Key factors limiting carbon nanotube yarn strength: Exploring processing-structure-property relationships

Allison M. Beese, Xiaoding Wei, Sourangsu Sarkar, Rajaprakash Ramachandramoorthy, Michael R. Roenbeck, Alexander Moravsky, Matthew Ford, Fazel Yavari, Denis T. Keane, Raouf O. Loutfy, Son Binh T. Nguyen, Horacio D. Espinosa

Research output: Contribution to journalArticle

45 Citations (Scopus)

Abstract

Studies of carbon nanotube (CNT) based composites have been unable to translate the extraordinary load-bearing capabilities of individual CNTs to macroscale composites such as yarns. A key challenge lies in the lack of understanding of how properties of filaments and interfaces across yarn hierarchical levels govern the properties of macroscale yarns. To provide insight required to enable the development of superior CNT yarns, we investigate the fabrication - structure - mechanical property relationships among CNT yarns prepared by different techniques and employ a Monte Carlo based model to predict upper bounds on their mechanical properties. We study the correlations between different levels of alignment and porosity and yarn strengths up to 2.4 GPa. The uniqueness of this experimentally informed modeling approach is the model's ability to predict when filament rupture or interface sliding dominates yarn failure based on constituent mechanical properties and structural organization observed experimentally. By capturing this transition and predicting the yarn strengths that could be obtained under ideal fabrication conditions, the model provides critical insights to guide future efforts to improve the mechanical performance of CNT yarn systems. This multifaceted study provides a new perspective on CNT yarn design that can serve as a foundation for the development of future composites that effectively exploit the superior mechanical performance of CNTs. (Chemical Equation Presented).

Original languageEnglish (US)
Pages (from-to)11454-11466
Number of pages13
JournalACS nano
Volume8
Issue number11
DOIs
StatePublished - Nov 25 2014

Fingerprint

yarns
Carbon Nanotubes
Yarn
Carbon nanotubes
carbon nanotubes
Processing
mechanical properties
Mechanical properties
composite materials
filaments
Composite materials
Bearings (structural)
Fabrication
fabrication
uniqueness
sliding
Porosity
alignment
porosity

All Science Journal Classification (ASJC) codes

  • Materials Science(all)
  • Engineering(all)
  • Physics and Astronomy(all)

Cite this

Beese, A. M., Wei, X., Sarkar, S., Ramachandramoorthy, R., Roenbeck, M. R., Moravsky, A., ... Espinosa, H. D. (2014). Key factors limiting carbon nanotube yarn strength: Exploring processing-structure-property relationships. ACS nano, 8(11), 11454-11466. https://doi.org/10.1021/nn5045504
Beese, Allison M. ; Wei, Xiaoding ; Sarkar, Sourangsu ; Ramachandramoorthy, Rajaprakash ; Roenbeck, Michael R. ; Moravsky, Alexander ; Ford, Matthew ; Yavari, Fazel ; Keane, Denis T. ; Loutfy, Raouf O. ; Nguyen, Son Binh T. ; Espinosa, Horacio D. / Key factors limiting carbon nanotube yarn strength : Exploring processing-structure-property relationships. In: ACS nano. 2014 ; Vol. 8, No. 11. pp. 11454-11466.
@article{07a9af80bc354d7ba239e256bf82e582,
title = "Key factors limiting carbon nanotube yarn strength: Exploring processing-structure-property relationships",
abstract = "Studies of carbon nanotube (CNT) based composites have been unable to translate the extraordinary load-bearing capabilities of individual CNTs to macroscale composites such as yarns. A key challenge lies in the lack of understanding of how properties of filaments and interfaces across yarn hierarchical levels govern the properties of macroscale yarns. To provide insight required to enable the development of superior CNT yarns, we investigate the fabrication - structure - mechanical property relationships among CNT yarns prepared by different techniques and employ a Monte Carlo based model to predict upper bounds on their mechanical properties. We study the correlations between different levels of alignment and porosity and yarn strengths up to 2.4 GPa. The uniqueness of this experimentally informed modeling approach is the model's ability to predict when filament rupture or interface sliding dominates yarn failure based on constituent mechanical properties and structural organization observed experimentally. By capturing this transition and predicting the yarn strengths that could be obtained under ideal fabrication conditions, the model provides critical insights to guide future efforts to improve the mechanical performance of CNT yarn systems. This multifaceted study provides a new perspective on CNT yarn design that can serve as a foundation for the development of future composites that effectively exploit the superior mechanical performance of CNTs. (Chemical Equation Presented).",
author = "Beese, {Allison M.} and Xiaoding Wei and Sourangsu Sarkar and Rajaprakash Ramachandramoorthy and Roenbeck, {Michael R.} and Alexander Moravsky and Matthew Ford and Fazel Yavari and Keane, {Denis T.} and Loutfy, {Raouf O.} and Nguyen, {Son Binh T.} and Espinosa, {Horacio D.}",
year = "2014",
month = "11",
day = "25",
doi = "10.1021/nn5045504",
language = "English (US)",
volume = "8",
pages = "11454--11466",
journal = "ACS Nano",
issn = "1936-0851",
publisher = "American Chemical Society",
number = "11",

}

Beese, AM, Wei, X, Sarkar, S, Ramachandramoorthy, R, Roenbeck, MR, Moravsky, A, Ford, M, Yavari, F, Keane, DT, Loutfy, RO, Nguyen, SBT & Espinosa, HD 2014, 'Key factors limiting carbon nanotube yarn strength: Exploring processing-structure-property relationships', ACS nano, vol. 8, no. 11, pp. 11454-11466. https://doi.org/10.1021/nn5045504

Key factors limiting carbon nanotube yarn strength : Exploring processing-structure-property relationships. / Beese, Allison M.; Wei, Xiaoding; Sarkar, Sourangsu; Ramachandramoorthy, Rajaprakash; Roenbeck, Michael R.; Moravsky, Alexander; Ford, Matthew; Yavari, Fazel; Keane, Denis T.; Loutfy, Raouf O.; Nguyen, Son Binh T.; Espinosa, Horacio D.

In: ACS nano, Vol. 8, No. 11, 25.11.2014, p. 11454-11466.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Key factors limiting carbon nanotube yarn strength

T2 - Exploring processing-structure-property relationships

AU - Beese, Allison M.

AU - Wei, Xiaoding

AU - Sarkar, Sourangsu

AU - Ramachandramoorthy, Rajaprakash

AU - Roenbeck, Michael R.

AU - Moravsky, Alexander

AU - Ford, Matthew

AU - Yavari, Fazel

AU - Keane, Denis T.

AU - Loutfy, Raouf O.

AU - Nguyen, Son Binh T.

AU - Espinosa, Horacio D.

PY - 2014/11/25

Y1 - 2014/11/25

N2 - Studies of carbon nanotube (CNT) based composites have been unable to translate the extraordinary load-bearing capabilities of individual CNTs to macroscale composites such as yarns. A key challenge lies in the lack of understanding of how properties of filaments and interfaces across yarn hierarchical levels govern the properties of macroscale yarns. To provide insight required to enable the development of superior CNT yarns, we investigate the fabrication - structure - mechanical property relationships among CNT yarns prepared by different techniques and employ a Monte Carlo based model to predict upper bounds on their mechanical properties. We study the correlations between different levels of alignment and porosity and yarn strengths up to 2.4 GPa. The uniqueness of this experimentally informed modeling approach is the model's ability to predict when filament rupture or interface sliding dominates yarn failure based on constituent mechanical properties and structural organization observed experimentally. By capturing this transition and predicting the yarn strengths that could be obtained under ideal fabrication conditions, the model provides critical insights to guide future efforts to improve the mechanical performance of CNT yarn systems. This multifaceted study provides a new perspective on CNT yarn design that can serve as a foundation for the development of future composites that effectively exploit the superior mechanical performance of CNTs. (Chemical Equation Presented).

AB - Studies of carbon nanotube (CNT) based composites have been unable to translate the extraordinary load-bearing capabilities of individual CNTs to macroscale composites such as yarns. A key challenge lies in the lack of understanding of how properties of filaments and interfaces across yarn hierarchical levels govern the properties of macroscale yarns. To provide insight required to enable the development of superior CNT yarns, we investigate the fabrication - structure - mechanical property relationships among CNT yarns prepared by different techniques and employ a Monte Carlo based model to predict upper bounds on their mechanical properties. We study the correlations between different levels of alignment and porosity and yarn strengths up to 2.4 GPa. The uniqueness of this experimentally informed modeling approach is the model's ability to predict when filament rupture or interface sliding dominates yarn failure based on constituent mechanical properties and structural organization observed experimentally. By capturing this transition and predicting the yarn strengths that could be obtained under ideal fabrication conditions, the model provides critical insights to guide future efforts to improve the mechanical performance of CNT yarn systems. This multifaceted study provides a new perspective on CNT yarn design that can serve as a foundation for the development of future composites that effectively exploit the superior mechanical performance of CNTs. (Chemical Equation Presented).

UR - http://www.scopus.com/inward/record.url?scp=84912570269&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84912570269&partnerID=8YFLogxK

U2 - 10.1021/nn5045504

DO - 10.1021/nn5045504

M3 - Article

AN - SCOPUS:84912570269

VL - 8

SP - 11454

EP - 11466

JO - ACS Nano

JF - ACS Nano

SN - 1936-0851

IS - 11

ER -

Beese AM, Wei X, Sarkar S, Ramachandramoorthy R, Roenbeck MR, Moravsky A et al. Key factors limiting carbon nanotube yarn strength: Exploring processing-structure-property relationships. ACS nano. 2014 Nov 25;8(11):11454-11466. https://doi.org/10.1021/nn5045504