Computational modeling of carbon nanostructurse for energy storage and nanoelectronics applications

Theoretical methods have evolved to a point where the properties of materials can be successfully predicted based solely on their atomic structure. As such, they provide a unique tool, able to help identifying the origins of the properties of a given structure and uncovering principles that can be used to tailor the structure for target applications. Here I will show two distinct uses of computational modeling for applications involving carbon-based nanostructures.

The first application presented is focused on capacitive electrical energy storage (i.e. not involving chemical reaction). Supercapacitors based on anoporous carbon materials, commonly called electric double-layer capacitors (EDLCs), are emerging as a novel type of energy-storage device with the potential to substitute for batteries in applications that require high power densities. The EDLC model has been used to characterize the energy storage of supercapacitors for decades. In particular, I will present a heuristic model that avoids the shortcomings o the EDLC modle and that takes pore curvature into account. The new model allows the properties of a supercapacitor to be correlated with pore size, specific surface area, Debye length, electrolyte concentration, dielectric constant, and solute ion size, and lead to a optimization pathway of carbon supercapacitors properties through experiments.m

In the second application discussed in this talk, I will present an overview of our work devoted to electronic transport in carbon nanomeshes and networks. I will first show how atomistic model can be built, based solely on carbon nanotubes as elementary building blocks and a combination of point and space group symmetries. A few specific cases will be presented in detail, highlighting the intricate mechanisms involved in the current distribution in the network. The effect of the presence of defects will also be highlighted, revealing that somewhat contrary to common wisdom, a sufficiently high density of topological defects can in fact induce functionality.

Finally, I will present the theoretical branching mechanism that can be used to devise experimental methods to create carbon nanonetworks. In particular, the importance of using hetero-doping during carbon nanostructure growth will be highlighted.