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Surface dynamic reconstruction of Ni-based catalysts for electrooxidation reaction

Cheng Wang ,  Li Zhou ,  Zhenghao Fei ,  Yanqing Wang ,  Yukou Du

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Citation:  Cheng Wang, Li Zhou, Zhenghao Fei, Yanqing Wang, Yukou Du. Surface dynamic reconstruction of Ni-based catalysts for electrooxidation reaction[J]. Chinese Chemical Letters, 2025, 36(12): 111746. doi: 10.1016/j.cclet.2025.111746 shu

Surface dynamic reconstruction of Ni-based catalysts for electrooxidation reaction

English

  • 1. Introduction

    Ni-based catalysts have been used as promising candidates for various electrooxidation processes, such as the oxygen evolution reaction (OER), urea oxidation reaction (UOR) [1,2]. However, under electrochemical reaction conditions, the surface of Ni-based catalysts may undergo dynamic reconstruction, including atomic rearrangement, valence state changes, thereby altering the chemical ingredient and electronic structure of the surface [3–5]. It is well documented that the surface reconstruction can tailor the type and distribution of active sites, thereby affecting the reaction kinetics [6–8]. By adjusting the composition and structure of Ni-based materials, the active sites can be optimized and the electrocatalytic performance can be enhanced [9,10]. Additionally, the surface reconstruction can also tune the electronic structure of Ni-based catalysts, affecting their interactions with reactants/intermediates [11,12]. By tailoring the chemical state and coordination environment of Ni, the electronic structure can be optimized, the greater catalytic activity and selectivity can be exhibited afterwards [13–15]. Therefore, the surface dynamic reconstruction of Ni-based materials holds great impact on their electrocatalytic performance. For example, during water electrolysis, the surface reconstruction phenomenon of Ni-based materials is crucial for enhancing their electrocatalytic performance [16,17]. In alkaline water electrolysis, Ni-based electrocatalysts, as a substitute for precious metal materials, have relatively high overpotentials [18,19]. However, through surface reconstruction, Ni-based compounds can form more active oxides/hydroxides/oxyhydroxides, significantly improving the activity of the OER [20,21]. This surface reconstruction not only involves chemical changes on the catalyst surface but also includes the modifications to the electronic structure [22–24]. These modifications have a direct impact on the interaction between the catalyst and reaction intermediates, thereby influencing the rate and efficiency of the catalytic reaction [25,26]. Accordingly, enormous endeavors have been dedicated to the investigations on the surface dynamic reconstruction of Ni-based materials, and many resultful strategies have been developed to tailor this surface dynamic reconstruction.

    Specifically, the modified Ni-based materials, such as the CeO2-Ni heterogeneous structure and the effect of Cr doping on Ni3N electrocatalysts, have shown that surface reconstruction can improve electrocatalytic performance. For example, the introduction of CeO2 accelerates the surface reconstruction of Ni-based non-oxides, promoting the development of active hydroxides, and significantly boosting the OER activity [27]. Similarly, Cr atom doping not only regulates the electronic structure of Ni3N but also acts as an oxygenphilic site, promoting the adsorption of oxygen-containing reactant species, thereby expediting the refactoring of Ni3N and improving the activities of HER and OER [28]. Furthermore, interface engineering strategies have also been proven to be effective, where the design of the pre-catalyst structure enables rapid surface self-reconstruction and stabilizes Ni3+ catalysis, thereby enhancing the electrocatalytic performance of the UOR [29,30]. These studies not only reveal the mechanism of surface reconstruction in Ni-based materials but also provide novel concepts and approaches for the design and advancement of electrocatalysts with superior performance. Therefore, the surface reconstruction of Ni-based materials significantly influences their electrocatalytic performance by tailoring the electronic structure and surface chemical states, providing an effective approach to solve energy and environmental issues.

    Although significant progress in tailoring the surface dynamic reconstruction of Ni-based catalysts has been reported, a systematic review of this interesting field has been rarely reported. Therefore, this review timely sums up the effective modulation strategies that boost the reconstructions of Ni-based catalysts to promote electrocatalytic performance during various electrooxidation reactions. As displayed in Fig. 1, the regulation strategies include the surface electrochemical activation, defect engineering, partial dissolution, ionic doping, and heterostructure construction. In addition, the influences of the surface dynamic reconstruction of Ni-based catalysts on their electrocatalytic performance for various electrooxidation reactions are also comprehensively discussed. Through this review, we hope to deepen the understanding of reconstruction chemistry for the benefit of readers that are focusing on the design and synthesis of more efficient Ni-based electrocatalysts.

    Figure 1

    Figure 1.  Schematic illustration of the modulation strategy for reconstructing Ni-based catalysts to enhance electrooxidation reactions.
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    2. Fundamentals of reconstruction

    2.1 Reconstruction phenomena of Ni-based catalysts

    The reconstruction typically refers to the variation of an electrocatalysts under electrochemical process, which is different from the original form in terms of crystalline, component, morphology, and so on. Surface reconstruction of catalysts is the basis of catalytic chemical reactions [31,32]. The surface structure of catalysts determines their catalytic properties and efficiency. By changing the surface structure through reconstruction, catalysts can more effectively adsorb and activate substances during the reaction process and easily desorb the products after the reaction is completed [33–36]. With the rapid advancement in situ detection techniques for the fine structure of catalyst surfaces, the surface dynamic reconstruction process can be clearly observed and the influence of surface reconstruction on electrocatalytic performance are further revealed [37]. It is unveiled that a reconstructed catalyst will generate more active reaction sites, consequently, enhance the reaction activity and accelerate the reaction rate [38,39]. In addition, it is widely recognized that the surface reconfiguration of a catalyst alters the structure of surface chemical bonds, reduces the rate of side reactions, and improves the selectivity of reaction products [40,41]. Furthermore, the surface reconstruction can make the chemical bonds on the catalyst surface reversible, consequently prolonging the operational lifespan of the catalyst.

    As well known, Ni-based catalysts can easily reconstruct and generate various species in chemical reactions, which will exert a substantial influence on their catalytic performance. For one thing, Ni-catalysts can undergo transitions between different oxidation states such as Ni(0), Ni(Ⅰ), Ni(Ⅱ). during the reaction process [42,43]. These Ni species with different oxidation states exhibit varying catalytic activity and selectivity [44]. For another, Ni can coordinate with reactants, intermediates, and additives to form different complexes. Changes in coordination environment can affect the electronic properties and spatial structure of Ni, thereby affecting catalytic performance [45]. Furthermore, some reactions involve intermediates involving Ni, such as Ni-C bonds, Ni-H bonds. The formation and reaction properties of these active intermediates also affect the overall catalytic performance. Therefore, the reconstruction behavior of Ni-based catalysts in reactions is complex and requires in-depth research and understanding in conjunction with specific reaction systems [46]. Optimizing the design and reaction conditions of Ni-based catalysts can effectively improve their catalytic performance and selectivity during electrooxidation reactions.

    2.2 Characterizations of reconstruction process

    Regarding monitoring the surface reconstruction process, the in situ/operando technologies play a crucial role. The characterization of surface dynamic reconstruction is an important aspect of understanding the changes and evolution of surfaces, particularly in the fields of material science, nanotechnology, and surface science [47]. Surface dynamic reconstruction refers to the process by which the morphology, chemical composition, and/or structural arrangement of a surface can undergo changes in response to various external or internal factors [48]. First, the changes in surface morphology and roughness over time have been extensively investigated using various techniques, including atomic force microscopy (AFM), scanning tunneling microscopy (STM), and electron microscopy (SEM, TEM) (Fig. 2). These techniques can provide high-resolution, real-time imaging of surface features and their evolution. Second, the spectroscopic techniques, such as in situ X-ray photoelectron spectroscopy (XPS), Auger electron spectroscopy (AES), in situ Raman spectroscopy, in situ X-ray absorption near edge spectroscopy (XANES), extended X-ray absorption fine structure spectroscopy (EXAFS), and in situ infrared (IR) spectroscopy, are used to determine the alterations in the chemical composition and bonding structures on the surface (Fig. 2) [49]. These methods can yield valuable information about the formation, transformation, and adsorption of different chemical species on the surface. Third, the diffraction techniques, such as low-energy electron diffraction (LEED) and in situ X-ray diffraction (XRD), focus on detecting the changes in the atomic-scale structure and ordering of the surface [50,51]. These techniques can reveal the formation, reconstruction, and relaxation of surface structures, as well as the presence of defects and adsorbates. Fourth, the time-resolved techniques, such as time-resolved XPS, time-resolved STM, and ultrafast laser spectroscopy, are employed to study the dynamic processes and the kinetics of surface reconstruction.

    Figure 2

    Figure 2.  Scheme of characterization technologies of reconstruction process.
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    Besides the in-situ electron microscopic, in situ and Operando spectra, electrochemical testing can characterize the in-situ reconstruction process. As well known, the cyclic voltammetry (CV) is a crucial test in electrochemical workstations. By observing the changes in the CV curve, such as changes in peak current and peak potential, changes of the active species in the electrode can be analyzed to infer the in-situ reconstruction process [52]. Additionally, by tracking changes in open circuit potential, it can reflect alterations in the physical and chemical properties of the electrode surface, thereby inferring the in-situ reconstruction process. Furthermore, by analyzing electrochemical impedance spectroscopy (EIS) data, parameters such as electrode interface charge transfer resistance and differential capacitance can be obtained to infer changes in interface structure and reflect the in-situ reconstruction process [53]. By comprehensively utilizing various electrochemical and characterization techniques mentioned above, the in-situ reconstruction process of electrode materials can be comprehensively and deeply studied, providing support for the optimization and application of related electrochemical systems.

    Although the in-situ characterization technologies have been rapidly developed to gain a deeper understanding of the dynamic reconstruction of Ni-based catalysts, they still face sone challenges. The current in situ characterization of surface dynamic reconstruction in Ni-based catalysts primarily faces three major challenges: (1) Insufficient spatiotemporal resolution for atomic-scale dynamic processes, (2) interference from physiochemical environments at surface/interfaces under Operando conditions, and (3) lack of multimodal data correlation analysis. Potential advancements include developing femtosecond-resolution XAFS coupled with environmental transmission electron microscopy (ETEM) techniques, establishing machine learning-assisted real-time analysis systems for synchrotron radiation data, and designing closed-loop characterization platforms integrating microreactors with in situ Raman spectroscopy/mass spectrometry. Such innovations hold promises for overcoming the current technological bottleneck where capture rates for reconstruction intermediates remain below 5%.

    3. Reconstruction strategies for Ni-based electrocatalysts

    3.1 Electrochemical activation

    Electrochemical activation for surface reconstruction refers to a technique used to modify the surface properties of catalysts through electrochemical means [54]. This process can be utilized to enhance various surface properties, such as wettability, corrosion resistance, catalytic activity, or to induce structural changes on the catalyst's surface [55,56]. The general principle behind electrochemical activation for surface reconstruction involves applying an electrical potential or current to the material in an electrolyte solution [57–59]. This electrochemical treatment can trigger various surface modifications, such as the formation or removal of specific surface species, such as oxides, hydroxides, or other compounds and the formation of new crystal phases, grain boundaries [60,61]. The specific electrochemical parameters, such as the applied potential, current density, electrolyte composition, and duration of the treatment, can be carefully controlled to achieve the desired surface modifications [62,63]. The resulting surface properties possess a significant impact on the electrocatalytic performance of catalysts. For example, Xu et al. has designed an electrochemical delithiation LiNiO2 catalyst that takes the full advantage of NiOO*, thereby exhibiting significant OER activity in the absence of Fe [64]. With the electrochemical delithiation proceeds by the CV cycling process, the Ni-rich surface is transformed into NiOOH (Fig. 3a). The characterization of EELS mirrors migration of Ni to the surface of LiNiO2 during more CV cycles (Fig. 3b). The increase of Ni valence state and the decrease of Ni-O bond length with long-term activation cycles, as revealed in Fig. 3c, demonstrating the formation of delithiated-LiNiO2/NiOOH heterojunction, which thus accounts for the enhanced OER activity. It is worth noting that the OER current density of LiNiO2 exhibits an initial increase from 1st to 500th, followed by a subsequent decrease from 500th to 1000th (Fig. 3d), indicating that the double-edged sword effect of activation cycles on the OER performance. Hence, tailoring the electrochemical activation process is also crucial for determining the electrocatalytic performance of catalysts. Besides, Pang and coworkers also employed the electrochemical activation strategy to contribute to the in-situ surface reconstruction of the NiOx microstructure, leading to the formation of crystalline/amorphous NiOx microbelt superstructure with a thicker outer amorphous Ni3+/Ni2+ layer (Fig. 3e) [65]. These studies prove that the electrochemical activation strategy is highly effective for the surface dynamic reconstruction of Ni-based catalysts.

    Figure 3

    Figure 3.  (a) Scheme of the surface reconstruction of LiNiO2. (b) Ni EELS intensity before and after prolonged CV cycling. (c) Ni valence state and Ni-O bond length of different catalysts. (d) CV curves of LiNiO2 with different electrochemical delithiation cycles. Reproduced with permission [64]. Copyright 2020, Wiley Publishing Group. (e) Schematic description of the electrochemical activation induced surface reconstruction of NiOx and the enhanced OER current density after surface reconstruction. Reproduced with permission [65]. Copyright 2022, Elsevier.
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    3.2 Defect engineering

    The surface defects, including vacancies, steps, kinks, and dislocations, can be intentionally introduced into the Ni-based catalyst surface through various techniques, such as ion bombardment, thermal treatment, or chemical etching [66–70]. The introduction and nature of these defects can alter the surface energy and the local electronic structure of the Ni-based catalyst, resulting in alterations to the surface reconstruction [71–73]. Additionally, the presence of defects can create local strain and distortion in the Ni-based catalyst surface, which can drive the surface atoms to rearrange and reconstruct to minimize the overall surface energy [74]. The extent and pattern of surface reconstruction can depend on the type, concentration, and distribution of the introduced defects [75]. Moreover, during catalytic reactions, the Ni-based catalyst surface can undergo dynamic restructuring in response to the reaction environment, such as temperature, pressure, and the presence of reactants or intermediates [76]. The pre-existing defects introduced through surface defect engineering can influence the kinetics and pathways of this surface reconstruction process, leading to different surface structures and compositions.

    The changes in the surface structure and electronic characteristics can influence the adsorption, activation, and reaction of the reactants, as well as the desorption of products, thereby impacting the overall catalytic performance [77]. And the introduction of surface defects can also affect the stability and durability of the Ni-based catalyst under operating conditions. Furthermore, the defects can either enhance or hinder the resistance of the catalyst to sintering or other deactivation processes, depending on the specific defect characteristics and the reaction environment [78]. By carefully engineering the surface defects, researchers can tune the surface reconstruction of Ni-based catalysts and optimize their catalytic performance for various applications.

    For instance, Gao and coworkers synthesized the Ni-Fe layered-double-hydroxides (LDH) with intrinsic oxygen vacancies (VO) (Fig. 4a). In time of the OER process, the intrinsic VO is proved to be effective for boosting the surface reconstruction and forming the p-n interfaces (i.e., γ-Ni-FeLDH/α-Ni-FeLDH) through deprotonation (Figs. 4b and c) [79]. The VO in both surfaces can tailor the electron densities and thus optimizes the free energies of OER pathway (Fig. 4d). Later, Zhao et al. investigated the influences of defects on the reconstruction of mono Ni-BDC (BDC = 1,4-benzenedicarboxylic acid) for the selective electrochemical synthesis of azo compounds, achieving a high Faradaic efficiency of 89.8% and a selectivity of 90.8% in the electrooxidation of 1-methyl-1H-pyrazol-3-amine (Pyr-NH2) to azo compounds [80]. XAS structure and various in situ spectroscopic techniques revealed the dynamic reconstruction of Ni(OH)2 and NiOOH electrochemical potentials, as well as the dynamic phase transitions and local lattice distortions in the Ni-O and Ni-Ni coordination environments at the atomic scale.

    Figure 4

    Figure 4.  (a) Mott–Schottky plots of different catalysts. (b) Schematic diagram of the formation of a p−n interface. (c) Simulated crystal structures of α-Ni-Fe and γ-Ni-Fe/α-Ni-Fe, and (d) the effect of different VO concentrations on the formation energies of γ-Ni-Fe from α-Ni-Fe. Reproduced with permission [79]. Copyright 2021, American Chemical Society.
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    3.3 Partial etching

    Partial etching is beneficial to the reconstruction of catalysts primarily because the etching process generates more catalytic sites and increases the specific surface area, thereby facilitating surface reconstruction of the catalyst [81,82]. Specifically, etching techniques create more active sites by removing part of the material from the catalyst's surface, providing additional reaction sites during catalytic reactions and enhancing the activity of the catalyst [83,84]. Moreover, etching can enlarge the specific surface area, and this enlargement in surface area helps improve the contact area between the catalyst and the reactants, further enhancing catalytic efficiency [85]. These changes collectively accelerate the reconstruction process of the catalyst, allowing it to better perform its catalytic role during reactions.

    Benefitting from these, partial etching techniques have thus been widely used for the modifications of Ni-based catalysts to promote their surface reconstruction to elevate the electrocatalytic performance [86,87]. For instance, Gao and coworkers propose a dual cation etching strategy that utilizes the etching properties of H2O2 to generate abundant cation defects and lattice mismatches on the surface of NiMoO4 (NMO), while tailoring the electronic structure of NMO [14]. In situ Raman experiments have shown that NMO can rapidly form high oxidation state of transition metal hydroxides (NiOOH) during OER process, which contributes to enhance the catalytic performance of NiMoO4 in OER. As shown in Figs. 5a and d, the etched sample has a deeper reconstruction layer, which is due to the corrosion and co-leaching of cations, causing the reconstruction layer to loosen and accelerate the reconstruction process. During the OER process, the LSV curve of NMO treated with 5 µL H2O2 for 30 min (NMO-30M) changes faster than that of NMO and has a lower overpotential (Figs. 5b and e). Figs. 5c and f show the in situ Raman spectra of pure NMO and etched samples, respectively. The results showed that the NMO-30M exhibited two weak vibration bands at 473 and 553 cm-1, belonging to the bending vibration mode of Eg (Ni3+-O) and the stretching vibration mode of A1g (Ni3+-O), indicating the formation of a NiOOH reconstruction layer.

    Figure 5

    Figure 5.  The TEM images of (a) NMO and (d) NMO-30M after self-reconstruction. The LSV curves of (b) NMO and (e) NMO-30M with different scans. In situ Raman spectra of (c) NMO and (f) NMO-30M during OER process. Reproduced with permission [14]. Copyright 2023, Springer.
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    In summary, the partial etching of Ni-based pre-catalysts in time of electrochemical reconstruction impacts the surface restructuring behavior and electrocatalytic performance of the emerging species. Consequently, it is feasible to introduce electrochemically unstable components into Ni-based pre-catalysts to facilitate effective reconstruction. Whereas, ion leaching can potentially compromise the crystal structure of samples, particularly in alkaline solutions. Therefore, the preservation of crystal matrix stability while inducing ion leaching has become a crucial research focus.

    3.4 Ionic doping

    Ionic doping can enhance the catalysts' reconfiguration by introducing oxygen vacancies, adjusting electronic structures, forming solid solution structures, and improving conductivity [88–90], thereby enhancing the activity and selectivity of catalysts and optimizing their catalytic performance. In recent years, ionic doping has now appeared as a potential way to enhance the surface dynamic reconstruction of catalysts [90,91]. For example, Li and coworkers have systematically investigated the influence of ionic doping on the surface dynamic reconstruction of Ni-based catalysts (Fig. 6a) [92]. To be specific, they have constructed a fluorinated Ni3S2 nanoarray with abundant low-crystalline nanosheets. According to detailed electrochemical measurements and characterizations, it is unveiled that the Ni-F bonds could be readily activated with F loss under OER operation, thereby yielding the highly active Ni-OOH species for boosting O*-OOH* step, which is regarded as the rate-determining step of OER. This work demonstrates the significant impact of anionic doping on the promotion of surface dynamic reconstruction of Ni-based catalysts.

    Figure 6

    Figure 6.  (a) Schematic description of the F doping promotes the dynamic reconstruction of Ni3S2 nanoarrays. Reproduced with permission [92]. Copyright 2021, Elsevier. (b, c) In situ Raman of Fe-Ni3S2. Reproduced with permission [63]. Copyright 2023, Wiley Publishing Group. (d) Schematically showing the dynamic reconstruction of multivalent nickel sulfide catalysts. Reproduced with permission [95]. Copyright 2022, Royal Society Chemistry.
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    Besides cationic doping, the anionic doping has also been revealed to be beneficial for promoting the surface dynamic reconstruction of Ni-based catalysts [93,94]. For instance, Zhao et al. have demonstrated that the Fe doping into Ni3S2 could modify the electrocatalyst surface reconstruction (Fig. 6b) [63]. Theoretical calculations demonstrate that the Fe doping can modify the local coordination environment and electronic structure of Ni3S2 to facilitate the self-reconstruction of catalyst to NiOOH at low overpotential (Fig. 6c), thereby significantly decreasing the rate-determining step energy barriers for electrochemical reactions. Zhang et al. revealed that specific Fe substitution enhances the structural elasticity and increases its capacity to obtain additional S vacancies in NiS2 to reduce the applied potential threshold for phase reconfiguration of NiS2 to Ni2S3 (Fig. 6d) [95].

    3.5 Heterostructure construction

    Designing heterostructure by combining two or more different makings to achieve common characteristics has been revealed to be effective for elevating electrocatalytic performance [96–98]. The heterointerface between two different materials can offer extra catalytic active sites and boost the electron transfer, which will further promote the catalytic performance [98,99]. More importantly, it is also unveiled that the formation of heterostructure could boost the reconstruction of pre-catalysts as the effective electron transfer according to the heterointerface could lead to the formation of electron-rich regions, which will promote the surface dynamic reconstruction of catalysts [100,101]. Hence, heterostructure construction has been widely employed to boost the surface dynamic reconstruction of various catalysts, especially for Ni-based materials. For example, Hao et al. constructed a heterostructured Co-Ni-S electrocatalyst with a well-defined heterointerface between Ni3S2 and Co9S8 [102]. It is revealed that the interface induced charge transfer between Ni3S2 and Co9S8 can accelerate the surface dynamic reconstruction. Detailed operando characterizations and theoretical calculations uncovered that the heterointerface involved more defects can lead to more OH- species adsorbed on the electron and benefitted for transforming into highly active NiOOH (Figs. 7a–d), which thus benefited for the enhanced electrocatalytic UOR performance.

    Figure 7

    Figure 7.  (a, b) In situ Raman spectra of Co-Ni-S@NF and Ni-S@NF under urea oxidation. (c, d) The morphology structures of Co-Ni-S@NF after long-term UOR electrocatalysis. Reproduced with permission [102]. Copyright 2022, Royal Society Chemistry. (e) Schematic illustration of the CeO2-promoted surface dynamic reconstruction of Ni-X via the creation of oxygen vacancies and electron transfer. Reproduced with permission [103]. Copyright 2022, American Chemical Society.
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    Gao et al. also demonstrated that the construction of heterointerfaces could boost the surface dynamic reconstruction of Ni-based catalysts [103]. They reported the synthesis of a battery of CeO2-modified Ni-X (X = S, P, and O) heterostructures. The in/ex situ studies identified that the CeO2 modifications on the Ni-X could strengthen the adsorption of OH- on the interfaces, which thus facilitated the surface dynamic reconstruction of Ni-X into the NiOOH and contributed to the outstanding electrocatalytic performance (Fig. 7e).

    To summarize, the interface effects can exert a significant influence on the electronic characters and distribution of active substances in heterostructures, which facilitate the reconstruction process during catalytic reactions. Therefore, investigating the impact of the interface on reconstruction under reaction conditions holds substantial research importance.

    4. Surface dynamic reconstruction of Ni-based catalysts for electrooxidation reaction

    4.1 Oxygen evolution reaction

    The reconstruction of Ni-based catalysts is of great importance to promote OER as it is a pivotal process in electrochemical water splitting and fuel cells, and the performance of the catalyst directly has an impact on the activity and efficiency [104,105]. During the OER, the surface of Ni-based catalysts may undergo phase transitions or transformations between different chemical forms, which can generate more active sites and significantly improve catalytic activity [106]. In addition, Ni can exist in various oxidation states during the OER process, such as Ni2+, Ni3+, and Ni4+. During the reconstruction process, the alteration in the oxidation state of Ni helps to improve the electronic conductivity and catalytic activity of the catalyst [107]. Moreover, the reconstruction of catalysts is often accompanied by structural changes at the nanoscale, which can increase the specific surface area, thereby improving the contact between reactants and reactants and helping to increase reaction rates [108]. Therefore, the keen appreciation of the surface dynamic reconstruction of Ni-based catalysts during OER conditions is of vital importance for guiding the further design of more efficient catalysts, which have thus stimulated great attention [109]. With the fast advancement of in/ex situ technologies, a deep understanding on the surface dynamic reconstruction of Ni-based catalysts is obtained. For instance, Wei et al. synthesized the Ni5P4@FeP nanoarrays to serve as advanced OER electrocatalysts [110]. The Ni5P4@FeP promptly restructured into NiFe2O4 during anodic scanning, while the inherent instability of the amorphous NiFe2O4 resulted in partial reconstruction into Ni/FeOOH at high potential range (Figs. 8a–c). The formed Ni/FeOOH@NiFe2O4, identified as the true active species with high structural reversibility, exhibited excellent alkaline OER activities with ultralow overpotentials of 205 mV (10 mA/cm2) and 242 mV (100 mA/cm2), respectively. This research revealed the dynamic structural conversion of hybrid phosphide pre-catalyst into activated catalysts with excellent performance (Fig. 8d), which provide deep understandings on the reconstruction of Ni-based catalysts during OER conditions.

    Figure 8

    Figure 8.  In situ Raman spectra of (a) FeP and (b) Ni5P4 in the 40th CV cycle. (c) Representative Raman spectra of different catalysts at 1.57 V (vs. RHE). (d) Schematically showing the dynamic surface reconstruction in Ni5P4@FeP pre-catalyst. Reproduced with permission [110]. Copyright 2022, Elsevier.
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    Based on the deep understandings on the reconstruction mechanism, varieties of available tactics have been proposed to guide the reconstruction of Ni-based catalysts for realizing superior OER performance. For instance, Tian et al. designed a surface electronic regulation strategy to transform the spin configuration of metal ions in Fe5Ni4S8 by modifying with electron-absorbing dodecyl sulfate (SDS) groups [111]. The introduction of SDS groups results in electron depletion in Fe within Fe5Ni4S8, which occurs attributed to the "flee" of electrons from the 3d orbitals of iron, generating farther alterations in the spin configuration (Figs. 9a and b). According to the in situ XPS spectra (Figs. 9c–f) and EIS plots (Figs. 9g and h), it is indicated that the high-spin configuration of Fe in Fe5Ni4S8–400 facilitates the amassing of surface OH-, expedites the electron transfer, and enhances the kinetics of the reconstruction reaction. DFT calculations show that the high-spin state of Fe exhibits a decreased d-band center, which favors the weakening of the adsorption of oxygen-containing intermediates, promoting the fast liberation of active intermediates and therefore boosting the electrocatalytic OER activity. As a result, the modified catalyst exhibits an ultralow overpotential of 245 mV at 10 mA/cm2 (Fig. 9i), along with long-term stability at 100 mA/cm2. Their findings reveal that the high-spin state of Fe promotes rapid reconstruction of the nickel pyrite surface for efficient OER, which paves a new way for guiding the surface reconstruction of Ni-based catalysts.

    Figure 9

    Figure 9.  (a) Schematic diagram of the high-spin state (HS) transition of Ni3+ to the low-spin state (LS) of Ni2+ and the LS transition of Fe2+ to the HS of Fe3+. (b) Magnetic hysteresis (M-H) loops of FNS and FNS-400. (c, d) High-resolution Ni 2p3/2 XPS spectra of different catalysts at various potentials. (e, f) O 1s XPS spectra of different catalysts at various potentials. (g, h) The Bode phase plots of different catalysts at various voltages. (i) OER polarization curves of different catalysts. Reproduced with permission [111]. Copyright 2024, Wiley Publishing Group.
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    4.2 Urea oxidation reaction

    Urea electrolysis technology can achieve energy-efficient hydrogen production while simultaneously treating urea-rich wastewater. The UOR involving six-electron transfer plays a crucial role as anodic half-reactions in sustainable development of energy conversion, such as direct urea/urine fuel cells and urea-assisted water electrolysis for hydrogen production [112,113]. The standard thermodynamic potential of the coupled UOR and HER is only 0.37 V (vs. RHE), which is observably lower than the 1.23 V (vs. RHE) required for electrolysis of water [114–116]. Hence, UOR has great potential to substitute the traditional OER at the anode, reducing the voltage input for hydrogen production. Ni-based electrocatalysts are commonly used for alkaline UOR reactions. Under normal conditions, the Ni-based catalysts experience surface reconstruction to form NiOOH as the active species during the UOR process, owing to the anodic potential and the presence of OH- in the electrolyte [117]. However, its electrochemical active phase (γ-NiOOH) is limited in its application because of the scarcity of active sites. Therefore, rational design and modification over Ni-based catalysts is highly imperative. For instance, Jiao and coworkers reported a dual-doping strategy to enhance the electrochemical UOR performance [118]. Their findings showed that the dual-active-site doping strategy of heteroatom and oxygen vacancy in Ni(OH)2 significantly promoted the UOR performance as the V doping provided more exposed active sites, while the introduction of oxygen vacancies synergistically lowered the thermodynamic barrier of UOR, leading to significantly improved UOR activity. In situ Raman confirmed the surface electrochemical reconstruction to the active γ-NiOOH phase under electrochemical conditions (Figs. 10a–d). DFT studies investigated the urea dissociation mechanism on different catalyst surfaces, revealing the synergistic role of V doping and oxygen vacancies in the UOR dissociation process (Figs. 10e and f). The doping of V exposed more intrinsic active sites on γ-NiOOH and modulated the electronic state of γ-NiOOH.

    Figure 10

    Figure 10.  In situ Raman spectra of (a) V0 and (b) V2 from circuit potential (OCP) to 1.6 V (vs. RHE). (c) The representative Raman spectra of V0 and V2 at 1.60 V (vs. RHE). (d) The peak intensity ratio of δ(Ni-O) to ν(Ni-O) of V0 and V2. The ΔG profiles of the proposed UOR pathway at (e) γ-NiOOH and (f) Ovac-V-γ-NiOOH. Reproduced with permission [118]. Copyright 2022, Wiley Publishing Group.
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    While the generated NiOOH is the highly active species for the OER as well, which is an undesirable side reaction for UOR. Moreover, OER can lead to the over-oxidation of NiOOH to high-valent nickel states, thus reducing electrode stability and consequently decreasing UOR performance. The competition between the two is particularly evident in actual UOR-relevant applications, peculiarly in devices operating at high working voltages and large current densities. This calls for the modification of Ni-based catalysts to repel the OH- and favor the UOR process in alkaline medium. Inspired by this, Qiao and coworkers fabricated an optimized sulfur-oxygen anionic engineered nickel powder catalyst (Ni-SOX) with high UOR performance (Figs. 11a and b) [119]. In comparison with the conventional nickel-based UOR catalyst (NiOx), which is prone to the undesirable e OER side reaction, Ni-SOx exhibited markedly enhanced UOR activity, stability, and nitrogen product selectivity. A series of in situ XAS (Fig. 11c) and in situ Raman spectroscopic (Figs. 11d-f) and theoretical calculations were employed to track and reveal the critical role of anionic oxygen doping in successfully suppressing OER and promoting UOR. The comprehensive mechanism was elucidated, including the competing adsorption behavior of OH- and urea molecules on the catalyst surface for UOR/OER, as well as the dynamic evolution of the Ni active sites in UOR (Figs. 11g and h). According to this advanced research, it is concluded that the reconstruction of Ni-based catalyst into highly active NiOOH species could function as the active center for UOR, while the overoxidation and competitive OER should be suppressed via the modification of Ni-based catalysts.

    Figure 11

    Figure 11.  (a) ECSA-normalized UOR polarization curves in 1 mol/L KOH + 0.33 mol/L urea (solid line), and OER polarization curves in 1 mol/L KOH (dash line). (b) In situ evaluation of O2 on Ni-SOX and NiOX using RRDE in 1 mol/L KOH + 0.33 mol/L urea. (c) In situ Ni K-edge XANES spectra for Ni-SOx. (d, e) In situ Raman spectra for Ni-SOx electrode. (f) In situ Raman spectra for NiOX electrode in 1 mol/L KOH + 0.33 mol/L urea. (g) Representation for UOR mechanism on Ni-SOX. (h) Representation for UOR and OER mechanism on NiOX. Reproduced with permission [119]. Copyright 2023, Nature Publishing Group.
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    4.3 Glycerol oxidation reaction

    Glycerol is a valuable platform chemical that can be obtained as a byproduct from the production of biodiesel. The oxidation of glycerol to chemicals with added value, such as dihydroxyacetone, glyceric acid, and tartronic acid, is an important reaction with numerous industrial applications [120–122]. Ni-based catalysts have shown promising activity and selectivity for the glycerol oxidation reaction (GOR). Similarly to OER and UOR, the Ni-based catalysts may also experience dynamic reconstruction during the GOR conditions [123,124]. Understanding the surface dynamic reconstruction of Ni-based catalysts is important to improve their performance and selectivity in GOR. Techniques such as in situ and Operando characterization methods, including XPS, XAS, Raman, and electron microscopy, can provide valuable insights into the surface changes occurring during the reaction. As previously discussed, the reconstruction of Ni-based catalysts into NiOOH will improve the intrinsic activity for OER and UOR, while the formed NiOOH may not be highly active toward the GOR. Therefore, controlling the deep reconstruction of Ni-based catalysts from the formation of NiOOH is of paramount importance.

    For example, Wang et al. have prepared a series of Ni-based catalysts featuring diverse chalcogenide coordination environments (NiOx/Ni, NiSx/Ni, and NiSex/Ni) to conduct a comprehensive analysis of the underlying mechanism by which the coordination of chalcogen anions influences the surface reconstruction and GOR catalytic activity [125]. By combining the in situ Raman spectroscopy and EIS, it is revealed that the Ni-Se coordination can effectually inhibit the deep oxidation of Ni active site, impeding the generation of NiOOH, which thus contributes to the high GOR activity of NiSex/Ni (Figs. 12a–d). The theoretical calculation reported that the RDS of GOR on the NiSex interface involves the oxidation of *C2H3O3 intermediates through H2O adsorption, while the RDS of other interfaces favors the overoxidation of formate to CO2 (Figs. 12e and f). This work demonstrated the great importance of deep understanding on the reconstruction process on guiding achieving high GOR activity and selectivity. Therefore, by elucidating the correlation among the catalyst's surface structure, composition, and its catalytic behavior, researchers can design more high-efficiency and selective Ni-based catalysts for the glycerol oxidation reaction, contributing to the advancement of sustainable and cost-effective processes for producing value-added chemicals from biomass-derived materials.

    Figure 12

    Figure 12.  Bode plots of in situ EIS of (a) NiSex/Ni and (b) NiSex/Ni during GOR. In situ Raman spectra of (c) NiSex/Ni and (d) NiSx/Ni for GOR. (e) Schematic illustration of the GOR pathway. (f) The ΔG profiles of GOR on NiSex, NiSx, NiOx, and NiOOH. Reproduced with permission [125]. Copyright 2024, Wiley Publishing Group.
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    4.4 HMF oxidation reaction

    Ni-based catalysts are generally applied to the electrooxidation of HMF, which is a key biomass derived platform chemical [126–128]. The surface reconstruction of these Ni-based materials is imperative for their catalytic performance for HMF electrooxidation [129]. The rapid advancement of in/ex situ characterizations, along with DFT calculations, has deepened the understanding of the surface reconstruction of Ni-based catalysts and its impact on HMF electrooxidation. For instance, Yan et al. have constructed an advanced NiSx/β-Ni(OH)2 nanocomposites to boost the selective electrooxidation of HMF, achieving exceptional electrocatalytic HMF selectivity (99.4%), conversion (97.7%), and Faradaic efficiency (98.3%) (Figs. 13a–c) [130]. According to the in-situ characterizations, it is unveiled that the modification of NiSx will induce the formation of high-valence Ni2+ δ species in the evolved β-Ni(OH)2 electrode, which serve as the genuine active substances in HMFOR (Figs. 13d and e). As a result, the formed NiSx/Ni(OH)O could modify the proton-coupled electron-transfer process of HMFOR, where the electrocatalytically produced Ni(OH)O can efficiently capture the protons from the CHO- in HMF for improving electronic conductivity (Figs. 13f-i).

    Figure 13

    Figure 13.  (a) LSV curves of NiSx/β-Ni(OH)2/Ni in 1 mol/L KOH + 50 mmol/L HMF solution (red line) and 1 mol/L KOH solution (black line). (b) Conversion and concentration variations of HMF and its oxidation products in HMFOR. (c) The HMFOR of NiSx/β-Ni(OH)2/Ni over 5 continuous cycles. (d) Bode plots of NiSx/β-Ni(OH)2/Ni for HMFOR and (e) OER (1 mol/L KOH). (f) Density of states on NiSx/β-Ni(OH)2/Ni systems. (g-i) In situ Raman spectra of NiSx/β-Ni(OH)2/Ni. Reproduced with permission [130]. Copyright 2023, Wiley Publishing Group.
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    More recently, Huang and coworkers also systematically investigated the influence of surface reconstruction of Ni-based catalysts on the electrocatalytic performance of HMFOR [131]. They have constructed a series of Ni3S2/NiOx-n catalysts. By controlling the extent of Ni3S2 surface reconstruction, the ratio of Ni3S2 and NiOx in the Ni3S2/NiOx-n catalyst can be effectively tuned (Fig. 14a), thereby equilibrating the rival adsorption of HMF and OH-. Profiting by the optimal adsorption of these two reactants, the Ni3S2/NiOx-15 catalyst exhibited excellent HMFOR performance (366 mA/cm2 at 1.5 V) and a FE of 98% for FDCA (Figs. 14b and c). Additionally, it is also uncovered that the adsorption of SO42− on the Ni3S2/NiOx surface facilitates the oxidation of NiO to NiOOH and the adsorption of intermediates in HMFOR, promoting the continued enhancement of catalytic performance (Figs. 14d–f).

    Figure 14

    Figure 14.  (a) Schematic description of the in situ controlled surface reconstruction of Ni3S2. (b) Open-circuit potentials and (c) in situ ATR-SEIRAS spectra over Ni3S2/NiOx-n and NiO in different solutions. (d) LSV curves of Ni3S2/NiOx-n and pristine Ni3S2 in 1 mol/L KOH + 20 mmol/L HMF. (e) Summarized current densities (j) at 1.5 V (vs. RHE) and Tafel slopes of Ni3S2/NiOx-n and pristine Ni3S2. (f) FEs of organic products and O2 generated on Ni3S2/NiOx-15 and references. Reproduced with permission [131]. Copyright 2023, Wiley Publishing Group.
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    4.5 Ammonia oxidation reaction

    Ammonia oxidation is a crucial reaction in various industrial processes, such as the production of nitric acid and the removal of ammonia from industrial waste streams [132,133]. Ni-based catalysts have been comprehensively studied for ammonia oxidation owing to their exceptional activity, selectivity, and stability [134,135]. However, the surface structure and composition of Ni-based catalysts can undergo dynamic changes during the reaction, which can significantly impact their catalytic performance [136]. As well known, the surface dynamic reconstruction refers to the modifications in both surface structure and composition of a catalyst that occur during the catalytic reaction. These changes can be driven by various factors, such as the reaction conditions, the existence of reactants and products, and the interaction between the catalyst and the support material.

    Regarding Ni-based catalysts for ammonia oxidation, the surface dynamic reconstruction may involve the processes of surface oxidation and reduction, surface segregation and restructuring, adsorption and desorption of reaction intermediates. Understanding and controlling the surface dynamic reconstruction of Ni-based catalysts is crucial for optimizing their catalytic performance and stability for ammonia oxidation reaction. This can be achieved through a combination of experimental techniques, such as in situ characterization methods, and theoretical modeling approaches, such as DFT calculations. Therefore, deep investigations on the surface dynamic reconstruction of Ni-based catalysts have provided insight into the influence of reconstruction process of Ni-based catalysts on the electrocatalytic performance toward AOR [137,138]. For example, Zhang and coworkers reported a two-stage reconfiguration method of “sulfur doping and electrochemical tuning” to induce the surface dynamic reconstruction of carbon paper supported NiCu alloy nanoparticles (Ni1Cu3-S-T/CP) for boosting the electrocatalytic AOR [139]. Detailed electrochemical tests revealed that the Ni1Cu3-S-T/CP electrode can reach the peak current density of 150 mA/cm2. In time of 5-h continuous nitrogen removal experiment at 1.50 V, the removal efficiency of NH4+-N reached an impressive 96.23%.

    More recently, Liu et al. also enabled the surface reconstruction of Ni-based catalysts to boost the electrooxidation of ammonia by constructing the heterostructure [140]. Specifically, a Ni3S4@NiCo2O4/NF heterostructured catalyst has been designed for boosting the electrooxidation of ammonia, which achieved a high AOR activity (10 mA/cm2 at 0.58 VHg/HgO) and stability (37.2 h at 100 mA/cm2) (Figs. 15a and b). According to the in situ Raman spectra (Figs. 15c and d), the heterostructured catalyst was found to undergo a representative evolution process of Ni(OH)2 → β-NiOOH → γ-NiOOH, optimizing the reconstruction energy barrier. DFT calculations revealed that the Ni3S4@NiCo2O4/NF catalyst facilitates the promotion of reconstruction process because of the electronic interactions, as well as decreases the energy barrier in *NHNH2 generation step, thereby improving the AOR performance (Fig. 15e). These researches have demonstrated that the surface dynamic reconstruction of Ni-based catalysts via defect engineering and heterostructure construction could yield some highly active species and modify the electronic interaction with intermediates, which would thus significantly decrease the energy barrier.

    Figure 15

    Figure 15.  (a) LSV curves of different catalysts for AOR. (b) Stability test of the heterostructured catalyst. (c) In situ Raman spectra of Ni3S4@NiCo2O4/NF. (d) δ(Ni-O)-to-ν(Ni-O) ratios in situ Raman spectra. (e) Optimized model of Ni3S4@NiCo2O4 and the schematic illustration of ammonia oxidation process. Reproduced with permission [140]. Copyright 2024, Elsevier.
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    4.6 Other electrooxidation reactions

    The surface dynamic reconstruction of Ni-based catalysts plays a crucial role in enhancing their electrooxidation capabilities for both methanol and ethanol. For methanol electrooxidation, Ni-based catalysts have received intensive attention due to their facile active site generation based on electrochemical-chemical oxidation mechanisms [141]. The surface dynamic reconstruction of these catalysts can lead to the formation of more active phases, such as NiOOH, which boosts the methanol oxidation reaction (MOR) [142]. For example, Luo et al. developed a novel preparation strategy to fabricate a new-type Ni(OH)2 electrocatalyst with an ultralow Ni-Ni coordination number [143]. This innovative electrocatalyst, crafted through chemical reconstruction of NiMoO4·0.75H2O, exhibits an amorphous structure. It demonstrates significantly enhanced catalytic performance compared to conventional Ni(OH)2, along with exceptional stability under high-current-density conditions and industrial-grade electrolyte concentration. This enables energy-efficient hydrogen production coupled with high-value formate generation (Fig. 16). DFT calculations and synchrotron radiation spectroscopy unveiled the material's refined structure and reaction mechanism, revealing that the improvements in catalytic activity and stability originate primarily from its ultralow Ni-Ni coordination number, three-dimensional mesh structure, and surface reconstruction process. This work proves the significance of dynamic reconstruction of Ni-based catalysts for boosting methanol oxidation.

    Figure 16

    Figure 16.  (a) Scheme of the synthesis of low coordination Ni(OH)2·xH2O catalysts and the application of boosting MOR and hydrogen evolution reaction. (b) LSV curves of different catalysts for MOR. (c) LSV curves of low coordination Ni(OH)2·xH2O catalysts with and without 0.5 mol/L methanol. Reproduced with the permission [143]. Copyright 2024, Springer.
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    Similarly, in the case of ethanol electrooxidation, Ni-based catalysts are pivotal in enabling efficient electrochemical ethanol oxidation reaction (EOR). The surface dynamic reconstruction of these catalysts can lead to the formation of different active sites and phases, which facilitate the formation of acetic acid/acetaldehyde or CO2 [144]. For example, Zhuang et al. synthesized defect-rich Ni3S2 nanowires through regulated design in this work to drive the electrocatalytic EOR [145]. Electrochemical tests revealed that the defect-rich Ni3S2 nanowires exhibited significantly enhanced catalytic performance for the ethanol electrooxidation reaction, along with exceptionally high catalytic stability. In situ tests demonstrated that S-doping in Ni3S2 lowers the oxidation potential required for the formation of the reactive intermediate NiOOH. This also enhances the adsorption capacity of the Ni3S2 nanowires for ethanol, thereby facilitating further progression of the reaction. Therefore, it is concluded that the surface dynamic reconstruction of Ni-based catalysts is favorable for facilitating the electrooxidation of methanol and ethanol. The aforementioned studies further demonstrate the beneficial role of surface dynamic reconstruction in Ni-based catalysts for enhancing electrocatalytic reactions. This reconstruction facilitates the formation of highly active NiOOH species, which serve as true active centers, while simultaneously optimizing the catalysts' surface/interface characteristics and electronic properties [146–151].

    5. Conclusion and outlooks

    Ni-based nanomaterials have been widely utilized as advanced catalysts for various electrooxidation reactions. It is also well known that the Ni sites will undergo a dynamic reconstruction process under high potential, yielding the species with high oxidation states. Lately, enormous endeavors have been dedicated to understanding the dynamic reconstruction of Ni-based catalysts for during the electrooxidation reactions, with numerous research leveraging advancements in operando/in situ experimental techniques and theoretical calculations. In this comprehensive review, we have systematically analyzed the dynamic behavior of Ni-based catalysts in time of electrooxidation reactions, studied some potential means used to activate and guide the surface reconstruction for achieving superior performance (Tables 1 and 2). Particular mechanism-focused investigations with the help of Operando/in situ technologies and computational simulations are imperative to construct the structure-activity relationship and manifest the influences of reconstruction on electrocatalytic performance. Upon achieving a basic understanding, the most pressing challenges faced in this area can be overcome (Fig. 17).

    Table 1

    Table 1.  Summary of the reconstructed Ni-based catalysts for promoting electrocatalytic performance of OER (electrolyte: 1 mol/L KOH).
    DownLoad: CSV
    Catalyst Reconstructed product Activity Ref.
    NiMoO4 NiMoO4@NiOOH ŋ = 260 mV@10 mA/cm2 [14]
    Ni@NiOOH DR-NiOOH ŋ = 281 mV@10 mA/cm2 [33]
    Ni-BDC Ni-BDC@NiOOH ŋ = 225 mV@10 mA/cm2 [60]
    Defective NiFeP/CC Defective NiFeP/NiOOH/CC ŋ = 185 mV@10 mA/cm2 [74]
    F-Ni3S2 NiOOH ŋ = 239 mV@10 mA/cm2 [92]
    CeO2-Ni-X (X = S, P, and O) CeO2-NiOOH ŋ = 251 mV@10 mA/cm2 [103]
    Fe5Ni4S8 Ni(Fe)OOH ŋ = 245 mV@10 mA/cm2 [111]
    Ni/Ni(OH)2 Ni(OH)2/NiOOH ŋ = 369 mV@200 mA/cm2 [146]
    Ni-based pnictide/sulfide γ-NiOOH ŋ = 225 mV@10 mA/cm2 [147]
    Ni(Fe)-MOF Ni(Fe)OOH—Ov 3300 mA/cm2 at 2.2 V [148]
    Ni3S2-NF Ni3S2/oxysulfide-NF ŋ = 185 mV@10 mA/cm2 [149]
    N-NiS2 N-NiS2/NiOOH ŋ = 272 mV@10 mA/cm2 [150]
    Sx-NiCr LDH S—NiOOH ŋ = 244.4 mV@10 mA/cm2 [151]

    Table 2

    Table 2.  Summary of the reconstructed Ni-based catalysts for promoting electrocatalytic performance of UOR, GOR, HMFOR, and AOR.
    DownLoad: CSV
    Catalyst Reconstructed product Reaction Electrolyte Activity Ref.
    aFe-NiB Fe-NiOOH UOR 0.1 mol/L KOH + 0.5 mol/L urea 10 mA/cm2 at 1.298 V [15]
    Co–Ni–S@NF Co-Ni-S/NiOOH@NF UOR 1 mol/L KOH + 0.33 mol/L urea 100 mA/cm2 at 1.35 V [102]
    CoMoO4/Ni(OH)2 CoOOH(Mo)/NiOOH UOR 1 mol/L KOH + 0.33 mol/L urea 10 mA/cm2 at 1.27 V [117]
    NiSex/Ni NiSex/NiOOH/Ni GOR 1 mol/L KOH + 1 mol/L glycerol FE of 92.9% for formate [125]
    V-Ni3N V-Ni3N/NiOOH HMFOR 1 mol/L KOH + 0.1 mol/L HMF 403 µmol cm-2 h-1 at 1.475 V for FDCA [42]
    Ni3S2/NiOx NiOOH HMFOR 1 mol/L KOH + 0.33 mmol/L HMF 366 mA/cm2 at 1.5 V [131]
    Ni1Cu3-S-T/CP NiOOH/NiO2/CuO AOR 1 mol/L NaOH + 0.2 mol/L NH4Cl 150 mA/cm2 at 1.69 V [139]
    Ni3S4@NiCo2O4/NF γ-NiOOH AOR 1 mol/L KOH + 1 mol/L NH3·H2O 10 mA/cm2 at 0.58 V [140]

    Figure 17

    Figure 17.  Schematic illustration of the summary of the pressing challenges in the field of reconstruction of Ni-based catalysts.
    DownLoad: Full-Size Img PowerPoint

    As mentioned above, significant challenges persist in the following aspects:

    The complexity and diversity of catalyst reconstruction mechanisms. Research on the reconstruction phenomenon of Ni-based catalysts has made some progress, but due to differences in catalytic reactions, reaction media, and application potential, it is still difficult to clearly explain the reconstruction phenomenon of Ni-based catalysts. This indicates that the complexity and diversity of catalyst reconstruction mechanisms have increased the difficulty of research and require deeper understanding and exploration.

    The reconstruction mechanisms of novel Ni-based catalysts remain unclear. Despite significant efforts and substantial progress in this fascinating field, existing research primarily addresses the dynamic reconstruction of conventional Ni-based catalysts, such as phosphides, oxides/hydroxides, sulfides, and selenides, leaving the reconstruction behaviors of novel catalysts, including high-entropy materials and single-atom catalysts, largely unexplored.

    Exploring more effective strategies for guiding the dynamic reconstruction process. Although some effective strategies have been demonstrated to be efficient for driving the surface reconstruction of catalysts and can fulfil dynamic transitions at a deeper level in electrocatalysts, the extent of reconstruction of catalyst is still uncontrollable. To this end, it is necessary to explore some advanced methods to guide dynamic reconstruction. In recent years, the built-in electric field construction and the spin state engineering have been demonstrated to be beneficial for adjusting the reconstruction kinetics. Therefore, more strategies should be proposed.

    Despite multifarious operando characterization methods have been employed to explore catalytic behaviors during reactions, there remains an insufficiency in characterizing activity. Spectroscopic techniques, such as Raman spectroscopy, can recognize the formed (oxy)hydroxide active species, but they are unable to assess the adsorption characteristics of surface ligands. Given the complexity of the surface environment and the invertibility of active species, integrating multiple techniques for in situ characterization of the electrochemical process at the nanoscale can provide compelling evidence to enhance our understanding of the mechanism.

    Ni-based catalysts commonly experience surface dynamic reconstruction during oxidation processes; however, their performance during electrochemical reduction has been rarely investigated. It is well known that Ni-based materials are also highly effective catalysts for various reduction reactions, including the HER, oxygen reduction reactions, and carbon dioxide reduction reactions. Whether Ni-based catalysts undergo a typical reconstruction process during electroreduction, and the characteristics of such reconstruction remain unclear.

    Declaration of competing interest

    The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

    CRediT authorship contribution statement

    Cheng Wang: Writing – original draft, Methodology, Investigation, Conceptualization. Li Zhou: Writing – review & editing, Investigation. Zhenghao Fei: Resources. Yanqing Wang: Resources. Yukou Du: Supervision, Resources, Funding acquisition.

    Acknowledgment

    This work was supported by National Natural Science Foundation of China (Nos. 52073199 and 52274304).


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  • Figure 1  Schematic illustration of the modulation strategy for reconstructing Ni-based catalysts to enhance electrooxidation reactions.

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    Figure 2  Scheme of characterization technologies of reconstruction process.

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    Figure 3  (a) Scheme of the surface reconstruction of LiNiO2. (b) Ni EELS intensity before and after prolonged CV cycling. (c) Ni valence state and Ni-O bond length of different catalysts. (d) CV curves of LiNiO2 with different electrochemical delithiation cycles. Reproduced with permission [64]. Copyright 2020, Wiley Publishing Group. (e) Schematic description of the electrochemical activation induced surface reconstruction of NiOx and the enhanced OER current density after surface reconstruction. Reproduced with permission [65]. Copyright 2022, Elsevier.

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    Figure 4  (a) Mott–Schottky plots of different catalysts. (b) Schematic diagram of the formation of a p−n interface. (c) Simulated crystal structures of α-Ni-Fe and γ-Ni-Fe/α-Ni-Fe, and (d) the effect of different VO concentrations on the formation energies of γ-Ni-Fe from α-Ni-Fe. Reproduced with permission [79]. Copyright 2021, American Chemical Society.

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    Figure 5  The TEM images of (a) NMO and (d) NMO-30M after self-reconstruction. The LSV curves of (b) NMO and (e) NMO-30M with different scans. In situ Raman spectra of (c) NMO and (f) NMO-30M during OER process. Reproduced with permission [14]. Copyright 2023, Springer.

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    Figure 6  (a) Schematic description of the F doping promotes the dynamic reconstruction of Ni3S2 nanoarrays. Reproduced with permission [92]. Copyright 2021, Elsevier. (b, c) In situ Raman of Fe-Ni3S2. Reproduced with permission [63]. Copyright 2023, Wiley Publishing Group. (d) Schematically showing the dynamic reconstruction of multivalent nickel sulfide catalysts. Reproduced with permission [95]. Copyright 2022, Royal Society Chemistry.

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    Figure 7  (a, b) In situ Raman spectra of Co-Ni-S@NF and Ni-S@NF under urea oxidation. (c, d) The morphology structures of Co-Ni-S@NF after long-term UOR electrocatalysis. Reproduced with permission [102]. Copyright 2022, Royal Society Chemistry. (e) Schematic illustration of the CeO2-promoted surface dynamic reconstruction of Ni-X via the creation of oxygen vacancies and electron transfer. Reproduced with permission [103]. Copyright 2022, American Chemical Society.

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    Figure 8  In situ Raman spectra of (a) FeP and (b) Ni5P4 in the 40th CV cycle. (c) Representative Raman spectra of different catalysts at 1.57 V (vs. RHE). (d) Schematically showing the dynamic surface reconstruction in Ni5P4@FeP pre-catalyst. Reproduced with permission [110]. Copyright 2022, Elsevier.

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    Figure 9  (a) Schematic diagram of the high-spin state (HS) transition of Ni3+ to the low-spin state (LS) of Ni2+ and the LS transition of Fe2+ to the HS of Fe3+. (b) Magnetic hysteresis (M-H) loops of FNS and FNS-400. (c, d) High-resolution Ni 2p3/2 XPS spectra of different catalysts at various potentials. (e, f) O 1s XPS spectra of different catalysts at various potentials. (g, h) The Bode phase plots of different catalysts at various voltages. (i) OER polarization curves of different catalysts. Reproduced with permission [111]. Copyright 2024, Wiley Publishing Group.

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    Figure 10  In situ Raman spectra of (a) V0 and (b) V2 from circuit potential (OCP) to 1.6 V (vs. RHE). (c) The representative Raman spectra of V0 and V2 at 1.60 V (vs. RHE). (d) The peak intensity ratio of δ(Ni-O) to ν(Ni-O) of V0 and V2. The ΔG profiles of the proposed UOR pathway at (e) γ-NiOOH and (f) Ovac-V-γ-NiOOH. Reproduced with permission [118]. Copyright 2022, Wiley Publishing Group.

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    Figure 11  (a) ECSA-normalized UOR polarization curves in 1 mol/L KOH + 0.33 mol/L urea (solid line), and OER polarization curves in 1 mol/L KOH (dash line). (b) In situ evaluation of O2 on Ni-SOX and NiOX using RRDE in 1 mol/L KOH + 0.33 mol/L urea. (c) In situ Ni K-edge XANES spectra for Ni-SOx. (d, e) In situ Raman spectra for Ni-SOx electrode. (f) In situ Raman spectra for NiOX electrode in 1 mol/L KOH + 0.33 mol/L urea. (g) Representation for UOR mechanism on Ni-SOX. (h) Representation for UOR and OER mechanism on NiOX. Reproduced with permission [119]. Copyright 2023, Nature Publishing Group.

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    Figure 12  Bode plots of in situ EIS of (a) NiSex/Ni and (b) NiSex/Ni during GOR. In situ Raman spectra of (c) NiSex/Ni and (d) NiSx/Ni for GOR. (e) Schematic illustration of the GOR pathway. (f) The ΔG profiles of GOR on NiSex, NiSx, NiOx, and NiOOH. Reproduced with permission [125]. Copyright 2024, Wiley Publishing Group.

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    Figure 13  (a) LSV curves of NiSx/β-Ni(OH)2/Ni in 1 mol/L KOH + 50 mmol/L HMF solution (red line) and 1 mol/L KOH solution (black line). (b) Conversion and concentration variations of HMF and its oxidation products in HMFOR. (c) The HMFOR of NiSx/β-Ni(OH)2/Ni over 5 continuous cycles. (d) Bode plots of NiSx/β-Ni(OH)2/Ni for HMFOR and (e) OER (1 mol/L KOH). (f) Density of states on NiSx/β-Ni(OH)2/Ni systems. (g-i) In situ Raman spectra of NiSx/β-Ni(OH)2/Ni. Reproduced with permission [130]. Copyright 2023, Wiley Publishing Group.

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    Figure 14  (a) Schematic description of the in situ controlled surface reconstruction of Ni3S2. (b) Open-circuit potentials and (c) in situ ATR-SEIRAS spectra over Ni3S2/NiOx-n and NiO in different solutions. (d) LSV curves of Ni3S2/NiOx-n and pristine Ni3S2 in 1 mol/L KOH + 20 mmol/L HMF. (e) Summarized current densities (j) at 1.5 V (vs. RHE) and Tafel slopes of Ni3S2/NiOx-n and pristine Ni3S2. (f) FEs of organic products and O2 generated on Ni3S2/NiOx-15 and references. Reproduced with permission [131]. Copyright 2023, Wiley Publishing Group.

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    Figure 15  (a) LSV curves of different catalysts for AOR. (b) Stability test of the heterostructured catalyst. (c) In situ Raman spectra of Ni3S4@NiCo2O4/NF. (d) δ(Ni-O)-to-ν(Ni-O) ratios in situ Raman spectra. (e) Optimized model of Ni3S4@NiCo2O4 and the schematic illustration of ammonia oxidation process. Reproduced with permission [140]. Copyright 2024, Elsevier.

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    Figure 16  (a) Scheme of the synthesis of low coordination Ni(OH)2·xH2O catalysts and the application of boosting MOR and hydrogen evolution reaction. (b) LSV curves of different catalysts for MOR. (c) LSV curves of low coordination Ni(OH)2·xH2O catalysts with and without 0.5 mol/L methanol. Reproduced with the permission [143]. Copyright 2024, Springer.

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    Figure 17  Schematic illustration of the summary of the pressing challenges in the field of reconstruction of Ni-based catalysts.

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    Table 1.  Summary of the reconstructed Ni-based catalysts for promoting electrocatalytic performance of OER (electrolyte: 1 mol/L KOH).

    Catalyst Reconstructed product Activity Ref.
    NiMoO4 NiMoO4@NiOOH ŋ = 260 mV@10 mA/cm2 [14]
    Ni@NiOOH DR-NiOOH ŋ = 281 mV@10 mA/cm2 [33]
    Ni-BDC Ni-BDC@NiOOH ŋ = 225 mV@10 mA/cm2 [60]
    Defective NiFeP/CC Defective NiFeP/NiOOH/CC ŋ = 185 mV@10 mA/cm2 [74]
    F-Ni3S2 NiOOH ŋ = 239 mV@10 mA/cm2 [92]
    CeO2-Ni-X (X = S, P, and O) CeO2-NiOOH ŋ = 251 mV@10 mA/cm2 [103]
    Fe5Ni4S8 Ni(Fe)OOH ŋ = 245 mV@10 mA/cm2 [111]
    Ni/Ni(OH)2 Ni(OH)2/NiOOH ŋ = 369 mV@200 mA/cm2 [146]
    Ni-based pnictide/sulfide γ-NiOOH ŋ = 225 mV@10 mA/cm2 [147]
    Ni(Fe)-MOF Ni(Fe)OOH—Ov 3300 mA/cm2 at 2.2 V [148]
    Ni3S2-NF Ni3S2/oxysulfide-NF ŋ = 185 mV@10 mA/cm2 [149]
    N-NiS2 N-NiS2/NiOOH ŋ = 272 mV@10 mA/cm2 [150]
    Sx-NiCr LDH S—NiOOH ŋ = 244.4 mV@10 mA/cm2 [151]
    下载: 导出CSV

    Table 2.  Summary of the reconstructed Ni-based catalysts for promoting electrocatalytic performance of UOR, GOR, HMFOR, and AOR.

    Catalyst Reconstructed product Reaction Electrolyte Activity Ref.
    aFe-NiB Fe-NiOOH UOR 0.1 mol/L KOH + 0.5 mol/L urea 10 mA/cm2 at 1.298 V [15]
    Co–Ni–S@NF Co-Ni-S/NiOOH@NF UOR 1 mol/L KOH + 0.33 mol/L urea 100 mA/cm2 at 1.35 V [102]
    CoMoO4/Ni(OH)2 CoOOH(Mo)/NiOOH UOR 1 mol/L KOH + 0.33 mol/L urea 10 mA/cm2 at 1.27 V [117]
    NiSex/Ni NiSex/NiOOH/Ni GOR 1 mol/L KOH + 1 mol/L glycerol FE of 92.9% for formate [125]
    V-Ni3N V-Ni3N/NiOOH HMFOR 1 mol/L KOH + 0.1 mol/L HMF 403 µmol cm-2 h-1 at 1.475 V for FDCA [42]
    Ni3S2/NiOx NiOOH HMFOR 1 mol/L KOH + 0.33 mmol/L HMF 366 mA/cm2 at 1.5 V [131]
    Ni1Cu3-S-T/CP NiOOH/NiO2/CuO AOR 1 mol/L NaOH + 0.2 mol/L NH4Cl 150 mA/cm2 at 1.69 V [139]
    Ni3S4@NiCo2O4/NF γ-NiOOH AOR 1 mol/L KOH + 1 mol/L NH3·H2O 10 mA/cm2 at 0.58 V [140]
    下载: 导出CSV
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  • 发布日期:  2025-12-15
  • 收稿日期:  2025-05-11
  • 接受日期:  2025-08-20
  • 修回日期:  2025-08-19
  • 网络出版日期:  2025-08-21
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