Conductance through multilayer graphene films

Double-Layer Graphene Outperforming Monolayer as Catalyst on Silicon Photocathode for Hydrogen Production

Photoelectrochemical cells are used to split hydrogen and oxygen from water molecules to generate chemical fuels to satisfy our ever-increasing energy demands. However, it is a major challenge to design efficient catalysts to use in the photoelectochemical process. Recently, research has focused on carbon-based catalysts, as they are nonprecious and environmentally benign. Interesting advances have also been made in controlling nanostructure interfaces and in introducing new materials as catalysts in the photoelectrochemical cell. However, these catalysts have as yet unresolved issues involving kinetics and light-transmittance. In this work, we introduce high-transmittance graphene onto a planar p-Si photocathode to produce a hydrogen evolution reaction to dramatically enhance photon-to-current efficiency. Interestingly, double-layer graphene/Si exhibits noticeably improved photon-to-current efficiency and modifies the band structure of the graphene/Si photocathode. On the basis of in-depth electrochemical and electrical analyses, the band structure of graphene/Si was shown to result in a much lower work function than Si, accelerating the electron-to-hydrogen production potential. Specifically, plasma-treated double-layer graphene exhibited the best performance and the lowest work function. We electrochemically analyzed the mechanism at work in the graphene-assisted photoelectrode. Atomistic calculations based on the density functional theory were also carried out to more fully understand our experimental observations. We believe that investigation of the underlying mechanism in this high-performance electrode is an important contribution to efforts to develop high-efficiency metal-free carbon-based catalysts for photoelectrochemical cell hydrogen production.

Tunable interaction between metal clusters and graphene

Using first principles calculations we find that the interaction between small transition metal clusters and graphene follows the d-band model.

Vertical transport in graphene-hexagonal boron nitride heterostructure devices

Research in graphene-based electronics is recently focusing on devices based on vertical heterostructures of two-dimensional materials. Here we use density functional theory and multiscale simulations to investigate the tunneling properties of single- and double-barrier structures with graphene and few-layer hexagonal boron nitride (h-BN) or hexagonal boron carbon nitride (h-BC₂N). We find that tunneling through a single barrier exhibit a weak dependence on energy. We also show that in double barriers separated by a graphene layer we do not observe resonant tunneling, but a significant increase of the tunneling probability with respect to a single barrier of thickness equal to the sum of the two barriers. This is due to the fact that the graphene layer acts as an effective phase randomizer, suppressing resonant tunneling and effectively letting a double-barrier structure behave as two single-barriers in series. Finally, we use multiscale simulations to reproduce a current-voltage characteristics resembling that of a resonant tunneling diode, that has been experimentally observed in single barrier structure. The peak current is obtained when there is perfect matching between the densities of states of the cathode and anode graphene regions.

Computational chemistry for graphene-based energy applications: progress and challenges

Research in graphene-based energy materials is a rapidly growing area. Many graphene-based energy applications involve interfacial processes. To enable advances in the design of these energy materials, such that their operation, economy, efficiency and durability is at least comparable with fossil-fuel based alternatives, connections between the molecular-scale structure and function of these interfaces are needed. While it is experimentally challenging to resolve this interfacial structure, molecular simulation and computational chemistry can help bridge these gaps. In this Review, we summarise recent progress in the application of computational chemistry to graphene-based materials for fuel cells, batteries, photovoltaics and supercapacitors. We also outline both the bright prospects and emerging challenges these techniques face for application to graphene-based energy materials in future.

Performance evaluation of highly conductive graphene (RGOHI–AcOH) and graphene/metal nanoparticle composites (RGO/Ni) coated on carbon cloth for supercapacitor applications

The application of graphene (RGO)-based composites as electrode materials in supercapacitors can be limited by the fabrication complexity and costs, and the non-environmentally friendly nature of the production process.

Hybridization effects on the out-of-plane electron tunneling properties of monolayers: is h-BN more conductive than graphene?

Electron transport properties through multilayers of hexagonal boron nitride (h-BN) sandwiched between gold electrodes is investigated by density functional theory together with the non-equilibrium Green's function method. The calculated results find that despite graphene being a gapless semimetal and h-BN two-dimensional layer being an insulator, the transmission function perpendicular to the atomic layer plane in both systems is nearly identical. The out-of-plane tunnel current is found to be strongly dependent on the interaction at the interface of the device. As a consequence, single layer h-BN coupled with atomically flat weakly interacting metals such as gold may not work as a good dielectric material, but the absence of sharp resonances would probably lead to more stable out-of-plane electronic transport properties compared to graphene.