Electrochemical Nitrate Reduction for Nitrogen Neutralization Cycle: Copper‐Based Catalysts via Atomic‐Level Manufacturing

Nitrogen is essential for life and ecosystems. The nitrogen cycle is fundamental to all life on earth and has been implicated in historical mass extinction events, where disruptions to its stability have played a critical role [1]. Moreover, the nitrogen cycle's response to climate change could critically influence atmospheric CO2 levels and the trajectory of global warming [2]. However, improper management of anthropogenic nitrogen-containing wastewater, including domestic sewage, agricultural runoff, and industrial effluents, has pushed the nitrogen cycle to the brink of imbalance [1]. This can lead to water quality deterioration, ecosystem degradation, and risks to human health, including the induction of methemoglobinemia and “blue baby syndrome” [3]. Addressing this challenge is essential to mitigating environmental and climatic impacts. Current approaches to addressing nitrate pollution, including biological methods, reverse osmosis, electrodialysis, and ion exchange, have been explored through multiple avenues [4-6]. However, these methods are often constrained by high energy consumption, complex operation, and low selectivity, which limit their practical application and scalability. Amid the global consensus on the urgent need to promote nitrogen neutrality and circularity, electrochemical nitrogen cycling, particularly nitrate electroreduction (NO3RR), with its environmental friendliness, sustainability, and mild operational conditions, has garnered significant attention [7]. Copper (Cu), owing to its strong nitrate adsorption capacity and earth-abundant resources, has become a focal point in recent studies [8]. Researchers have further enhanced its catalytic activity, selectivity, and stability through sophisticated material design [9]. However, the weak adsorption of *H on Cu limits subsequent hydrogenation steps, restricting further improvements in catalytic activity and potentially generating toxic nitrite (NO2−) [10]. Atomic level manufacturing (ALM), an emerging synthesis strategy, enables precise electrochemical performance modulation by engineering composite sites through atomic-scale modifications [11-14]. Recently, our group published two groundbreaking studies on Cu-based ALM. In one study, atomic-level Cu-modified Fe-based nitrogen-doped carbon nanotube electrodes achieved an exceptional NO3−-N removal capacity of 15,593.8 mg N g−1 cat and ∼92% N2 selectivity [15]. In situ differential electrochemical mass spectrometry (DEMS) and density functional theory (DFT) calculations revealed that Cu on the Fe3C (200) crystal plane significantly accelerated *NO3 and *NO2 conversion by facilitating electron transfer from the metal to *NO3, lowering energy barriers for deoxygenation and hydrogenation steps, thereby enhancing overall NO3RR performance. Electrochemical impedance spectroscopy (EIS) confirmed that Cu incorporation reduced charge transfer resistance and improved electrocatalytic efficiency. In another study, Cu was introduced into Pd nanoparticles, and ultrafine CuPd alloy nanoparticles were confined in situ within a conductive core-shell carbon nanotube@mesoporous carbon matrix (CNTs@mesoC@CuPd) [16]. In situ DEMS demonstrated that NH3 dominated the product spectrum for CNTs@mesoC@Pd, while N2 became the primary gaseous product after Cu introduction. Density functional theory (DFT) calculations reveal that Cu sites facilitate the adsorption and activation of NO, whereas Pd sites favor the formation of nitrogen species. The CuPd alloy enhances the thermodynamic favorability of N2 production by lowering the activation energy of critical steps, such as the conversion of *N2O to *N2. This results from a shift in the binding energy of Cu in the alloy relative to monometallic Cu, indicating strong electronic interactions between Cu and Pd. These interactions increase the electron density of Cu, thereby altering its adsorption and activation capabilities for intermediates. Specifically, Cu sites show a preference for oxygen-containing intermediates (e.g., NO3 and NO2), while Pd sites favor the adsorption and activation of nitrogen-containing intermediates (e.g., N and *N2O). This synergistic effect enables the CuPd alloy to selectively promote N2 generation over NH3 production. The CNTs@mesoC@CuPd catalyst exhibited outstanding performance: 100% NO3− conversion, 98% N2 selectivity, > 30-day stability, and a removal capacity of 30,000 mg N g−1CuPd, surpassing most previously reported catalysts. Advanced synthesis strategies. Current methods struggle to precisely control the phase, composition, size, and spatial distribution of active sites. The heterogeneity of active sites complicates mechanism studies and reduces performance. Using supports with high surface area, conductivity, and structural stability (e.g., fibrous scaffolds [17]) offers a viable approach for unified on-site engineering. Future priorities include developing atomic-level manufacturing techniques using metal-support and organic-inorganic interactions to create precisely distributed, exposed active sites. Machine learning. While theoretical calculations are widely used in catalysis, machine learning (ML) is emerging as a powerful tool. However, ML relies on large, high-quality datasets, which are currently limited. Improving databases or developing techniques to generate reliable ML models from smaller datasets is crucial. Describing complex catalytic mechanisms with simple, interpretable descriptors is challenging. Descriptors bridge catalyst characteristics and catalytic dynamics and significantly impact ML model quality. Selecting features from potential descriptor libraries is, therefore, essential. Industrial applications. Scaling up NO3RR systems is a comprehensive task that requires coordinated cooperation among various components. Developing suitable reactors, such as optimizing membrane electrode assemblies, and achieving synergy among catalysts, reactors, and electrolytes for long-term operation at high current densities, is essential. However, changes in reactor internal pressure and temperature during high-current, long-term operation pose significant challenges to the entire catalytic system. Additionally, real industrial wastewater contains numerous impurity ions. Metal ions may be reduced on the catalyst surface, affecting performance, while other anions could compete with NO3− for adsorption. Therefore, research on real industrial wastewater is also crucial. Cross-disciplinary applications. The insights gained from this study could inform other related electrochemical processes, such as CO2 reduction and oxygen evolution reactions (OER), where atomic-level manufacturing (ALM) could also provide significant benefits. The synergistic effects observed in CuPd alloys, such as the strong electronic interactions between Cu and Pd that enhance catalyst stability and selectivity, may offer valuable strategies for designing catalysts in CO2 reduction, where precise control of adsorption and activation of intermediates is critical. Similarly, in OER, the ability to modulate the electronic structure of active sites through ALM could optimize oxygen intermediate adsorption and desorption, thereby improving catalytic efficiency. By extending the principles of ALM to these processes, researchers could develop more efficient and durable catalysts, further advancing sustainable energy and environmental technologies. This cross-disciplinary approach would not only broaden the appeal of the paper to researchers in adjacent fields but also highlight the versatility of ALM in addressing broader challenges in electrochemistry. Schematic diagram of the ALM future research direction and green catalysis. These efforts will drive the development of ALM-based catalysts toward sustainable nitrogen management and industrial scalability. Lin Gu: writing – original draft, conceptualization. Jian-Ping Yang: supervision, writing – review and editing, resources. This work was financially supported by the National Natural Science Foundation of China (Nos. 52172291, 52122312 and 52473294), the “Shuguang Program” supported by Shanghai Education Development Foundation and Shanghai Municipal Education Commission (No. 22SG31), and the State Key Laboratory of Advanced Fiber Materials, Donghua University. The authors declare no conflicts of interest. Data sharing is not applicable to this article as no datasets were generated or analyzed during the current study.