The effect of two critical operating factors on the enhanced catalytic conversion of aqueous NO3– to NH4+ by Pt-Co@NC and theoretical verification of its surface reaction mechanism

2025

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DOI 10.1016/j.cej.2025.159874
Data confidence 70 medium
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Abstract

Elevated nitrate (NO 3 − ) levels in water sources, primarily due to agricultural activities, landfills, and inadequate wastewater treatment, pose significant health risks. Traditional nitrate removal technologies face challenges like high costs and byproduct formation. This study aims to explore the catalytic reduction of NO 3 − to green ammonia (NH 3 ) and ammonium (NH 4 + ) using a Pt-Co@NC (Pt-impregnated core–shell Cobalt N-doped Carbon Nanocage (acid-washed) catalyst), offering a sustainable alternative to the Haber-Bosch process. To elucidate the underlying mechanisms contributing to the superior reactivity of Pt-Co@NC, density functional theory (DFT) calculations were performed, aiming to provide an in-depth understanding of the nitrate reduction process that facilitates the selective conversion of NO 3 – to NH 4 + . We proved that the Pt cluster can provide a favorable environment for hydrogenation steps in nitrate reduction. Based on calculation results, with experiments and kinetic modeling, we optimized conditions such as hydrogen flow rate (200 mL⋅min −1 ) and NO 3 − concentration (5 m g⋅L -1 ) to maximize efficiency and selectivity. In following synthetic wastewater tests, the Pt-Co@NC catalyst maintained high NH 4 + selectivity and efficient NO 3 − reduction despite the presence of competing ions, demonstrating robust performance with a kinetic rate constant of 6.67 × 10 -2 min −1 . These results advance our understanding of NO 3 − reduction mechanisms and provide a viable solution for sustainable nitrate removal and ammonia production. The Pt-Co@NC catalyst’s effectiveness in controlled and synthetic wastewater conditions highlights its potential applicability in real-world water treatment scenarios. The insights on the catalyst design and its operational optimization could lead to the development of advanced catalytic materials and green technologies for efficient treatment and remediation of contaminated water environments.