Abstract

In recent years, nitrate has emerged as a significant groundwater pollutant due to its potential ecotoxicity. In particular, nitrate contamination of brackish groundwater poses a serious threat to both ecosystems and human health and remains difficult to treat. A promising, sustainable, and environmentally friendly solution when biological treatments are not applicable is the conversion of nitrate to harmless nitrogen (N2) or ammonia (NH3) as a nutrient by electrocatalytic nitrate reduction (eNO3R) using solar photovoltaic energy. This review provides a comprehensive overview of the current advances in eNO3R for the production of nitrogen and ammonia. The discussion begins with fundamental concepts, including a detailed examination of the mechanisms and pathways involved, supported by Density Functional Theory (DFT) to elucidate specific aspects of ammonium and nitrogen formation during the process. Furthermore, the integration of artificial intelligence (AI) and machine learning (ML) offers promising advancements in enhancing the predictive power of DFT, accelerating the discovery and optimization of novel catalysts. In this review, we also explore various electrode preparation methods and emphasize the importance of in situ characterization techniques to investigate surface phenomena during the reaction process. The review highlights numerous examples of copper-based catalysts and analyses their feasibility and effectiveness in ammonia production. It also explores strategies for the conversion of nitrate to N2, focusing on nanoscale zerovalent iron as a selective material and the subsequent oxidation of the produced ammonia. Finally, this review addresses the implementation of the eNO3R process for the treatment of brackish groundwater, discussing various challenges and providing reasonable opinions on how to overcome these obstacles. By synthesizing current research and practical examples, this review highlights the potential of eNO3R as a viable solution to mitigate nitrate pollution and improve water quality.

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