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◆ Small2026-06-15· Soft robotics

3D‐Printed Metamaterial‐Based Soft Sensors: Materials, Design, and Fabrications

Seong-Jin Park, Tri Dung Nguyen, Eunji Kim, Jaemin Jung, Hayeon Shin, B Kim, Annika Kienzlen, Alexander Verl, Seonggun Joe

原始摘要(英文原文)· Original abstract
Additive manufacturing has enabled highly sophisticated three-dimensional soft bodies through material distribution, opening new possibilities for architected soft matter systems. In parallel, rapid development in soft robotics has intensified the necessity of compliant, distributed, and deformation-driven sensing solutions. Among possible solutions, 3D-printed metamaterial-based soft sensors are promising due to unprecedented mechano-sensing performances. Specifically, by integrating material design and structural topology into a unified functional entity, these metamaterial-based sensing solutions enable tunable stiffness, controlled instability, and efficient electromechanical transduction. With these promising findings in mind, this review aims to provide a comprehensive framework addressing additive manufacturing technologies, material systems, and sensing mechanisms in 3D-printed metamaterial-based sensors. In this work, available 3D printing technologies are discussed, highlighting trade-offs in resolution, multi-material capability, and structural fidelity. In parallel, a variety of 3D printing materials, including polymer-based, functional composite, and smart responsive materials, is examined, emphasizing material-structure interactions determining sensing performance. Subsequently, metamaterial-based transduction mechanisms are classified into resistive, capacitive, and inductive modalities, together with emerging multifunctional and multimodal sensing modality. Conclusively, by synthesizing fabrication technologies, material systems, and sensing architectures within an additive manufacturing perspective, this review provides design frameworks and outlooks for perceptive soft machines and their applications in real-world scenarios.
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