Tunneling Effects and Electrical Conductivity of CNT Polymer Composites

2011 ◽  
Vol 1304 ◽  
Author(s):  
S. Xu ◽  
O. Rezvanian ◽  
K. Peters ◽  
M.A. Zikry
Keyword(s):  
Electrical Conductivity ◽  
Polymer Composites ◽  
Current Flow ◽  
Electron Tunneling ◽  
Search Algorithm ◽  
Matrix Material ◽  
Three Dimensional ◽  
Current Transport ◽  
Current Densities ◽  
Tunneling Distance

ABSTRACTA three-dimensional (3D) carbon nanotube (CNT) network computational model was developed to investigate the electrical conductivity and current flow in polymer composites with randomly dispersed CNTs. A search algorithm was developed to determine conductive paths for 3D CNT arrangements and to account for electron tunneling effects. Tunneled currents were obtained as a function of tunneling distance and matrix material. Several possible CNT conductive paths were obtained and finite-element representative volume elements (RVEs) were then used to predict current densities in different CNT arrangements. The predictions indicate that random CNT arrangements can be optimized for current transport.

Microstructural Modeling of Electrical Behavior in CNT Polymer Composites

2012 ◽  
Vol 1420 ◽  
Author(s):  
S. Xu ◽  
O. Rezvanian ◽  
K. Peters ◽  
M.A. Zikry
Keyword(s):  
Electrical Conductivity ◽  
Polymer Composites ◽  
Electron Tunneling ◽  
Search Algorithm ◽  
Three Dimensional ◽  
Thermal Flow ◽  
Electrical Behavior ◽  
Microstructural Modeling ◽  
Polymer Dispersions ◽  
Tunneling Distance

ABSTRACTA three-dimensional (3D) carbon nanotube (CNT) resistor network computational model was developed to investigate the electrical conductivity, and current and thermal flow in polymer composites with randomly dispersed CNTs. A search algorithm was developed to determine conductive paths for 3D CNT arrangements and to account for electron tunneling effects. By coupling Maxwell specialized finite-element (FE) formulation with Fermi-based tunneling resistance, specialized FE techniques were then used to obtain current density evolution for different CNT/polymer dispersions and tunneling distances. These computational approaches address the limitations of percolation theories that are used to estimate electrical conductivity of CNTs. The predictions indicate that tunneling distance significantly affects 3D electrical conductivity and thermal distributions.

Exceptionally high thermal and electrical conductivity of three-dimensional graphene-foam-based polymer composites

RSC Advances ◽  
2016 ◽  
Vol 6 (27) ◽  
pp. 22364-22369 ◽  
Author(s):  
Zhiduo Liu ◽  
Dianyu Shen ◽  
Jinhong Yu ◽  
Wen Dai ◽  
Chaoyang Li ◽  
...  
Keyword(s):  
Thermal Conductivity ◽  
Electrical Conductivity ◽  
Polymer Composites ◽  
Epoxy Matrix ◽  
Three Dimensional ◽  
Neat Epoxy ◽  
Graphene Foam

Three dimensional graphene foam incorporated into epoxy matrix greatly enhance its thermal conductivity (up to 1.52 W mK−1) at low graphene foam loading (5.0 wt%), over an eight-fold enhancement in comparison with that of neat epoxy.

Electrothermomechanical Modeling and Analyses of Carbon Nanotube Polymer Composites

2013 ◽  
Vol 135 (2) ◽  
Author(s):  
S. Xu ◽  
O. Rezvanian ◽  
M. A. Zikry
Keyword(s):  
Finite Element ◽  
Carbon Nanotube ◽  
Polymer Composites ◽  
Volume Fraction ◽  
Electron Tunneling ◽  
Three Dimensional ◽  
Fe Modeling ◽  
Aspect Ratios ◽  
Reinforced Polymer ◽  
Polymer Dispersions

A new finite element (FE) modeling method has been developed to investigate how the electrical-mechanical-thermal behavior of carbon nanotube (CNT)–reinforced polymer composites is affected by electron tunneling distances, volume fraction, and physically realistic tube aspect ratios. A representative CNT polymer composite conductive path was chosen from a percolation analysis to establish the three-dimensional (3D) computational finite-element (FE) approach. A specialized Maxwell FE formulation with a Fermi-based tunneling resistance was then used to obtain current density evolution for different CNT/polymer dispersions and tunneling distances. Analyses based on thermoelectrical and electrothermomechanical FE approaches were used to understand how CNT-epoxy composites behave under electrothermomechanical loading conditions.

Three-dimensional porous stretchable and conductive polymer composites based on graphene networks grown by chemical vapour deposition and PEDOT:PSS coating

2015 ◽  
Vol 51 (15) ◽  
pp. 3169-3172 ◽  
Author(s):  
Mengting Chen ◽  
Shasha Duan ◽  
Ling Zhang ◽  
Zhihui Wang ◽  
Chunzhong Li
Keyword(s):  
Electrical Conductivity ◽  
Polymer Composites ◽  
Vapour Deposition ◽  
Conductive Polymer ◽  
Three Dimensional ◽  
Chemical Vapour ◽  
Electrical Performance ◽  
Retention Capacity ◽  
Cvd Graphene ◽  
Conductive Polymer Composites

The porous CVD graphene–PEDOT:PSS–PDMS composite has outstanding electrical performance, including higher electrical conductivity and better resistance retention capacity than the CVD graphene–PDMS composite.

Three-Dimensional Monte Carlo Simulation of the Electrical Conductivity of Carbon Nanotube/Polymer Composites

2012 ◽  
Vol 5 (4) ◽  
pp. 045101 ◽  
Author(s):  
Dong Choon Lee ◽  
Gyemin Kwon ◽  
Heesuk Kim ◽  
Hyun-Jung Lee ◽  
Bong June Sung
Keyword(s):  
Electrical Conductivity ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Carbon Nanotube ◽  
Polymer Composites ◽  
Three Dimensional

Carbon nanotube-filled polymer composites. Numerical simulation of electrical conductivity in three-dimensional entangled fibrous networks

2006 ◽  
Vol 54 (11) ◽  
pp. 2923-2931 ◽  
Author(s):  
Florent Dalmas ◽  
Rémy Dendievel ◽  
Laurent Chazeau ◽  
Jean-Yves Cavaillé ◽  
Catherine Gauthier
Keyword(s):  
Numerical Simulation ◽  
Electrical Conductivity ◽  
Carbon Nanotube ◽  
Polymer Composites ◽  
Three Dimensional ◽  
Filled Polymer

3D Simulation Modeling for the Electrical Conductivity of Carbon Nanotube Networks in Polymer Nanocomposites

2021 ◽  
Vol 896 ◽  
pp. 39-44
Author(s):  
Yuan Zheng Luo ◽  
You Qi Wan ◽  
Wei Hong
Keyword(s):  
Carbon Nanotubes ◽  
Electrical Conductivity ◽  
Aspect Ratio ◽  
Search Algorithm ◽  
Three Dimensional ◽  
Conductive Network ◽  
Dimethyl Siloxane ◽  
Potential Applications ◽  
The Relationship ◽  
Carbon Nanotube Networks

In this paper, we developed a three-dimensional percolation model to investigate the effects of the concentration and morphology of CNTs (carbon nanotubes) on the electrical conductivity of the nanocomposites. In the model, we judged the connections between CNTs by range search algorithm based on KD-Tree structure. At the same time, DIJKSTRA-Melissa algorithm was applied to efficiently find all the conductive paths instead of finding conductive network in traditional methods. From the simulation results, CNTs with higher aspect ratio were easier to form the conductive network. In a certain range of CNT’s concentration, the relationship between the conductivity of the conductive network and the carbon nanotubes was basically consistent with the classical percolation theory. To verify our simulation model, the morphological, electrical properties of Carbon nanotubes (CNTs)/poly(dimethyl siloxane) (PDMS) nanocomposites with different aspect ratio (AR) of MWNTs were systematically studied. In conclusion, these unique advantageous properties could be exploited to suggest potential applications of artificial electronic skin.

scholarly journals Calculating the Electrical Conductivity of Graphene Nanoplatelet Polymer Composites by a Monte Carlo Method

Nanomaterials ◽  
2020 ◽  
Vol 10 (6) ◽  
pp. 1129 ◽  
Author(s):  
Chao Fang ◽  
Juanjuan Zhang ◽  
Xiqu Chen ◽  
George J. Weng
Keyword(s):  
Electrical Conductivity ◽  
Monte Carlo ◽  
Monte Carlo Method ◽  
Polymer Composites ◽  
Current Flow ◽  
Tunneling Effect ◽  
Graphene Nanoplatelet ◽  
Barrier Heights ◽  
Set Up ◽  
Coated Surfaces

Electrical conductivity is one of several outstanding features of graphene–polymer nanocomposites, but calculations of this property require the intricate features of the underlying conduction processes to be accounted for. To this end, a novel Monte Carlo method was developed. We first established a randomly distributed graphene nanoplatelet (GNP) network. Then, based on the tunneling effect, the contact conductance between the GNPs was calculated. Coated surfaces (CSs) were next set up to calculate the current flow from the GNPs to the polymer. Using the equipotential approximation, the potentials of the GNPs and CSs met Kirchhoff’s current law, and, based on Laplace equation, the potential of the CSs was obtained from the potential of the GNP by the walk-on-spheres (WoS) method. As such, the potentials of all GNPs were obtained, and the electrical conductivity of the GNP polymer composites was calculated. The barrier heights, polymer conductivity, diameter and thickness of the GNP determining the electrical conductivity of composites were studied in this model. The calculated conductivity and percolation threshold were shown to agree with experimental data.

scholarly journals The Impact of Filler Geometry on Polylactic Acid-Based Sustainable Polymer Composites

Molecules ◽  
2020 ◽  
Vol 26 (1) ◽  
pp. 149
Author(s):  
Karol Leluk ◽  
Stanisław Frąckowiak ◽  
Joanna Ludwiczak ◽  
Tomasz Rydzkowski ◽  
Vijay Kumar Thakur
Keyword(s):  
Polymer Composites ◽  
Polylactic Acid ◽  
Matrix Material ◽  
Chemical Properties ◽  
Precipitated Calcium Carbonate ◽  
Cellulose Fibres ◽  
Shape Factors ◽  
Pure Cellulose ◽  
Physico Chemical ◽  
The Impact

Recently, biocomposites have emerged as materials of great interest to the scientists and industry around the globe. Among various polymers, polylactic acid (PLA) is a popular matrix material with high potential for advanced applications. Various particulate materials and nanoparticles have been used as the filler in PLA based matrix. One of the extensively studied filler is cellulose. However, cellulose fibres, due to their hydrophilic nature, are difficult to blend with a hydrophobic polymer matrix. This leads to agglomeration and creates voids, reducing the mechanical strength of the resulting composite. Moreover, the role of the various forms of pure cellulose and its particle shape factors has not been analyzed in most of the current literature. Therefore, in this work, materials of various shapes and shape factors were selected as fillers for the production of polymer composites using Polylactic acid as a matrix to fill this knowledge gap. In particular, pure cellulose fibres (three types with different elongation coefficient) and two mineral nanocomponents: precipitated calcium carbonate and montmorillonite were used. The composites were prepared by a melt blending process using two different levels of fillers: 5% and 30%. Then, the analysis of their thermomechanical and physico-chemical properties was carried out. The obtained results were presented graphically and discussed in terms of their shape and degree of filling.

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