The discrete-element-method application for the numerical investigation of the carbon nanotube-based polymer composite

Conductive polymer composites (CPCs) combine the high electrical conductivity of nanofillers with the lightweight, processability, and corrosion resistance of polymers, making them promising materials for electrochemical applications. This work extends a previously developed discrete element method (DEM)-based conductivity calculation approach from point-like conductive particles to one-dimensional linear fillers, with carbon nanotubes (CNTs) used as the representative filler system. CNTs are represented as chains of connected spherical computational elements, enabling filler curvature, inter-filler contacts, and conductive network topology to be incorporated into the conductivity calculation. A multiscale modeling framework combining the extended DEM framework, molecular dynamics (MD)-generated morphologies, and equivalent circuit modeling is employed to analyze filler morphology, percolation behavior, and processing-induced electrical anisotropy. The results demonstrate the strong influence of CNT connectivity, curvature, orientation, hybridization with carbon black (CB), and network percolation on the macroscopic electrical conductivity. The proposed framework supports the predictive design of CPCs containing fibrous conductive fillers for applications in energy storage, electrochemical sensors, and flexible bioelectronics.