- 2:35 PM

Computational Study of Electrical Energy Storage In Supercapacitors Based on Carbon Nanotube Forests

Lu Yang1, Lawrence R. Pratt2, Brian H. Fishbine1, David E. Hanson1, and Albert Migliori1. (1) T-12, Los Alamos National Laboratory, Los Alamos, NM 87545, (2) Department of Chemical and Biomolecular Engineering, Tulane University, Room 334, Lindy Boggs Center, New Orleans, LA 70118

Depletion of fossil fuels, increased energy consumption, and the desirability of low CO2 emissions have heightened the need for efficient, clean, and renewable energy sources. However, many carbon-neutral renewable energy resources, e.g. solar and wind, are intermittent and require effective energy storage. Achieving a significant increase in the energy density of capacitive energy storage devices, while retaining their characteristic advantages of high power and extraordinary cyclability will open up great possibilities for the use of these devices across the entire energy sector. At present, there is a lack of fundamental understanding of the molecular interactions in both bulk electrolyte and the electrode-electrolyte interface, which has lead to an Edisonian approach to improvements in these systems. Here I will describe the first molecular scale calculations on the performance of supercapacitors based on carbon nanotube forests as electrodes, systems proposed to respond to these effective energy storage needs. To provide baseline information for modeling the capacitance of nanotube forests, we first calculated the dielectric constant of propylene carbonate, both as a uniform bulk liquid and in thin films confined between oppositely charged parallel graphite electrodes. We then calculated the capacitance for a fully realistic simulation of the experimental system. We find that the computational results are in good agreement with experiment. Calculations for different spacings of the nanotubes confirm an anomalous dependence of capacitance on pore radius that has been reported previously for supercapacitors. The present results therefore offer a basis for better understanding of capacitive energy storage and provide new insight into device design.