Covalent organic framework-based solid polymer electrolytes for metal-ion batteries: pioneering the future of DFT, MD, and ML techniques

Abstract

The accelerating global demand for efficient, safe, and sustainable energy storage has driven extensive research into next-generation metal-ion batteries. Among the key components, the electrolyte plays a pivotal role in determining battery performance, safety, and longevity. Solid polymer electrolytes (SPEs) offer improved thermal stability and safety compared to their liquid counterparts, yet they often suffer from limited ionic conductivity and poor interfacial compatibility. Recently, covalent organic frameworks (COFs) have emerged as highly promising scaffolds for designing advanced SPEs due to their intrinsic crystallinity, structural tunability, and permanent porosity. This review explores the frontier of COF-based SPEs, emphasizing their unique advantages, current limitations, and potential applications in metal-ion batteries (MIBs). We examine how density functional theory (DFT) and molecular dynamics (MD) simulations have elucidated the fundamental mechanisms of ion transport, structural stability, and electronic properties in COFs, while machine learning (ML) has accelerated the pre-design, discovery, and optimization of promising candidates through data-driven prediction and high-throughput screening. By highlighting the synergistic integration of DFT, MD, and ML approaches, we present a roadmap for the rational design of next-generation COF-based electrolytes. Finally, we address the persistent challenges, such as synthetic scalability, interface engineering, and multi-scale modeling, and outline future directions for building efficient, cost-effective, and sustainable battery systems. This review provides a comprehensive reference for researchers seeking to leverage computational and experimental insights to accelerate the development and design of COF-based SPEs for metal-ion batteries.