Capacitive deionisation for water desalination review: experimental and simulation - Rokhsareh Akbarzadeh; Mathias Ernst; Robert Meißner; Bodo Fiedler (Science and Technology of Advanced Materials)
Capacitive Deionization (CDI) has emerged as an energy-efficient and environmentally friendly technology for water desalination. This review provides a comprehensive analysis of CDI, covering both experimental and simulation approaches. It introduces the background, definition, and diverse applications of CDI, from water desalination to environmental monitoring and resource recovery. The review highlights CDI’s advantages, such as low energy consumption and operational simplicity, as well as its limitations, particularly its design-specific operating window favoring low-to-moderate salinity waters and sensitivity to organic-rich conditions. Strategies such as hybrid CDI systems and electrode surface functionalization are discussed to mitigate these challenges. Key working principles and advancements, including innovations in electrode materials, synthesis methods, and reactor design, are examined to improve ion removal efficiency, selectivity, energy use, and system durability. Material modification strategies are presented in the context of structure – performance relationships, emphasizing rational design principles. The review also explores simulation methods, including reactor modeling, computational fluid dynamics, molecular dynamics, and numerical approaches, and machine learning highlighting their synergy with experiments in optimizing CDI performance and guiding scale-up. Coupling CDI with other systems and its applications in water purification, particularly for ion and organic compound removal are also discussed. Finally, challenges in both experimental and simulation efforts, such as material cost, model complexity, computational demands, and scalability, are discussed. While CDI shows promise for sustainable water desalination and resource recovery, further research on hybrid configurations, predictive modeling, and pilot-scale validation is needed to address its limitations and enable large-scale adoption.