Process Chain Optimization for SWCNT/Epoxy Nanocomposite Parts with Improved Electrical Properties

Abstract

Electrically conductive nanocomposites present opportunities to replace metals in several applications. Usually, the electrical properties emerging from conductive particles and the resulting bulk values depend on the micro/nano scale morphology of the particle network formed during processing. The final electrical properties are therefore highly process dependent. In this study, the electrical resistivity of composites made from single-walled carbon nanotubes in epoxy was investigated. Three approaches along the processing chain were investigated to reduce the electrical resistivity of nanocomposites-the dispersion strategy in a three-roll mill, the curing temperature, and the application of electric fields during curing. It was found that a progressive increase in the shear forces during dispersion leads to a more than 50% reduction in the electrical resistivities. Higher curing temperatures of the nanocomposite resin also lead to a decrease of around 50% in resistivity. Furthermore, a scalable resin transfer molding set-up with gold-coated electrodes was developed and tested with different mold release agents. It has been shown that curing the material under electric fields leads to an electrical resistivity approximately an order of magnitude lower, and that the properties of the mold release agent also influence the final resistivity of different samples in the same batch.

Processing‐structure‐property relationship of multilayer graphene sheet thermosetting nanocomposites manufactured by calendering

“…It is known that the driving force of a TRM (the shear strain rate) scales with the difference between the speed of the rollers, [ 38 ] but excessive shear strain rate (or equivalently, energy density) may yield fragmentation of the nanostructures. [ 39 ] Estimations of the energy densities for all nanocomposites examined herein are included in section S3 of the supporting information. Based on the theoretical analysis conducted by Huang and Terentjev, [ 11 ] the range of energy densities used in this work are deemed within the interval of energy which is enough to break the GS agglomerates, avoiding substantial fragmentation.…”

“…However, N does not increase in this case because the bundles removed do not form agglomerates. Morais et al [39] argue that when the dispersion using a TRM begins with narrow gaps which remain constant (such as C3) the mixture experiences high shearing stresses from the beginning which promotes dispersion through rupture and an increase in N. On the other hand, when dispersion begins with wide gaps that are gradually reduced (such as ABC) the shear stresses increase gradually, promoting erosion. [39] In Figure 2C it can be seen that the nanocomposite C3 has a significantly higher agglomerate density (N) than ABC, and thus increased conductivity.…”

“…Morais et al [39] argue that when the dispersion using a TRM begins with narrow gaps which remain constant (such as C3) the mixture experiences high shearing stresses from the beginning which promotes dispersion through rupture and an increase in N. On the other hand, when dispersion begins with wide gaps that are gradually reduced (such as ABC) the shear stresses increase gradually, promoting erosion. [39] In Figure 2C it can be seen that the nanocomposite C3 has a significantly higher agglomerate density (N) than ABC, and thus increased conductivity. This supports the hypothesis that the predominant mechanism of dispersion for C3 is rupture and for ABC erosion, and points out that the parameter N plays a paramount role in the determination of effective electrical conductivity of the nanocomposite.…”

“…[22] Additionally, overly supply of energy density may cause fragmentation of the GSs, reducing their aspect ratio and, as a consequence, reducing the conductivity of the nanocomposite. [39,49] This morphology of small, far apart (given their homogeneous distribution), and disconnected agglomerates renders a less effective percolative network for transporting electrons. When comparing the nanocomposites ABC and U-ABC with C, a considerable difference in their conductivities is observed in Figure 3.…”

Editorial for the Special Issue on Discontinuous Fiber Composites, Volume II

“…Meyer et al [13] applied a direct fiber simulation approach to successfully identify fitting parameters for phenomenological fiber orientation models. Morais et al [14] present their research on carbon nanotube (CNTs) composites and investigate the influence of local nanofiber microstructure on electrical conductivity. They show that with optimized microstructure, polymers can be designed as electrically conductive and hence, can be suitable for metal substitution and implementation in complex component design.…”