Materials Engineering of High-Performance Anodes as Layered Composites with Self-Assembled Conductive Networks

The practical implementation of nanomaterials in high capacity batteries has been hindered by the large mechanical stresses during ion insertion/extraction processes that lead to the loss of physical integrity of the active layers. The challenge of combining the high ion storage capacity with resilience to deformations and efficient charge transport is common for nearly all battery technologies. Layer-by-layer (LBL/LbL) engineered nanocomposites are able to mitigate structural design challenges for materials requiring the combination of contrarian properties. Herein, we show that materials engineering capabilities of LBL augmented by self-organization of nanoparticles (NPs) can be exploited for constructing multiscale composites for high capacity lithium ion anodes that mitigate the contrarian nature of three central parameters most relevant for advanced batteries: large intercalation capacity, high conductance, and robust mechanics. The LBL multilayers were made from three function-determining components, namely polyurethane (PU), copper nanoscale particles, and silicon mesoscale particles responsible for the high nanoscale toughness, efficient electron transport, and high lithium storage capacity, respectively. The nanocomposite anodes optimized in respect to the layer sequence and composition exhibited capacities as high as 1284 and 687 mAh/g at the first and 300th cycle, respectively, with a fading rate of 0.15% per cycle. Average Coulombic efficiencies were as high as 99.099.4% for 300 cycles at 1.0 C rate (4000 mA/g). Self-organization of copper NPs into three-dimensional (3D) networks with lattice-to-lattice connectivity taking place during LBL assembly enabled high electron transport efficiency responsible for high battery performance of these Si-based anodes. This study paves the way to finding a method for resolution of the general property conflict for materials utilized in for energy technologies.