title: Optimally conductive networks in randomly dispersed CNT:graphene hybrids.
abstract: A predictive model is proposed that quantitatively describes the synergistic behavior of the electrical conductivities of CNTs and graphene in CNT:graphene hybrids. The number of CNT-to-CNT, graphene-to-graphene, and graphene-to-CNT contacts is calculated assuming a random distribution of CNTs and graphene particles in the hybrids and using an orientation density function. Calculations reveal that the total number of contacts reaches a maximum at a specific composition and depends on the particle sizes of the graphene and CNTs. The hybrids, prepared using inkjet printing, are distinguished by higher electrical conductivities than that of 100% CNT or graphene at certain composition ratios. These experimental results provide strong evidence that this approach involving constituent element contacts is suitable for investigating the properties of particulate hybrid materials.
authors.affiliation: Department of Materials Science and Engineering and Research Institute of Advanced Materials (RIAM), Seoul National University, Seoul, Korea.
authors.forename: Wonbo
authors.initials: W
authors.lastname: Shim
authors.affiliation: Department of Materials Science and Engineering and Research Institute of Advanced Materials (RIAM), Seoul National University, Seoul, Korea.
authors.forename: Youbin
authors.initials: Y
authors.lastname: Kwon
authors.affiliation: Department of Materials Science and Engineering and Research Institute of Advanced Materials (RIAM), Seoul National University, Seoul, Korea.
authors.forename: Seung-Yeol
authors.initials: SY
authors.lastname: Jeon
authors.affiliation: Department of Materials Science and Engineering and Research Institute of Advanced Materials (RIAM), Seoul National University, Seoul, Korea.
authors.forename: Woong-Ryeol
authors.initials: WR
authors.lastname: Yu