It is reported that carbon nanotube (CNT)-based conductive polymer composites have potential application prospect in structural health monitoring and flexible sensors. However, the current price of CNTs is relatively high compared with other fillers. To reduce the materials cost and ensure the sensing characteristics of this type of materials, the most economic and least amount of CNTs needed should be found, this balance value is called as electrical percolation threshold (EPT) in this study. First, a large number of numerical models containing CNTs with three-dimensional random distribution and epoxy resin matrix are established by Monte Carlo method. Then, the construct of conductive network is observed using these models, and the influence of electron tunneling between two adjacent CNTs on the EPT is investigated. Furthermore, the influence of length-diameter ratio (L/D) of CNTs, length variation and angle distribution of CNTs on EPT is investigated. This research provides useful information on how to produce conductive composites more economically.

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