1. Mechanochromic Detection for Soft Opto-Magnetic Actuators
- Author
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Josep Nogués, Borja Sepúlveda, Filippos Giannis Perdikos, Pau Güell-Grau, Pedro Escudero, Rosa Villa, C. Pascual-Izarra, Mar Álvarez, José Francisco López-Barbera, Generalitat de Catalunya, and Ministerio de Ciencia, Innovación y Universidades (España)
- Subjects
Smart sensing ,Smart system ,Materials science ,business.industry ,Soft actuator ,Mechanochromic ,Opto-magnetic ,Highly sensitive ,Broadband ,Structural coloration ,RGB color model ,Wireless ,Optoelectronics ,General Materials Science ,business ,Actuator ,Magnetic actuation ,Research Article - Abstract
New multi-stimuli responsive materials are required in smart systems applications to overcome current limitations in remote actuation and to achieve versatile operation in inaccessible environments. The incorporation of detection mechanisms to quantify in real time the response to external stimuli is crucial for the development of automated systems. Here, we present the first wireless opto-magnetic actuator with mechanochromic response. The device, based on a nanostructured-iron (Fe) layer transferred onto suspended elastomer structures with a periodically corrugated backside, can be actuated both optically (in a broadband spectral range) and magnetically. The combined opto-magnetic stimulus can accurately modulate the mechanical response (strength and direction) of the device. The structural coloration generated at the corrugated back surface enables to easily map and quantify, in 2D, the mechanical deflections by analyzing in real time the hue changes of images taken using a conventional RGB smartphone camera, with a precision of 0.05°. We demonstrate the independent and synergetic optical and magnetic actuation and detection with a detection limit of 1.8 mW·cm-2 and 0.34 mT, respectively. The simple operation, versatility, and cost-effectiveness of the wireless multiactuated device with highly sensitive mechanochromic mapping paves the way to a new generation of wirelessly controlled smart systems., We acknowledge funding from the Generalitat de Catalunya through the 2017-SGR-292 project. The funding from the Spanish Ministerio de Ciencia, Innovación y Universidades (MICINN) through the PID2019-106229RB-I00, MAT2016-77391-R, PCIN2016-093 (M-ERA-NET), DPI2015-68197-R, and RTI2018-096786-B-I00 projects and the Ramon y Cajal Fellowship (RyC2013-14479) is acknowledged. The PhD fellowship CIBAE-023-2014 (from SENESCYT) is also acknowledged. ICN2 is funded by the CERCA programme/Generalitat de Catalunya. The ICN2 is supported by the Severo Ochoa Centres of Excellence programme, funded by the Spanish Research Agency (AEI, grant no. SEV-2017-0706).
- Published
- 2021
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