The design of functional structures from primary building blocks requires a thorough understanding of how size, shape, and particle–particle interactions steer the assembly process. Specifically, for electrically conductive networks build from carbon nanotubes (CNTs) combining macroscopic characterization and simulations shows that the achievable conductivity is mainly governed by CNT aspect ratio, length dispersity and attractive interactions. However, a direct link between the actual 3D network topology that leads to the observed electrical conductivity has not been established yet due to a lack in nanoscale experimental approaches. Here it is shown experimentally for randomly packed (jammed) CNT networks that the CNT aspect ratio determines, as theoretically predicted, the contact number per CNT which in turn scales linearly with the resulting electrical conductivity of the CNT network. Furthermore, nanoscale packing density, contact areas, contact distribution in random and nonrandom configurations, and least resistance pathways are quantified. The results illustrate how complex nanoscale networks can be imaged and quantified in 3D to understand and model their functional properties in a bottom-up fashion.
- carbon nanotubes
- characterization tools
- composite materials
- hierarchical structure
- structure–property relationship