microstructures, leading to improved performance in various applications. However, controlling fracture behavior remains a challenge. Studies have explored strategies like pre-engineered compressive deformations and crystal-mimicking phase meta-structures to enhance mechanical properties. Nevertheless, achieving programmable fracture to prevent catastrophic failure remains a significant hurdle. Prior work has primarily focused on general crack deflection by introducing pre-designed vacancies or localized material weakening. Other approaches aim to increase overall fracture energy through the use of nanolattices, multi-material designs, or novel repetitive structures. Despite these efforts, a systematic approach for precise spatial damage programming and effective crack-resisting mechanisms specifically tailored for metamaterials are still largely underdeveloped.

The researchers developed a data-driven damage-programming metamaterial design method based on machine learning (ML). This method leverages a ML model trained on extensive datasets of fracture strength (σf), fracture energy (Gf), and fracture angle (θ) for DP design. The model uses an ML-enabled algorithm to optimize the fiber orientations within DP cells to achieve desired (σf, Gf, θ) values. The base architecture for illustration was a body-centered cubic (BCC) structure, although the method is adaptable to other topologies. The DP metamaterials were fabricated using Formlabs® Tough 2000 resin with a Formlabs® Form 3 stereolithography (SLA) 3D printer. The effectiveness of the damage-programming designs was experimentally validated by creating a trigonometric fracture surface. Digital image correlation (DIC) and X-ray computed tomography (XCT) were used to analyze the crack propagation and strain fields. Finite element analysis (FEA) was employed to study the fracture properties and the local fracture behaviors of different crack-resisting mechanisms. The FEA models were generated using Rhino 6 and imported into Abaqus CAE for analysis. The experimental setup involved a three-layer configuration to allow for evaluating crack-resisting mechanisms with extended design space vertical to the fracture propagation surface. The thickness of the sidebars was designed to restrict maximum bending displacement to under 1 mm, ensuring limited unexpected strains from the sidebars during testing.

The study successfully demonstrated the ability to spatially program complex crack paths in DP metamaterials. Experimental results confirmed that the targeted crack path was achieved as designed. DIC analysis revealed a significant fracture confinement effect initiated at the programmed crack path, with strain confinement increasing up to 94% before complete fracture. The incorporation of nature-inspired toughening units (crack tip interactions, crack shielding, reinforcement bridging) into the metamaterials significantly enhanced fracture resistance. Crack shielding showed a 4.2-fold increase in normalized fracture energy and a 2.0-fold increase in strength during crack initiation. Crack tip interactions led to a 3.2-fold increase in normalized fracture energy and a 1.9-fold increase in delayed fracture strain during crack propagation. Reinforcement bridges showed a 1.2-fold increase in crack initiation strength and a 2.2-fold increase in normalized fracture energy. Theoretical models were developed to describe the fracture energies contributed by different crack-resisting mechanisms. Metamaterials with combined toughening features (crack tip interactions, crack shielding, reinforcement bridging, and crack dissipation) exhibited a twofold increase in normalized fracture strength and a significantly higher plateau load compared to a reference metamaterial without these features. DIC and XCT experiments showed that the DP metamaterial had a more uniformly distributed strain field, leading to crack tip blunting and increased fracture strength. The DP metamaterials effectively diverted cracks away from vulnerable sites. Finally, the DP metamaterials displayed a remarkable fracture energy density up to 1235% higher than conventional lattices at the same density.

The findings of this study demonstrate the successful translation of natural crack-resisting mechanisms into artificial metamaterials. The ability to precisely program complex crack paths opens new possibilities for designing damage-tolerant materials. The significant enhancement in fracture energy absorption achieved through the integration of various toughening mechanisms highlights the effectiveness of this bio-inspired approach. The theoretical models provide valuable insights into the underlying mechanics of crack propagation in DP metamaterials. The results suggest that the combination of crack-resisting mechanisms is crucial for achieving optimal fracture resistance, with different mechanisms contributing at different stages of crack propagation. This work provides a strong foundation for the development of advanced lightweight materials with enhanced damage tolerance.

This research presents a groundbreaking approach for designing damage-programmable mechanical metamaterials, inspired by nature's crack-resisting strategies. The successful programming of complex crack paths and the significant enhancement in fracture energy absorption demonstrate the potential of this method for developing next-generation lightweight materials. The integration of multiple crack-resisting mechanisms provides superior damage tolerance compared to conventional metamaterials. Future research could focus on exploring the behavior of these metamaterials under complex load scenarios, investigating different parent materials and meta-structure topologies, and exploring diverse applications in lightweight engineering systems.

The current study focuses on a specific resin material and a limited range of metamaterial topologies. The generalizability of the findings to other materials and designs needs further investigation. The experimental conditions might not fully represent real-world loading scenarios, limiting the direct applicability to some practical applications. Future work should explore the performance under complex and dynamic loading conditions, as well as with different materials and manufacturing processes.