A unified Monte-Carlo to effective-medium study on the electrical conductivity of CNT polymer nanocomposites with electron tunneling

Accurately measuring inter-filler distances at the micro/nanoscale in CNT-polymer nanocomposites poses a significant experimental challenge, yet it critically influences percolation network formation and electron tunneling effects that govern macroscopic electrical properties. Traditional modeling approaches often rely solely on either Monte-Carlo (MC) simulations-which are computationally intensive and struggle to accurately capture percolation thresholds, or effective-medium approximations (EMA)-which typically lack a physical description of electron tunneling. This study proposes a unified numerical framework that adopts the MC method to statistically predict the inter-CNT distances distribution, and incorporates an EMA method to efficiently determine the macroscopic conductive properties of the composite. An interface model is introduced to deal with the imperfect bonding between the matrix and CNT, and to describe the electron tunneling between adjacent CNTs. The combined approach enables physically grounded modeling of tunneling conductivity while efficiently capturing the percolation threshold and macroscopic conductive behavior. Validation against experimental data confirms the model’s accuracy and demonstrates the essential roles of CNT size, concentration, and inter-tube distance in determining electrical performance and percolation characteristics. • Monte-Carlo method with effective-medium approach for CNT composite conductivity. • Electron tunneling and imperfect interface are considered in a coated-CNT model. • Computes inter-CNT distances statistically to evaluate tunneling probability. • Tunneling ratio is predicted under different CNT volume fractions. • Calculation results align well with experimental data across multiple composites.