CNT considerations when inputting component properties

Various tools, like the techniques described in this chapter, make use of macro properties to simulate the effective properties of composite structures. At some scales, those tools will normally give sufficient accuracy to determine effective properties, thanks to the nature of the simulated property at that scale. As seen in the previous section, at the nano-scale, some properties might need the use of quantum mechanics to predict the properties of a composite material as some components show properties such as current transport that are better described by such theories (Lee, 2000 Shunin and Schwartz, 1997), for example, it is well known that graphene may develop a resistivity of 10 2 cm (derived from early experiments on electron mobility graphite), but its manufacturing process as well as impurities cause different macroscopic electrical properties. 

When the same approach is used to simulate thermal conductivity, quantum theory might be needed again to predict the resulting thermal properties of composite structures. On the other hand chirality, diameter, and the thickness of, for example, multi-walled carbon nanotubes, as well as morphology (both non-aligned and random - whiskers or straight and curved nanotubes), may play an important role in how to approach the effective determination of properties. Finally, the conductance at the metal catalyst-nanotube junction in the catalyst layers may be different 

---