关键词: 电容去离子, 分子动力学, 密度泛函理论, 有限元分析, 机器学习

Abstract:

Capacitive deionization (CDI) technology is considered to be an emerging water treatment technology in the 21st century, owing to its low energy consumption, absence of secondary pollution, and straightforward operation. The advancement of basic theory and computer science has facilitated the use of multi-angle numerical simulations for CDI. However, due to errors in experimental methods, a direct understanding of mechanisms such as the kinetic characteristics of ion diffusion inside electrode materials, structural evolution during charging and discharging, and the intrinsic connection between potentials and structures is lacking. Existing experimental methods fall short of providing clear theoretical explanations for these phenomena. In contrast, numerical simulations offer a better comprehension of the chemical and electrochemical evolution in CDI. Beyond electrode materials, the device configuration of CDI significantly impacts its performance. Utilizing numerical simulations to study the optimal device configuration is expected to enhance economic efficiency and promote the practical application of CDI. While current reviews of CDI focus primarily on electrode materials and device configurations, there is a dearth of comprehensive reviews on cutting-edge numerical simulation research in the CDI field. This review commences with the earliest continuous-scale model used to describe the dynamic process of CDI. It systematically categorizes multi-angle numerical simulations in CDI, summarizes the strengths and weaknesses of different numerical simulation methods, and anticipates future development directions. Continuous-scale models accurately characterize the ion dynamics of CDI, determining rate and process constraints. Pore-scale models analyze the microstructure of porous media, obviating the need for empirical formulas to preset transport parameters for continuous-scale models. Researchers have introduced molecular dynamics simulation and density functional theory into CDI research, effectively analyzing the influence of structural features at the molecular/atomic level of electrode materials on the CDI system. This aids researchers in enhancing the efficacy and ionic selectivity of CDI electrode materials through pore engineering, defect engineering, and electrochemical microcosmic modulation engineering. Finite element analysis guides improvements in ion diffusion and stability of electrode materials, while computational fluid dynamics provides references for designing high-performance CDI devices. Data-driven machine learning excels in handling nonlinear data and uncovering complex mechanisms of CDI water treatment processes, while digital twin technology can reduce operation and maintenance costs of CDI. Considering costs in practical applications, techno-economic analysis plays a pivotal role in promoting the practical application of CDI technology. This review, the first of its kind, provides an essential theoretical foundation and research ideas for the new paradigm of CDI research by summarizing the advantages and disadvantages of different numerical simulation methods and offering insights into cutting-edge perspectives in the field of CDI.

Key words: Capacitive deionization, Molecular dynamics, Density functional theory, Finite element analysis, Machine learning