Research and prospects of electrochemical technology and educational innovation in water pollution treatment

Abstract

Electrochemical wastewater treatment technologies, such as electrodeposition, electroflocculation, and electrocatalytic electrosorption, are effective and environmentally friendly but have challenges in large-scale applications due to low efficiency, poor stability, and high electrode material costs. Density functional theory (DFT) and artificial intelligence (AI) offer strong support for the design of new electrode materials. These technologies enable efficient material screening and deeply investigate electrochemical mechanisms. However, current models struggle to simulate complex reactions, causing a gap between theory and practice. While new materials exhibit good performance in the lab, their long-term stability and high cost limit industrial use. Future efforts should focus on improving electrode material stability and efficiency, using DFT for more accurate predictions and AI for faster material discovery and optimization. Additionally, integrating educational innovation research in electrochemical techniques into these efforts will help train skilled professional students and encourage them to develop cutting-edge thinking. Reducing material costs and enhancing reaction efficiency are also key to achieving industrial-scale applications.

Keywords

Electrochemical technology / electrocatalysis / machine learning / education

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