Suwoo Lee1,Hyeonseo Song1,Yeonwoo Jang1,Youn-Kyoung Baek2,Jiyun Kim1
UNIST1,Korea Institute of Materials Science2
Suwoo Lee1,Hyeonseo Song1,Yeonwoo Jang1,Youn-Kyoung Baek2,Jiyun Kim1
UNIST1,Korea Institute of Materials Science2
Tactile sensors for human-machine interface (HMI), that convert mechanical stimuli into electrical signals, have gained great attention in various applications. In particular, self-powered soft sensors such as piezoelectric, triboelectric, and magnetoelastic soft sensors have shown great potential due to their safety, adaptability, and low production and maintenance costs. However, piezoelectric and triboelectric sensors have high internal impedance, which lowers the current flow, reducing the current density and the output power density. Furthermore, their output sensing performance is susceptible to humidity conditions of the surrounding environment, including even sweat on the skin. On the other hand, soft self-powered tactile sensor based on magnetoelastic mechanism has the potential to provide high output power density due to their high current density and more reliable output performance regardless of humidity.<br/>Here, we present highly compressible 3D-printed soft magnetoelastic sensors (H-MELS) by using 3D printing methods with sacrificial mold, which allow us to program the material, and mechanical properties of H-MELSs, influencing the mechanoelectrical converting performances of H-MELS. In addition, we developed elastomeric magnetic composite materials for a magnetic part and elastomeric electrical parts using a coiled-copper coil to fabricate H-MELSs. This strategy allows us to achieve highly scalable and compliant 3D architectures made of very compliant materials for 3D soft magnetoelastic sensors, and even integrate them into robotic systems as a robot operation units and robot’s perception units for practical Human-Machine Interface applications. We believe H-MELS with high compressibility in various form factors leads to significant advancements in design and manufacturing of self-powered soft sensors for human-machine interfaces.