Literature DB >> 17500878

Modeling percolation in high-aspect-ratio fiber systems. I. Soft-core versus hard-core models.

L Berhan1, A M Sastry.   

Abstract

Numerical and analytical studies of the onset of percolation in high-aspect-ratio fiber fiber systems such as nanotube reinforced polymers available in the literature have consistently modeled fibers as penetrable, straight, capped cylinders, also referred to as spherocylinders. In reality, however, fibers of very high-aspect ratio embedded in a polymer do not come into direct physical contact with each other, let alone exhibit any degree of penetrability. Further, embedded fibers of very high-aspect ratio are often actually wavy, rather than straight. In this two-part paper we address these critical differences between known physical systems, and the presently used spherocylinder percolation model. In Paper I we evaluate the effect of allowing penetration of the model fibers on simulation results by comparing the soft-core and the hard-core approaches to modeling percolation onset. We use Monte Carlo simulations to investigate the relationship between percolation threshold and excluded volume for both modeling approaches. Our results show that the generally accepted inverse proportionality between percolation threshold and excluded volume holds for both models. We further demonstrate that the error introduced by allowing the fibers to intersect is non-negligible, and is a function of both aspect ratio and tunneling distance. Thus while the results of both the soft-core model and hard-core assumptions can be matched to select experimental results, the hard-core model is more appropriate for modeling percolation in nanotubes-reinforced composites. The hard-core model can also potentially be used as a tool in calculating the tunneling distance in composite materials, given the fiber morphology and experimentally derived electrical percolation threshold. In Paper II we investigate the effect of the waviness of the fibers on the onset of percolation in fiber reinforced composites.

Entities:  

Year:  2007        PMID: 17500878     DOI: 10.1103/PhysRevE.75.041120

Source DB:  PubMed          Journal:  Phys Rev E Stat Nonlin Soft Matter Phys        ISSN: 1539-3755


  4 in total

1.  Predicting the electrical conductivity in polymer carbon nanotube nanocomposites based on the volume fractions and resistances of the nanoparticle, interphase, and tunneling regions in conductive networks.

Authors:  Zhenling Liu; Wanxi Peng; Yasser Zare; David Hui; Kyong Yop Rhee
Journal:  RSC Adv       Date:  2018-05-23       Impact factor: 4.036

2.  Aggregate-driven reconfigurations of carbon nanotubes in thin networks under strain: in-situ characterization.

Authors:  Laurence Bodelot; Luka Pavić; Simon Hallais; Jérôme Charliac; Bérengère Lebental
Journal:  Sci Rep       Date:  2019-04-02       Impact factor: 4.379

3.  Estimation of the tensile modulus of polymer carbon nanotube nanocomposites containing filler networks and interphase regions by development of the Kolarik model.

Authors:  Shenggui Chen; Mohsen Sarafbidabad; Yasser Zare; Kyong Yop Rhee
Journal:  RSC Adv       Date:  2018-06-29       Impact factor: 4.036

4.  Modeling the effect of interfacial conductivity between polymer matrix and carbon nanotubes on the electrical conductivity of nanocomposites.

Authors:  Yasser Zare; Kyong Yop Rhee
Journal:  RSC Adv       Date:  2020-01-02       Impact factor: 4.036

  4 in total

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