Towards Optimal 3D Battery Electrode Architecture: Integrating Structural Engineering with AI-Driven Optimization

The rapid evolution of energy storage devices, driven by increasing demands for prolonged battery life in electronics as well as sustainable energy solutions has elevated lithium-ion batteries (LIBs) to prominence in modern energy systems. With electric vehicle sales and LIB demand surging, the need for high-performing batteries is at an all-time high, critical issues with LIBs have become apparent, particularly in energy degradation due to poor mass transport, emphasising the need for advancements in electrode design. This review explores the influence of electrode structural factors on mass transport properties, with a specific focus on the latest developments in three-dimensional (3D) battery electrodes featuring diverse pore arrangements—ranging from random to ordered pores or porosity gradients. The review delves into recent breakthroughs achieved through structural diversification by applying an inverse design to proximity-field nanopatterning (PnP), laying the groundwork for collaborative efforts aimed at advancing energy storage technologies. Various fabrication methods for 3D electrodes are discussed, highlighting the promising role of integrating the PnP technique with computational algorithms to enhance the precision and design capabilities of 3D nanostructures.