作者
Yaoxin Huang,Yanwen Zhang,Jianghuai Li,Tien‐Dat Hoang,Qisheng Jiang
摘要
Mechanical metamaterials, with architected microstructures and programmable properties, represent a transformative class of materials that overcome the intrinsic limitations of conventional solids. Their integration with smart structures enables multifunctionality, adaptability, and environment-responsive behaviors. While traditional strategies, such as microstructural tailoring and composite reinforcement, have achieved notable progress, they now face bottlenecks in scalability, nonlinear control, and multifunctional integration. In this context, 3D and 4D printing technologies provide a disruptive pathway, enabling the fabrication of complex geometries, multi-material assemblies, and time-dependent, stimuli-responsive functions. This review systematically examines the design principles and unique characteristics of mechanical metamaterials and smart structures, emphasizing their integration through additive manufacturing. Recent advances in material systems, including metals, polymers, ceramics, composites, and stimuli-responsive materials, are discussed, alongside emerging computational strategies such as AI-driven inverse design and topology optimization. Representative applications in aerospace, biomedicine, and flexible electronics demonstrate the practical potential of such integrated systems. Despite significant progress, critical challenges remain, including the durability of responsive materials, limitations in manufacturing precision and scalability, difficulties in nonlinear structure–property modeling, and the lack of standardized validation. Future directions include the development of multi-responsive material systems, multi-physics collaborative design, multi-scale modeling, multifunctional integration, and intelligent manufacturing. By advancing these directions, 3D/4D printing-enabled metamaterials and smart structures are expected to transition from laboratory prototypes to real-world applications, driving disruptive innovations in adaptive and intelligent devices.