Insights into adsorbent materials for lithium extraction by capacitive deionization: reconceptualizing the role of materials informatics

Abstract

The exponential expansion of the lithium battery market has led to challenges in acquiring lithium resources. Extracting lithium from seawater has been explored as a potential solution to address the shortage of lithium supply. However, seawater lithium extraction presents significant challenges due to its low lithium-ion concentration and complex marine environment. Capacitive deionization (CDI) technology has demonstrated a remarkable ability to selectively separate metal ions from seawater, in which electrode materials play a crucial role. Traditional methods of discovering electrode materials have relied on the trial-and-error principle, and the experimental process of material design and synthesis requires substantial manpower and material resources. The emergence of materials informatics has revolutionized the design and development of electrode materials, substantially reducing the application cost of CDI. Combining our research experience, we explored the application prospects of theoretical calculations in CDI lithium extraction and introduced the development progress of electrode materials that are not limited to CDI lithium extraction in recent years. The key points of using density functional theory (DFT), molecular dynamics (MD), and finite element simulation (FES) to study the mechanism of lithium extraction process, using high-throughput computing and machine learning (ML) to screen new electrode materials are emphasized. The research emphasizes the synergistic utilization of DFT, MD, ML, and FES methodologies to provide instructive insights, aimed at advancing the design of effective CDI electrode materials tailored for lithium extraction from seawater.