(Invited) Are Nanotube Networks the Key to High-Rate, High Capacity Lithium Ion Batteries?

Abstract

Increasing the energy storage capability of lithium-ion batteries necessitates maximization of their areal capacity. This requires thick electrodes performing at near-theoretical specific capacity. However, achievable electrode thicknesses are restricted by mechanical instabilities, with high-thickness performance limited by the attainable electrode conductivity. Here we show that forming a segregated network composite of carbon nanotubes with a range of lithium storage materials (for example, silicon, graphite and metal oxide particles) suppresses mechanical instabilities by toughening the composite, allowing the fabrication of high-performance electrodes with thicknesses of up to 800 μm. Such composite electrodes display conductivities up to 1 × 104 S m−1 and low charge-transfer resistances, allowing fast charge-delivery and enabling near-theoretical specific capacities, even for thick electrodes. The combination of high thickness and specific capacity leads to areal capacities of up to 45 and 30 mAh cm−2 for anodes and cathodes, respectively. Combining optimized composite anodes and cathodes yields full cells with state-of-the-art areal capacities (29 mAh cm−2) and specific/volumetric energies (480 Wh kg−1 and 1,600 Wh l−1).However, such thick electrode might be expected to show poor rate performance. Optimisation of the combination of areal capacity and rate performance would be simplified if a simple mechanistic model linked both parameters to electrode properties. Here we demonstrate an equation which can fit capacity versus rate data, outputting three parameters which fully describe rate performance. Most important is the characteristic time associated with charge/discharge which can be linked by a second equation to physical electrode/electrolyte parameters via various rate-limiting processes. We fit these equations to ~200 data sets, deriving parameters such as diffusion coefficients or electrolyte conductivities. It is possible to show which rate-limiting processes are dominant in a given situation, facilitating rational design and cell optimisation. In addition, this model predicts the upper speed limit for lithium/sodium ion batteries, yielding a value that is consistent with the fastest electrodes in the literature. We show that this equation completely describes much experimental rate data.