Thermally Drawn Highly Conductive Fibers with Controlled Elasticity
Name
Advanced Materials - 2022 - Marion - Thermally Drawn Highly Conductive Fibers with Controlled Elasticity.pdf
Description
Published version
Size
3.68 MB
Format
Adobe PDF
Checksum (MD5)
6ed889fd4370c6e31d394916f2fce213
Author(s)
Marion, Juliette S
Gupta, Nikhil
Cheung, Henry
Monir, Kirmina
Anikeeva, Polina
Fink, Yoel
Date Issued
March 12, 2022
Journal
Advanced Materials
Publisher
Wiley
Citation
Marion, Juliette S, Gupta, Nikhil, Cheung, Henry, Monir, Kirmina, Anikeeva, Polina et al. 2022. "Thermally Drawn Highly Conductive Fibers with Controlled Elasticity." Advanced Materials.
Version
Final published version
Abstract
Electronic fabrics necessitate both electrical conductivity and, like any textile, elastic recovery. Achieving both requirements on the scale of a single fiber remains an unmet need. Here, two approaches for achieving conductive fibers (107 S m-1 ) reaching 50% elongation while maintaining minimal change in resistance (<0.5%) in embedded metallic electrodes are introduced. The first approach involves inducing a buckling instability in a metal microwire within a cavity of a thermally drawn elastomer fiber. The second approach relies on twisting an elastomer fiber to yield helical metal electrodes embedded in a stretchable yarn. The scalability of both approaches is illustrated in apparatuses for continuous buckling and twisting that yield tens of meters of elastic conducting fibers. Through experimental and analytical methods, it is elucidated how geometric parameters, such as buckling pre-strain and helical angle, as well as materials choice, control not only the fiber's elasticity but also its Young's modulus. Links between mechanical and electrical properties are exposed. The resulting fibers are used to construct elastic fabrics that contain diodes, by weaving and knitting, thus demonstrating the scalable fabrication of conformable and stretchable antennas that support optical data transmission.
MIT Department
Massachusetts Institute of Technology. Research Laboratory of Electronics
Massachusetts Institute of Technology. Department of Materials Science and Engineering
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
McGovern Institute for Brain Research at MIT
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Massachusetts Institute of Technology. Institute for Soldier Nanotechnologies
Terms of Use
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Licens
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1002/adma.202201081
