Xiaojuan Ni

Tailoring graphene-based electrodes from semiconducting to metallic to increase the energy density in supercapacitors.

The semiconducting character of graphene and some carbon-based electrodes can lead to noticeably lower total capacitances and stored energy densities in electric double layer (EDL)capacitors. This paper discusses the chemical and electronic structure modifications that enhance the available energy bands, density of states and quantum capacitance of graphene substrates near the Fermi level, therefore restoring the conducting character of these materials. The doping of graphene with p or n dopants, such as boron and nitrogen atoms, or the introduction of vacancy defects that introduce zigzag edges, can significantly increase the quantum capacitance within the potential range of interest for the energy storage applications by either shifting the Dirac point away from the Fermi level or by eliminating the Dirac point. We show that a combination of doping and vacancies at realistic concentrations is sufficient to increase the capacitance of a graphene-based electrode to within 1 μF cm(−2) from that of a metallic surface.Using a combination of ab initio calculations and classical molecular dynamics simulations we estimate how the changes in the quantum capacitance of these electrode materials affect the total capacitance stored by the open structure EDL capacitors containing room temperature ionic liquid electrolytes.

Monte Carlo simulations of electrical percolation in multicomponent thin films with nanofillers

We developed a 2D disk-stick percolation model to investigate the electrical percolation behavior of an insulating thin film reinforced with 1D and 2D conductive nanofillers via Monte Carlo simulation. Numerical predictions of the percolation threshold in single component thin films showed good agreement with the previous published work, validating our model for investigating the characteristics of the percolation phenomena. Parametric studies of size effect, i.e., length of 1D nanofiller and diameter of 2D nanofiller, were carried out to predict the electrical percolation threshold for hybrid systems. The relationships between the nanofillers in two hybrid systems was established, which showed differences from previous linear assumption. The effective electrical conductance was evaluated through Kirchhoffs current law by transforming it into a resistor network. The equivalent resistance was obtained from the distribution of nodal voltages by solving a system of linear equations with a Gaussian elimination method. We examined the effects of stick length, relative concentration, and contact patterns of 1D/2D inclusions on electrical performance. One novel aspect of our study is its ability to investigate the effective conductance of nanocomposites as a function of relative concentrations, which shows there is a synergistic effect when nanofillers with different dimensionalities combine properly. Our work provides an important theoretical basis for designing the conductive networks and predicting the percolation properties of multicomponent nanocomposites.