Fig. 4: Morphology of printed graphene networks as a function of nanosheet size.
a Network specific surface area plotted against lNS in (μm2 μm−3) and (m2 g-1) units. SSA is calculated from network volumes of 279 – 706 µm3 with an uncertainty of ± segmentation error. b Nanosheet aggregation factors in thickness, χt, and length, χl, post-deposition plotted as a function of nanosheet length. The data are presented as means ± the RSS of segmentation error and SE in the mean for (lNS, tNS) (n = 190 − 270) and (lNet, tNet) (n > 9000). c Plot of the pore and nanosheet tortuosity factors in the out-of-plane (y) and in-plane (x,z) directions against lNS. d Plot of the pore and nanosheet tortuosity factors in each direction as a function of the volume fraction of pores (P) and nanosheets (1-P). The solid lines are fits to an adjusted Bruggeman relation described by \(\kappa=\alpha {P}^{1-\beta }\) for the pore data and \(\kappa=\alpha {(1-P)}^{1-\beta }\) for the nanosheets, where \(\alpha\) is a prefactor and β is the fitted Bruggeman exponent. The uncertainty in κ is ± segmentation error. e Hermans orientation factor, S, plotted as a function of nanosheet length for each network. The data are presented as means ± the upper and lower bounds of the 3D distance transform watershed (n > 1800, Supplementary Note 10). f Plot of the morphologically scaled network resistivity \(({\rho }_{{{{{{\rm{IP}}}}}}}(1-P))/{\kappa }_{{{{{{\rm{IP}}}}}}}\) against lNS, where ρIP is the in-plane electrical resistivity and κIP is the in-plane tortuosity factor of the nanosheets. The straight line is a fit to Eq. 1. The data are presented as means ± SE in the mean (n = 9). Source data are provided as a Source Data file.
