Strong size-dependent stress relaxation in electrospun polymer nanofibers
Abstract
Here, electrospun polymer nanofibers have garnered significant interest due to their strong size-dependent material properties, such as tensile moduli, strength, toughness, and glass transition temperatures. These properties are closely correlated with polymer chain dynamics. In most applications, polymers usually exhibit viscoelastic behaviors such as stress relaxation and creep, which are also determined by the motion of polymer chains. However, the size-dependent viscoelasticity has not been studied previously in polymer nanofibers. Here, we report the first experimental evidence of significant size-dependent stress relaxation in electrospun Nylon-11 nanofibers as well as size-dependent viscosity of the confined amorphous regions. In conjunction with the dramatically increasing stiffness of nano-scaled fibers, this strong relaxation enables size-tunable properties which break the traditional damping-stiffness tradeoff, qualifying electrospun nanofibers as a promising set of size-tunable materials with an unusual and highly desirable combination of simultaneously high stiffness and large mechanical energy dissipation.
- Authors:
-
- Univ. of California, San Diego, La Jolla, CA (United States)
- Argonne National Lab. (ANL), Argonne, IL (United States)
- Publication Date:
- Research Org.:
- Argonne National Laboratory (ANL), Argonne, IL (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), Basic Energy Sciences (BES); National Science Foundation (NSF)
- OSTI Identifier:
- 1421770
- Alternate Identifier(s):
- OSTI ID: 1361718
- Grant/Contract Number:
- AC02-06CH11357
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Journal of Applied Physics
- Additional Journal Information:
- Journal Volume: 121; Journal Issue: 1; Journal ID: ISSN 0021-8979
- Publisher:
- American Institute of Physics (AIP)
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 42 ENGINEERING
Citation Formats
Wingert, Matthew C., Jiang, Zhang, Chen, Renkun, and Cai, Shengqiang. Strong size-dependent stress relaxation in electrospun polymer nanofibers. United States: N. p., 2017.
Web. doi:10.1063/1.4973486.
Wingert, Matthew C., Jiang, Zhang, Chen, Renkun, & Cai, Shengqiang. Strong size-dependent stress relaxation in electrospun polymer nanofibers. United States. https://doi.org/10.1063/1.4973486
Wingert, Matthew C., Jiang, Zhang, Chen, Renkun, and Cai, Shengqiang. Wed .
"Strong size-dependent stress relaxation in electrospun polymer nanofibers". United States. https://doi.org/10.1063/1.4973486. https://www.osti.gov/servlets/purl/1421770.
@article{osti_1421770,
title = {Strong size-dependent stress relaxation in electrospun polymer nanofibers},
author = {Wingert, Matthew C. and Jiang, Zhang and Chen, Renkun and Cai, Shengqiang},
abstractNote = {Here, electrospun polymer nanofibers have garnered significant interest due to their strong size-dependent material properties, such as tensile moduli, strength, toughness, and glass transition temperatures. These properties are closely correlated with polymer chain dynamics. In most applications, polymers usually exhibit viscoelastic behaviors such as stress relaxation and creep, which are also determined by the motion of polymer chains. However, the size-dependent viscoelasticity has not been studied previously in polymer nanofibers. Here, we report the first experimental evidence of significant size-dependent stress relaxation in electrospun Nylon-11 nanofibers as well as size-dependent viscosity of the confined amorphous regions. In conjunction with the dramatically increasing stiffness of nano-scaled fibers, this strong relaxation enables size-tunable properties which break the traditional damping-stiffness tradeoff, qualifying electrospun nanofibers as a promising set of size-tunable materials with an unusual and highly desirable combination of simultaneously high stiffness and large mechanical energy dissipation.},
doi = {10.1063/1.4973486},
journal = {Journal of Applied Physics},
number = 1,
volume = 121,
place = {United States},
year = {Wed Jan 04 00:00:00 EST 2017},
month = {Wed Jan 04 00:00:00 EST 2017}
}
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