Dataset Information

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.

SUBMITTER: Shim W

PROVIDER: S-EPMC4643282 | biostudies-literature | 2015 Nov

REPOSITORIES: biostudies-literature

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Optimally conductive networks in randomly dispersed CNT:graphene hybrids.

Shim Wonbo W Kwon Youbin Y Jeon Seung-Yeol SY Yu Woong-Ryeol WR

Scientific reports 20151113

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 particl ...[more]

PMID: 26564249

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Project description:A simple hydrothermal route assisted by a triblock copolymer was used to synthesize Ag2O/Ag nanoparticles on a robotic support consists of functionalized MWCNTs and graphene composite (Ag2O/Ag/CNT-graphene). The composites together with the individual analog of Ag/CNT and Ag/graphene were characterized by means of XRD, TEM-SAED, N2 sorptiometry, Raman, FTIR, UV-Vis, and photoluminescence spectroscopy. These nanomaterials were then tested for the catalytic reduction of 4-nitrophenol (4-NP) to the technologically beneficial 4-aminophenol (4-AP). The Ag2O@Ag@CNT-graphene composite calcined at 400°C has shown fascinating reduction performances for 4-NP either in the dark (k = 0.014 s-1) or under visible light illumination (k = 0.039 s-1) in the presence of 5 mM NaBH4 compared to Ag/CNT (0.0112 s-1) and Ag/graphene (0.010 s-1) catalysts. This was chiefly because Ag2O@Ag@CNT-graphene comprises the highest pore volume (0.49 cm3/g) and involves three types of pores in the margin from 1.8 to 4.0 nm in front of only one modal type of pores for the rest of the catalysts and thus maximizes the adsorptive capacity of the reactants (4-NP and NaBH4). Moreover, the former composite exhibits the highest concentration of the Ag2O component as established by numerous techniques in addition to the cyclic voltammetry, proposing it's facile reaction with 4-NP along with the simultaneous transfer of surface hydrogen and electrons from NaBH4 ions to produce 4-AP. The promotion of the p-n junction evaluated using the Mott-schottky equation on Ag2O@Ag@CNT-graphene assisted by charges separation and surface plasmon resonance bands of Ag and Ag2O are found to be advantageous for 4-NP reduction. The latter composite delivers a specific capacitance of 355 F g-1 at 1.0 A g-1 exceeding those of Ag/CNT (230 F g-1) and Ag/graphene (185 F g-1). The EIS study establishes the high electronic conductivity of the metallic Ag and Ag2O moieties, low internal resistance of CNT-graphene as well as the marked ionic transfer facilitated by the composite porous nature.

Dataset Information

Optimally conductive networks in randomly dispersed CNT:graphene hybrids.

Publications

Optimally conductive networks in randomly dispersed CNT:graphene hybrids.

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