Mechanical properties of carbon nanotube reinforced polymer nanocomposites: A coarse-grained model

TL;DR

This paper introduces a coarse-grained model for CNT-reinforced polymer nanocomposites that accurately predicts elastic properties while significantly reducing computational costs, enabling multiscale simulations.

Contribution

A novel coarse-grained modeling approach that captures polymer-nanotube interactions and predicts mechanical properties efficiently across scales.

Findings

CG model accurately estimates elastic properties

Model reduces computational cost compared to atomistic simulations

Effect of CNT volume fraction on Young's modulus analyzed

Abstract

In this work, a coarse-grained (CG) model of carbon nanotube (CNT) reinforced polymer matrix composites is developed. A distinguishing feature of the CG model is the ability to capture interactions between polymer chains and nanotubes. The CG potentials for nanotubes and polymer chains are calibrated using the strain energy conservation between CG models and full atomistic systems. The applicability and efficiency of the CG model in predicting the elastic properties of CNT/polymer composites are evaluated through verification processes with molecular simulations. The simulation results reveal that the CG model is able to estimate the mechanical properties of the nanocomposites with high accuracy and low computational cost. The effect of the volume fraction of CNT reinforcements on the Young's modulus of the nanocomposites is investigated. The application of the method in the modeling of large unit cells with randomly distributed CNT reinforcements is examined. The established CG model will enable the simulation of reinforced polymer matrix composites across a wide range of length scales from nano to mesoscale.