Highly Compressible and Conductive N-Doped Graphene Foam for Lithium Batteries

Abstract

Over almost five years, 3-dimensional graphene and graphene-based nanostructured foams have been widely progressed. These materials have potential for use in next-generation energy-related technology for energy storage and generation as well as use in sensors and actuators. Among graphene-based materials, graphene oxides (GOs) can be described as rising material candidates because they show multiple advantage of ultra-light, strong, flexible, elastic, and porous. In addition, they have excellent properties such as high surface area, robust mechanical strength, resistive chemical behavior, and scaffolds with high conducivity. In this presentation, we describe the simple synthesis of ultralow-density 3-dimensional reduced graphene oxide (rGO) foams that show high electrical conductivity and excellent compressibility for the applicaion of lithium batteries. The rGO foams are synthesized using the combination of hydrothermal and thermal annealing method in which hexamethylenetetramine is employed. We confirm that the N-binding configurations of rGO foams increase as evidenced by the change in pyridinic-N/quaternary-N ratio. The conductivity of this graphene foam is almost 12 S/m at 0 strain, whereas the conductivity is ≈704 S/m at the compressive strain (≈80%), which is comparable to previous reported any 3D sponge-like low-density carbon materials. The foam also has excellent hydrophobicity (contact angle on water surface: ≈137°) and shows selective absorption for organic solvents and oils. The compressive modulus of the rGO foam is higher than that of other carbon-based foams. This graphene foam is the simplified, light-weight architecture allowing for large mass loading of guest materials. Our graphen foam has unique electrical and mechanical properties due to the presence of N-doped monolithic graphene, and can be suitable for the use in electrodes for lithium batteries, fuel cells, energy absorption, energy storage, and sensing applications. * K.-Y. Chun & J. Oh are equally contributed as corresponding authors in this study .