Abstract
This study introduces an analytical model using mean-field theory to estimate the effective electrical conductivity in composites of spherocylindrical carbon nanotubes (CNTs). The model adjusts the interphase layer's thickness and conductivity based on CNT concentration, affecting the electrical tunneling effect, and incorporates the properties of both CNTs and the interphase layer. Validated through detailed comparisons with experimental data, the model accurately predicts the electrical conductivities of polymer-CNT composites (PCNTs). Mean Squared Error analysis highlights its enhanced precision and superiority over traditional cylindrical CNT models. The model also explores how CNT dimensions, intrinsic conductivity, tunneling distance, potential barrier height, and variations in interphase thickness and conductivity influence electrical conductivity and percolation thresholds. This analytical model improves accuracy in predicting PCNT electrical conductivity and provides critical insights for designing and optimizing conductive polymer nanocomposites.
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