Conductivity Of Carbon Nanotubes Nanocomposites Research Articles

A new analytical model for predicting the electrical conductivity of carbon nanotube nanocomposites

In predicting the electrical conductivity (EC) of carbon nanotube (CNT)/polymer nanocomposites (CPCs), previous analytical models did not simultaneously consider the effects of CNT waviness and dispersion state, which exist inevitably for real CPCs. In this work, an effective and comprehensive analytical model is developed to predict the percolation threshold and the EC of CPCs by taking into account the effects of CNT waviness and dispersion, etc. A detailed investigation of the effects of CNT content, conductivity, size, waviness and dispersion is conducted on the EC of CPCs. In particular, it is shown that both CNT waviness and dispersion play significant roles in determining the composite EC. Moreover, the predicted results agree well with the existing experimental results and display a higher prediction accuracy compared with the previous typical models for predicting the composite EC. Analytical results indicate that a high EC can be achieved for CPCs with CNTs of a high conductivity, a large aspect ratio (AR), a perfect dispersion state and a low degree of waviness.

Significances of interphase conductivity and tunneling resistance on the conductivity of carbon nanotubes nanocomposites

AbstractThis article expresses a simple model for prediction of conductivity in polymer carbon nanotubes (CNT) nanocomposites (PCNT). This model suggests the roles of CNT concentration, CNT dimensions, CNT conductivity, the percentage of networked CNT, interphase thickness and tunneling properties in the conductivity of PCNT. The suggested model is applied to predict the conductivity in several samples. In addition, the significances of all parameters attributed to CNT, interphase and tunneling regions on the predicted conductivity are justified to confirm the suggested model. The calculations of conductivity properly agree with the experimental results demonstrating the capability of suggested model for prediction of conductivity. Thick interphase increases the conductivity of nanocomposites, because it enlarges the conductive networks. In addition, high tunneling resistivity due to polymer layer, large tunneling distance between adjacent CNT and small tunneling diameter deteriorate the conductivity, because they enhance the tunneling resistance limiting the charge transferring via tunneling regions. The suggested model can replace the available models to predict the conductivity in future researches.

Tunneling resistance and its effect on the electrical conductivity of carbon nanotube nanocomposites

In this paper, we examined the effect of electron tunneling upon the electrical conductivity of carbon nanotube (CNT) polymer nanocomposites. A CNT percolating network model was developed to account for the random distribution of the CNT network using Monte Carlo simulations, where the tunneling resistance between CNTs was established based on the electron transport theory. Our work shows several novel features that result from this tunneling resistance: (i) direct contact resistance is the result of one-dimensional electron ballistic tunneling between two adjacent CNTs, (ii) the nanoscale CNT-CNT contact resistance should be represented by the Landauer-Büttiker (L-B) formula, which accounts for both tunneling and direct contact resistances, and (iii) the difference in contact resistance between single-walled CNTs (SWCNTs) and multi-walled CNTs (MWCNTs) can be modeled by the channel number in the L-B model. The model predictions reveal that the contact resistance due to electron tunneling effects in nanocomposites with dispersed SWCNTs plays a more dominant role than those with MWCNTs. These results compare favorably with existing experimental data and demonstrate that the proposed model can properly estimate the electrical conductivity of nanocomposites containing homogeneously dispersed percolating CNT network.