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Article

Harnessing Heterogeneous Interface and Oxygen Vacancy in Cu/Cu2O for Efficient Electrocatalytic Nitrate Reduction to Ammonia

by
Yaxuan Li
1,
Ling Fang
2,* and
Yuanjuan Bai
1,*
1
Hunan Province Key Laboratory of Materials Surface & Interface Science and Technology, College of Material Science and Engineering, Central South University of Forestry and Technology, Changsha 410004, China
2
Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, China
*
Authors to whom correspondence should be addressed.
Energies 2024, 17(17), 4467; https://doi.org/10.3390/en17174467
Submission received: 1 August 2024 / Revised: 27 August 2024 / Accepted: 4 September 2024 / Published: 5 September 2024
(This article belongs to the Section D: Energy Storage and Application)
Browse Figures
Versions Notes

Abstract

In recent years, the electrocatalytic reduction of nitrate to ammonia (NRA) has garnered significant research attention. However, the complex multi-step proton–electron transfer process often results in various by-products, limiting NH3 production. Therefore, designing and developing highly active and selective electrocatalysts for efficient NRA is crucial. This study proposes a method to construct Cu/Cu2O nanosheet arrays with heterogeneous interfaces and oxygen vacancies on copper foam surfaces through electrochemical reduction. The interface coupling between Cu and Cu2O significantly optimizes the catalyst’s surface electronic structure, providing sufficient active sites. In addition, the presence of oxygen vacancies in Cu/Cu2O can optimize the adsorption kinetics of intermediates in the NRA process and effectively inhibit the formation of by-products. The results show that Cu/CuO2 nanosheet arrays are superior NRA catalysts, achieving a Faradaic efficiency of up to 91.1%, a nitrate conversion of 96.25%, and an NH3 yield rate of 6.11 mg h−1 cm−2.

1. Introduction

Electrocatalytic nitrate reduction to ammonia (NRA) not only helps to mitigate the potential hazards of nitrate to the environment and human health but also enables the continuous production of valuable ammonia under ambient conditions [1,2,3,4]. Nitrate pollution is a significant global environmental issue, primarily stemming from the excessive use of fertilizers in agriculture, industrial wastewater discharge, and the degradation of household waste. Compared to other nitrate reduction methods, NRA offers distinct advantages in terms of energy efficiency, environmental friendliness, reaction conditions, ammonia selectivity, and operational convenience [5,6]. Ammonia stands as a crucial raw material in contemporary industry, holding an indispensable position in areas such as agriculture and electrical and chemical synthesis. At present, the Haber–Bosch process dominates NH3 production; however, its severe operational requirements lead to the use of around 2% of the global annual energy and substantial CO2 emissions [7,8,9]. Electrocatalytic nitrate reduction reaction (NRA), with its mild reaction conditions and high selectivity, is considered a promising method for future ammonia synthesis [10].
NRA is a complex eight-electron reaction involving various intermediates (such as NO2− and NO) and slow multi-electron transfer rates. During the reaction, NRA often competes with the hydrogen evolution reaction (HER) [11,12]. Therefore, developing suitable catalysts to accelerate electron transfer rates and suppress HER is crucial for improving the Faradaic efficiency (FE) of NH3 and NH3 yield rate. In recent years, a wide range of noble and transition metal catalysts (including Ru, Pd, Au, Ni, Co, Cu, Fe, and their related compounds) have been applied in the field of NRA [13,14,15,16,17,18]. Compared to other metals, copper-based materials offer several advantages, including a moderate cost, abundant availability, 3d transition metal structure, and ease of modification. Additionally, the d-orbital energy level of copper is close to the LUMO π* molecular orbital of nitrate, facilitating electron transfer to the adsorbed nitrate [19,20,21]. Consequently, copper-based materials have become a focal point in the electrocatalytic ammonia production field. Many researchers have designed various strategies to enhance the application of copper-based catalysts in NRA, including constructing heterogeneous interfaces, introducing defects, alloying, and doping with noble metals [22,23]. Among these, copper-based oxide nanomaterials exhibit diverse dual-function active centers with variable valence states, and superior reaction kinetics. The surface of copper-based oxides can be easily modified through electrochemical reduction to create structural defects and heterogeneous interfaces [24,25]. Introducing defects can alter the electronic structure of the catalyst and optimize electron distribution. Defect areas typically have a higher local electron density or hole concentration, which can promote electron transfer [26,27,28]. Heterogeneous interfaces can increase the number and types of active sites, alter the electron density and energy level distribution at the interface, and thereby optimize the reaction pathway [29,30]. Fang et al. [31] utilized a hydrothermal method to synthesize cupric oxide nanowire arrays (SCF) with high-density stacking fault defects. These surface stacking fault defects reduce the coordination number of surface atoms, increasing adsorption capacity and inhibiting hydrogen evolution reactions. As a result, the conversion of nitrate removal notably improved to 93%, and ammonia selectivity reached 94%. Yanshi et al. [32] obtained oxygen vacancy-rich Cu/Cu2O heterogeneous nanorods (Cu/Cu2O NRs) This indicates that, compared to Cu, Cu/Cu2O NRs with abundant OVs are more effective in promoting the formation of *NOH intermediates, with the reduced reaction barrier on the surface being the primary reason for their high ammonia selectivity.
In this study, we propose a method of constructing a nanosheet array (Cu/Cu2O) rich in oxygen vacancies and heterogeneous interfaces on a copper foam surface through electrochemical regulation of the surface interface. The nanosheet array can expose sufficient active sites. The synergistic impact of heterogeneous interface and oxygen vacancies can alter the electron concentration, optimize the reaction pathway, improve the adsorption performance of nitrate and its intermediates, and accelerate the transfer of electrons. These outstanding physicochemical properties endow Cu/Cu2O with excellent catalytic performance in NRA. At −0.6 V (vs. RHE), the ammonia production rate on the Cu/Cu2O can reach 6.11 mg h−1 cm−2, with excellent nitrate conversion (96.52%) and Faradaic efficiency (91.6%).

2. Materials and Methods

2.1. Preparation of CuO

First, copper foam (4 cm × 2 cm) was cleaned in 3.0 M HCl to remove surface oxide impurities. It was then rinsed with deionized water and placed in a vacuum drying oven for future use. To prepare the oxidizing solution, 3.2 g of (NH4)2S2O8 and 16 g of NaOH were dissolved in 70 mL of deionized water. The dried copper foam was then placed into the prepared solution and shaken in a shaker at 60 °C for 20 min. The CuO obtained by surface oxidation was rinsed with deionized water, dried, and cut into 1 cm × 1 cm pieces.

2.2. Preparation of Cu/Cu2O

In the electrochemical measurement, a three-electrode system was used with CuO as the working electrode, saturated calomel as the reference electrode, and iridium-ruthenium-titanium as the counter electrode with 0.5 M phosphate-buffered solution (PBS) as the electrolyte. The i-t program was run for 150 s at different voltage conditions. To select the appropriate voltage, we set a series of voltage gradients and named the samples CuO-x (where x indicates the voltage vs. SCE). We compared CuO-2.0, CuO-2.5, CuO-3.0, CuO-3.5, and CuO-4.0 as catalyst samples. Among them, CuO-2.5 showed the best NRA performance, with the highest ammonia yield (6.11 mg h−1 cm−2) and ammonia FE (91.1%). The ammonia yields (5.58, 5.662, 5.135, 5.004 mg h−1 cm−2) and ammonia FEs (85.35%, 90.5%, 89.78%, 87.05%) of CuO-2.0, CuO-3.0, CuO-3.5, and CuO-4.0 were all lower than those of CuO-2.5 (Figure S7). Therefore, we chose to run the i-t program for 150s at −2.5 V vs. SCE, resulting in Cu/Cu2O.

2.3. Characterization

The morphology of the materials was investigated using scanning electron microscopy (SEM, JEOL JSM-7800F, Tokyo, Japan) and transmission electron microscopy (TEM, Talos-FEG, Thermo Fisher Scientific, Waltham, MA, USA), both equipped with energy-dispersive X-ray spectroscopy (EDX) at 200 kV. X-ray diffraction (XRD) measurements were conducted on a D8 ADVANCE diffractometer (Bruker, Karlsruhe, Germany) with Cu Kα radiation. The chemical states were analyzed by X-ray photoelectron spectroscopy (XPS) using an ESCALAB MK II spectrometer (Thermo Fisher Scientific, Waltham, MA, USA).

2.4. Electrocatalytic Experiments

NRA tests were evaluated on a CHI660E (Chenhua Co., Shanghai, China) electrochemical workstation at room temperature. We conducted the reaction in an H-type reactor, which was divided by a proton exchange membrane. The cathode electrolyte consisted of 100 mL of 0.5 M PBS with 100 mg L−1 of NO3−-N, while the anode electrolyte was 100 mL of 0.5 M PBS. Prior to each NRA test, cyclic voltammetry (CV) was performed repeatedly at a scan rate of 50 mV s−1 until the CV curve stabilized. Then, chronoamperometric measurements were conducted for 2 h under different applied potentials with stirring (stirring rate: 380 rpm). Electrochemical impedance spectroscopy (EIS) was carried out in 0.5 M PBS containing 100 mg L−1 of NO3−-N, with a frequency range from 100 kHz to 0.1 Hz. All potentials were converted to the RHE scale using the equation E (V vs. RHE) = E (V vs. SCE) + 0.059 × pH + 0.234. Additionally, the current density data in this study were normalized to the geometric area of the working electrode.

3. Results

3.1. Characterizing Structure

Figure 1a illustrates the schematic diagram of the synthesis of Cu/Cu2O nanosheet arrays. CuO was produced by water-treating copper foam (CF) in a mixed solution of concentrated NaOH and (NH4)2S2O8 through a straightforward surface oxidation process at 60 °C. Subsequently, the CuO was in situ-reconstructed in a 0.5 M PBS for 150 s to obtain the Cu/Cu2O. The CuO grows at random angles on the copper foam substrate, with straight outlines and smooth surfaces (Figure 1b). As shown in Figure 1e, irregular particles formed on the surface of the Cu/Cu2O NRs, resulting in a rougher surface and a larger specific surface area. During the electrochemical reduction process, the CuO was converted into Cu/Cu2O, creating heterogeneous interfaces and oxygen vacancies that provide more catalytic sites for electrochemical nitrate reduction (NRA). Additionally, the nanosheet array structures with heterogeneous interfaces offer unique electron transfer channels that are beneficial for enhancing NRA activity. The CuO and Cu/Cu2O were peeled off from the CF and subjected to TEM and HRTEM analysis. CuO is created through the radial arrangement of irregular flakes with smooth surfaces (Figure 1c). A high-resolution TEM analysis reveals lattice spacings of 0.249 nm and 0.232 nm, corresponding to the (−111) and (111) planes of CuO, respectively (Figure 1d). After electrochemical reduction and reconstruction, the Cu/Cu2O nanosheets retain an array structure with obvious void structures and rough morphological features (Figure 1e). An HRTEM analysis shows that the Cu/Cu2O nanosheets have high crystallinity, with lattice spacings of 0.18 nm and 0.212 nm corresponding to the Cu (200) and Cu2O (200) planes, respectively, confirming the presence of the heterogeneous interface structure (Figure 1f). This further confirms the formation of Cu and Cu2O. Moreover, HAADF-STEM images and elemental mapping images show the uniform distribution of Cu and O elements, confirming that Cu/Cu2O is composed of Cu and O (Figure 1h). The EDS results show that the O atomic ratio in Cu/Cu2O is lower than CuO, indicating the reduction of CuO to Cu/Cu2O on the surface (Figure S1).
The XRD patterns of CuO are identified as Cu substrate and pure CuO. Cu substrate has the cubic crystalline structure of copper (PDF #85-1326), with three strong peaks at 43.31°, 50.45°, and 74.13°, corresponding to (111), (200), and (220). The main peaks in the XRD patterns, located at 35.49°, 38.68°, 48.66°, and 68.01°, correspond well to the (−110), (111), (−202), and (220) planes of CuO (PDF #80-1916), indicating relatively a high purity of CuO. After electrochemical reduction, three peaks corresponding to Cu (PDF #85-1326) and two peaks belonging to Cu2O (PDF #99-0041) can be found, indicating the reduction of CuO to Cu/Cu2O (Figure 2a). XPS was used to analyze the composition and valence states of Cu/Cu2O and CuO. The XPS survey spectra of both samples show signals of Cu 2p, Cu LMM, and O 1s. In the Cu 2p spectra, two peaks at 932.92 eV and 952.48 eV can be assigned to Cu 2p3/2 Cu0/1+ and Cu 2p1/2 Cu0/1+, respectively. Two peaks at 962.38 eV and 943.98 eV can be assigned to Cu 2p satellite peaks. Additionally, two peaks at 934.8 eV and 954.2 eV are attributed to Cu 2p3/2 Cu2+ and Cu 2p1/2 Cu2+. By comparing the areas of different peaks, it can be determined that the surface of CuO mainly consists of Cu2+, while the surface of Cu/Cu2O primarily consists of Cu0/1+, indicating that electrochemical modulation can reduce most Cu2+ to Cu0/1+ (Figure 2b). Cu LMM XPS spectra were used to determine the distribution and relative abundance of Cu+ and Cu0 in peaks of Cu/Cu2O. The Cu LMM spectrum of CuO shows only the highest peak of Cu2+ of 569.2 eV, whereas the spectrum of Cu/Cu2O shows the highest peak of Cu+ of 570.2 eV (Figure 2c), indicating that a reduction reaction occurred on the surface of CuO. Additionally, the O 1s XPS spectra of CuO and Cu/Cu2O deconvoluted into three peaks at 529.86 eV, 530.39 eV, and 531.09 eV, corresponding to the Cu-O bonds in CuO, Cu-O bonds in Cu2O, and oxygen vacancies (OVs), respectively (Figure 2d). To determine the relative amounts of lattice oxygen and oxygen vacancies, the areas of their respective peaks were normalized against the total O 1 s spectral area. Figure 2e show that the oxygen of Cu-O and oxygen of OVs in CuO account for 45.766% and 45.35% of the total oxygen content, respectively. After in situ electrochemical reduction, the content of oxygen of Cu-O decreases to 20.27%, while the content of oxygen of OVs up to 79.72%, indicating the formation of more OVs in Cu/Cu2O. Compared to lattice oxygen, OVs provide a higher electron density, making it easier to adsorb nitrates on the catalyst. These characterization results suggested that Cu/Cu2O with heterogeneous interfaces and oxygen vacancies was successfully prepared through electrochemical reduction.

3.2. Performance of Electrocatalytic Nitrate Reduction to Ammonia

The NRA tests of Cu/Cu2O were evaluated in a three-electrode system (Figure S2). We used UV-Vis and a standard curve to determine the concentrations of NO3−-N, NO2−-N, and NH3-N in the electrolyte after electrocatalysis 20 min (Figure S3). Initially, LSV was conducted in 0.5 M PBS with (100 mg L−1) and without NO3− to evaluate the electrocatalytic reduction of nitrates by the Cu/Cu2O catalyst. The LSV curves of Cu/Cu2O show a significant increase in the current density and a notable decrease in the onset potential upon the addition of NO3−-N (100 mg L−1), suggesting electrocatalytic nitrate reduction to ammonia (NRA) (Figure 3a). Figure 3b shows the NH3 Faradaic efficiency and NH3 yield rate at a range of potentials from −0.4 to −0.8 V (vs. RHE). Among these potentials, the Faradaic efficiency of NH3 follows a volcano-type trend, peaking at 91.1% at −0.6 V (vs. RHE) with a corresponding NH3 yield of 6.01 mg h−1 cm−2 and exhibits a high current density exceeding 100 mA cm−2 (Figure S4). However, as the potential shifts to more negative values (e.g., −0.8 V vs. RHE), the NH3 Faradaic Efficiency drops to 74.386%, primarily due to the competitive HER. The increase in applied voltage enhances the HER, which inhibits nitrate adsorption and consequently reduces the ammonia selectivity of Cu/Cu2O. Figure 3c shows that the NO3−-N conversion initially increases with potential and reaches a maximum of 96.52% at −0.6 V (vs. RHE). Additionally, Figure 3d illustrates the temporal changes in NO3−-N, NO2−-N, and NH3-N during the NRA process. NO3−-N is almost entirely converted to NH3-N with minimal NO2−-N byproduct formation, which first increases and then gradually decreases over time. After 120 min, the concentrations of produced NO2−-N and remaining NO3−-N are below the WHO’s international drinking water standards. For Cu/Cu2O, such a NH3 yield rate, NH3 Faradaic efficiency, and current density outperform many catalysts in NRA (Table S1).
To objectively evaluate the electrocatalytic stability of Cu/Cu2O and understand the changes in catalyst activity during the reaction process, a series of characterizations were performed to monitor the morphological and chemical composition changes in the catalyst before and after the nitrate reduction reaction (NRA) over 120 min. After 120 min of reaction, the morphology of the catalyst did not show significant changes, with its rough surface and array structure still clearly observable (Figure S5). Significant differences were observed in the XRD patterns, with signals related to Cu2O almost disappearing, and only the metallic copper (PDF #70-3038) reflection peaks present in the sample after 120 min of the NRA reaction (Figure S6a). Changes before and after the reaction were not evident in the Cu 2p spectra since the positions of Cu+ and Cu0 peaks are indistinguishable in Cu 2p (Figure S6b). Therefore, a precise analysis was conducted using Cu LMM under the same conditions. The Cu LMM peak area indicates an increase in Cu0 on the Cu/Cu2O surface after 120 min of NRA, suggesting that some Cu+ continues to reduce to Cu0 during the reaction. However, the phase of the heterogeneous interface remains unchanged, and only the proportions of Cu0 and Cu+ vary (Figure S6c). The O 1 s spectra reveal that the oxygen peak does not change significantly before and after the NRA reaction, even with an increase in oxygen vacancy proportion after 120 min of NRA (Figure S6d–e), indicating that the NRA reaction does not affect the distribution and proportion of oxygen vacancies. This indirectly proves the good cycling stability of the material. To verify this hypothesis, we conducted 10 consecutive cycling tests at −0.6 V (vs. RHE). As shown in Figure 3e, after ten cycles, the Faradaic efficiency showed slight variations, and the ammonia production rate decreased compared to the initial cycles but remained at a relatively high level. The NO3−-N conversion and NH3 selectivity of Cu/Cu2O remained at high levels, although the NO3−-N conversion decreased with increasing cycle number (Figure 3f). Overall, Cu/Cu2O exhibits good cycling stability.

3.3. Mechanism Analysis

To better understand how heterogeneous interfaces and oxygen vacancies affect NRA activity, a comparative evaluation of NRA performance was conducted. The analysis focused on samples such as Cu/Cu2O, CuO, and the CF substrate, all tested under the same conditions. The LSV curves show that the current density of Cu/Cu2O was close to that of CuO, maintaining a high current density, indicating that the formed Cu/Cu2O retains the advantage of high electron transfer efficiency of CuO (Figure 4a). As shown in Figure 4b, the NO3− conversion, NH3 FE, and NH3 yield rate of Cu/Cu2O are significantly higher than those of CuO, measuring 90.9%, 73.26%, and 4.916 mg h−1 cm−2 under −0.6 V (vs. RHE). The very low NH3 yield rate observed with bare CF as the electrode indicates that the catalytic NRA activity mainly stems from Cu/Cu2O (Figure 4c). Additionally, testing Cu/Cu2O in 0.5M PBS without NO3−-N confirmed that external environmental factors did not influence the experimental results (Figure 4d).
We established an equivalent circuit model to assess the ease of hydrogen adsorption (*H) on Cu/Cu2O during the reaction process and its impact on the NRA reaction. Generally, water splitting reactions can be divided into two basic steps: the Volmer step (H2O + M + e−→ M-H* + OH−) and the Heyrovsky step (H2O + M-H* + e− → M + H2 + OH−) [33]. In the Bode plot, the intensity of the phase angle peak signifies the charge transfer rate at the reaction interface, while the frequency range of the phase angle peak indicates the dominant step in the water decomposition reaction. Typically, the low-frequency and mid-frequency ranges in the Bode plot correspond to the Volmer and Heyrovsky steps, respectively [34,35,36]. Compared with CF and CuO, Cu/Cu2O moves the phase angle towards low frequency, indicating that Cu/Cu2O can significantly inhibit the Heyrovsky step and easily generate *H (Figure 4e). EIS results indicate that the diameter of the semicircle, which represents the charge transfer resistance, is lower for Cu/Cu2O compared to CuO. This suggests that the heterogeneous interface of Cu/Cu2O has more active sites, which reduces the overall electron transfer resistance from NO3− to NH3. In addition, using bare CF, the resistance is large, indicating that the advantages of small resistance mainly come from the Cu/Cu2O materials themselves (Figure 4f). In addition, it can be seen from Figure S8 that CuO accumulates more nitrite than Cu/Cu2O in the same period, which also indicates that Cu/Cu2O can easily produce adsorbed hydrogel (*H) for the reduction of nitrite and its intermediates.
According to the above results, the electrocatalytic reduction of the nitrate to ammonia reaction pathway in Cu/Cu2O can be described as a series of adsorption and reduction steps. Under reducing potential, Cu/Cu2O as a dual active site adjusts the adsorption energy of key nitrogen intermediates. OVs can reduce the N-O bond energy, which is more conducive to the adsorption of NO3− on the Cu/Cu2O [28,37,38]. H2O molecules adsorbed on Cu0/1+ sites are more easily reduced to form active adsorbed hydrogen (*H). The production of adsorbed hydrogen (*H) can allow nitrite and intermediates to be reduced within a short period of time. The synergistic effect of oxygen vacancy defects and heterogeneous interfaces enables Cu/Cu2O to exhibit excellent ammonia production rates and ammonia selectivity (Figure 4g).

4. Conclusions

In this study, we introduce a novel Cu/Cu2O catalyst created through in situ electrochemical control, demonstrating excellent NRA performance with the NH3 yield rate of 6.01 mg h−1 cm−2, NH3 Faradaic efficiency of 91.1% and NO3− conversion of 96.52%. The favorable electrochemical performance was attributed to the synergistic effect of heterogeneous interfaces and plentiful oxygen vacancies. These results also confirm that fabricating defects and heterogeneous interfaces via in situ electrochemical reduction methods is both straightforward and effective. This research could pave the way for the rational design of defective electrocatalysts with optimal performance and functionality for ammonia electrosynthesis and other applications.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/en17174467/s1, Figure S1. EDX spectrum of the CuO and Cu/Cu2O; Figure S2. Schematic diagram for electrocatalytic NRA measurement; Figure S3. Calibration curve for calculating the concentration of (a) NO3−-N, (b) NO2−-N and (c) NH3; Figure S4. The i-t curves of Cu/Cu2O measured for 2 h under various applied potentials; Figure S5. SEM images of the Cu/Cu2O after electrochemical NRA measurement; Figure S6. (a) XRD patterns, (b) Cu 2p survey spectra, (c) Cu LMM XPS spectrum, (d) O 1s XPS spectra. (e) the relative contents of lattice oxygen and defective oxygen in Cu/Cu2O after electrochemical NRA measurement; Figure S7. (a) NH3 yield rate and Faradaic efficiency of NH3 over CuO-2.0-150, CuO-2.5-150, CuO-3.0-150, CuO-3.5-150 and CuO-4.0-150 under −0.6 V vs. RHE in 1 h; Figure S8. The concentration of nitrite in the electrolyte varies over different time periods; Table S1. The comparison of electrochemical nitrate reduction activity between the Cu/Cu2O and some other reported electrocatalysts. References [39,40,41,42] are cited in Supplementary Materials.

Author Contributions

Conceptualization, L.F. and Y.L.; methodology, Y.L.; investigation, Y.L.; data curation, L.F. and Y.L.; writing—original draft, Y.L.; writing—review and editing, L.F.; funding acquisition, L.F. and Y.B. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by National Natural Science Foundation of China (grant number 52370057, 22005348, 42007180).

Data Availability Statement

The data of this study are available from the corresponding author upon reasonable request. The data of this study are not publicly available due to privacy reasons.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Nishina, K. New Ammonia Demand: Ammonia Fuel as a Decarbonization Tool and a New Source of Reactive Nitrogen. Environ. Res. Lett. 2022, 17, 021003. [Google Scholar] [CrossRef]
  2. Liu, X.; Elgowainy, A.; Wang, M. Life Cycle Energy Use and Greenhouse Gas Emissions of Ammonia Production from Renewable Resources and Industrial By-Products. Green Chem. 2020, 22, 5751–5761. [Google Scholar] [CrossRef]
  3. Ye, S.; Chen, Z.; Zhang, G.; Chen, W.; Peng, C.; Yang, X.; Zheng, L.; Li, Y.; Ren, X.; Cao, H. Elucidating the Activity, Mechanism and Application of Selective Electrosynthesis of Ammonia from Nitrate on Cobalt Phosphide. Energy Environ. Sci. 2022, 15, 760–770. [Google Scholar] [CrossRef]
  4. Yang, M.; Jin, Z.; Cao, Z.; Wang, X.; Ma, H.; Pang, H.; Yang, G. Polyoxometalates-derived Ternary Metal Oxides Electrocatalyst for N2 Reduction under Ambient Conditions. Tungsten 2024, 6, 428–437. [Google Scholar] [CrossRef]
  5. Tran, N.N.; Escribà-Gelonch, M.; Sarafraz, M.M.; Pho, Q.H.; Sagadevan, S.; Hessel, V. Process Technology and Sustainability Assessment of Wastewater Treatment. Ind. Eng. Chem. Res. 2023, 62, 1195–1214. [Google Scholar] [CrossRef]
  6. Su, J.F.; Kuan, W.-F.; Liu, H.; Huang, C.P. Mode of Electrochemical Deposition on the Structure and Morphology of Bimetallic Electrodes and Its Effect on Nitrate Reduction toward Nitrogen Selectivity. Appl. Catal. B Environ. 2019, 257, 117909. [Google Scholar] [CrossRef]
  7. He, W.; Zhang, J.; Dieckhöfer, S.; Varhade, S.; Brix, A.C.; Lielpetere, A.; Seisel, S.; Junqueira, J.R.; Schuhmann, W. Splicing the Active Phases of Copper/Cobalt-Based Catalysts Achieves High-Rate Tandem Electroreduction of Nitrate to Ammonia. Nat. Commun. 2022, 13, 1129. [Google Scholar] [CrossRef]
  8. Wu, Y.; Jiang, Z.; Lin, Z.; Liang, Y.; Wang, H. Direct Electrosynthesis of Methylamine from Carbon Dioxide and Nitrate. Nat. Sustain. 2021, 4, 725–730. [Google Scholar] [CrossRef]
  9. Wang, Y.; Wang, C.; Li, M.; Yu, Y.; Zhang, B. Nitrate Electroreduction: Mechanism Insight, in Situ Characterization, Performance Evaluation, and Challenges. Chem. Soc. Rev. 2021, 50, 6720–6733. [Google Scholar] [CrossRef]
  10. Jing, H.; Long, J.; Li, H.; Fu, X.; Xiao, J. Computational Insights on Potential Dependence of Electrocatalytic Synthesis of Ammonia from Nitrate. Chin. J. Catal. 2023, 48, 205–213. [Google Scholar] [CrossRef]
  11. Fang, L.; Wang, S.; Lu, S.; Yin, F.; Dai, Y.; Chang, L.; Liu, H. Efficient electroreduction of nitrate via enriched active phases on copper-cobalt oxides. Chin. Chem. Lett. 2024, 35, 108864. [Google Scholar] [CrossRef]
  12. Dortsiou, M.; Kyriacou, G. Electrochemical Reduction of Nitrate on Bismuth Cathodes. J. Electroanal. Chem. 2009, 630, 69–74. [Google Scholar] [CrossRef]
  13. Lim, J.; Liu, C.-Y.; Park, J.; Liu, Y.-H.; Senftle, T.P.; Lee, S.W.; Hatzell, M.C. Structure Sensitivity of Pd Facets for Enhanced Electrochemical Nitrate Reduction to Ammonia. ACS Catal. 2021, 11, 7568–7577. [Google Scholar] [CrossRef]
  14. Deng, X.; Yang, Y.; Wang, L.; Fu, X.-Z.; Luo, J.-L. Metallic Co Nanoarray Catalyzes Selective NH3 Production from Electrochemical Nitrate Reduction at Current Densities Exceeding 2 A cm−2. Adv. Sci. 2021, 8, 2004523. [Google Scholar] [CrossRef] [PubMed]
  15. Fan, X.; Xie, L.; Liang, J.; Ren, Y.; Zhang, L.; Yue, L.; Li, T.; Luo, Y.; Li, N.; Tang, B. In Situ Grown Fe3O4 Particle on Stainless Steel: A Highly Efficient Electrocatalyst for Nitrate Reduction to Ammonia. Nano Res. 2022, 15, 1–6. [Google Scholar] [CrossRef]
  16. Murphy, E.; Liu, Y.; Matanovic, I.; Rüscher, M.; Huang, Y.; Ly, A.; Guo, S.; Zang, W.; Yan, X.; Martini, A. Elucidating Electrochemical Nitrate and Nitrite Reduction over Atomically-Dispersed Transition Metal Sites. Nat. Commun. 2023, 14, 4554. [Google Scholar] [CrossRef]
  17. Murphy, E.; Liu, Y.; Sun, B.; Chen, Y.-H.; Guo, S.; Atanassov, P. Atomically Dispersed Metal–Nitrogen–Carbon Catalysts for Electrochemical Nitrogen Transformations to Ammonia and Beyond. ACS Catal. 2024, 14, 9797–9811. [Google Scholar] [CrossRef]
  18. Xiong, Y.; Wang, Y.; Zhou, J.; Liu, F.; Hao, F.; Fan, Z. Electrochemical Nitrate Reduction: Ammonia Synthesis and the Beyond. Adv. Mater. 2024, 36, 2304021. [Google Scholar] [CrossRef]
  19. Sagar, P.; Arun Kumar, N.S.; Shreenivasa, L.; Srinivasa, N.; De, D.; Yogeeshwari, R.T.; Siddaramanna, A. Citric Acid Assisted One-Pot Approach to Synthesize CuO, CuO/Cu2O, Cu/Cu2O, and Metallic Cu: Potential Electrocatalyst for Enhanced OER. Ionics 2023, 29, 711–719. [Google Scholar] [CrossRef]
  20. Teng, M.; Ye, J.; Wan, C.; He, G.; Chen, H. Research Progress on Cu-Based Catalysts for Electrochemical Nitrate Reduction Reaction to Ammonia. Ind. Eng. Chem. Res. 2022, 61, 14731–14746. [Google Scholar] [CrossRef]
  21. Zhou, B.; Zhan, G.; Yao, Y.; Zhang, W.; Zhao, S.; Quan, F.; Fang, C.; Shi, Y.; Huang, Y.; Jia, F. Renewable Energy Driven Electroreduction Nitrate to Ammonia and In-Situ Ammonia Recovery via a Flow-through Coupled Device. Water Res. 2023, 242, 120256. [Google Scholar] [CrossRef] [PubMed]
  22. Martínez, J.; Ortiz, A.; Ortiz, I. State-of-the-Art and Perspectives of the Catalytic and Electrocatalytic Reduction of Aqueous Nitrates. Appl. Catal. B Environ. 2017, 207, 42–59. [Google Scholar] [CrossRef]
  23. Peel, J.W.; Reddy, K.J.; Sullivan, B.P.; Bowen, J.M. Electrocatalytic Reduction of Nitrate in Water. Water Res. 2003, 37, 2512–2519. [Google Scholar] [CrossRef]
  24. Zhao, Y.; Liu, Y.; Zhang, Z.; Mo, Z.; Wang, C.; Gao, S. Flower-like Open-Structured Polycrystalline Copper with Synergistic Multi-Crystal Plane for Efficient Electrocatalytic Reduction of Nitrate to Ammonia. Nano Energy 2022, 97, 107124. [Google Scholar] [CrossRef]
  25. Zhao, J.; Shen, Z.; Yu, J.; Guo, Y.; Mushtaq, M.A.; Ding, Y.; Song, Z.; Zhang, W.; Huang, X.; Li, Y.; et al. Constructing Cu-CuO Heterostructured Skin on Cu Cubes to Promote Electrocatalytic Ammonia Production from Nitrate Wastewater. J. Hazard. Mater. 2022, 439, 129653. [Google Scholar] [CrossRef] [PubMed]
  26. Wang, Q.; Lei, Y.; Wang, D.; Li, Y. Defect Engineering in Earth-Abundant Electrocatalysts for CO2 and N2 Reduction. Energy Environ. Sci. 2019, 12, 1730–1750. [Google Scholar] [CrossRef]
  27. Li, X.; Liu, X.; Liu, C.; Zeng, J.; Qi, X. Co3O4/stainless Steel Catalyst with Synergistic Effect of Oxygen Vacancies and Phosphorus for Overall Water Splitting. Tungsten 2023, 5, 100–108. [Google Scholar] [CrossRef]
  28. Daiyan, R.; Tran-Phu, T.; Kumar, P.; Iputera, K.; Tong, Z.; Leverett, J.; Khan, M.H.A.; Esmailpour, A.A.; Jalili, A.; Lim, M. Nitrate Reduction to Ammonium: From CuO Defect Engineering to Waste NOx-to-NH3 Economic Feasibility. Energy Environ. Sci. 2021, 14, 3588–3598. [Google Scholar] [CrossRef]
  29. Wang, Z.; Richards, D.; Singh, N. Recent Discoveries in the Reaction Mechanism of Heterogeneous Electrocatalytic Nitrate Reduction. Catal. Sci. Technol. 2021, 11, 705–725. [Google Scholar] [CrossRef]
  30. Wang, H.; Guo, Y.; Li, C.; Yu, H.; Deng, K.; Wang, Z.; Li, X.; Xu, Y.; Wang, L. Cu/CuOx In-Plane Heterostructured Nanosheet Arrays with Rich Oxygen Vacancies Enhance Nitrate Electroreduction to Ammonia. ACS Appl. Mater. Interfaces 2022, 14, 34761–34769. [Google Scholar] [CrossRef]
  31. Fang, L.; Wang, S.; Song, C.; Lu, S.; Yang, X.; Qi, X.; Liu, H. Boosting Nitrate Electroreduction to Ammonia via in Situ Generated Stacking Faults in Oxide-Derived Copper. Chem. Eng. J. 2022, 446, 137341. [Google Scholar] [CrossRef]
  32. Shi, Y.; Li, Y.; Li, R.; Zhao, X.; Yu, Y.; Yang, M. In-Situ Reconstructed Cu/Cu2O Heterogeneous Nanorods with Oxygen Vacancies for Enhanced Electrocatalytic Nitrate Reduction to Ammonia. Chem. Eng. J. 2024, 479, 147574. [Google Scholar] [CrossRef]
  33. Liang, S.; Teng, X.; Xu, H.; Chen, L.; Shi, J. H* Species Regulation by Mn-Co(OH)2 for Efficient Nitrate Electro-Reduction in Neutral Solution. Angew. Chem. 2024, 136, e202400206. [Google Scholar] [CrossRef]
  34. Fan, K.; Xie, W.; Li, J.; Sun, Y.; Xu, P.; Tang, Y.; Li, Z.; Shao, M. Active Hydrogen Boosts Electrochemical Nitrate Reduction to Ammonia. Nat. Commun. 2022, 13, 7958. [Google Scholar] [CrossRef] [PubMed]
  35. Xu, H.; Xu, G.; Huang, B.; Yan, J.; Wang, M.; Chen, L.; Shi, J. Zn-Organic Batteries for the Semi-Hydrogenation of Biomass Aldehyde Derivatives and Concurrently Enhanced Power Output. Angew. Chem. 2023, 135, e202218603. [Google Scholar] [CrossRef]
  36. Ma, M.; Yu, H.; Deng, L. Interfacial Engineering of Heterostructured Carbon-supported Molybdenum Cobalt Sulfides for Efficient Overall Water Splitting. Tungsten 2023, 5, 589–597. [Google Scholar] [CrossRef]
  37. Fang, L.; Lu, S.; Wang, S.; Yang, X.; Song, C.; Yin, F.; Liu, H. Defect Engineering on Electrocatalysts for Sustainable Nitrate Reduction to Ammonia: Fundamentals and Regulations. Chem.–Eur. J. 2024, 30, e202303249. [Google Scholar] [CrossRef]
  38. Xu, Y.; Ren, K.; Ren, T.; Wang, M.; Wang, Z.; Li, X.; Wang, L.; Wang, H. Ultralow-Content Pd in-Situ Incorporation Mediated Hierarchical Defects in Corner-Etched Cu2O Octahedra for Enhanced Electrocatalytic Nitrate Reduction to Ammonia. Appl. Catal. B Environ. 2022, 306, 121094. [Google Scholar] [CrossRef]
  39. Fu, Y.; Wang, S.; Wang, Y.; Wei, P.; Shao, J.; Liu, T.; Wang, G.; Bao, X. Enhancing Electrochemical Nitrate Reduction to Ammonia over Cu Nanosheets via Facet Tandem Catalysis. Angew. Chem. Int. Ed. 2023, 62, e202303327. [Google Scholar] [CrossRef]
  40. Jiang, M.; Zhu, Q.; Song, X.; Gu, Y.; Zhang, P.; Li, C.; Cui, J.; Ma, J.; Tie, Z.; Jin, Z. Batch-Scale Synthesis of Nanoparticle-Agminated Three-Dimensional Porous Cu@Cu2O Microspheres for Highly Selective Electrocatalysis of Nitrate to Ammonia. Environ. Sci. Technol. 2022, 56, 10299–10307. [Google Scholar] [CrossRef]
  41. Chen, G.-F.; Yuan, Y.; Jiang, H.; Ren, S.-Y.; Ding, L.-X.; Ma, L.; Wu, T.; Lu, J.; Wang, H. Electrochemical Reduction of Nitrate to Ammonia via Direct Eight-Electron Transfer Using a Copper–Molecular Solid Catalyst. Nat. Energy 2020, 5, 605–613. [Google Scholar] [CrossRef]
  42. Cheng, X.; He, J.; Ji, H.; Zhang, H.; Cao, Q.; Sun, W.; Yan, C.; Lu, J. Coordination Symmetry Breaking of Single-Atom Catalysts for Robust and Efficient Nitrate Electroreduction to Ammonia. Adv. Mater. 2022, 34, 2205767. [Google Scholar] [CrossRef] [PubMed]
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Figure 1. (a) Scheme for the fabrication and nitrate electroreduction of Cu/Cu2O. (b) SEM, (c) TEM, and (d) HETEM images of CuO. (e) SEM, (f) TEM, and (g) HETEM images of Cu/Cu2O. (h) HAADF-STEM elemental mapping images of Cu/Cu2O.
Figure 1. (a) Scheme for the fabrication and nitrate electroreduction of Cu/Cu2O. (b) SEM, (c) TEM, and (d) HETEM images of CuO. (e) SEM, (f) TEM, and (g) HETEM images of Cu/Cu2O. (h) HAADF-STEM elemental mapping images of Cu/Cu2O.
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Figure 2. (a) XRD patterns. (b) Cu 2p survey spectra. (c) Cu LMM XPS spectrum. (d) O 1s XPS spectra. (e) The relative contents of lattice oxygen and oxygen vacancies in CuO and Cu/Cu2O.
Figure 2. (a) XRD patterns. (b) Cu 2p survey spectra. (c) Cu LMM XPS spectrum. (d) O 1s XPS spectra. (e) The relative contents of lattice oxygen and oxygen vacancies in CuO and Cu/Cu2O.
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Figure 3. (a) LSV of Cu/Cu2O in 0.5 M PBS with 100 mg L−1 of NO3−-N and without. (b) NH3 yield rate and NH3 Faradaic efficiency over Cu/Cu2O under various voltages in 1 h and (c) conversion of NO3−-N in 2 h. (d) Time dependence test of NO3−-N, NO2−-N, and NH3-N concentration catalyzed by Cu/Cu2O at −0.6 V vs. RHE. (e) FE and NH3 yield rate for ten cycles in 1 h under −0.6 V vs. RHE. (f) Conversion of NO3−-N and selectivity of NH3-N for ten cycles in 2 h under −0.6V vs. RHE.
Figure 3. (a) LSV of Cu/Cu2O in 0.5 M PBS with 100 mg L−1 of NO3−-N and without. (b) NH3 yield rate and NH3 Faradaic efficiency over Cu/Cu2O under various voltages in 1 h and (c) conversion of NO3−-N in 2 h. (d) Time dependence test of NO3−-N, NO2−-N, and NH3-N concentration catalyzed by Cu/Cu2O at −0.6 V vs. RHE. (e) FE and NH3 yield rate for ten cycles in 1 h under −0.6 V vs. RHE. (f) Conversion of NO3−-N and selectivity of NH3-N for ten cycles in 2 h under −0.6V vs. RHE.
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Figure 4. (a) LSV curves of CuO and Cu/Cu2O. (b) The comparisons of NO3−-N conversion, NH3-N selectivity, and NH3 FE of CuO and Cu/Cu2O at −0.6 V vs. RHE. (c) NH3 yield of the Cu foam, CuO, and Cu/Cu2O at −0.6 V vs. RHE in 1 h. (d) NH3 yield of the Cu/Cu2O in 0.5 M PBS with and without 100 mg L−1 NO3−. (e) EIS spectra and dashed lines represent the variation in frequency (f) Bode plot of Cu foam, CuO, and Cu/Cu2O at −0.6 V (vs. RHE) in a 0.5M PBS with 100 mg L−1 nitrate. (g) Schematic illustration showing the NRA reaction pathway over the Cu/Cu2O.
Figure 4. (a) LSV curves of CuO and Cu/Cu2O. (b) The comparisons of NO3−-N conversion, NH3-N selectivity, and NH3 FE of CuO and Cu/Cu2O at −0.6 V vs. RHE. (c) NH3 yield of the Cu foam, CuO, and Cu/Cu2O at −0.6 V vs. RHE in 1 h. (d) NH3 yield of the Cu/Cu2O in 0.5 M PBS with and without 100 mg L−1 NO3−. (e) EIS spectra and dashed lines represent the variation in frequency (f) Bode plot of Cu foam, CuO, and Cu/Cu2O at −0.6 V (vs. RHE) in a 0.5M PBS with 100 mg L−1 nitrate. (g) Schematic illustration showing the NRA reaction pathway over the Cu/Cu2O.
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MDPI and ACS Style

Li, Y.; Fang, L.; Bai, Y. Harnessing Heterogeneous Interface and Oxygen Vacancy in Cu/Cu2O for Efficient Electrocatalytic Nitrate Reduction to Ammonia. Energies 2024, 17, 4467. https://doi.org/10.3390/en17174467

AMA Style

Li Y, Fang L, Bai Y. Harnessing Heterogeneous Interface and Oxygen Vacancy in Cu/Cu2O for Efficient Electrocatalytic Nitrate Reduction to Ammonia. Energies. 2024; 17(17):4467. https://doi.org/10.3390/en17174467

Chicago/Turabian Style

Li, Yaxuan, Ling Fang, and Yuanjuan Bai. 2024. "Harnessing Heterogeneous Interface and Oxygen Vacancy in Cu/Cu2O for Efficient Electrocatalytic Nitrate Reduction to Ammonia" Energies 17, no. 17: 4467. https://doi.org/10.3390/en17174467

APA Style

Li, Y., Fang, L., & Bai, Y. (2024). Harnessing Heterogeneous Interface and Oxygen Vacancy in Cu/Cu2O for Efficient Electrocatalytic Nitrate Reduction to Ammonia. Energies, 17(17), 4467. https://doi.org/10.3390/en17174467

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