Soft Magnetoelastic\nTactile Multi-Sensors with Energy-Absorbing\nProperties for Self-Powered Human–Machine Interfaces

Tactile sensors play a key role in human–machine\ninterfaces\n(HMIs) for augmented and virtual reality, point-of-care devices, and\nhuman–robot collaboration, which show the promise of revolutionizing\nour ways of life. Here, we present a sensor (EMTS) that utilizes the\nmagnetoelastic effect in a soft metamaterial to convert mechanical\npressure into electrical signals. With this unique mechanism, the\nproposed EMTS simultaneously possesses self-powering, waterproof,\nand compliant features. The soft metamaterial is essentially a porous\nmagnetoelastomer structure designed based on the Fourier series expansion,\nwhich allows for programmable mechanical response and sensing performance\nof the EMTS. Fabricated by simple 3D-printed molds, the EMTS also\nholds potential for low-cost production. Particularly, the porous\nmagnetoelastomer structure comes with selectable buckling instabilities\nthat can significantly enhance biomechanical-to-electrical energy\nconversion. Also, with the embedded magnetic microparticles, the energy-absorbing\nperformance of the sensor is greatly improved, which is highly beneficial\nto HMIs. To pursue practical applications, the EMTSs are further integrated\nwith two systems as control and perception modules. It is demonstrated\nthat the EMTS is able to identify different hand gestures to control\na lighting system even in a high-humidity environment. Also, the EMTS\nstands out for its superior capability of simultaneous impact perception\nand energy absorption in drop tests. Overall, with its compelling\narray of features, the presented EMTS gives impetus to multi-sensing\ntechnology and practically enables a variety of HMI applications.

Publication Details

Journal
Figshare
Published
2024-09-12
DOI
https://doi.org/10.1021/acsami.4c10703.s001
Primary Topic
Advanced Sensor and Energy Harvesting Materials
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article
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article

Soft Magnetoelastic\nTactile Multi-Sensors with Energy-Absorbing\nProperties for Self-Powered Human–Machine Interfaces

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Advanced Sensor and Energy Harvesting Materials
article

Soft Magnetoelastic\nTactile Multi-Sensors with Energy-Absorbing\nProperties for Self-Powered Human–Machine Interfaces

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Abstract

Tactile sensors play a key role in human–machine\ninterfaces\n(HMIs) for augmented and virtual reality, point-of-care devices, and\nhuman–robot collaboration, which show the promise of revolutionizing\nour ways of life. Here, we present a sensor (EMTS) that utilizes the\nmagnetoelastic effect in a soft metamaterial to convert mechanical\npressure into electrical signals. With this unique mechanism, the\nproposed EMTS simultaneously possesses self-powering, waterproof,\nand compliant features. The soft metamaterial is essentially a porous\nmagnetoelastomer structure designed based on the Fourier series expansion,\nwhich allows for programmable mechanical response and sensing performance\nof the EMTS. Fabricated by simple 3D-printed molds, the EMTS also\nholds potential for low-cost production. Particularly, the porous\nmagnetoelastomer structure comes with selectable buckling instabilities\nthat can significantly enhance biomechanical-to-electrical energy\nconversion. Also, with the embedded magnetic microparticles, the energy-absorbing\nperformance of the sensor is greatly improved, which is highly beneficial\nto HMIs. To pursue practical applications, the EMTSs are further integrated\nwith two systems as control and perception modules. It is demonstrated\nthat the EMTS is able to identify different hand gestures to control\na lighting system even in a high-humidity environment. Also, the EMTS\nstands out for its superior capability of simultaneous impact perception\nand energy absorption in drop tests. Overall, with its compelling\narray of features, the presented EMTS gives impetus to multi-sensing\ntechnology and practically enables a variety of HMI applications.

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Soft Magnetoelastic\nTactile Multi-Sensors with Energy-Absorbing\nProperties for Self-Powered Human–Machine Interfaces · Figshare (2024) | TGRS Research Map | TGRS