at Google ScholarTitle data
Xu, Rui ; Cañón Bermúdez, Gilbert Santiago ; Pylypovskyi, Oleksandr V. ; Volkov, Oleksii M. ; Oliveros Mata, Eduardo Sergio ; Zabila, Yevhen ; Illing, Rico ; Makushko, Pavlo ; Milkin, Pavel ; Ionov, Leonid ; Fassbender, Jürgen ; Makarov, Denys:
Self-healable printed magnetic field sensors using alternating magnetic fields.
In: Nature Communications.
Vol. 13
(3 November 2022)
Issue 1
.
- 6587.
ISSN 2041-1723
DOI: https://doi.org/10.1038/s41467-022-34235-3
Abstract in another language
We employ alternating magnetic fields (AMF) to drive magnetic fillers actively and guide the formation and self-healing of percolation networks. Relying on AMF, we fabricate printable magnetoresistive sensors revealing an enhancement in sensitivity and figure of merit of more than one and two orders of magnitude relative to previous reports. These sensors display low noise, high resolution, and are readily processable using various printing techniques that can be applied to different substrates. The AMF-mediated self-healing has six characteristics: 100% performance recovery; repeatable healing over multiple cycles; room-temperature operation; healing in seconds; no need for manual reassembly; humidity insensitivity. It is found that the above advantages arise from the AMF-induced attraction of magnetic microparticles and the determinative oscillation that work synergistically to improve the quantity and quality of filler contacts. By virtue of these advantages, the AMF-mediated sensors are used in safety application, medical therapy, and human-machine interfaces for augmented reality.
Further data
| Item Type: | Article in a journal |
|---|---|
| Refereed: | Yes |
| Institutions of the University: | Faculties > Faculty of Engineering Science > Professor Biofabrication Faculties > Faculty of Engineering Science > Professor Biofabrication > Professor Biofabrication - Univ.-Prof. Dr. Leonid Ionov |
| Result of work at the UBT: | Yes |
| DDC Subjects: | 500 Science > 540 Chemistry |
| Date Deposited: | 03 May 2023 06:52 |
| Last Modified: | 03 May 2023 06:52 |
| URI: | https://eref.uni-bayreuth.de/id/eprint/76135 |