Monte Carlo simulation for investigating influence of junction and nanofiber properties on electrical conductivity of segregated-network nanocomposites
Source abstract
Abstract
Electrical transport properties of nanocomposites with and without segregation were studied using a Monte Carlo method. In the segregated composites, the percolation and electrical properties strongly depend on the junctions between tubes/fibers that are located only at interstitial spaces between polymer matrix particles. A three-dimensional Monte Carlo model for determining the critical volume fraction (CVF), path length, and the number of junctions in composites was developed. It has been found that composites containing longer and smaller-diameter fibers with polymer matrix particles (segregated composites) resulted in lower CVF values. The junction properties were calculated by utilizing experimental results obtained with electrically insulating Gum Arabic (GA) and conducting poly(3,4-ethylenedioxythiophene) poly(styrenesulfonate) (PEDOT:PSS). The resistance ratios of fibers to junctions as a function of CVF are also presented. The ratio increases with longer and smaller fibers and the ratio is also higher with PEDOT:PSS than GA for a given CVF. The results including the relation regarding percolation behaviors and resistance ratios as a function of fiber dimensions, fiber type, and stabilizers can be used by experimentalists as a guide to make composites of desired electrical properties.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Conducting polymers and applications · Polymer Nanocomposite Synthesis and Irradiation · Advanced Sensor and Energy Harvesting Materials
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (28)
Show source-provided references
1. Yu · Nano Lett · 2008 · 8 · 442810.1021/nl802345s ↗
2. Kim · ACS Nano · 2009 · 4 · 51310.1021/nn9013577 ↗
3. Kim · Macromol Mater Eng · 2010 · 295 · 43110.1002/mame.200900243 ↗
4. Rowe · 1995
5. Yenny · Scripta Mater · 2008 · 58 · 6910.1016/j.scriptamat.2007.08.025 ↗
6. Dalmas · Acta Mater · 2006 · 54 · 292310.1016/j.actamat.2006.02.028 ↗
7. Wu · J Reinf Plast Compos · 2006 · 25 · 195710.1177/0731684406069923 ↗
8. Ounaies · Compos Sci Technol · 2003 · 63 · 163710.1016/S0266-3538(03)00067-8 ↗
9. Du · Phys Rev B · 2005 · 72 · 12140410.1103/PhysRevB.72.121404 ↗
10. Biercuk · Appl Phys Lett · 2002 · 80 · 276710.1063/1.1469696 ↗
11. Kilbride · J Appl Phys · 2002 · 92 · 402410.1063/1.1506397 ↗
12. Stauffer · 1992
13. Pike · Phys Rev B · 1974 · 10 · 142110.1103/PhysRevB.10.1421 ↗
14. Kirkpatrick · Rev Mod Phys · 1973 · 45 · 57410.1103/RevModPhys.45.574 ↗
15. Vyssotsky · Phys Rev · 1961 · 123 · 156610.1103/PhysRev.123.1566 ↗
16. Dean · Math Proc Cambridge Philos Soc · 1963 · 59 · 39710.1017/S0305004100037026 ↗
17. Balberg · Phys Rev Lett · 1983 · 51 · 160510.1103/PhysRevLett.51.1605 ↗
18. Natsuki · Physica A · 2005 · 352 · 49810.1016/j.physa.2004.12.059 ↗
19. Balberg · Phys Rev Lett · 1984 · 52 · 146510.1103/PhysRevLett.52.1465 ↗
20. Taya · Trans ASME, J Eng Mater Technol · 1987 · 109 · 25210.1115/1.3225972 ↗
21. Lee · J Mater Sci · 1995 · 30 · 303310.1007/BF01209213 ↗
22. Foygel · Phys Rev B · 2005 · 71 · 10420110.1103/PhysRevB.71.104201 ↗
23. Yi · J Appl Phys · 2004 · 96 · 131810.1063/1.1763240 ↗
24. Ma · Polymer · 2008 · 49 · 423010.1016/j.polymer.2008.07.034 ↗
25. Grunlan · Adv Mater · 2004 · 16 · 15010.1002/adma.200305409 ↗
26. Park · Commun ACM · 1988 · 31 · 119210.1145/63039.63042 ↗
27. http://en.wikipedia.org/wiki/Second_partial_derivative_test.
28. Kovacs · Compos Sci Technol · 2007 · 67 · 92210.1016/j.compscitech.2006.02.037 ↗