A review of printing methods, materials, and artificial intelligence applications in sodium-ion battery manufacturing and management systems

Abstract

Sodium is abundant in the Earth’s crust and presents a promising, more sustainable alternative to lithium for battery technologies. However, achieving comparable electrochemical performance, safety, and recyclability to lithium-ion batteries remains a critical research challenge. This review focuses on printable sodium-ion batteries (SIBs) as a viable pathway to advance next-generation, low-cost, and flexible energy storage devices. Emphasis is placed on printing methods particularly inkjet and screen printing due to their scalability, customizability, and low material waste. Metallic and organic nanomaterials used in battery printing are covered including the main fabrication methods for such inks. Key nanoink parameters such as viscosity (1–15 mPa·s) and surface tension (20–70 mN m⁻¹), as well as rheological indicators like Reynolds and Weber numbers, are reviewed for their impact on print quality and electrode performance. Battery characterization techniques including cyclic voltammetry and galvanostatic charge–discharge methods are discussed. The review explores the emerging integration of artificial intelligence in printable SIB development, covering machine learning for printing optimization, deep learning for state-of-health prediction, and AI-enabled battery waste management. This comprehensive overview offers insight for both new and established researchers exploring the future of printable, sustainable SIBs.