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Self-healable printed magnetic field sensors using alternating magnetic fields

Titelangaben

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. Bd. 13 (3 November 2022) Heft 1 . - 6587.
ISSN 2041-1723
DOI: https://doi.org/10.1038/s41467-022-34235-3

Abstract

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.

Weitere Angaben

Publikationsform: Artikel in einer Zeitschrift
Begutachteter Beitrag: Ja
Institutionen der Universität: Fakultäten > Fakultät für Ingenieurwissenschaften > Professur Biofabrikation
Fakultäten > Fakultät für Ingenieurwissenschaften > Professur Biofabrikation > Professur Biofabrikation - Univ.-Prof. Dr. Leonid Ionov
Titel an der UBT entstanden: Ja
Themengebiete aus DDC: 500 Naturwissenschaften und Mathematik > 540 Chemie
Eingestellt am: 03 Mai 2023 06:52
Letzte Änderung: 03 Mai 2023 06:52
URI: https://eref.uni-bayreuth.de/id/eprint/76135