Cross-scale understanding of cascade electrocatalysis for carbon and nitrogen utilization

Abstract

Cascade electrocatalysis is increasingly being recognized as a promising approach for achieving efficient and selective conversion of carbon and nitrogen resources, in response to critical challenges in energy sustainability and environmental management. Compared to conventional single-site systems, cascade pathways are designed to enable spatial and temporal coordination of multiple reaction steps, through which the generation, migration, and transformation of key intermediates can be precisely controlled. In this review, a multiscale perspective is provided, spanning atomic, sub-nanoscale, nanoscale, and macroscopic dimensions. Recent progress is summarized in several representative strategies, including the use of multiple active sites for relay catalysis, the engineering of crystal facets and heterointerfaces, the application of nanoconfinement, and the implementation of tandem reactor systems. Particular emphasis is placed on their applications in CO₂ reduction, nitrate reduction, and urea electrosynthesis. Moreover, state-of-the-art in situ characterization techniques are highlighted, through which dynamic insights into catalyst evolution and intermediate behaviour have been obtained. Finally, opportunities are outlined for future development, where rational catalyst design, integrated system construction, and data-driven optimization are expected to further advance cascade electrocatalysis for sustainable chemical transformations.

---

Guihua Yu

Dr Guihua Yu is John J. McKetta Centennial Energy Chair in Engineering, Temple Foundation Endowed Professor of Materials Science and Engineering and Mechanical Engineering at The University of Texas at Austin, affiliated with Texas Materials Institute, UT Energy Institute and UT Chemistry. He received his BS degree in chemistry with the highest honor from USTC, PhD in chemistry from Harvard University, followed by postdoc research at Stanford. He has been focusing on the rational design of polymeric materials and hybrid organic–inorganic nanomaterials, fundamental understanding of their chemical and physical properties, and exploration of their applications in environment, energy, and sustainability technologies.

Panpan Li

Dr Panpan Li is a Professor at Sichuan University. She received her BS in Chemistry, MEng. in Environmental Engineering, and PhD in Environmental Science from Sichuan University. She was a postdoctoral scholar at the University of Texas at Austin starting from 2019. She joined Sichuan University as a faculty member and established her independent research group in late 2021. Her research focuses on innovative materials and electrochemical technologies for environmental and energy sustainability.

---

Introduction

Carbon and nitrogen cycles are fundamental processes that govern Earth's climate regulation and resource metabolism.^1–3 However, intensified human activities have profoundly disturbed the equilibrium of these two cycles. In the case of the nitrogen cycle, although the traditional Haber–Bosch process can effectively reduce nitrogen to synthesize ammonia, its high temperature and pressure requirements not only result in enormous energy consumption but also cause severe environmental impacts.^4,5 In contrast, electrochemical approaches, which can achieve the reaction under mild conditions and directly utilize renewable electricity, are considered as more sustainable alternatives. Nevertheless, electrochemical nitrogen reduction suffers from low efficiency due to the strong N≡≡N bond strength (945 kJ mol⁻¹) and resultant high reaction overpotentials.^6–8 Nitrate, with its lower N–O bond dissociation energy, is more readily reduced electrochemically and is viewed as a promising alternative nitrogen source for ammonia synthesis.^9,10 Similarly, the carbon cycle plays a crucial role in addressing climate change and global warming, but excessive CO₂ emissions have intensified the greenhouse effect, creating an urgent demand for carbon capture and conversion technologies. CO₂ electroreduction, as a potential carbon resource utilization method, has emerged as a research focus.^11,12 However, both CO₂ and NO₃⁻ electroreduction reactions involve complex multistep reaction pathways and face challenges such as slow reaction kinetics, poor selectivity, and high energy barriers.¹³ Due to thermodynamic and kinetic limitations, traditional single-step electrochemical reduction processes lack sufficient control over key intermediates, thereby leading to low utilization rates and poor product selectivity, which severely hampers the efficient and directional conversion of carbon and nitrogen resources.

Cascade electrocatalysis, a strategy that converts reactants through multiple reaction steps, provides a new approach to address carbon and nitrogen resource utilization challenges. Cascade electrocatalysis refers to the integration of multiple electrocatalytic reaction steps in space and time, where different active sites sequentially transform intermediates, thus overcoming the thermodynamic and kinetic constraints of a single reaction step.^14,15 In microbes, the conversion of NO₃⁻ to NH₃ is a cascade reaction: nitrate reductase reduces NO₃⁻ to NO₂⁻, which is then further reduced to NH₃ by nitrite reductase or nitrogenase.^16–18 Inspired by this, researchers have started applying cascade electrocatalysis to carbon and nitrogen resource utilization. Cascade electrocatalysis allows multiple electrocatalytic reactions to occur in series on a single catalyst surface or within a reaction system, not only overcoming the thermodynamic and selectivity limitations in nitrogen and carbon conversion but also significantly improving reaction efficiency and product selectivity.^19,20 Current research on cascade electrocatalysis primarily focuses on studies at a single scale, such as investigating single-atom catalysis mechanisms at the atomic scale. While such studies help to elucidate the reaction mechanisms of individual active sites, they face numerous limitations, such as limited compatibility of single active sites and hindered interfacial mass transfer. To address these limitations, cross-scale cooperative effects have drawn increasing attention. In cascade catalytic systems, structural features and reaction behaviors at different scales are closely coupled. At the atomic scale, active sites govern the adsorption and transformation pathways of key intermediates. At the nanoscale, interfacial and confinement structures regulate intermediate migration, short-range spillover, and the local reaction microenvironment. At the reactor scale, mass-transfer rates, electrolyte distribution, and pH collectively dictate overall reaction kinetics and efficiency^21,22 Integrating these multiscale strategies enables precise control over the spatiotemporal distribution of reaction intermediates, thereby establishing an efficient and selective cascade pathway for complex multistep reactions. However, this cross-scale research also faces challenges, including the limitations of multiscale modeling and characterization techniques, the complexity of reaction mechanisms, and the challenges of material design. Through a deeper understanding and optimization of cascade electrocatalysis mechanisms at multiple scales, future advancements could offer viable solutions to the global energy crisis and environmental pollution issues.

This review provides a comprehensive assessment of the mechanisms and applications of cascade electrocatalysis from a multiscale perspective (Fig. 1). It begins by elucidating the reaction mechanisms underlying cascade electrocatalysis, encompassing atomic, sub-nanoscale, nanometer, and macroscopic scales. The review then highlights in situ characterization techniques employed to study cascade electrocatalysis. Subsequently, it summarizes key advancements in cascade electrocatalytic strategies, including multiple active sites, crystal facets and heterointerfaces, nanoconfinement and tandem reactors with a particular focus on their application in the utilization of carbon and nitrogen resources, such as nitrate reduction reaction (NO₃RR), carbon dioxide reduction reaction (CO₂RR), and urea synthesis. Finally, the challenges facing the field of cascade electrocatalysis are discussed, along with a forward-looking perspective on its future prospects, aiming to promote the development of cascade electrocatalysis in the field of electrochemical technologies.

Fig. 1 Cascade electrocatalysis for carbon and nitrogen utilization.

Cross-scale strategies for cascade electrocatalysis

Cascade electrocatalytic reactions, involving sequential transformations, hold immense potential for efficient resource conversion. However, their mechanistic complexity remains a formidable challenge. At the atomic scale, catalytic behaviour is dictated by single-atom effects and synergistic interactions between multi-atom sites. At the nanoscale, catalytic performance relies on the interplay between surface structure and reactant dynamics. Given the diversity of intermediates and their varied migration pathways, single-scale analyses are insufficient to capture the full mechanistic landscape. Therefore, a comprehensive multiscale approach is indispensable for elucidating the formation, transformation, and coupling of intermediates, thereby laying a robust theoretical foundation for cascade electrocatalysis. This section systematically explores the mechanisms at the atomic, sub-nanoscale, nanoscale, and macroscopic levels (Fig. 2), highlighting the distinct contributions of each to cascade processes.

Fig. 2 Mechanistic study of cascade electrocatalytic reactions.

Atomic scale: single-atom and dual/multi-atom site interactions

Cascade electrocatalysis achieves high efficiency through consecutive reactions, with atomic-scale insights proving pivotal for optimizing both selectivity and conversion. At this scale, single-atom and dual- and multi-atom site effects govern catalytic performance. Single-atom catalysts (SACs) utilize isolated metal atoms as active centers, exploiting their distinct electronic structures and maximizing atomic utilization to enhance reaction kinetics and selectivity.²³ In the NO₃RR, SACs provide well-defined active sites and efficient electron transfer pathways, thereby lowering energy barriers and accelerating reaction rates.^24–27 Li et al.²⁸ developed a copper-based single-atom gel (Cu SAGs) catalyst that selectively adsorbs and activates nitrite intermediates at single-atom sites during the cascade NO₃RR. This configuration effectively suppresses the competing hydrogen evolution reaction (HER), enabling highly selective NO₃⁻ to NH₃ conversion under neutral conditions. This work demonstrates the synergistic integration of pulse electrolysis and three-dimensional (3D) structured SAGs, facilitating highly efficient NO₃⁻ to NH₃ conversion via tandem catalysis of otherwise unfavorable intermediates.

Beyond single-atom effects, dual- and multi-atom catalysts leverage cooperative interactions between adjacent metal centers to modulate intermediate adsorption and migration, thereby enhancing both activity and selectivity.^29–31 In the CO₂RR and NO₃RR, such bimetallic sites can establish energetically favorable tandem pathways.³² For instance, Xie et al.³³ reported a MOF-supported Pd–Cu bimetallic catalyst that promotes CO₂ to C₂₊ conversion through a tandem mechanism: Cu facilitates *CO adsorption and C–C coupling, while Pd stabilizes *CH₂CHO intermediates, achieving a C₂₊ faradaic efficiency (FE) of 81.9%. Similarly, Yan et al.³⁴ designed a Cu–Ni bimetallic MOF catalyst where Cu reduces NO₃⁻ to NO₂⁻, and Ni subsequently converts NO₂⁻ to NH₃. Although SACs exhibit high atom utilization and selectivity, their isolated nature limits the cooperative interactions crucial for multistep transformations.³⁵ In contrast, dual- and multi-atom configurations enable spatially adjacent, functionally complementary active centers that facilitate sequential intermediate conversion and minimize diffusion losses.^36,37

Sub-nanoscale: interfacial effects

At the sub-nanoscale, interfacial effects arising from charge redistribution and atomic coordination at boundaries between distinct catalytic phases play a pivotal role in intermediate stability, charge transfer kinetics, and reaction selectivity.³⁸ These interfacial regions can significantly influence reaction pathways by modulating local electronic structures and adsorption energetics.³⁹ Metal–metal interfaces often exhibit catalytic behavior that differs markedly from that of their individual components. As demonstrated by Zhang et al.,⁴⁰ a well-designed Cu/Ag interface promotes asymmetric CO–CHO coupling: Ag domains generate *CO intermediates, while the Cu/Ag interface concurrently suppresses the HER, favors *CO hydrogenation to *CHO, and enhances C₂H₄ formation. Similarly, metal–support interactions can substantially tune electronic states and surface reactivity. Xu et al.⁴¹ developed a MOF-derived CuPd/N-doped carbon nanoarrays catalyst, wherein interfacial charge polarization between the metal sites and carbon support facilitates an efficient cascade pathway for the NO₃RR to NH₃.

Nanoscale: confinement effects

Confinement effects in nanostructured catalysts create spatially restricted environments that enhance reactant-site interaction frequency and minimize diffusion distances.^42,43 This spatial confinement accelerates reaction kinetics while suppressing side reactions, thereby improving selectivity.⁴⁴ For instance, Qiu et al.⁴⁵ validated this concept in a nanoconfinement-based cascade denitrification system, utilizing pulsed photocatalysis to mediate chlorine spillover within TiO₂ nanotubes integrated with CuO_x. In this confined environment, cathodically generated NH₄⁺ and photogenerated chlorine radicals (˙Cl) are localized in close proximity. The spillover of ˙Cl facilitates the selective oxidation of NH₄⁺ to N₂. This approach demonstrates highly efficient treatment of nitrate-contaminated wastewater and holds great promise for the removal of complex nitrate pollutants from water bodies in future applications.

Macroscopic scale: reactor cascading

At the macroscopic scale, cascade electrocatalysis can be engineered through reactor-level integration, where sequential reactions are spatially separated into interconnected electrolyzers. In these systems, the first cell produces intermediates that are subsequently converted in downstream reactors under optimized conditions of potential, pH, and electrolyte composition.⁴⁶ This modular approach enables precise reaction control and enhanced product selectivity. Ozden et al.⁴⁷ developed a two-step CO₂ to C₂H₄ system that integrates a solid oxide electrolyzer cell (for CO₂ to CO conversion) with a membrane electrode assembly (for CO to C₂H₄ reduction). This configuration minimizes CO₂ loss to carbonate formation and reduces total energy consumption by nearly 48%, achieving efficient ethylene synthesis. Moreover, hybrid cascade systems can further integrate electrochemical, thermocatalytic, or biocatalytic processes. For example, Xia et al.⁴⁸ presented a tandem electrothermal-catalytic system that efficiently utilizes cathodic CO and anodic O₂ products in the CO₂RR, converting arylboronic acids and amines into valuable organic amides within a tandem thermocatalytic reactor. This study demonstrates the feasibility of a tandem electrothermal-catalytic strategy for achieving CO₂ conversion and amide synthesis. It offers a novel pathway for comprehensively exploiting CO₂ electrolysis. In addition, Han et al.⁴⁹ presented a spatially decoupled electrobiological system that first utilizes tannic acid-Cu²⁺ metal-phenolic networks to electrocatalytically convert CO₂ into ethanol. Subsequently, engineered Escherichia coli ferment the ethanol into itaconic acid, isopropanol, and polyhydroxybutyrate, achieving efficient conversion of CO₂ into high-value chemicals.

Advanced in situ techniques for probing cascade reactions

In cascade electrocatalytic reactions, the intricate and interdependent nature of successive reaction steps demands precise coordination among active sites. Achieving a comprehensive understanding of both the underlying reaction mechanisms and the catalyst's performance under working conditions is therefore essential. In situ characterization techniques serve as powerful, real-time analytical tools, enabling the direct observation of reaction dynamics. These techniques provide direct insights into the evolution of catalyst surface microstructures and reaction processes, thereby furnishing critical experimental evidence that can inform the optimization of catalytic performance and the design of advanced catalysts. This section highlights several widely utilized in situ techniques and underscores their pivotal contributions to advancing cascade electrocatalysis research.

Synchrotron X-ray techniques

Synchrotron X-ray techniques, particularly X-ray absorption spectroscopy (XAS), have found extensive application in elucidating the electronic structure, oxidation states, and local coordination environments of catalysts (Fig. 3a). Specifically, in situ extended X-ray absorption fine structure (EXAFS) analysis enables the tracking of variations in the coordination environments of absorbing atoms under reaction conditions, thus facilitating the determination of atomic coordination states. Concurrently, in situ X-ray absorption near-edge structure (XANES) offers insights into potential-dependent chemical state changes.^50–52 In cascade electrocatalysis, XAS is instrumental in monitoring valence state evolution within tandem catalysts across multiple reaction stages, thereby providing mechanistic insights for each step.⁵³ For instance, Lou et al.⁵⁴ employed XAS to quantitatively analyze the atomic structure of a Janus Cu@Ni catalyst (Fig. 3b and c). EXAFS confirmed the distinct Cu- and Ni-enriched domains, while XANES, in conjunction with XPS, revealed electron transfer from Ni to Cu. These findings corroborated a tandem mechanism, wherein NO₃⁻ adsorption and activation occur on Cu sites, while H species generated on Ni sites migrate to the interface, facilitating N–O bond cleavage. Such studies elucidate the intrinsic nature of multi-site synergy and cascade reaction mechanisms at the electronic level, advancing our understanding of the coupling between charge transfer and reaction pathways in catalytic processes.

Fig. 3 In situ characterization techniques. (a) Schematic diagram of in situ XAS. (b) Cu K-edge and (c) Ni K-edge XANES spectra of Cu₅₀Ni₅₀-Janus/C, Cu₅₀Ni₅₀-SSA/C, and reference samples. Reproduced with permission.⁵⁴ Copyright 2024, American Chemical Society. (d) Schematic diagram of in situ FTIR spectroscopy. In situ FTIR spectra of Cu₅/Mo_0.6WO₃ (e) from OCP to −0.7 V vs. RHE, and (f) from OCP (0 s) to 900 s at −0.7 V vs. RHE. Reproduced with permission.⁵⁵ Copyright 2025, Wiley-VCH. (g) Schematic diagram of in situ Raman spectroscopy. In situ Raman spectra of (h) DiMe-Cu₃-MOF and (i) NonMe-Cu₃-MOF at various applied potentials in 50 mM KNO₃ and 0.5 M K₂SO₄ electrolytes. Reproduced with permission.⁵⁶ Copyright 2025, Royal Society of Chemistry. (j) Schematic diagram of in situ SECM. (k) Schematic diagram of the NO₃RR via pulse electrolysis cascade catalysis. (l) Kinetic rate constants of NO₂⁻, NO₃⁻, and H₂O adsorption on Cu SAGs determined with SI-SECM. Reproduced with permission.²⁸ Copyright 2023, American Chemical Society.

Infrared spectroscopy

Fourier-transform infrared spectroscopy (FTIR) detects molecular vibrations via infrared absorption at characteristic frequencies, offering real-time, molecular-level insights into the chemical species involved in electrocatalytic processes.^57,58 Fig. 3d illustrates a schematic of the FTIR setup. Within cascade electrocatalytic systems, this technique allows for the direct monitoring of adsorbed reactants, intermediates, and products on electrode surfaces, facilitating the identification of intermediate species within the cascade pathway and their transformation processes. When integrated with complementary techniques, FTIR can effectively track the formation, conversion, and consumption of key intermediates, offering crucial evidence for understanding reaction kinetics, electron transfer, and molecular interactions.⁵⁹ Dai et al.⁵⁵ utilized FTIR to confirm the cascade mechanism of a Cu/Mo-WO₃ catalyst, dynamically capturing the spectral evolution of key intermediates. The depletion of certain peaks and the emergence of new ones provided real-time evidence of NO₃⁻ reduction to NO₂⁻ and subsequent conversion to NH₃, validating the proposed stepwise mechanism (Fig. 3e and f). Such real-time spectral tracking under operando conditions underscores the power of FTIR in unraveling complex cascade reaction pathways.

Raman spectroscopy

Raman spectroscopy, which integrates laser excitation with electrochemical measurements, provides valuable information on chemical composition and molecular structure by detecting characteristic shifts in scattered light (Fig. 3g).^60,61 This technique offers real-time tracking of intermediates, enabling the precise tracking of pathway changes in complex cascade reactions.⁶² Such molecular-level insight is essential for correlating structural dynamics with the optimization of catalytic performance. For instance, Fu et al.⁵⁶ utilized Raman spectroscopy to monitor the characteristic peaks of the NHO intermediate and dynamic Cu–N bond variations on DiMe-Cu₃-MOF and NonMe-Cu₃-MOF surfaces (Fig. 3h and i). Based on the Raman results, the *NHO intermediate was detected on both DiMe-Cu₃-MOF and NonMe-Cu₃-MOF, whereas the *NOH intermediate was not detected, indicating that NO₃⁻ is reduced to NH₃ via the NHO pathway. Combined with DFT calculations, the results revealed a 0.32 eV reduction in the energy barrier for *NO₂ to *NO₂H conversion through hydrogen bonding, thus optimizing the cascade pathway toward highly selective and industrially relevant NO₃RR to NH₃ conversion.

Scanning probe microscopy

Scanning electrochemical microscopy (SECM) is a high-resolution in situ electrochemical imaging technique that enables the study of local surface reactivity with micrometer spatial and millisecond-scale temporal resolution (Fig. 3j).^63,64 Using micro- or nanoelectrode probes, SECM quantifies current responses between the probe and the substrate, allowing real-time mapping of localized reaction activity, kinetics, and intermediate distribution.⁶⁵ In cascade electrocatalysis, SECM is particularly useful for visualizing how intermediates form and dissipate at different active sites. For example, in NO₃RR and CO₂RR, SECM has been employed to track key intermediates such as NO₂⁻ and CO, elucidating reaction coupling between spatially separated active centers.^66–68 He et al.⁶⁹ utilized the surface generation-tip collection (SG-TC) mode to detect NO₂⁻ and NH₃ formed on a Cu/Co(OH)₂ model catalyst during NO₃⁻ electroreduction. NH₃ generation significantly increased at the Cu-Co(OH)₂ interface, accompanied by a marked decrease in NO₂⁻ production. These results confirmed that NO₂⁻ preferentially forms on Cu sites and subsequently diffuses to adjacent Co(OH)₂ sites, where it undergoes further reduction to NH₃ via a tandem process. In another study, Li et al.²⁸ employed surface interrogation scanning electrochemical microscopy (SI-SECM) to demonstrate that a Cu SAG catalyst exhibited a substantially higher adsorption affinity for NO₂⁻ than for NO₃⁻ or H₂O (Fig. 3k and l). This finding established a potential-dependent cascade mechanism, where intermediate accumulation was observed at low potentials followed by efficient conversion to NH₃ at high potentials, enabling highly efficient NO₃RR.

In addition to these techniques, in situ electron microscopy, such as liquid-cell transmission electron microscopy (TEM), is emerging as a powerful approach for visualizing catalyst structural evolution during electrochemical reactions.^70–72 While its application to cascade electrocatalysis remains limited, it holds significant promise. However, current in situ characterization methods still face notable limitations. Their temporal and spatial resolutions are often insufficient to fully capture the short-lived intermediates and transient changes at nanoscale active sites during cascade reactions, and it remains challenging to simultaneously resolve the dynamic evolution of catalyst structures and reaction intermediates. Given the strong complementarity among different in situ techniques, a comprehensive understanding of cascade electrocatalytic mechanisms requires the combined use of multiple in situ methods to compensate for individual weaknesses and to investigate the reaction from distinct temporal and spatial perspectives. For example, coupling synchrotron-based X-ray methods with in situ vibrational spectroscopy enables the concurrent tracking of catalyst structural evolution and the formation and consumption of intermediates. Moreover, advancing in situ techniques with higher temporal and spatial resolution, such as ultra-high-resolution SECM, will provide powerful tools for probing mechanistic pathways in greater detail.

Recent progress on cascade electrocatalysis

Carbon and nitrogen resource utilization is a pivotal link in advancing sustainable energy and green chemistry.^73–75 However, typical CO₂RR, NO₃RR, and their coupled reactions often involve multi-electron/proton transfers and the dynamic migration of various reaction intermediates. This presents a series of challenges, including sluggish reaction kinetics, complex competitive pathways, and low product selectivity.^22,76–84 Traditional single-step electrocatalysis often suffers from intermediate accumulation, low energy efficiency, and limited product selectivity in these reactions. In contrast, cascade electrocatalysis, where multiple reaction steps are spatially and temporally integrated, offers a new avenue for efficient carbon–nitrogen resource utilization by enabling effective intermediate generation, transport, and transformation. This section discusses recent advancements in cascade electrocatalytic systems targeting carbon and nitrogen resource conversion.

Relay catalysis with multiple active sites

The strategy of relay catalysis with multiple active sites leverages the different selectivities of various sites for specific reaction steps, decoupling elementary steps within complex reaction networks in space. This approach utilizes the cooperative effect between sites to integrate each reaction step in a relay fashion, optimizing the functional complementarity and energy matching between active sites, thereby significantly enhancing overall reaction efficiency and product selectivity.^85,86 In the typical multi-electron and multi-proton transfer process of the NO₃RR, researchers have successfully achieved precise regulation of reaction pathways and directional transformation of intermediates by rationally designing multiple active site catalysts, significantly improving catalytic performance and opening new avenues for the development of efficient NO₃RR processes.^87–92 For instance, Qin et al.⁹³ designed an atomically precise Ag₃₀Pd₄ bimetallic nanocluster, where Ag sites preferentially adsorb NO₃⁻ and efficiently convert it into NO₂⁻ intermediates. Subsequently, the NO₂⁻ intermediate migrates directionally to the adjacent Pd sites for deep reduction to the final product NH₃. This study decoupled the NO₃RR steps and allocated them to Ag and Pd sites, achieving high FE for NH₃ production (>90%). Furthermore, external field control can effectively enhance the relay catalysis of the NO₃RR via multiple active sites. For instance, Liu et al.⁹⁴ designed a Ni-modified copper oxide single-atom alloy (Ni₁Cu SAAO) catalyst, which achieved efficient NO₃RR to NH₃ via a thermally-coupled electrocatalytic strategy. The cascade reaction mechanism, shown in Fig. 4a, involved heating (60–80 °C), which significantly promoted the hydrolysis of Ni single-atom sites to generate active hydrogen. These active hydrogens were relayed to neighboring Cu sites, accelerating the hydrogenation of NO_x intermediates (e.g., NO₂) adsorbed on the Cu surface, thereby overcoming the kinetic barriers of NO_x hydrogenation and the competition with the HER. This catalyst exhibited optimized NH₃ production performance at elevated temperatures, with a FE of approximately 80% and a rate of 9.70 mg h⁻¹ cm⁻² (Fig. 4b).

Fig. 4 Relay catalysis with multiple active sites. (a) Schematic diagram of the electrothermal synergistic effect of Cu₂O NWs and Ni₁Cu SAAO in the NO₃RR process. (b) FE and yield of NH₃ for Cu₂O NWs and Ni₁Cu SAAO at different applied potentials. Reproduced with permission.⁹⁴ Copyright 2024, American Chemical Society. (c) Scheme of the cascade catalysis mechanism over AgCu SANP. (d) FE results of Cu NP, AgCu SAA, AgCu SANP, and Ag NP catalysts toward the CO₂RR at −0.65 V. (e) Comparison of the C–C coupling activation barrier for the *CHO (on CuAg and pure Cu) and *COH intermediates (CuAg). Reproduced with permission.⁹⁶ Copyright 2023, Springer Nature. (f) Mixed catalyst design where one component (blue) lowers the activation energy for C–N bond formation, and the second component (orange) reduces the activation energy for protonation steps required for urea formation. (g) Zn/Cu hybrid catalyst and its single-component counterparts for urea FE. (h) FE and yield of urea on the Zn-0.5/Cu hybrid catalyst at different applied potentials. Reproduced with permission.¹ Copyright 2023, Springer Nature.

In addition, relay catalysis with multiple active sites can significantly promote key processes such as C–C coupling and C–N coupling, enabling the efficient synthesis of high-value multi-carbon or nitrogen-containing compounds.⁹⁵ Du et al.⁹⁶ reported an Ag–Cu bimetallic catalytic system that demonstrated exceptional performance in the CO₂RR. In this system, Ag nanoparticles efficiently reduced CO₂ to CO, while the Ag sites induced compression strain in the Cu lattice, enhancing the adsorption energy of the *CO intermediate on the Cu sites and significantly promoting C–C coupling kinetics, thereby achieving a high FE for multi-carbon products (94%) (Fig. 4c–e). Similarly, Luo et al.¹ designed a Zn/Cu bimetallic catalyst that further extended the application of tandem catalysis in C–N coupling reactions. As shown in Fig. 4f, the Zn sites preferentially stabilized the key C–N coupling intermediate CO₂NO₃, while the Cu sites relayed the reduction of the COOHNH₂ protonation energy barrier. This strategy successfully optimized the reaction pathway and suppressed side reactions, achieving 75% selectivity in simulated wastewater containing 1000 ppm NO₃⁻ (Fig. 4g and h). In summary, multi-active-site catalysts can sequentially activate different reactants and intermediates based on the selective specificity of different sites toward reaction steps. This enables them to regulate the energy barriers and pathways of key steps, thereby achieving tandem catalysis for complex reactions. However, cascade strategies based on multiple active sites still face limitations. These include insufficient microenvironmental compatibility between sites, restricted migration of reaction intermediates, and the structural complexity of catalysts, which complicates mechanistic analysis and undermines stability.⁹⁷ Integrating multiscale approaches can help align individual steps more effectively and thereby improve the overall efficiency and stability of cascade reactions. Table 1 summarizes the catalytic processes of various multiple active site catalysts. This strategy provides important theoretical and experimental paradigms for the design of high-performance cascade catalytic systems and the high-value conversion of carbon and nitrogen cycles.

Table 1 Summary of multiple active site catalysts

Catalyst	Mechanism	Electrolyte	Potential	FE
Cu2O–CoPO-2 (ref. 88)	Cu2O: NO3^− → NO2^−	0.1 M NO3^− + 1.0 M KOH	−0.37 V vs. RHE	95%
	CoPO: H2O → *H
Ru–Ni nanosheets (ref. 89)	Ru: NO3^− → *HONO	0.1 M K2SO4 + 0.002 M KNO3	−0.8 V vs. RHE	96%
	Ni: *HONO + *H → NH3
TTA–TPH–CuCo (ref. 98)	Cu: NO3^− → NO2^−	0.5 M K2SO4 + 0.3 M KNO3	−0.75 V vs. RHE	92%
	Co: NO2^− → NH3
Ag30Pd4 nanocluster (ref. 93)	Ag: NO3^− → NO2^−	1.0 M NaOH + 1500 ppm NO3^−–N	−0.6 V vs. RHE	90%
	Pd: NO2^− → NH3
Ni1Cu single-atom alloy oxide nanowires (ref. 94)	Ni: H2O → *H	1.0 M KOH + 0.1 M KNO3	+ 0.1 V vs. RHE	80%
	Cu: *NOx + *H → NH3
Mo1Fe1Pd dual single-atom alloy (ref. 99)	Mo: NO3^− → NO2^−	1.0 M KNO3 + 1.0 M KOH	−0.7 V vs. RHE	94%
	Fe: NO2^− → NH3
AgCu single-atom and nanoparticle (ref. 96)	Ag NP: CO2 → CO	1.0 M KOH	−0.65 V vs. RHE	94%
	AgCu SAA: C–C coupling
0.2% CoCu single-atom alloy (ref. 100)	Co: CO2 → CO	1.0 M KHCO3	−1.01 V vs. RHE	51%
	Cu: C–C coupling
Cu3N–Ag nanocubes (ref. 97)	Ag: CO2 → CO	1.0 M KOH	−0.7 V vs. RHE	50%
	Cu: CO → *CHO → C2H4
CuO/Ni single atoms (ref. 101)	Ni: CO2 → CO	1.0 M KOH	−0.892 V vs. RHE	81%
	Cu: CO → C2+
CoCu composite (ref. 102)	Co: CO2 → CO	0.1 M KHCO3	−0.8 V vs. RHE	71%
	Cu: CO → C2H5OH
Mo1Cu single-atom alloy (ref. 103)	Mo: H2O → *H	1.0 M KOH	−1.7 V vs. RHE	86%
	Cu^0: CO2 → CO
	Cu^δ+: C–C coupling
Zn/Cu hybrid catalyst (ref. 1)	Zn: stabilize CO2NO3	0.1 M KHCO3 + 500 ppm NO3^−–N	−0.6 V vs. RHE	75%
	Cu: lower the protonation barrier of COOHNH2
Zn1/In2O3−x (ref. 83)	In-OV: CO2 → *CO	0.1 M KHCO3 + 0.1 M KNO3	−0.7 V vs. RHE	56%
	Zn1-OV: NO3^− → *NH2
Fe1/MoS2 (ref. 104)	Fe1–S3: *CO2NO2 → * CO2NH2	0.1 M KHCO3 + 0.1 M KNO3	−0.5 V vs. RHE	55%
	MoS2: *CO2NH2 → *COOHNH2
Mo–PCN-222(Co) (ref. 105)	Co: CO2 → *CO	0.1 M KHCO3 + 50 mM KNO3	−0.4 V vs. RHE	34%
	Mo: NO3^− → *NH2
CuPd1Rh1 diatomic alloy (ref. 106)	Pd1–Cu: *CO2NO2 → * CO2NH	0.1 M KHCO3 + 0.1 M KNO3	−0.5 V vs. RHE	72%
	Rh1–Cu: *CO2NH2 → *COOHNH2
CuSn composite (ref. 107)	Cu: CO2 → *CO	0.1 M KNO3	−0.7 V vs. RHE	79%
	Sn: NO3^− → *NH2

---

Crystal facet and heterointerface coupling

The crystal facet and heterointerface cascade catalysis enhances the overall catalytic efficiency by constructing functionally complementary active regions, which collaboratively guide the orientation and coupling of reaction pathways. This synergy optimizes the multiple step reaction energy barriers and the mass transfer of intermediates, ultimately improving catalytic performance. The facet-based cascade strategy involves tuning the exposed crystal facets of the catalyst, leveraging the distinct catalytic properties arising from variations in atomic arrangement, coordination, and electronic structure across different facets. These properties enable the selective catalysis of specific reaction steps.^108–110 Fu et al.¹¹¹ proposed a crystal facet cascade catalysis strategy, where the Cu(100) and Cu(111) facets cooperatively perform tandem catalysis (Fig. 5a). The Cu(100) facet preferentially adsorbs NO₃⁻ and efficiently reduces them to NO₂⁻, while the NO₂⁻ intermediate migrates to the adjacent Cu(111) facet for the hydrogenation step. This catalyst achieves a current density of 665 mA cm⁻² for NH₃ production and a rate of 1.41 mmol h⁻¹ cm⁻² in a flow cell under −0.59 V vs. RHE (Fig. 5b), significantly enhancing the NO₃RR to NH₃ performance.

Fig. 5 Crystal facet and heterointerface coupling in cascade catalysis. (a) Synergistic effects between Cu(100) and Cu(111) crystal facets. (b) Total current density and FE of different products on Cu nanosheets. Reproduced with permission.¹¹¹ Copyright 2023, Wiley-VCH. (c) Schematic illustration of the proposed mechanism for NO₃⁻ to NH₃ conversion on the Cu/Ru HHNS. (d) Projected density of states (PDOS) for b-Cu, b-Ru, and i-CuRu. (e) FE_NH3 and EE_NH3 of Cu/Ru-Un, Cu/Ru-300, and Cu/Ru-800 across a potential range of 0.2 to −0.3 V_RHE. Reproduced with permission.¹¹² Copyright 2025, American Chemical Society. (f) Schematic diagram of CO₂ and NO₃⁻ co-reduction to urea on the Ag-CuNi(OH)₂ electrocatalyst. (g) FE of possible products from the Ag-CuNi(OH)₂ composite material. (h) Comparison of urea yield and FE between Ag NPs, CuNi(OH)₂ NSs, their physical mixture, and Ag-CuNi(OH)₂. Reproduced with permission.¹¹³ Copyright 2024, Wiley-VCH.

In contrast, the heterointerface cascade strategy capitalizes on the unique local atomic and electronic environments created at the interfaces of different materials due to lattice mismatch, electronic interactions, and other factors. These environments facilitate the effective adsorption and activation of reactants and intermediates.^114,115 For example, Chen et al.¹¹² demonstrated a Cu/Ru heterointerface shell–core nanocavity catalyst that enabled efficient cascade electroreduction of NO₃⁻ to NH₃, significantly enhancing the reaction rate and selectivity (Fig. 5c–e). NO₃⁻ is first adsorbed and reduced to NO₂⁻ at the Cu site, after which NO₂⁻ desorbs and accumulates in the nanocavity. The accumulated NO₂⁻ is rapidly transferred to the Cu/Ru heterointerface, where it undergoes further reduction to NH₃. The Cu/Ru heterointerface facilitates electron transfer from Cu to Ru, improving the adsorption and activation of reaction intermediates at the interface, thus enhancing the utilization of NO₂⁻ intermediates. Moreover, the heterointerface cascade strategy can also be employed to regulate the generation and conversion of active hydrogen intermediates, facilitating C–N coupling reactions for the synthesis of complex carbon–nitrogen compounds. For instance, Ye et al.¹¹³ designed an Ag-CuNi(OH)₂ heterostructure that efficiently catalyzed urea electrosynthesis. As shown in Fig. 5f, at the Ag site of the Ag-CuNi(OH)₂ catalyst, CO₂ is reduced to the critical *CO intermediate, while at the CuNi(OH)₂ site, NO₃⁻ is reduced to the *NH₂ intermediate. These intermediates spontaneously couple at the adjacent heterointerface to form urea, while the interface also optimizes the H₂O splitting process to provide active hydrogen atoms. The Ag-CuNi(OH)₂ composite material achieved an impressive urea production rate of 25.6 mmol g⁻¹ h⁻¹ and a FE of 46% (Fig. 5g and h). The cascade catalysis via crystal facets and heterointerfaces allows precise control over reaction pathways and intermediate transformations, substantially enhancing the overall efficiency and selectivity of cascade reactions. This approach offers valuable insights into the efficient use of carbon- and nitrogen-based resources and the sustainable synthesis of green chemicals. Although this strategy holds potential for enhancing cascade reaction efficiency, its practical implementation remains constrained. Differences in adsorption selectivity between crystal facets and interfacial charge redistribution can impede the transfer of intermediates across interfaces. In addition, interfacial reconstruction or fluctuations in the local environment during operation may disrupt the stability of the cascade process.¹¹⁶ Employing multiscale strategies can reinforce interfacial stability, strengthen the coupling between reaction steps, and improve system scalability, offering new pathways for practical deployment. Table 2 summarizes the catalytic processes of crystal facet and heterointerface-based cascade catalysts.

Table 2 Summary of crystal facet and heterointerface-based cascade catalysts

Catalyst	Mechanism	Electrolyte	Potential	FE
Cu nanosheets (ref. 111)	Cu(100): NO3^− → NO2^−	1.0 M KOH + 0.2 M KNO3	−0.59 V vs. RHE	88%
	Cu(111): NO2^− → NH3
Cu/Ru hollow heteronanostructure (ref. 112)	Cu: NO3^− → NO2^−	0.1 M KNO3 + 0.1 M KOH	−0.1 V vs. RHE	97%
	Cu/Ru: NO2^− → NH3
4H/fcc Au–Cu heterostructures (ref. 117)	4H/fcc Au: NO3^− → NO2^−	1.0 M KOH + 1.0 M KNO3	−0.6 V vs. RHE	98%
	4H/fcc Cu: NO2^− → NH3
CuO@CeO2−x heterostructured nanotubes (ref. 118)	Amorphous CuO: NO3^− → NO2^−	0.1 M KOH + 0.01 M KNO3	−0.4 V vs. RHE	96%
	Cu–Ce: NO2^− → NH3
c-Co3O4/a-CuO heterostructure (ref. 119)	a-CuO: NO3^− → *NO2	0.2 M K2SO4 + 0.1 M NO3^−	−0.8 V vs. RHE	90%
	c-Co3O4: *NO2 → NH3
Ni@Cu2−xSe nanoarrays (ref. 120)	Cu2−xSe: NO3^− → NO2^−	1.0 M KOH + 0.1 M KNO3	−0.4 V vs. RHE	91%
	Interface: modulating *H
	Ni: H2O → *H
CoO–CuOx heterostructure (ref. 121)	CuOx: NO3^− → *NO2	0.5 M Na2SO4 + 200 ppm NaNO3–N	−0.5 V vs. RHE	92%
	Interface: promoting the transfer of electrons
	CoO: *NO2 → NH3
Ag–Cu heterostructure (ref. 116)	Ag: NO3^− → NO2^−	0.1 M KOH + 0.1 M KNO3	−0.5 V vs. RHE	>80%
	Interface: facilitating the spillover of intermediates
	Cu: NO2^− → NH3
SnO2/Cu6Sn5/CuO nanocatalysts (ref. 122)	Cu6Sn5/SnO2: CO2 → *CO2^−	0.5 M NaHCO3	−0.95 V vs. RHE	90%
	Cu6Sn5/CuO: H2O → *H
Ag/Cu self-evolution tandem catalysts (ref. 123)	Ag: CO2 → CO	1.0 M KOH	−1.8 V vs. RHE	89%
	Interface: enhancing the adsorption of intermediates
	Cu: CO → C2+
Au–Cu heterostructure (ref. 124)	AuCu: CO2 → CO	0.1 M KHCO3	−0.75 V vs. RHE	—
	Cu: CO → C2+
Au/Cu heterostructure (ref. 125)	Au (110): CO2 → *CO	0.1 M KHCO3	−0.75 V vs. RHE	—
	Cu(110): CO → C2+
Cu2O nanoparticle (ref. 126)	(100): CO2 → *CO; C–C coupling	0.2 M KI	−1.3 V vs. RHE	57%
	(111): C2H4 overflow
Ag–Cu Janus nanostructures (ref. 127)	Ag domains: CO2 → CO	0.1 M KHCO3	−1.2 V vs. RHE	72%
	Cu domains: CO → C2+
Ag–Cu biphasic heterostructure (ref. 128)	Ag: CO2 → CO	0.1 M KHCO3	−1.05 V vs. RHE	44%
	Interface: promoting the transport of intermediates
	Cu: CO → C2+
Cu/Cu2O heterostructures (ref. 129)	Cu^0: NO3^− → *NH2; C–N coupling	0.5 M KNO3; 0.2 M PA	−0.6 V vs. RHE	75%
	Interface: promoting the transport of intermediates
	Cu^+: *CH3CNHCOO^− → *CH3CHNH2COO^−
Ag–Cu composite (ref. 130)	Ag: CO2 → CO	3.0 M KOH	−1.0 V vs. RHE	80%
	Interface: promoting the transport of intermediates
	Cu: CO → C2+

---

Nanoconfinement

Nanoconfinement involves constructing nanoreactors or confined spaces that impose spatial constraints on reactants and intermediates, effectively orchestrating multistep reactions within a limited volume. Confined cascade catalysis capitalizes on these spatial constraints to enhance intermediate retention and proximity, leading to higher reaction rates and selectivity.^131–134 For example, Li et al.¹³⁵ designed a trifunctional nanoreactor system with a 1D geometry, open mesoporous channels, and synergistic active sites for the highly efficient electrocatalytic NO₃RR to NH₃ (Fig. 6a and b). The system uses one-dimensional mesoporous carbon as a support, creating a unique microenvironment that favors NO₃⁻ transport and adsorption while restricting the diffusion of NO_x intermediates. Simultaneously, the iron single-atom sites (Fe–N₄) and iron nanoclusters (Fe₄) embedded within the support synergistically control the electronic structure to dominate the reduction of NO₃⁻ and the oxidation of H₂O, respectively. This system demonstrates excellent NO₃RR performance under both alkaline and neutral conditions. Qiu et al.⁴⁵ confined the intermediate product (NH₄⁺) and the active chlorine species (˙Cl) within localized regions using TiO₂ nanotubes (Fig. 6c and d). Leveraging the spillover effect of ˙Cl, they achieved the highly efficient and directed conversion of NH₄⁺ to N₂. Furthermore, by precisely controlling the structure of the nanoreactor, the confinement effect can be enhanced, promoting the formation, diffusion, and subsequent utilization of reaction intermediates. For instance, Lu et al.¹³⁶ synthesized a series of Ag@Cu₂O cascade nanoreactors with tunable shell thicknesses, where the Cu₂O shell thickness was precisely controlled to achieve spatial confinement of the CO intermediate (Fig. 6e and f). In this system, the Ag core efficiently generates the CO intermediate, which, upon escaping, is confined within the porous Cu₂O shell, significantly increasing the local CO concentration and thus promoting C–C coupling to form C₂₊ products. This study not only proposes an effective strategy for fine-tuning the local CO concentration through precise control of the Cu₂O shell thickness but also provides important theoretical insights into the confinement catalysis mechanisms within cascade nanoreactors.

Fig. 6 Nanoconfinement in cascade catalysis. (a) Schematic illustration of the three-in-one nanoreactor design to accelerate NO₃RR to NH₃ synthesis. (b) FE_NH3 of FeN₄@mCNR and FeN₄/Fe₄@mCNR at varied potentials. Reproduced with permission.¹³⁵ Copyright 2025, American Chemical Society. (c) Schematic illustration of NO₃⁻-to-N₂ process via the pulsed photoelectrolysis-mediated reactive chlorine spillover process. (d) FE of NH₃ for TiO₂ NTs and TiO₂ NTs/CuO_x. Reproduced with permission.⁴⁵ Copyright 2025, Elsevier B.V. (e) Schematic illustration of the confinement catalysis mechanism in Ag@Cu₂O cascade nanoreactors. (f) FE for C₂₊ and C₁ products at various applied potentials. Reproduced with permission.¹³⁶ Copyright 2024, American Chemical Society. (g) The Cu-CDs/Cu₅FeS₄ multisite nanoreactor for stepwise multiple species coupling to synthesize urea within the CDs-dominated nano-space via utilizing the CO poisoning effect. (h) Urea yield rate and FE of Cu₅FeS₄ and Cu-CDs/Cu₅FeS₄. (i) FE of urea, NH₃, NO₂⁻, and H₂ of Cu-CDs/Cu₅FeS₄ in the H-cell_. Reproduced with permission.¹³⁷ Copyright 2025, Wiley-VCH.

Moreover, confined cascade catalysis can effectively control the accumulation behavior of toxic intermediates, converting them into beneficial factors and enabling complex reactions involving multiple species.¹³⁸ For example, Zhang et al.¹³⁷ designed a nanoreactor composed of copper-carbon dots (Cu-CDs) and chalcopyrite (Cu₅FeS₄) for the efficient synthesis of urea (Fig. 6g–i). In this system, Cu-CDs provide confined nano-spaces that stabilize *CO intermediates, preventing CO poisoning of the Fe sites. Meanwhile, two structurally distinct Cu sites facilitate the activation and transformation of nitrogen-containing species, driving the continuous C–N coupling steps and ultimately enabling efficient urea synthesis. This system achieved a urea yield of 1131.84 µg h⁻¹ mg_cat⁻¹ with a selectivity of 42%, significantly enhancing the thermodynamic and kinetic advantages of multiple site synergy and multiple species integration in urea synthesis. These examples demonstrate that nanoscale confinement can markedly influence cascade catalysis by spatially constraining and locally enriching reactive intermediates, thereby promoting desired cascade pathways while suppressing side reactions. Designing catalysts with intrinsic nanoscale confinement or incorporating external confined architectures, such as porous frameworks or core–shell structures, has thus become a key strategy for enhancing the performance of cascade electrocatalytic systems. Nevertheless, confined cascade strategies still present notable limitations. Excessive confinement may suppress intermediate diffusion and poison active sites. Moreover, precisely constructing confined architectures with appropriate spatial dimensions, pore connectivity, and optimized interfacial chemistry remains challenging.¹³⁹ Combining confinement engineering with multiscale approaches enables the coordinated optimization of intermediate transport, interfacial mass transfer, and overall system stability. Table 3 summarizes the performance data for relevant confined cascade catalytic systems.

Table 3 Summary of the confined cascade catalytic systems

Catalyst	Mechanism	Electrolyte	Potential	FE
FeN4/Fe4 mesoporous carbon nanorod (ref. 135)	Fe–N4: NO3^− → NO2^−	0.1 M NO3^− + 1.0 M KOH	−0.3 V vs. RHE	92%
	NO2^− confinement
	Fe4: H2O → *H
CuFe@CuNi composite (ref. 140)	CuFe LDH: NO3^− → NO2^−	0.1 M Na2SO4 + 50 ppm NO3^−–N	−1.4 V vs. Ag/AgCl	100%
	NO2^− confinement
	CuNi LDH: NO2^− → NH3
(CoPc-NH2 + NiPc-OCH3)/carbon nanotubes (ref. 141)	NiPc-OCH3: CO2 → CO	0.1 M KHCO3	−0.98 V vs. RHE	50%
	CO confinement
	NiPc-OCH3: CO → CH3OH
Ni sodalite topology/NC (ref. 142)	NiN3: CO2 → CO	0.5 M KHCO3	−0.72 V vs. RHE	62%
	CO confinement
	Cu NPs: CO → C2H4
Ag@Cu2O cascade nanoreactor (ref. 136)	Ag core: CO2 → CO	0.1 M KHCO3	−1.6 V vs. RHE	78%
	CO confinement
	Cu2O shell: CO → C2+
CoPc/carbon nanotubes (ref. 44)	CoPc-out: CO2 → CO	0.1 M KHCO3	−0.96 V vs. RHE	41%
	CO confinement
	CoPc-in: CO → CH3OH
Ag@Cu2O-x nanoreactors (ref. 143)	Ag core: CO2 → CO	1.0 M KOH	−1.2 V vs. RHE	74%
	CO confinement
	Cu2O shell: CO → C2+
Ag–Cu nanoporous bimetallic catalyst (ref. 144)	Ag: CO2 → CO	0.2 M KHCO3	−1.2 V vs. RHE	73%
	CO confinement
	Cu: CO → C2+
Cu-CDs/Cu5FeS4 nanoreactor (ref. 137)	Fe: CO2 → CO	0.1 M KNO3	−0.35 V vs. RHE	42%
	C and N intermediate confinement
	Cu: NO3^− → *NH2
CuCo@N-doped microporous hollow carbon spheres (ref. 145)	Co: CO2 → CO	0.05 M KNO3 + 0.1 M KHCO3	−0.55 V vs. RHE	32%
	C and N intermediate confinement
	Cu: NO3^− → *NH2

---

Tandem reactors

The strategy of tandem reactors enables the sequential integration of different reaction steps across multiple reactors, where the differential conditions between reactors (e.g., pH, potential, and temperature) can be finely tuned to optimize the reaction environment. This approach enhances both the rate of target product formation and its selectivity.^46,146 For instance, Fig. 7a illustrates a cascaded electrolyzer system in which the reduction of CO₂ to CO and the subsequent reduction of CO to C₂₊ are coupled in different electrolyzers.¹⁴⁷ By creating tailored catalytic environments in each electrolyzer, this strategy significantly accelerates the production rate of C₂₊ products (Fig. 7b). Chi et al.¹⁴⁸ reported a dual electrolyzer cascade system: the first electrolyzer operates under alkaline conditions to electrochemically reduce CO₂ to ethanol, while the second electrolyzer, under acidic conditions, electrooxidizes ethanol and condenses it into the high-value six-carbon compound 1,1-diethoxyethane (DEE). This system achieves a highly efficient and selective conversion from CO₂ to multi-carbon products. The cascading reactor design not only greatly enhances product selectivity but also leads to efficient energy utilization and resource conversion.

Fig. 7 Tandem reactors. (a) Schematic diagram of the tandem CO₂ electrolyzer. (b) Comparison of C₂H₄ yield between the tandem electrolyzer cascade structure and a single electrolyzer. Reproduced with permission.¹⁴⁷ Copyright 2023, Springer Nature. (c) Tandem electrochemical-thermochemical reactors for CO₂ conversion to C₃ oxygenate products. (d) CO₂-based selectivity of products for 5 cm² Cu/C, oxide-derived Cu/C, and Cu/reinforced C cathodes at −220 mA cm⁻² in combination with 160 and 200 °C hydroformylation temperatures. Reproduced with permission.¹⁴⁹ Copyright 2022, American Chemical Society. (e) Hybrid electrocatalytic-bioelectrocatalytic cascade integrated on a gas diffusion electrode for the CO₂RR under selective formation of methanol. (f) FE for the CO₂RR performed with a GDE constituted of Ag-Bi₂O₃ nanofibers on a hydrophobic carbon paper. Reproduced with permission.¹⁵⁰ Copyright 2025, Wiley-VCH.

Additionally, electrochemical reactors can be coupled with thermocatalytic and biocatalytic reactors, forming hybrid cascaded systems. This strategy effectively overcomes the limitations of single electrochemical transformations, improving reaction efficiency and enabling the synthesis of more complex, high-value products, thereby significantly enhancing the economic viability of the entire conversion process. For example, Chen et al.¹⁴⁹ proposed a cascaded electrochemical-thermochemical strategy in which C₂H₄ reacts with CO and H₂ to produce propanol and propionaldehyde (Fig. 7c and d). In this approach, CO₂ is first electrochemically reduced to C₂H₄, CO, and H₂, followed by a thermocatalytic hydrogenation–formylation reaction that converts these intermediates into C₃ oxygenated compounds. This cascading method achieves approximately 18% selectivity for C₃ products. Wang et al.¹⁵⁰ proposed a system that integrates electrochemical and biocatalytic processes on a gas diffusion electrode for the CO₂RR (Fig. 7e and f). Under neutral pH conditions, Ag-Bi₂O₃ selectively reduces gaseous CO₂ to carbonates, which are then further reduced to formaldehyde and methanol by formaldehyde dehydrogenase and alcohol dehydrogenase, respectively. This hybrid reactor cascade not only enhances reaction efficiency but also improves the overall selectivity and sustainability of the system. In summary, the tandem reactor strategy enhances the efficiency and selectivity of complex reactions at the macroscale by optimizing environmental conditions within each reactor and precisely controlling product distribution. Although tandem reactors can optimize reaction environments and regulate product distribution, diffusion limitations in intermediate transport between reactors, system operational complexity, and coupling interference between reaction conditions at different stages still constrain their precise control and efficiency enhancement for multistep reactions.¹⁵¹ Therefore, integrating multiscale strategies to construct an integrated catalytic system featuring active sites, nanoconfinement, interfacial mass transfer, and reactor series connection enables efficient intermediate transport, thereby enhancing the overall efficiency of cascade reactions. Table 4 summarizes the catalytic performance of tandem reactors.

Table 4 Summary of tandem reactors

Cascade system	Catalyst	Mechanism	Electrolyte	Reaction conditions
Electrochemical–electrochemical	Ni–N–C; Cu (ref. 147)	Cell-1: CO2 → CO	Cell-1: 0.1 M KHCO3	Cell-1: 200 mA cm^−2
		Cell-2: CO → C2+	Cell-2: 1.0 M KHCO3	Cell-2: 700 mA cm^−2
	Graphite flakes (ref. 148)	Cell-1: CO2 → ethanol	Cell-1: 1.0 M KOH	Cell-1: −1.8 V vs. SCE
		Cell-2: ethanol → DEE	Cell-2: 0.5 M H2SO4 ethanol solution	Cell-2: 20 mA cm^−2
	3D single-atom Ni; Cu2O (ref. 152)	Cell-1: CO2 → CO	Cell-1: 0.5 M KHCO3	Cell-1: 140 mA cm^−2
		Cell-2: CO → n-propanol	Cell-2: 1.0 M KOH	Cell-2: 42.5 mA cm^−2
	Solid-oxide electrolysis cell; membrane electrode assembly (ref. 47)	Cell-1: CO2 → CO	Cell-1: 30 wt% aqueous ethanolamine	Cell-1: 815 mA cm^−2
		Cell-2: CO → C2H4	Cell-2: 3.0 M KOH	Cell-2: 150 mA cm^−2
	Ni–N–C; Cu nanoparticle (ref. 153)	Cell-1: CO2 → CO	Cell-1: 0.5 M K2SO4 + H2SO4	Cell-1: 5 A
		Cell-2: CO → C2+	Cell-2: 0.5 M KOH	Cell-2: 4 A
	Ni–Cu; Cu–Al (ref. 154)	Cell-1: CO2 → CO	Cell-1: 1.0 M KOH	Cell-1: 400 mA cm^−2
		Cell-2: CO → C2+	Cell-2: 1.0 M KOH	Cell-2: 300 mA cm^−2
Electrochemical–thermochemical	Cu; Rh1Co3/MCM-41 (ref. 149)	Cell-1: CO2 → C2H4	Cell-1: 50 mM KHCO3	Cell-1: 220 mA cm^−2
		Cell-2: C2H4 → C3	Cell-2: —	Cell-2: 160, 200 °C
	Pd/C; FeCo (ref. 155)	Cell-1: CO2 → CO	Cell-1: 50 mM KHCO3	Cell-1: 150 mA cm^−2
		H2O → H2	Cell-2: —	Cell-2: 450 °C
		Cell-2: CO2, H2 → CNF
	Ag-hexamethylenetetramine/Ni-hydroxide carbonate; Pd(II) (ref. 48)	Cell-1: CO2 → CO	Cell-1: 0.5 M KHCO3	Cell-1: −0.8 V vs. RHE
		H2O → H2	Cell-2: —	Cell-2: 120 °C
		Cell-2: CO2, O2 → organic amides
	Rh/SmxCe1−xO2−δ (ref. 156)	Cell-1: H2O → H2	Cell-1: acceptor-doped LaGaO3	Cell-1: 300–500 mA cm^−2
		Cell-2: CO2 + CH4 → CO + H2	Cell-2: —	Cell-2: 800 °C
	Membrane electrode assembly; Ga/ZSM-5/P (ref. 157)	Cell-1: CO2 → C2H4	Cell-1: 0.5 M KHCO3	Cell-1: 200 mA cm^−2
		Cell-2: C2H4 → BTEX	Cell-2: —	Cell-2: 600 °C
Electrochemical-biocatalytic	Ag-Bi2O3; dehydrogenase (ref. 150)	Cell-1: CO2 → formate	Cell-1: 0.1 M phosphate	Neutral PH
		Cell-2: formate → formaldehyde → methanol	Cell-2: —	25–400 mA cm^−2
	MPN@deCOP@Ag-Cu2O; engineered Escherichia coli (ref. 49)	Cell-1: CO2 → ethanol	Cell-1: 1.0 M KOH	Cell-1: 900 mA cm^−2
		Cell-2: ethanol → itaconic acid, isopropanol, and PHB	Cell-2: —	Cell-2: ADH, ALDH
	Cu–Ag; Cupriavidus necator (ref. 158)	Cell-1: CO2 → C2 oxygenates	Cell-1: 0.1 M KH2PO4	Cell-1: 300 mA cm^−2
		Cell-2: C2 oxygenates → PHB	Cell-2: —	Cell-2: pH 7.0
	C/Ag/carbon GDE (ref. 159)	Cell-1: CO2 → CO	Cell-1: 0.05 M H2SO4 + 3.0 M KCl	Cell-1: 100 mA
		Cell-2: CO → MCFAs	Cell-2: —	Cell-2: 35 °C, pH 6.2
	Cu/Cu2O (ref. 160)	Cell-1: CO2 → formate	Cell-1: 0.5 M KHCO3	Cell-1: 50 mA
		Cell-2: formate → SCP	Cell-2: —	Cell-2: 37 °C

---

Conclusion and outlook

Based on the above, cascade electrocatalysis provides a novel pathway for the efficient conversion of carbon and nitrogen resources through atomic-scale catalyst design, nanoscale structural engineering, and macroscopic reactor integration. This review systematically summarizes the latest advancements in this field, delving into the crucial role of the synergistic effects between single-atom/multi-atom sites at the atomic scale, interfacial and confinement effects at the sub-nanoscale and nanoscale, and reactor design at the macroscopic level in enhancing reaction activity and selectivity. Through multiscale cooperative effects, cascade electrocatalysis not only effectively reduces the energy barriers of reactions but also significantly improves reaction selectivity, especially in complex multistep reaction systems, demonstrating unique advantages. Despite substantial progress across various applications, cascade electrocatalysis continues to face several key challenges. Limited compatibility among different active sites constrains the sequential coupling required for efficient cascade pathways. The coexistence of multiple competing reaction routes further complicates selective control over the desired pathway. Moreover, the short lifetimes and low concentrations of critical intermediates hinder real-time detection and impede mechanistic elucidation. Nevertheless, with advances in cross-scale design strategies and in situ characterization techniques featuring high temporal and spatial resolution, cascade electrocatalysis is poised to offer broad opportunities for future applications (Fig. 8).

Fig. 8 Schematic illustration of future directions for the development of cascade electrocatalysis.

Design of multiscale catalytic systems

Cascade reactions involve multiple elementary steps and diverse intermediates, with overall efficiency constrained by the synergistic interplay of active site spatial distribution, mass transport processes, and electron transfer kinetics. Therefore, constructing catalysts with a multiscale framework is pivotal for enhancing the performance of cascade reactions. Future research will focus on the deep integration of artificial intelligence with experimental methods, employing machine learning models to predict and optimize the structural features of cascade catalysts. High-throughput synthesis and characterization platforms will be employed for rapid screening, thus establishing a closed-loop research and development cycle encompassing computational design, high-throughput fabrication and testing, and machine learning-driven optimization. The ultimate goal is to construct an integrated catalytic system spanning from atom-level active sites and nanoscale mass transport structures to reactor-scale engineering.

Investigation of reaction mechanisms

In cascade electrocatalysis, the dynamic evolution of complex intermediates and multiple reaction pathways presents significant challenges for real-time monitoring and mechanistic analysis. Future advancements may leverage artificial intelligence to predict possible reaction pathways and combine SI-SECM with in situ spectroscopic techniques such as infrared, Raman, and X-ray absorption spectroscopy to track the dynamic evolution of different active sites and the generation and consumption of intermediates in real time. This integrated approach will comprehensively reveal the intrinsic mechanisms and kinetic processes underlying cascade reactions.

Expansion of cascade systems

In single-mode electrocatalysis, driving complex multistep cascade reactions is often limited by low energy efficiency. Future developments will focus on hybrid catalytic systems that couple multiple energy fields, such as electrochemical-photonic, electrochemical-thermal, and electrochemical-biological coupling. By rationally designing and optimizing these multi-energy input, multi-reaction integrated systems, this approach should overcome the constraints of traditional single-mode catalysis, substantially expanding the scope of cascade catalysis for chemical synthesis, environmental remediation, and energy conversion. Such advances may enable higher selectivity, efficiency, and sustainability in complex molecule construction, deep pollutant transformation, and renewable energy utilization.

In summary, cascade electrocatalysis has been extensively explored for carbon–nitrogen resource utilization. With continued development in multiscale catalyst design, reaction mechanism investigation, and the integration of cascade systems, cascade electrocatalysis holds great promise for achieving more efficient resource conversion, thereby advancing the sustainable development of energy and the environment.

Author contributions

Writing – original draft, S. Li.; visualization, H. Li., R. Y., Y. P.; writing – review & editing, Z. J., P. Li.; funding acquisition, Z. J., P. Li.; supervision, P. Li, G. Y.

Conflicts of interest

There are no conflicts to declare.

Data availability

No primary research results, software or code have been included and no new data were generated or analysed as part of this review.

Acknowledgements

P. L. acknowledges funding support from the National Natural Science Foundation of China (22476141), the China Postdoctoral Science Foundation (2025M771235), and the Open Fund of Sichuan Engineering Technology Research Center for High Salt wastewater Treatment and Resource Utilization, Sichuan University of Science and Engineering (SCGCY-2403). G. Y. acknowledges the funding support from the Welch Foundation Award F-1861.

Notes and references

1. Y. Luo, K. Xie, P. Ou, C. Lavallais, T. Peng, Z. Chen, Z. Zhang, N. Wang, X.-Y. Li, I. Grigioni, B. Liu, D. Sinton, J. B. Dunn and E. H. Sargent, Nat. Catal., 2023, 6, 939–948.
2. E. T. A. Mitchard, Nature, 2018, 559, 527–534.
3. P. H. van Langevelde, I. Katsounaros and M. T. M. Koper, Joule, 2021, 5, 290–294.
4. C. Smith, A. K. Hill and L. Torrente-Murciano, Energy Environ. Sci., 2020, 13, 331–344.
5. W. Chen, X. Yang, Z. Chen, Z. Ou, J. Hu, Y. Xu, Y. Li, X. Ren, S. Ye, J. Qiu, J. Liu and Q. Zhang, Adv. Funct. Mater., 2023, 33, 2300512.
6. P. Li, Z. Jin, Z. Fang and G. Yu, Energy Environ. Sci., 2021, 14, 3522–3531.
7. S. Kuang, T. Xiao, H. Chi, J. Liu, C. Mu, H. Liu, S. Wang, Y. Yu, T. J. Meyer, S. Zhang and X. Ma, Angew. Chem., Int. Ed., 2024, 63, e202316772.
8. Y. Xiong, Y. Wang, J. Zhou, F. Liu, F. Hao and Z. Fan, Adv. Mater., 2024, 36, 2304021.
9. Y. Liu, K. Liu, P. Wang, Z. Jin and P. Li, Carbon Neutrality, 2023, 2, 14.
10. M. Yi, H. Li, M. Xie, P. Li, Z. Jin and G. Yu, Sci. China: Chem., 2025, 68, 2322–2342.
11. T. Galimova, M. Ram, D. Bogdanov, M. Fasihi, A. Gulagi, S. Khalili and C. Breyer, Renewable Sustainable Energy Rev., 2023, 183, 113420.
12. W. Zhang, B. Jia, X. Liu and T. Ma, SmartMat, 2022, 3, 5–34.
13. S. Guo, T. Asset and P. Atanassov, ACS Catal., 2021, 11, 5172–5188.
14. Y.-B. Huang, J. Liang, X.-S. Wang and R. Cao, Chem. Soc. Rev., 2017, 46, 126–157.
15. Y. Zhu, X. Cui, H. Liu, Z. Guo, Y. Dang, Z. Fan, Z. Zhang and W. Hu, Nano Res., 2021, 14, 4471–4486.
16. M. Duca, J. R. Weeks, J. G. Fedor, J. H. Weiner and K. A. Vincent, ChemElectroChem, 2015, 2, 1086–1089.
17. R. D. Milton and S. D. Minteer, ChemPlusChem, 2017, 82, 513–521.
18. C. Coelho and M. J. Romao, Protein Sci., 2015, 24, 1901–1911.
19. J. M. Carceller, K. S. Arias, M. J. Climent, S. Iborra and A. Corma, Chem. Soc. Rev., 2024, 53, 7875–7938.
20. C. Zhang, Q. Wang, Z. Li, H. Liu, L. Zhong, J. Liu, Z. Wang, R. Wu, P. Song, W. J. Chen, Z. Qi, C. Yan, L. Song, Q. Yan and C. Lv, Angew. Chem., Int. Ed., 2025, 64, e202502957.
21. X. Gao, C. Zhu and L. Zhang, Chem Catal., 2025, 5, 101544.
22. T. Yan, X. Chen, L. Kumari, J. Lin, M. Li, Q. Fan, H. Chi, T. J. Meyer, S. Zhang and X. Ma, Chem. Rev., 2023, 123, 10530–10583.
23. C. Liu, B. Qiao and T. Zhang, JACS Au, 2024, 4, 4129–4140.
24. H. Yin, F. Dong, H. Su, Z. Zhuang, Y. Wang, D. Wang, Y. Peng and J. Li, ACS Nano, 2023, 17, 25614–25624.
25. X. F. Cheng, J. H. He, H. Q. Ji, H. Y. Zhang, Q. Cao, W. J. Sun, C. L. Yan and J. M. Lu, Adv. Mater., 2022, 34, e2205767.
26. Y. Wang, P. Zhu, R. Wang, K. C. Matthews, M. Xie, M. Wang, C. Qiu, Y. Liu, H. Zhou, J. H. Warner, Y. Liu, H. Wang and G. Yu, ACS Nano, 2024, 18, 26751–26758.
27. Z. Li, Y. Xie, Y. Han, H. Wang, J. Gao, L. Chen, L. Xu, L. Lu, Y. Zhao, E. Wang and G. Li, Nano Res. Energy, 2025, 4, e9120169.
28. P. Li, R. Li, Y. Liu, M. Xie, Z. Jin and G. Yu, J. Am. Chem. Soc., 2023, 145, 6471–6479.
29. C. Wang, Z. Lv, X. Feng, W. Yang and B. Wang, Adv. Energy Mater., 2024, 14, 2400160.
30. J. Xiang, P. Wang, P. Li, M. Zhou, G. Yu and Z. Jin, Angew. Chem., Int. Ed., 2025, 64, e202500644.
31. S. Zhu, K. Liu, Z. Feng, H. Jiang and J. Lin, Nano Res. Energy, 2025, 4, e9120188.
32. Y. Hu, J. Liu, W. Luo, J. Dong, C. Lee, N. Zhang, M. Chen, Y. Xu, D. Wu, M. Zhang, Q. Zhu, E. Hu, D. Geng, L. Zhong and Q. Yan, Chem. Sci., 2024, 15, 8204–8215.
33. G. Xie, W. Guo, Z. Fang, Z. Duan, X. Lang, D. Liu, G. Mei, Y. Zhai, X. Sun and X. Lu, Angew. Chem., Int. Ed., 2024, 63, e202412568.
34. J. Yan, J. Li, P. Liu, H. Huang and W. Song, Green Chem., 2023, 25, 8645–8651.
35. Y. Wang, H. Su, Y. He, L. Li, S. Zhu, H. Shen, P. Xie, X. Fu, G. Zhou, C. Feng, D. Zhao, F. Xiao, X. Zhu, Y. Zeng, M. Shao, S. Chen, G. Wu, J. Zeng and C. Wang, Chem. Rev., 2020, 120, 12217–12314.
36. K. Liu, J. Li, Y. Liu, M. Wang and H. Cui, J. Energy Chem., 2023, 79, 515–534.
37. K. Liu, Z. Sun, X. Peng, X. Liu, X. Zhang, B. Zhou, K. Yu, Z. Chen, Q. Zhou, F. Zhang, Y. Wang, X. Gao, W. Chen and P. Chen, Nat. Commun., 2025, 16, 2167.
38. Y. Cheng, Q. Li, M. I. B. Salaman, C. Wei, Q. Wang, X. Ma, B. Liu and A. B. Wong, J. Am. Chem. Soc., 2025, 147, 12438–12448.
39. M. Melchionna, P. Fornasiero, M. Prato and M. Bonchio, Energy Environ. Sci., 2021, 14, 5816–5833.
40. Y. Zhang, F. Chen, X. Hao, Y. Liu, W. Wu, X. Zhang, Z. Zang, H. Dong, W. Wang, F. Lu, Z. Lu, H. Liu, H. Liu, F. Luo and Y. Cheng, Appl. Catal., B, 2024, 344, 123666.
41. Y. Xu, K. Shi, T. Ren, H. Yu, K. Deng, X. Wang, Z. Wang, H. Wang and L. Wang, Small, 2022, 18, 2203335.
42. H. Liu, L. An, P. Wang, C. Yu, J. Zhang, H. Shin, B. Peng, J. Li, M. Li, H. An, J. Yu, Y. Chen, P. Wang, K.-S. Lee, K. Lalit, Z. Liu, O. K. Farha, W. Huang, J. Z. Liu, L. Qi, K. Xie and E. H. Sargent, Nat. Commun., 2025, 16, 6185.
43. C. Bie, J. Yang, X. Zeng, Z. Wang, X. Sun, Z. Yang, J. Yu and X. Zhang, Small, 2025, 21, e2411184.
44. G. Shi, W. Zhang, Y. Kang, J. Zhao, T. Lu, C. Yang, M. Chang, Y. Shen, X. Gao, J. Wu, Y.-F. Li, K. Cao and L. Zhang, Nat. Commun., 2025, 16, 7359.
45. W. Qiu, P. Wang, Z. Jin, W. Liu, P. Li and Z. Pan, Appl. Catal., B, 2025, 367, 125102.
46. M. Wang, W. Fang, D. Zhu, C. Xia, W. Guo and B. Y. Xia, Chin. J. Catal., 2025, 69, 1–16.
47. A. Ozden, Y. Wang, F. Li, M. Luo, J. Sisler, A. Thevenon, A. Rosas-Hernández, T. Burdyny, Y. Lum, H. Yadegari, T. Agapie, J. C. Peters, E. H. Sargent and D. Sinton, Joule, 2021, 5, 706–719.
48. G. Mei, Y. Lu, X. Yang, S. Chen, X. Yang, L. M. Yang, C. Tang, Y. Sun, B. Y. Xia and B. You, Angew. Chem., Int. Ed., 2024, 63, e202314708.
49. L. Han, Y. Li, X. Wang, Z. Yao, Z. Chen, J. p. Li, T. Tan, S. Y. Lee and Y. Lv, Adv. Energy Mater., 2025, 15, e03056.
50. Y. Liu, X. Su, J. Ding, J. Zhou, Z. Liu, X. Wei, H. B. Yang and B. Liu, Chem. Soc. Rev., 2024, 53, 11850–11887.
51. S. K. Beaumont, Phys. Chem. Chem. Phys., 2020, 22, 18747–18756.
52. Z. Jin, R. Guan, X. Li, D. Yuan and P. Li, Chin. Chem. Lett., 2025, 36, 110506.
53. Q. Xu, J. A. Zamora Zeledon, B. O. Joensen, L. Trotochaud, A. Sartori, L. M. Kaas, A. B. Moss, M. Mirolo, L. Mairena, S. Huynh, S. Garg, S. Helveg, I. Chorkendorff, S. Zhao, B. Seger and J. Drnec, Nat. Nanotechnol., 2025, 20, 889–896.
54. Y.-Y. Lou, Q.-Z. Zheng, S.-Y. Zhou, J.-Y. Fang, O. Akdim, X.-Y. Ding, R. Oh, G.-S. Park, X. Huang and S.-G. Sun, ACS Catal., 2024, 14, 5098–5108.
55. Y. Dai, S. Li, X. Li, K. Liu, Y. Guo, H. Li and B. Jiang, Adv. Funct. Mater., 2025, 35, 2420282.
56. X.-X. Fu, H. Guo, D.-H. Si, H.-J. Zhu, Y.-Y. Lan, Y.-B. Huang and R. Cao, Chem. Sci., 2025, 16, 13503–13513.
57. J. Ding, L. Liu, J. Zhang, Y. Liu, H. Xu, Z. Shen, H. B. Yang, X. Feng, Y. Huang and B. Liu, J. Am. Chem. Soc., 2025, 147, 9601–9609.
58. W. Shen, Y. Ye, Q. Xia and P. Xi, EES Catal., 2025, 3, 10–31.
59. K. Chen, F. Wang, X. Lu, Y. Li and K. Chu, ACS Catal., 2023, 13, 9550–9557.
60. A. Prajapati, C. Hahn, I. M. Weidinger, Y. Shi, Y. Lee, A. N. Alexandrova, D. Thompson, S. R. Bare, S. Chen, S. Yan and N. Kornienko, Nat. Commun., 2025, 16, 2593.
61. J. Song, Z.-X. Qian, J. Yang, X.-M. Lin, Q. Xu and J.-F. Li, ACS Energy Lett., 2024, 9, 4414–4440.
62. Z. Yao, C. Lin, J. Gao, J. Feng, M. Li, W. Yan, W. Zhang and H. Wang, Appl. Catal., B, 2025, 378, 125550.
63. J. Xu, R. Chen, J. Song, S. Liu, Y. Shen and Y. Zhang, Chem. Sci., 2025, 16, 9564–9576.
64. H. Li, Y. Guo and Z. Jin, Carbon Neutrality, 2023, 2, 22.
65. L. He, Z. Cai, C. Wang, L. Yang, W. Yong and Z. Jin, Adv. Funct. Mater., 2025, e14592.
66. Z. Jin, Anal. Chem., 2023, 95, 6477–6489.
67. P. Wang, P. Li, Z. Pan, K. Liu, M. Xie, L. Zhou, M. Zhou, G. Yu and Z. Jin, Nat. Commun., 2025, 16, 5581.
68. R. Yang, L. Yang, W. Yong, P. Li, M. Zhou and Z. Jin, Chem. Sci., 2025, 16, 18482–18495.
69. W. He, J. Zhang, S. Dieckhöfer, S. Varhade, A. C. Brix, A. Lielpetere, S. Seisel, J. R. C. Junqueira and W. Schuhmann, Nat. Commun., 2022, 13, 1129.
70. L. Xiao, G. Wang, X. Huang, S. Zhou, R. Zhou, Y. Jiang, S. Liu, G. Li, H. Zheng, S.-G. Sun and H.-G. Liao, Appl. Catal., B, 2022, 307, 121164.
71. Q. Zhang, Z. Song, X. Sun, Y. Liu, J. Wan, S. B. Betzler, Q. Zheng, J. Shangguan, K. C. Bustillo, P. Ercius, P. Narang, Y. Huang and H. Zheng, Nature, 2024, 630, 643–647.
72. T.-H. Shen, R. Girod, J. Vavra and V. Tileli, J. Electrochem. Soc., 2023, 170, 056502.
73. Y. Yao, Z. Sun, T. Li, Z. Zhao, Z. Li, X. Lu, Y. Wan, Y. Fan and Z. Chen, ACS Nano, 2025, 19, 18947–18975.
74. X. Peng, L. Zeng, D. Wang, Z. Liu, Y. Li, Z. Li, B. Yang, L. Lei, L. Dai and Y. Hou, Chem. Soc. Rev., 2023, 52, 2193–2237.
75. Y. Zhou, G. Xing, C. Sun, Z. Chen, S. Li, R. Yang, M. Chen, P. Zhang, C. Feng, A. Abudula and G. Guan, Adv. Funct. Mater., 2025, e15635.
76. W. Qiu, Y. Liu, M. Xie, Z. Jin, P. Li and G. Yu, EES Catal., 2024, 2, 202–219.
77. X. Liang, H. Zhu, X. Yang, S. Xue, Z. Liang, X. Ren, A. Liu and G. Wu, Small Struct., 2022, 4, 2200202.
78. T. Yang, M. Kuang and J. Yang, Nano Res., 2023, 16, 8670–8683.
79. J. Li, Z. Wang, C. McCallum, Y. Xu, F. Li, Y. Wang, C. M. Gabardo, C.-T. Dinh, T.-T. Zhuang, L. Wang, J. Y. Howe, Y. Ren, E. H. Sargent and D. Sinton, Nat. Catal., 2019, 2, 1124–1131.
80. X. Kong, J. Zhao, J. Ke, C. Wang, S. Li, R. Si, B. Liu, J. Zeng and Z. Geng, Nano Lett., 2022, 22, 3801–3808.
81. L. Lv, H. Tan, Y. Kong, B. Tang, Q. Ji, Y. Liu, C. Wang, Z. Zhuang, H. Wang, M. Ge, M. Fan, D. Wang and W. Yan, Angew. Chem., Int. Ed., 2024, 63, e202401943.
82. Y. Wan, M. Zheng, W. Yan, J. Zhang and R. Lv, Adv. Energy Mater., 2024, 14, 2303588.
83. Y. Zhang, Z. Li, K. Chen, X. Yang, H. Zhang, X. Liu and K. Chu, Adv. Energy Mater., 2024, 14, 2402309.
84. J. M. Moore and A. R. Fout, Chem. Sci., 2025, 16, 840–845.
85. S. Tian, R. Wu, H. Liu, C. Yan, Z. Qi, P. Song, W. J. Chen, L. Song, Z. Wang and C. Lv, Angew. Chem., Int. Ed., 2025, 64, e202510665.
86. J. Liu, Y. Xu, R. Duan, M. Zhang, Y. Hu, M. Chen, B. Han, J. Dong, C. Lee, L. S. R. Kumara, O. Seo, J. Tseng, T. Watanabe, Z. Liu, Q. Zhu, J. Xu, M.-F. Ng, D. Wu and Q. Yan, Nat. Commun., 2025, 16, 3595.
87. Z. Wu, Y. Song, H. Guo, F. Xie, Y. Cong, M. Kuang and J. Yang, Interdiscip. Mater., 2024, 3, 245–269.
88. B. Kang, B. Xu, Z. Chen, F. Li and Y. Wang, Appl. Catal., B, 2025, 360, 124528.
89. X. You, J. Xu, Z. Zhuang, J. Xia, S. Wang, H. Wei, Y. Li, Y. Cai, H. Xiang and B. Yu, Nano Res., 2024, 17, 4815–4824.
90. M. Xie, S. Tang, Z. Li, M. Wang, Z. Jin, P. Li, X. Zhan, H. Zhou and G. Yu, J. Am. Chem. Soc., 2023, 145, 13957–13967.
91. Z. Liu, C. Xing, Y. Shan, M. Ma, S. Wu, R. Ge, Q. Xue and J. Tian, Chem. Sci., 2025, 16, 7010–7017.
92. C.-H. Shen, Y. Zhao, H. N. Nam, L. Zhu, Q. M. Phung, V. Austen, M. Kim, D. Jiang, X. Wei, T. Yokoshima, C.-W. Kung and Y. Yamauchi, Chem. Sci., 2025, 16, 7026–7038.
93. L. Qin, F. Sun, Z. Gong, G. Ma, Y. Chen, Q. Tang, L. Qiao, R. Wang, Z.-Q. Liu and Z. Tang, ACS Nano, 2023, 17, 12747–12758.
94. K. Liu, H. Li, M. Xie, P. Wang, Z. Jin, Y. Liu, M. Zhou, P. Li and G. Yu, J. Am. Chem. Soc., 2024, 146, 7779–7790.
95. Z. Jin, K. Liu, Z. Pan, X. Shan, F. Cai, D. Yang, P. Li, G. Yu and M. Zhou, J. Am. Chem. Soc., 2025 DOI:10.1021/jacs.5c15278.
96. C. Du, J. P. Mills, A. G. Yohannes, W. Wei, L. Wang, S. Lu, J.-X. Lian, M. Wang, T. Guo, X. Wang, H. Zhou, C.-J. Sun, J. Z. Wen, B. Kendall, M. Couillard, H. Guo, Z. Tan, S. Siahrostami and Y. A. Wu, Nat. Commun., 2023, 14, 6142.
97. J. Li, Y. Chen, B. Yao, W. Yang, X. Cui, H. Liu, S. Dai, S. Xi, Z. Sun, W. Chen, Y. Qin, J. Wang, Q. He, C. Ling, D. Wang and Z. Zhang, J. Am. Chem. Soc., 2024, 146, 5693–5701.
98. J. Zhong, H. Duan, M. Cai, Y. Zhu, Z. Wang, X. Li, Z. Zhang, W. Qu, K. Zhang, D. Han, D. Cheng, Y. Shen, M. Xie, E. Cortes and D. Zhang, Angew. Chem., Int. Ed., 2025, 64, e202507956.
99. W. Ye, Y. Yao, X. Wei, M. Xu, S. Zhao, W. Wang, G. Jia, F. Dai, P. Gao, X. Lu, X. Li, B. Xi, N. Wang and S. Xiong, Angew. Chem., Int. Ed., 2025, 64, e202509303.
100. B. Kim, Y. C. Tan, Y. Ryu, K. Jang, H. G. Abbas, T. Kang, H. Choi, K.-S. Lee, S. Park, W. Kim, P.-P. Choi, S. Ringe and J. Oh, ACS Energy Lett., 2023, 8, 3356–3364.
101. Y. Zhang, P. Li, C. Zhao, G. Zhou, F. Zhou, Q. Zhang, C. Su and Y. Wu, Sci. Bull., 2022, 67, 1679–1687.
102. S. A. Chala, R. Liu, E. O. Oseghe, S. T. Clausing, C. Kampf, J. Bansmann, A. H. Clark, Y. Zhou, I. Lieberwirth, J. Biskupek, U. Kaiser and C. Streb, ACS Catal., 2024, 14, 15553–15564.
103. C. Jin, Y. Lin, Y. Wang, J. Shi, R. Li, Y. Liu, Z. Yue, K. Leng, Y. Zhao, Y. Wang, X. Han, Y. Qu and J. Bai, Adv. Mater., 2025, 37, 2412658.
104. W. Du, Z. Sun, S. Shang, K. Chen, X. Yang and K. Chu, ACS Nano, 2024, 18, 27718–27726.
105. Y. Gao, J. Wang, M. Sun, Y. Jing, L. Chen, Z. Liang, Y. Yang, C. Zhang, J. Yao and X. Wang, Angew. Chem., Int. Ed., 2024, 63, e202402215.
106. K. Chen, D. Ma, Y. Zhang, F. Wang, X. Yang, X. Wang, H. Zhang, X. Liu, R. Bao and K. Chu, Adv. Mater., 2024, 36, e2402160.
107. X. Wu, Y. Chen, B. Tang, Q. Yan, D. Wu, H. Zhou, H. Wang, H. Zhang, D. He, H. Li, J. Zeng, L. Lu, S. Yang and T. Ma, Nat. Commun., 2025, 16, 8785.
108. J. Lim, C.-Y. Liu, J. Park, Y.-H. Liu, T. P. Senftle, S. W. Lee and M. C. Hatzell, ACS Catal., 2021, 11, 7568–7577.
109. Z. Li, M. Zheng, C. Yan, D. Yang, R. Yang, C. Zhang, H. Liu, P. Song, C. Yin, Z. Qi, D. Liu, X. Zhou, L. Song, C. Lv and G. Yu, Nat. Commun., 2025, 16, 8940.
110. S. Bhowmick, A. Adalder, A. Maiti, S. Kapse, R. Thapa, S. Mondal and U. K. Ghorai, Chem. Sci., 2025, 16, 4806–4814.
111. Y. Fu, S. Wang, Y. Wang, P. Wei, J. Shao, T. Liu, G. Wang and X. Bao, Angew. Chem., Int. Ed., 2023, 62, e202303327.
112. S. Chen, Z. Zhu, K. Song, H. Zhang, D. Luo, T. Cao, Y. Zou, C. Liu, L. Gan, D. Zhang, Y. Han and J. Huang, J. Am. Chem. Soc., 2025, 147, 36494–36507.
113. W. Ye, Y. Zhang, L. Chen, F. Wu, Y. Yao, W. Wang, G. Zhu, G. Jia, Z. Bai, S. Dou, P. Gao, N. Wang and G. Wang, Angew. Chem., Int. Ed., 2024, 63, e202410105.
114. Z. Li, Z. Shi, Y. Ou, L. Zhong, C. Yan, C. Zhang, K. Song, H. Liu, D. Liu, P. Song, C. Yin, Z. Qi, L. Song and C. Lv, Angew. Chem., Int. Ed., 2025, 64, e202510287.
115. C. Zhang, Q. Zhou, Z. Li, C. Yan, H. Liu, D. Liu, L. Song, Q. Yan and C. Lv, Angew. Chem., Int. Ed., 2025, 64, e202507869.
116. X. Gao, C. Zhu, C. Yang, G. Shi, Q. Xu and L. Zhang, ACS Catal., 2024, 14, 17871–17878.
117. Y. Ma, L. Guo, L. Chang, W. Guo, T. Zhou, F. Hao, W. Su, J. Zhou, G. Wang, M. Shao, J. Yu, J. Yin, Y. Wang, F. Liu, A. Zhang, K. Qian, J. Wang, X. Zhang, W. Zhou, S. Chu, C. Ling, L. Gan, Z. Guo and Z. Fan, Nat. Commun., 2025, 16, 7632.
118. Z. Li, Q. Wang, L. Zhong, C. Yan, Z. Shi, Y. Ou, Y. Shang, C. Zhang, S. Tian, H. Liu, D. Liu, P. Song, Z. Qi, L. Song and C. Lv, Mater. Today, 2025, 85, 49–59.
119. Y. Chen, X. Liu, S. Li, J. Li, M. Fan and S. Shu, Adv. Funct. Mater., 2025, e21409.
120. Y. Dang, R. Zhang, S. Ren, S. Pitchaimuthu, S. Liu, R. Xing and X. Yang, Chem. Eng. J., 2025, 520, 166370.
121. Y. Tang, S. Liu, C. Guo, Y. Liu and Z. Tang, Sustainable Energy Fuels, 2023, 7, 5039–5045.
122. Y. Shi, Y. Wang, J. Yu, Y. Chen, C. Fang, D. Jiang, Q. Zhang, L. Gu, X. Yu, X. Li, H. Liu and W. Zhou, Adv. Energy Mater., 2023, 13, 2203506.
123. Z. Zhang, X. Ma, Y. Song, X. Yang, Q. Fang, Y. Yamauchi and J. Tang, Angew. Chem., Int. Ed., 2025, 64, e202511704.
124. C. Zhu, L. Zhou, Z. Zhang, C. Yang, G. Shi, S. Zhao, H. Gu, J. Wu, X. Gao, Y. Li, K. Liu, S. Dai and L. Zhang, Chem, 2022, 8, 3288–3301.
125. C. Zhu, Z. Zhang, R. Qiao, C. Yang, S. Zhao, G. Shi, X. Gao, H. Gu, K. Liu and L. Zhang, J. Phys. Chem. C, 2023, 127, 3470–3477.
126. Z.-x. Yang, X. Wen, L.-j. Gao, J. Zhang, R.-p. Wei, X.-m. Pan and G.-m. Xiao, Catal. Commun., 2023, 174, 106595.
127. Y. Ma, J. Yu, M. Sun, B. Chen, X. Zhou, C. Ye, Z. Guan, W. Guo, G. Wang, S. Lu, D. Xia, Y. Wang, Z. He, L. Zheng, Q. Yun, L. Wang, J. Zhou, P. Lu, J. Yin, Y. Zhao, Z. Luo, L. Zhai, L. Liao, Z. Zhu, R. Ye, Y. Chen, Y. Lu, S. Xi, B. Huang, C. S. Lee and Z. Fan, Adv. Mater., 2022, 34, e2110607.
128. X. Gao, Y. Jiang, J. Liu, G. Shi, C. Yang, Q. Xu, Y. Yun, Y. Shen, M. Chang, C. Zhu, T. Lu, Y. Wang, G. Du, S. Li, S. Dai and L. Zhang, Nat. Commun., 2024, 15, 10331.
129. J. Tan, Q. Shen, X. Jin, M. Wang, B. A, W. Chen, Z. Wei, L. Zhang and J. Shi, J. Am. Chem. Soc., 2025, 147, 23635–23642.
130. Z. Cai, N. Cao, F. Zhang, X. Lv, K. Wang, Y. He, Y. Shi, H. Bin Wu and P. Xie, Appl. Catal., B, 2023, 325, 122310.
131. Y. Chen, X. Y. Li, Z. Chen, A. Ozden, J. E. Huang, P. Ou, J. Dong, J. Zhang, C. Tian, B. H. Lee, X. Wang, S. Liu, Q. Qu, S. Wang, Y. Xu, R. K. Miao, Y. Zhao, Y. Liu, C. Qiu, J. Abed, H. Liu, H. Shin, D. Wang, Y. Li, D. Sinton and E. H. Sargent, Nat. Nanotechnol., 2024, 19, 311–318.
132. Y. Yu, D. Wang, Y. Hong, T. Zhang, C. Liu, J. Chen, G. Qin and S. Li, Chem. Commun., 2022, 58, 11163–11166.
133. C. Lv, C. Lee, L. Zhong, H. Liu, J. Liu, L. Yang, C. Yan, W. Yu, H. H. Hng, Z. Qi, L. Song, S. Li, K. P. Loh, Q. Yan and G. Yu, ACS Nano, 2022, 16, 8213–8222.
134. R. Qi, Q. Jiang, L. Deng, X. Yu, B. Shi, M. Zhong, Y. Wang and X. Lu, Chem. Sci., 2025, 16, 378–385.
135. M. Li, C. Qi, J. Xu, R. Zou, L. Wang, W. Jiang, Y. Fan, P. Qiu and W. Luo, ACS Nano, 2025, 19, 11309–11322.
136. Y. Lu, H. Li, H. Sun, J. Zhao, Y. Zhang, Y. Wang, C. Zhu, D. Gao, Y. Tuo, J. Zeng, D. Chen and Z. Yan, ACS Catal., 2024, 14, 14744–14753.
137. D. Zhang, D. Jiang, B. Mao, Y. Liu, Q. Chen, H. Li, L. Xing, H. Huang, W. Zhang, W. Shi and Z. Kang, Angew. Chem., Int. Ed., 2025, 64, e202511259.
138. W. Huang, W. Luo, J. Liu, B.-E. Jia, C. Lee, J. Dong, L. Yang, B. Liu and Q. Yan, ACS Nano, 2024, 18, 20258–20267.
139. L. Chen, M. Li and J.-N. Zhang, Nano Res., 2024, 17, 7880–7899.
140. B. Zhang, Y. Hou, S. Wang, S. Zhou, Z. Li, Y. Hou, L. Lei and B. Yang, Appl. Catal., B, 2025, 379, 125727.
141. J. Li, Q. Zhu, A. Chang, S. Cheon, Y. Gao, B. Shang, H. Li, C. L. Rooney, L. Ren, Z. Jiang, Y. Liang, Z. Feng, S. Yang, L. Robert Baker and H. Wang, Nat. Nanotechnol., 2025, 20, 515–522.
142. J. Chen, D. Wang, X. Yang, W. Cui, X. Sang, Z. Zhao, L. Wang, Z. Li, B. Yang, L. Lei, J. Zheng, L. Dai and Y. Hou, Angew. Chem., Int. Ed., 2023, 62, e202215406.
143. F. Yu, X. Liu, L. Liao, G. Xia and H. Wang, Small, 2023, 19, e2301558.
144. H. Pan, J. Wu, X. Lu, Y. Li, Q. Zhang, J. Ling, Y. Wang and B. Min, ACS Appl. Energy Mater., 2025, 8, 8299–8310.
145. X. Yu, S. Zeng, R. Li, X. Dong, Q. Cao, L. Li and X. Guo, Chem. Eng. J., 2025, 519, 165559.
146. M. Liu, X. Lu, R. He, Y. Zhou, Y. Liu, L. Chen, X. Suo, J. Hou, Q. Ke, Z. Chen, P. Feng and C. Wan, Chem. Eng. J., 2025, 523, 168293.
147. T. Möller, M. Filippi, S. Brückner, W. Ju and P. Strasser, Nat. Commun., 2023, 14, 5680.
148. H. Chi, Z. Liang, S. Kuang, Y. Jin, T. Xiao, J. Lin, D. Han, L. Wang, S. Zhang and X. Ma, J. Am. Chem. Soc., 2025, 147, 32640–32648.
149. A. N. Biswas, Z. Xie, R. Xia, S. Overa, F. Jiao and J. G. Chen, ACS Energy Lett., 2022, 7, 2904–2910.
150. P. Wang, X. Wang, S. Chandra, A. Lielpetere, T. Quast, F. Conzuelo and W. Schuhmann, Angew. Chem., Int. Ed., 2025, 64, e202422882.
151. J. Feng, A. Badreldin and Y. Li, Energy Fuels, 2025, 39, 21175–21225.
152. G. Wu, Y. Song, Q. Zheng, C. Long, T. Fan, Z. Yang, X. Huang, Q. Li, Y. Sun, L. Zuo, S. Lei and Z. Tang, Adv. Energy Mater., 2022, 12, 2202054.
153. H. Li, H. Li, P. Wei, Y. Wang, Y. Zang, D. Gao, G. Wang and X. Bao, Energy Environ. Sci., 2023, 16, 1502–1510.
154. J. Weidner, C. N. Tchassem, D. Das, R. Zerdoumi, G. Lu, X. Wang, M. Muhler, N. Sikdar and W. Schuhmann, ChemElectroChem, 2025, 12, e202400664.
155. Z. Xie, E. Huang, S. Garg, S. Hwang, P. Liu and J. G. Chen, Nat. Catal., 2024, 7, 98–109.
156. H. Lv, X. Dong, R. Li, C. Zeng, X. Zhang, Y. Song, H. Liu, J. Shao, N. Ta, Q. Zhao, Q. Fu, J. Xiao, G. Wang and X. Bao, Nat. Chem., 2025, 17, 695–702.
157. S. Garg, Z. Xie, A. X. Lam and J. G. Chen, ACS Energy Lett., 2024, 9, 2990–2996.
158. G. Lee, H. J. Jo, J. Choi, M. F. Guzman, Y. Shan, H. K. D. Le, J. Feijoo, N. Soland, D. S. Clark and P. Yang, Proc. Natl. Acad. Sci. U. S. A., 2025, 122, e2512565122.
159. Y. Pu, Y. Wang, G. Wu, X. Wu, Y. Lu, Y. Yu, N. Chu, X. He, D. Li, R. J. Zeng and Y. Jiang, Environ. Sci. Technol., 2024, 58, 7445–7456.
160. H. Cui, W. Liu, C. Ma, P. Shiri, Z. Zhu, H. Jiang, D. Li and L. Zhang, Appl. Catal., B, 2024, 350, 123946.

---