Prediction of the Percolation Threshold and Electrical conductivity of Self-Assembled Antimony-Doped Tin Oxide Nanoparticles into Ordered Structures in PMMA/ATO Nanocomposites

被引:16
作者
Jin, Youngho [1 ]
Gerhardt, Rosario A. [1 ]
机构
[1] Georgia Inst Technol, Sch Mat Sci & Engn, Atlanta, GA 30332 USA
基金
美国国家科学基金会;
关键词
polymer matrix composites (PMCs); nanocomposite; functional composite; electrical properties; finite element analysis (FEA); POLY(METHYL METHACRYLATE); OPTICAL-PROPERTIES; MATRIX COMPOSITES; SEGREGATED NETWORKS; FABRICATION; FILMS; POLYMERS; SIZE;
D O I
10.1021/am5061239
中图分类号
TB3 [工程材料学];
学科分类号
0805 ; 080502 ;
摘要
Electrical percolation in nanocomposites consisting of poly(methyl methacrylate) (PMMA) and antimony tin oxide (ATO) nanoparticles was investigated experimentally using monosize and polydisperse polymer particles. The nanocomposites were fabricated by compression molding at 170 degrees C. The matrix PMMA was transformed into space filling polyhedra while the ATO nanoparticles distributed along the sharp edges of the matrix, forming a 3D interconnected network. The measured electrical resistivity showed that percolation was achieved in these materials at a very low ATO content of 0.99 wt % ATO when monosize PMMA was used, whereas 1.48 wt % ATO was needed to achieve percolation when the PMMA was polydispersed. A parametric finite element approach was chosen to model this unique microstructure-driven self-assembling percolation behavior. COMSOL Multiphysics was used to solve the effects of phase segregation between the matrix and the filler using a 2D simplified model in the frequency domain of the AC/DC module. It was found that the percolation threshold (pc) is affected by the size ratio between the matrix and the filler in a systematic way. Furthermore, simulations indicate that small deviations from perfect interconnection result mostly in changes in the electrical resistivity while the minimum DC resistivity achievable in any given composite is governed by the electrical conductivity of the filler, which must be accurately known in order to obtain an accurate prediction. The model is quite general and is able to predict percolation behavior in a number of other similarly processed segregated network nanocomposites.
引用
收藏
页码:22264 / 22271
页数:8
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