Interfacial engineering of Cu–Fe₂O₃ nanotube arrays with built-in electric field and oxygen vacancies for boosting the electrocatalytic reduction of nitrates

Abstract

The key to enhancing electrocatalytic nitrate reduction to ammonium (ENRA) is to improve the slow mass transfer of nitrates and the effective electron transfer on the catalyst surface. Based on the thermal diffusion theory and electroreduction mechanism, a Cu–Fe₂O₃ nanotube electrocatalyst with enriched oxygen vacancies and a built-in electric field was designed by controlling the heating and electroreduction time. Because of its unique structure, it could induce the generation of a built-in electric field and promote the enrichment of nitrate ions and electron transfer on the catalyst surface. Combined with the oxygen vacancy (OV)-anchoring mechanism, Cu–Fe₂O₃-60 showed remarkable Faraday efficiency (80.1%) and selectivity (88.47%). In addition, even when the reactor was scaled up to a pilot capacity of 180 L, the conversion rate was close to 85%. This work demonstrates that controlling the staggered interface distribution and oxygen vacancy number in metal–semiconductor is an effective way to design high-efficiency electrocatalysts.

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1. Introduction

Nitrate pollution is one of the most urgent environmental problems in the world, especially due to its accumulation in surface water and groundwater, seriously threatening human health.^1–4 The eight-electron transfer reaction of NO₃⁻ conversion to NH₄⁺ is employed not to partially reduce NO₃⁻ into N₂ for purification but to provide an opportunity to convert polluting NO₃⁻ into NH₄⁺, which is an economically competitive product.^5,6 Compared with the traditional commercial technologies,^7–11 the electrocatalytic technology is considered one of the most effective strategies for mitigating nitrate pollution due to its pollution-free process, low energy consumption and high energy efficiency.^12–14

However, as an active but challenging field in current research, electrocatalysis also faces some inevitable difficulties. First, in the eight-electron transfer electrocatalytic nitrate reduction to ammonium, the main competitive side reaction is the hydrogen evolution reaction, which is accompanied by a five-electron transfer reaction that partially reduces NO₃⁻ to N₂.^15,16 Moreover, the yield of ammonium also depends on solutions to key problems, such as the slow mass transfer of nitrate in solution, small concentration gradient near the electrode and weak anchoring on the catalyst surface.^17,18 In this scenario, the core of the technology lies in designing an integrated catalytic system to fully improve the catalytic performance.

As with any typical heterogeneous catalytic reaction, constructing heterogeneous interfaces between the constituent active components to achieve effective electron transfer is crucial in ENRA systems.^19–22 In metal-semiconductor electrocatalysts, the heterogeneous interface connects metals and a semiconductor; this structure, on the one hand, promotes efficient electron transport at the metal–semiconductor interface, and on the other hand, induces charge redistribution to affect the reactive activity.^23–26 Based on these advantages, we believe that this structure will achieve great ENRA performance. Metal–semiconductor electrocatalysts have indeed shown great potential in the ENRA field.^27–29 For example, Yu et al. prepared Co/CoO nanosheet arrays by a thermal reduction method, which utilized the rectification effect of Schottky contact between the metal and semiconductor to construct electron-deficient Co, thereby realizing selective electroreduction of nitrate to ammonium and turning waste into treasure.³⁰ Li et al. utilized the sulfur-diffusion method to construct high-density Ni nanoparticles on nitrogen-rich carbon supports (Ni/NC), which promoted the enrichment and immobilization of all NO_x⁻ ions on the electrode surface, thereby ensuring the ultimate selectivity toward ammonia.³¹ In addition, OVs, the most basic form of defects, have been widely used in the ENRA field.^32–35 For example, OVs in TiO₂ can not only capture nitrate and weaken the N–O bond energy but also inhibit the generation of by-products, thus significantly improving the efficiency of electrocatalytic ammonia production.³⁶ OVs in the amorphous RuO₂ phase effectively regulate the d-band center and hydrogen affinity, thereby reducing the energy of the potential-determining step.³⁷ As we know, the electrochemical reduction of nitrates begins with its initial adsorption on the electrode surface (NO₃⁻(aq) ⇄ NO₃⁻(ads)).³⁸ Thus, OVs can reasonably be considered as “grippers” that can effectively anchor nitrate ions to the metal–semiconductor catalyst. Based on the above description, the design and synthesis of metal–semiconductor electrocatalysts with OVs are expected to promote the electroreduction of nitrates to ammonium.

Herein, Cu–Fe₂O₃-x nanotubes with OVs (labeled as Cu–Fe₂O₃-x) were designed and prepared on three-dimensional Cu foams (CF) and adopted as efficient electrocatalysts for ENRA as these materials exhibit promising advantages with respect to cost, efficiency, stability, and scalability (Fig. S1, S2 and Tables S1, S2, ESI†). The built-in electric field generated by electron transfer at the interface between the metal and semiconductor, as well as the oxygen vacancies on the surface of the semiconductor, promoted ENRA. The OVs in Cu–Fe₂O₃-60 exhibited high adsorption energy for NO₃⁻ and high H₂ generation energy, which inhibited the generation of H₂. This work verifies the effect of built-in electric field and OVs in enhancing nitrate electroreduction both theoretically and experimentally and provides ideas for the development of low-cost, efficient and stable electrocatalysts for full-scale application to achieving energy efficiency, emission reduction and environmental protection.

2. Experimental section

2.1 Chemicals and materials

Sodium hydroxide (NaOH, ≥96.0%), ammonium persulphate ((NH₄)₂S₂O₈, ≥98.0%), iron nitrate nonahydrate (Fe(NO₃)₃·9H₂O, ≥98.0%), ammonium sulfate-¹⁴N ((¹⁴NH₄)₂SO₄, 98.5%), ammonium sulfate-¹⁵N ((¹⁵NH₄)₂SO₄, ≥99 at%, 98.5%), sodium nitrate-¹⁴N (Na¹⁴NO₃, 98.5%), sodium nitrate-¹⁵N (Na¹⁵NO₃, ¹⁵N ≥ 99 at%, 98.5%), maleic acid (C₄H₄O₄, ≥99.0%), deuterium oxide (D₂O, 99 at% D) were bought from commercial sources. Milli-Q water (18.25 MΩ cm⁻¹) was used across all the experiments. Before use, Cu foam (CF, pore density 120 PPI) was ultrasonically rinsed in acetone, ethanol, and deionized water for 15 minutes to completely remove surface impurities and natural oxides.³⁹

2.2 Synthesis of the Cu–Fe₂O₃ nanostructure

The Cu–Fe₂O₃ nanostructure on CF was synthesized via three steps. Based on the method reported previously by our group, Cu(OH)₂ nanowires (NWs) were successfully grown on the surface of CF by in situ oxidation.⁴⁰ The color of the Cu foams changed from orange–red to blue (see Fig. S3, ESI†). The as-prepared Cu(OH)₂ NWs were immersed in a 10 mM Fe³⁺ solution for some time, and a unique Cu(OH)₂–Fe(OH)₃ nanostructure was obtained at room temperature. The color of the sample changed to brown–yellow after washing and drying. The prepared samples were denoted as Cu(OH)₂–Fe(OH)₃-x (x is the immersion time). Then, a heat treatment was carried out under the air for 2 h at 300 °C at a heating rate of 2 °C min⁻¹, after which CuO-Fe₂O₃-x was obtained. The color changed from brown–yellow to dark-red during this step. The Cu–Fe₂O₃-x with OVs were obtained by chronopotentiometric electroreduction performed at the current density of 20 mA cm⁻¹. The color of Cu–Fe₂O₃-x was black (see Fig. S3, ESI†). The details of the samples are listed in Table S3 (ESI†).

3. Results and discussion

3.1 Materials characterization

The Cu–Fe₂O₃-x NTs were prepared by a three-step process (For details, see Fig. 1a and the Experimental section). First, uniform Cu(OH)₂ nanowire arrays were directly grown on the skeleton of the copper foam by a surface oxidation process. The foam was then immersed into a 10 mM Fe³⁺ solution to obtain a unique Cu(OH)₂–Fe(OH)₃-x (x is the immersion time) (Fig. S4, ESI†). Interestingly, the wall thickness of the nanotubes could be regulated by controlling the immersion time (Fig. S4, ESI†). After air heating and electroreduction, Cu–Fe₂O₃-x (with an average length and mass loading of ≈1.3 μm and 0.89 mg cm⁻², respectively) were successively obtained (Fig. 1b and Fig. S5, ESI†). At the same time, by comparing the scanning electron microscopic (SEM) images of Cu–Fe₂O₃-30, 60, and 120, we found that when the immersion time was increased to 120s, the nanotube structure broke and was unfavorable for the catalytic reaction. Therefore, we chose Cu–Fe₂O₃-60 as the experimental material for specific research. As shown in Fig. 1c, the transmission electron microscopic (TEM) images of Cu–Fe₂O₃-60 at different magnifications showed that the inner diameter of the nanotubes, which were composed of nanoparticles, remained at about 190 nm. In addition, the hybridization distribution of the elements in Cu–Fe₂O₃-60 was further confirmed by the corresponding crossing-sectional composition line profiles. As shown in Fig. 1d, in Cu–Fe₂O₃-60, Cu, Fe, and O were evenly distributed in the measured area, which proves that molecular thermal diffusion promoted the hybrid distribution of elements. The elemental hybrid distribution in Cu–Fe₂O₃-60 was additionally confirmed by the element mappings (Fig. 1e–h). As shown in Fig. 1i, the HR-TEM image of Cu–Fe₂O₃-60 clearly showed the 0.208, 0.295, and 0.252 nm lattice spacings corresponding to the plane of Cu(111), Fe₂O₃(220), Fe₂O₃(311), respectively.^41,42 The crystalline phase of the as-prepared sample was characterized using the XRD patterns (Fig. 1j). Except for the diffraction peaks assigned to the Cu (JCPDS No. 04-0836) phase,⁴³ the other diffraction peaks were consistent with those of the standard Fe₂O₃ (JCPDS No. 21-0920) (JCPDS No. 39-1346) phase.⁴⁴ The above results show that Cu–Fe₂O₃-60 nanotubes composed of nano-Cu and nano-Fe₂O₃ were successfully synthesized by the proposed method.

Fig. 1 (a) Schematic of defective Cu–Fe₂O₃ synthesis. (b) The SEM image (c) TEM image, (d) elemental concentration profile images, (e–h) elemental mapping images, (i) HR-TEM image, (j) XRD pattern of Cu–Fe₂O₃-60.

As an electrocatalyst, its surface chemical composition and interface properties would directly affect its catalytic performance; therefore, these characteristics were further analyzed by XPS and EPR. As shown in Fig. 2a and b, charge transfer at the interface of Cu–Fe₂O₃-60 was investigated. First, the typical Cu, Fe 2p XPS spectra of CuO-Fe₂O₃ and Cu–Fe₂O₃-60 were obtained to further clarify the electron redistribution.³⁰ Compared with CuO-Fe₂O₃, Cu–Fe₂O₃-60 had additional main peaks at 932.8 eV and 952.8 eV, which were attributed as the characteristic peaks of Cu 2p_3/2 and Cu 2p_1/2 of Cu⁰, respectively (Fig. 2a).⁴⁵ Compared with Cu (932.4 eV and 952.2 eV for Cu⁰),⁴⁶ the binding energy of Cu⁰ in Cu–Fe₂O₃-60 appeared to have shifted slightly in the positive direction, indicating the decreased electron density of metal Cu in Cu–Fe₂O₃-60 due to electron loss.⁴⁷ Simultaneously, the slight negative shifts (ca. 0.3 eV for Fe 2p_3/2 and 0.4 eV for Fe 2p_1/2) in the binding energy of Fe³⁺ in Cu–Fe₂O₃-60 compared with CuO-Fe₂O₃ (710.7 and 724.3 eV) suggested that Cu–Fe₂O₃-60 had gained electrons and become an electron-rich body on the Fe₂O₃ side (Fig. 2b).^48,49 The O 1s XPS and EPR were examined to confirm the presence of more OVs in Cu–Fe₂O₃-x. The O 1s XPS spectra (Fig. 2c) showed three peaks centered at 530.2, 531.4 and 532.6 eV, corresponding to lattice oxygen (O_L), oxygen vacancies (O_V) and hydroxyl groups (O_H), respectively.⁵⁰ The area ratios of the O_V peak relative to the total area of the O_L, O_V and O_H peaks [SO_V/(SO_L + SO_V + SO_H)] were 11.12% and 34.99% for CuO-Fe₂O₃ and Cu–Fe₂O₃-60, respectively. The larger area percentage at ∼531.4 eV in the Cu–Fe₂O₃-60 spectrum indicates that the concentration of OVs in Cu–Fe₂O₃-60 was much higher than that in CuO-Fe₂O₃ due to the electroreduction treatment. Besides, compared with Cu–Fe₂O₃-30 and Cu–Fe₂O₃-120 after electroreduction, Cu–Fe₂O₃-60 exhibited a stronger EPR signal at g = 2.003, indicating that a higher concentration of OVs in Cu–Fe₂O₃-60 (Fig. 2d).⁵¹ The above results prove that electron transfer from metallic Cu to semiconductor Fe₂O₃ at the interface of Cu–Fe₂O₃-60 and the electroreduction treatment could create much more OVs in Cu–Fe₂O₃-x.⁵² The change in the built-in electric field in Cu–Fe₂O₃-x due to electron transfer was further studied. As shown in Fig. 2e and Fig. S6, (ESI†) we used a Kelvin probe atomic force microscope to analyze the surface charge of Cu–Fe₂O₃-x. Compared with Cu–Fe₂O₃-30 (12.76 mV) and Cu–Fe₂O₃-120 (19.96 mV), the contact potential difference between the internal Cu and Fe₂O₃ heterogeneous interface and Si substrate in Cu–Fe₂O₃-60 (32.62 mV) was more negative (Fig. 2f). In other words, it is logical to believe that the negatively charged surface field on Fe₂O₃ NPs expands by accepting more electrons from Cu NP-based electron donors in Cu–Fe₂O₃-60.

Fig. 2 High-resolution XPS spectra of Cu–Fe₂O₃-60 and CuO-Fe₂O₃. (a) The Cu 2p, (b) Fe 2p, and (c) O 1s spectra. (d) The EPR spectra of Cu–Fe₂O₃-x and CuO-Fe₂O₃. (e) The built-in electric field distribution of Cu–Fe₂O₃-60. (f) Surface potential values extracted across the lines in e.

We directly associate the built-in electric field with the enrichment of nitrate ions near the catalyst. To understand the catalytic enhancement effect of the built-in electric field, we further simulated the nitrate enrichment process using finite element analysis. As shown in Fig. 3a–d and Fig. S7 (ESI†), to quantitatively calculate the influence of the electric field on the concentration of nitrate on the surface, we used a two-dimensional plane model to simulate the enrichment of nitrate ion density near the electrode. Compared with the negligible neutral surface, the charged electrode with a local electric field could greatly increase the nitrate ion density, and the stronger the electric field was, the more obvious the nitrate enrichment effect. More importantly, the nitrate anion density on the simulated heterogeneous interface increased from 1 to 1.87 mM with the introduction of a small number of charges (0.06 C m⁻²), theoretically demonstrating the key role of the built-in electric field in enhancing the enrichment of nitrate anions (Fig. 3e).

Fig. 3 Nitrate distribution on the electrode after introducing a small number of charges: (a) 0 C m⁻², (b) 0.02 C m⁻², (c) 0.04 C m⁻², (d) 0.06 C m⁻². (e) The line graph of surface charge density and surface-enriched nitrate anion density.

3.2 Electrochemical nitrate reduction activity

The ENRA performance of Cu–Fe₂O₃-x was evaluated by using a typical three-electrode system (Fig. S8, ESI†). The concentrations of nitrate, nitrite, and ammonium in the electrolyte before and after the test were determined by colorimetric methods (Fig. S9, ESI†).^53–55 Before the experiment, we measured the electrochemical double-layer capacitance by cyclic voltammetry and then compared the electrochemical surface area (ECSA) of the different catalysts. As shown in Fig. S10 and Table S4 (ESI†), the ECSAs of Cu–Fe₂O₃-30, Cu–Fe₂O₃-60 and Cu–Fe₂O₃-120 were 27.51, 40.53 and 33.91 cm², respectively, which preliminarily reflect the catalytic superiority of Cu–Fe₂O₃-60. Then, LSV measurements of Cu–Fe₂O₃-30, 60, and 120 were performed in a 0.5 M Na₂SO₄ solution with and without 50 ppm NO₃⁻–N (Fig. 4a and Fig. S11, ESI†). The current density increased significantly at −0.3 V vs. RHE with the addition of NO₃⁻, suggesting that NO₃⁻ in the solution participated in the reduction reactions. Thus, the nitrate reduction reactions on Cu–Fe₂O₃-30, 60 and 120 were studied in the potential range from −0.3 to −0.7 V vs. RHE (Fig. S12, ESI†). Under the same potential, the nitrate conversion rate, ammonium selectivity and yield rate of Cu–Fe₂O₃-60 were obviously higher than those of Cu–Fe₂O₃-30 and Cu–Fe₂O₃-120. Based on the above results, Cu–Fe₂O₃-60 was selected for follow-up research. From −0.3 V to −0.7 V vs. RHE, the conversion rate of NO₃⁻ increased gradually, while the Faraday efficiency showed a volcano-shaped curve, which reached a maximum of 80.1% at −0.6 V vs. RHE (Fig. 4b). In addition, Fig. 4c displays the selectivity and yield of ammonium at different potentials. The results show that the optimal selectivity of 88.47% and the yield rate of 0.108 mmol h⁻¹ cm⁻² were achieved at −0.6 V vs. RHE. Meanwhile, the selectivity of NO₂⁻−N and NH₄⁺–N both tended to reach the optimal value at −0.6 V vs. RHE (Fig. S13, ESI†). Therefore, we chose −0.6 V vs. RHE as the operational potential for the ENRA activity test. With the prolongation of the reduction reaction time, the concentration of NO₃⁻–N continuously decreased, while the concentration of NH₄⁺–N increased, which means that NO₃⁻–N was reduced to NH₄⁺–N. At the same time, the concentration of NO₂⁻–N ramped up first and then declined, indicating that the reaction had high selectivity for ammonium (Fig. 4d). Simultaneously, the nitrite selectivity of Cu–Fe₂O₃-30, Cu–Fe₂O₃-60, Cu–Fe₂O₃-120 decreased gradually and tended to a lower value at −0.6 V vs. RHE, which further proved the high selectivity for the reduction of nitrate to ammonium (Fig. S14, ESI†). Moreover, the nitrate conversion and ammonium yield rate of Cu–Fe₂O₃-60 showed no obvious decay after five consecutive recycling tests using the same piece of catalyst, confirming its excellent stability (Fig. 4e). In addition, Cu–Fe₂O₃-60 still retained the original tubular array morphology (Fig. S15, ESI†). At the same time, the XRD and XPS data of the tested samples also showed that the phase of Cu–Fe₂O₃-60 had not changed significantly (Fig. S16, ESI†). Finally, the performance of Cu–Fe₂O₃-30, Cu–Fe₂O₃-120, CuO-Fe₂O₃-60 and Cu NWs was studied and compared with that of Cu–Fe₂O₃-60. As shown in Fig. 4f, the conversion rate of NO₃⁻ and selectivity for ammonium were 91.25% and 60.96% over Cu–Fe₂O₃-30, 92.72% and 65.43% over Cu–Fe₂O₃-120, 75.46% and 49.59% over CuO-Fe₂O₃-60, and 52.35% and 42.96% over Cu NWs, respectively, which were significantly lower than those of Cu–Fe₂O₃-60 (conversion rate of NO₃⁻: 97.33%, selectivity of ammonium: 88.47%). Compared with Cu–Fe₂O₃-60, the yield of ammonium while using Cu–Fe₂O₃-30, Cu–Fe₂O₃-120, CuO-Fe₂O₃-60 and Cu NWs at −0.6 V vs. RHE was also far from satisfactory (Fig. S17, ESI†). Based on the previous evaluation of the built-in electric field and oxygen vacancies in Cu–Fe₂O₃-x, we could conclude that the best catalytic performance of Cu–Fe₂O₃-60 was due to the positive effect of the built-in electric field and oxygen vacancies. To expand this experiment from the laboratory to industrial scale, we constructed a 180 L pilot-scale reactor that used Cu–Fe₂O₃-60 integrated with a titanium plate to convert nitrate to ammonium in simulated wastewater. Fig. S18 (ESI†) shows the physical setup of the reactor, in which the internal circulation was implemented by using a circulating pump to enhance mass transfer to amplify the overall performance of electrocatalysis. As shown in Fig. 5, the concentrate-time curves of nitrate and ammonium were recorded under different current densities. It was found that a conversion rate close to 85% was maintained at the current density of 20 mA cm⁻², which preliminarily supports the application of the catalyst at the industrial scale. The above results show that Cu–Fe₂O₃-60, which exhibits high catalytic activity, selectivity and stability in both experimental and industrial settings, is suitable for large-scale application in ENRA.

Fig. 4 (a) The LSV curves of Cu–Fe₂O₃-60 in 0.5 M Na₂SO₄ with and without 50 ppm NO₃⁻-N. (b) The faradaic efficiency of ammonium and the conversion rate of nitrate over Cu–Fe₂O₃-60. (c) The selectivity and yield rate of ammonium over Cu–Fe₂O₃-60. (d) Concentrate-time curves of nitrate, nitrite, and ammonium over Cu–Fe₂O₃-60 at −0.6 V vs. RHE. (e) The conversion of nitrate and yield rate of ammonium after consecutive recycling test at −0.6 V vs. RHE. (f) The conversion rates of nitrate and selectivity for ammonium over different samples at −0.6 V vs. RHE.

Fig. 5 (a) Schematic of the pilot-scale electrochemical reactor. The concentrate-time curves of (a) nitrate and (b) ammonium over Cu–Fe₂O₃-60. (c) The nitrate conversion rate and ammonium selectivity of Cu–Fe₂O₃-60 under different current densities.

To eliminate possible interferences from the electrocatalyst itself or the environment, the electrochemical measurement was performed in the pure Na₂SO₄ electrolyte (Fig. 6a), and the result showed that the generation of ammonium could be ignored. In addition, ¹⁵N isotope labeling experiments were implemented to verify the sources of ammonium, and the yield rate of ammonium was quantified by the ¹H NMR spectra.^56–59 We carried out electrochemical measurements at −0.6 V vs. RHE for 2.0 h in the solutions with Na¹⁵NO₃ and Na¹⁴NO₃ as the N sources, respectively. As shown in Fig. 6b, when the electrocatalytic reduction was implemented in the solution with Na¹⁵NO₃, the ¹H NMR spectra of the products showed the representative double peaks of ¹⁵NH₄⁺ at δ = 6.97 and 7.09 ppm, and there was no triple peak representing ¹⁴NH₄⁺ at δ = 6.94, 7.03 and 7.12 ppm (Fig. 6b). This result proves that the ammonium produced by electrocatalytic reduction came entirely from nitrate. Maleic acid (C₄H₄O₄) was used as the external standard for quantifying the produced ¹⁵NH₄⁺–N and ¹⁴NH₄⁺–N products (Fig. S19 and S20, ESI†). The standard curve of the integral area against the concentration of NH₄⁺–N was established to determine the concentration of ¹⁵NH₄⁺–N or ¹⁴NH₄⁺–N (Fig. 6c and d). The quantitative ¹H NMR results of ammonium produced were very close to the quantitative results from the colorimetric methods (Table S5, ESI†), which confirms the accuracy of the different quantitative methods.

Fig. 6 (a) The ammonia yield over Cu–Fe₂O₃-60 in the 0.5 M Na₂SO₄ electrolyte with and without NO₃⁻. (b) ¹H NMR spectra of the electrolyte while using ¹⁵NO₃⁻–N and ¹⁴NO₃⁻–N as the nitrogen sources. The standard curves of (c) the integral area of (¹⁴NH₄⁺–N/C₄H₄O₄) against ¹⁴NH₄⁺–N concentration, and (d) the integral area of (¹⁵NH₄⁺–N/C₄H₄O₄) against ¹⁵NH₄⁺–N concentration.

Based on the excellent catalytic performance of Cu–Fe₂O₃-60, the enhancement mechanism of OV and the reaction path of nitrate electroreduction in Cu–Fe₂O₃-60 were explored by the in situ Raman test and theoretical calculations. For comparison, the Fe₂O₃(220) surface without OVs and with OVs were chosen as models (Fig. S21, ESI†). The adsorption energy of NO₃⁻ on Fe₂O₃(220) with OVs was −2.38 eV, which was much higher than that on Fe₂O₃(220) without OVs (−1.02 eV) (Fig. 7a). This result confirmed the key role of OVs in anchoring NO₃⁻. In other words, the existence of OVs promoted the initial anchoring of NO₃⁻ on the catalyst surface, and the strong anchoring of NO₃⁻ on the catalyst surface will inhibit the competitive anchoring of other anions in the solution, thus ensuring the overall reduction reaction process. Hence, the anchoring mechanism of OVs should be considered an important factor that favors the subsequent reduction reaction of NO₃⁻ along with the proton–electron pairs. Additionally, the energy barrier of H₂ formation on Cu–Fe₂O₃-60 with OVs was 1.6 eV, which was higher than that on Cu NWs (1.27 eV), indicating poor HER activity over the Cu–Fe₂O₃ NTs (Fig. 7b). Then, the in situ Raman spectra were recorded to capture the adsorbed intermediates on the electrode.⁶⁰Fig. 7c displays the absorbance spectra from −0.3 to −0.8 V vs. RHE. During electrocatalytic nitrate reduction, an obvious Raman characteristic peak was observed at 1045 cm⁻¹, which was attributed to the stretching vibration of adsorbed NO₃⁻.⁶¹ Surprisingly, a significant Raman peak was observed at 1315–1330 cm⁻¹, which could be designated to ammonia adsorption.⁶² In addition, the characteristic peak observed at 1375 cm⁻¹ could be assigned to the antisymmetric stretching of NO₂⁻ in nitrate during the electrocatalytic nitrate reduction process.⁶¹ Theoretically, the Raman shift of NH₄⁺ is around 1400 cm⁻¹ and 1480 cm⁻¹,⁶³ but its Raman signal could not be detected due to its weak intensity in water. However, colorimetric methods and nuclear magnetic resonance have long been used to prove the existence of NH₄⁺. The schematic of the built-in electric field formation and electrocatalytic reduction is shown in Fig. 7d. When metals and semiconductors are placed together, spontaneous charge directional movement occurs at their interface, thereby resulting in a built-in electric field. As the external driving force of nitrate enrichment, the built-in electric field plays a vital role. Based on the spontaneous electron transfer from Cu to Fe₂O₃, the built-in electric field verified by KPFM promotes the enrichment of NO₃⁻ at the interface, which solves the problem of slow mass transfer of nitrate in the solution. The OVs act as grippers and anchor the NO₃- at the interface, giving rise to the adsorbed nitrate state , which completes the overall reduction reaction due to the action of proton–electron pairs. Based on the above intermediates detected in the in situ Raman spectra and reported in the literature,⁶⁴ we propose the steps of the whole process from the anchoring of OVs to the recovery of OVs after the reduction of nitrate to ammonium (Fig. 7e). The three O atoms in NO₃⁻ are labeled as O1, O2 and O3, respectively. For NO₃⁻ anchoring on the Cu–Fe₂O₃-60 surface with vacancies, O1 of NO₃⁻ fills in the OV site to form . The N–O3 bond is broken by the action of the proton–electron pairs to form and H₂O. Then, by adsorbing a proton to couple with an electron transfer, the N–O2 bond in is broken, and is converted to H₂NO*. Subsequently, H₂NO* couples with the proton–electron pairs to form NH₄⁺, leaving O1 on the OV site. Finally, the O filling the OV site is reduced to H₂O by protons to restore the oxygen vacancy on the surface. Based on the built-in electric field and OVs of Cu–Fe₂O₃-60, an assembly-line electrocatalytic reduction route for the recovery of the nitrate-anchoring vacancies, thereby achieving a cycle-efficient catalytic effect.

Fig. 7 (a) The calculated adsorption energies of NO₃⁻ on the Fe₂O₃(220) surfaces with and without OVs. (b) The calculated relative reaction energy of H₂ formation on Cu NWs and Cu–Fe₂O₃-60. (c) The in situ Raman spectra of Cu–Fe₂O₃-60. (d) The mechanism diagram. (e) The electrocatalytic reduction path diagram.

4. Conclusions

In summary, we successfully synthesized Cu–Fe₂O₃-60, which exhibits excellent catalytic activity, faradaic efficiency, and selectivity for nitrate electroreduction. The XPS, KPFM and EPR results confirmed the formation of a built-in electric field and OVs. Based on the enhancement effect of the built-in electric field and OVs, we have reasonably proposed an assembly-line electroreduction route for nitrate enrichment via anchoring. Under the optimal potential, the nitrate conversion rate, faradaic efficiency and selectivity for ammonium reached 97.33%, 80.1%, and 88.47%, respectively. The ¹⁵N isotope labeling experiment certified that ammonium was produced solely from nitrate electroreduction. The accuracy of the data was verified mutually by ¹H NMR spectroscopy and colorimetric methods. Based on the results of in situ Raman spectroscopy and the colorimetric methods, we deduced the reaction path. The results of the theoretical calculations and structural model show that an oxygen atom in nitrate fills the OV site, which weakens N–O bonding and promotes the speed-controlling step of nitrate conversion. The subsequent intermediate generates the target ammonium and restores the oxygen vacancies on the surface under the action of proton–electron pairs. The assembly-line-like design for material engineering is conducive to solving the problem of low ammonium generation rate at low concentrations.

Author contributions

Yihong Gao: conceptualization, investigation, formal analysis, data curation, methodology, writing – original draft, writing – review & editing; Kun Huang: conceptualization, investigation, formal analysis, data curation, validation; Chen Yan: theoretical calculation; Hui Zhang: methodology, investigation; Shikuo Li: methodology, investigation; Longjiu Cheng: formal analysis, performed the theoretical calculations; Fangzhi Huang: conceptualization, data curation, formal analysis, funding acquisition, resources, supervision.

Conflicts of interest

There are no conflicts to declare.

Acknowledgements

This work was supported by the National Natural Science Foundation of China (52172174 and 21771001), Key projects of quality engineering teaching and research in Anhui Province (2018jyxm0365), Anhui provincial key research and development plan (202004a07020026), the Program of Anhui Scientific and Technical Leaders Reserve Candidates (2018H168), the Scholar Program for the Outstanding Innovative Talent of College Discipline (Specialty), and open fund for Discipline Construction, Institute of Physical Science and Information Technology, Anhui University. Key Lab of Photovoltaic and Energy Conservation Materials, Chinese Academy of Sciences is gratefully acknowledged by the authors.

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Footnotes

† Electronic supplementary information (ESI) available. See DOI: https://doi.org/10.1039/d2ma00685e

‡ These authors contribute equally to this paper.

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