Bending two-dimensional Cu(I)-based coordination networks to inverse electrocatalytic HER/CO₂RR selectivity

Abstract

Two-dimensional (2D) coordination polymers have attracted great attention for catalysis because of their abundant exposed active sites. Here, we show that bending the local structure of 2D coordination polymers can inverse the electrocatalytic selectivity. A series of ultrathin nanosheets based on isoreticular/isostructural/isomeric 2D Cu(I) triazolate coordination polymers were successfully prepared. By introducing an amino group on the triazolate ligand, the shape of the 2D layer transforms from planar into wavy, which inverses the electrocatalytic selectivity from the HER (selectivity ∼ 80%) to the CO₂RR (selectivity ∼ 76%, C₂H₄ up to 52%). Computational simulations showed that the wavy structure allows the amino groups to form attractive hydrogen-bonding interactions with the key reaction intermediates of the CO₂RR for C₂H₄ and steric hindrance with the key reaction intermediates of the HER, giving lower and higher reaction energy barriers, respectively.

---

Dong-Dong Zhou

Dr Dong-Dong Zhou was born in 1990. He received his BSc degree (2011) from South China Agricultural University and his PhD degree (2016) in inorganic chemistry under the supervision of Professor Jie-Peng Zhang from Sun Yat-Sen University. Then, he became an associate researcher in the Chen & Zhang Group at Sun Yat-Sen University. Since 2019, he has been an associate professor in the School of Chemistry at Sun Yat-Sen University. His current research interest focuses on the design and synthesis of porous coordination polymers or metal–organic frameworks, especially for their dynamic structural changes playing roles in applications of adsorption, separation, catalysis, etc.

Introduction

The electrochemical CO₂ reduction reaction (CO₂RR) is considered a viable carbon-neutralization strategy.^1–5 The hydrogen evolution reaction (HER) is the main competing reaction of the CO₂RR. Therefore, CO₂RR catalysts should show not only high product selectivity but also low HER selectivity.^6–12 Besides the coordination geometry and/or electronic structure,^13–16 the supramolecular microenvironment of the metal center also plays an important role in catalysis.¹⁷ Compared to traditional inorganic materials, coordination polymers (CPs) have defined and diverse structures with designability as well as tunable functionality, which facilitates the exploration of structure–activity relationships in catalysis. In this regard, coordination complexes could offer distinct advantages over traditional inorganic materials.^18–22

Compared with three-dimensional (3D) bulk materials, 2D nanomaterials with abundant exposed active sites have demonstrated exceptional catalytic performances.^11,23,24 Ultrathin nanosheets of 2D coordination polymers (CPs) combining the advantages of CPs and 2D materials have attracted increasing attention for catalysis.^25–29 However, the supramolecular microenvironment of 2D CPs has been scarcely considered for catalysis. Because coordination bonds are weaker than conventional covalent bonds, to maintain the 2D structure and/or facilitate exfoliating, these 2D CPs usually exhibit planar structures rather than more complex ones.

Recently, we reported high and tunable CO₂RR performances of a series of isoreticular (nbo-a) 3D Cu(I)-based porous frameworks, i.e., [Cu(detz)] (MAF-2, Hdetz = 3,5-diethyl-1,2,4-triazole) and its analogs consisting of different ligand side groups (methyl, ethyl, and propyl).³⁰ With even smaller ligand side groups, [Cu(tz)] (Htz = 1,2,4-triazole)³¹ and [Cu(atz)] (Hatz = 3-amino-1,2,4-triazole)³² can retain the coordination modes of MAF-2 analogs, i.e., three-coordinated Cu(I) ions and triazolate ligands, as well as planar Cu₂(tz)₂ units, but they adopt the 2D sql-a network topology (Fig. 1).³³ If these 2D CPs can be exfoliated into ultrathin nanosheets, high CO₂RR performances similar to those of 3D porous MAF-2 analogs may be achieved. More importantly, because the pores of the sql-a network are too small for amino groups, the 2D networks of [Cu(tz)] and [Cu(atz)] are planar and wavy in their crystal structures, respectively. In other words, the layer structure of [Cu(atz)] exhibits 3D characteristics of molecular complexes, enzymes, and metal–organic frameworks.

Fig. 1 Crystal structures of 2D CPs. (a and b) [Cu(tz)] and (c and d) [Cu(atz)] viewed perpendicularly (a and c) and parallelly (b and d) to the coordination layers.

In this work, we synthesize ultrathin nanosheets of not only isoreticular [Cu(tz)] and [Cu(atz)] but also isostructural/isomeric solid-solution framework structures containing different concentrations of amino groups and demonstrate that the bending of the layer structure is critical for enhancing the CO₂RR and avoiding the HER.

Results and discussion

Syntheses and characterization

The solution reaction of [Cu(NH₃)₂]OH with Htz or Hatz at room temperature gave white microcrystalline samples of [Cu(tz)] or [Cu(atz)], respectively (Fig. S1 and S2†). SEM of [Cu(tz)] or [Cu(atz)] samples shows shale-like morphology, indicating that they could potentially be exfoliated into ultrathin nanosheets (Fig. S3†). Simple ultrasonic exfoliation treatments of microcrystalline [Cu(tz)] or [Cu(atz)] in methanol gave the corresponding nanosheets. Considering a common chemical formula of [Cu(tz)_x%(atz)_100−x%], the nanosheet samples prepared from [Cu(tz)] and [Cu(atz)] are denoted as (p-A_xH_100−x, x = 0, i.e., p-A₀H₁₀₀) and (w-A_xH_100−x, x = 100, i.e., w-A₁₀₀H₀) respectively (p/w for planar/wavy and A/H for amino/hydrogen).

Transmission electron microscopy (TEM) and atomic force microscopy (AFM) showed ultrathin nanosheets with thicknesses of ca. 4.5 and 4.9 nm for p-A₀H₁₀₀ and w-A₁₀₀H₀, respectively (Fig. 2 and S4†). Considering that the thickness of each layer of [Cu(tz)] and [Cu(atz)] is 3.1 and 3.6 Å, respectively (Fig. 1), the ultrathin nanosheets contained ∼14 layers of the 2D coordination networks. X-ray photoelectron spectroscopy (XPS) showed characteristic peaks of Cu(I) at 914.8 eV, 932.6 eV and 952.6 eV, but no satellite peaks of Cu(II) appeared. Since the characteristic peaks of Cu(0) and Cu(I) cannot be distinguished, the 914 eV is further attributed to Cu(I) by the Cu LMM region (Fig. S5†).^30,34 Powder X-ray diffraction (PXRD) of p-A₀H₁₀₀ and w-A₁₀₀H₀ showed only one or two of the strongest diffraction peaks of [Cu(tz)] or [Cu(atz)], without any typical inorganic species (Fig. S1 and S2†), respectively, indicating that p-A₀H₁₀₀/w-A₁₀₀H₀ should have a similar coordination structure to those of [Cu(tz)]/[Cu(atz)]. Moreover, these diffraction peaks are significantly broadened, being typical for ultrathin nanosheets.^26,35,36 In CO₂-saturated KHCO₃ solution (0.1 M, electrolyte for the CO₂RR), their PXRD patterns can remain unchanged for at least one week, indicating that they are suitable for the CO₂RR (Fig. S1 and S2†).

Fig. 2 Morphology of ultrathin nanosheets. TEM images of (a) p-A₀H₁₀₀ and (b) w-A₁₀₀H₀ (insets: the Tyndall effect of a colloidal solution). AFM images of (c) p-A₀H₁₀₀ and (d) w-A₁₀₀H₀ (insets: the corresponding height profiles).

Electrocatalytic CO₂RR performances

The CO₂RR performances of p-A₀H₁₀₀ and w-A₁₀₀H₀ (coated on a glassy carbon electrode) were investigated in 0.1 M KHCO₃ solution (Fig. 3a and S6†). Under saturated CO₂, their current densities were obviously higher than those in Ar, indicating catalytic activities for the CO₂RR. Moreover, the current densities of w-A₁₀₀H₀ were much higher than those of p-A₀H₁₀₀, indicating that the wavy structure and/or the amino groups are beneficial for the CO₂RR (Fig. 3a). Interestingly, p-A₀H₁₀₀ and w-A₁₀₀H₀ showed similar and high hydrophilicity (water contact angles < 20°) but very different CO₂ affinities (Fig. 3a and S7†). The contact angles for CO₂ gas bubbles and electrolytes of p-A₀H₁₀₀ and w-A₁₀₀H₀ were determined to be 135 ± 1° and 85 ± 1°, respectively. In other words, p-A₀H₁₀₀ is aerophobic and w-A₁₀₀H₀ is aerophilic.^37,38 To the best of our knowledge, hydrophilic materials are always aerophobic and hydrophobic materials are generally aerophilic.³⁹

Fig. 3 Electrocatalytic performances of p-A₀H₁₀₀ and w-A₁₀₀H₀. (a) Linear sweep voltammetry curves (Ar-saturated conditions were used for comparison). (b) Faradaic efficiency (FE) of gas products at different potentials. (c) Comparison of typical performances. (d) Comparison of FE (C₂H₄) of benchmark catalysts. (e) Chronoamperometry of w-A₁₀₀H₀ at −1.3 V.

The different affinities toward H₂O and CO₂ can be explained by Grand Canonical Monte Carlo (GCMC) simulations and periodic density functional theory (PDFT) calculations (Fig. S8 and S9†). The results showed that H₂O molecules evenly distribute on the surfaces of both p-A₀H₁₀₀ (C–H⋯O 3.53–3.62 Å) and w-A₁₀₀H₀ (N–H⋯O 3.07 Å and C–H⋯O 3.48–3.73 Å) with similar binding energies of −16.1 and −18.9 kJ mol⁻¹, respectively. On the other hand, CO₂ molecules interact very differently with p-A₀H₁₀₀ and w-A₁₀₀H₀. For w-A₁₀₀H₀, CO₂ molecules concentrate in the groove sections of the wavy layer surface and simultaneously interact with Cu(I) and –NH₂ groups (Cu⋯O 3.13 Å and N–H⋯O 3.18 Å) with a relatively strong binding energy of −24.7 kJ mol⁻¹. For p-A₀H₁₀₀, CO₂ evenly distributed on the flat layer surface (C–H⋯O 3.71–3.84 Å) with a weak binding energy of −12.2 kJ mol⁻¹ (Fig. S8†).

Gas chromatography (GC) and ¹H nuclear magnetic resonance (NMR) showed that most CO₂RR products are gases (i.e., H₂, CO, CH₄ and C₂H₄) (Fig. 3b, S10–S15 and Tables S1–S4†). For p-A₀H₁₀₀, the H₂ selectivity remained ∼80% over a wide potential range (−1.1 V to −1.5 V), and the total selectivity of CO₂RR products was ∼20%. In contrast, w-A₁₀₀H₀ exhibited high CO₂RR selectivity (∼76%) and low HER selectivity (∼24%) under the same conditions. Moreover, the C₂H₄ selectivity (44–52%) is significantly higher than those of other products, such as CO (4–24%) and CH₄ (3–24%). It is noteworthy that the C₂H₄ selectivity of w-A₁₀₀H₀ can reach 51.8 ± 0.6% at −1.3 V, which is 26-fold higher than that of p-A₀H₁₀₀ (2.0 ± 0.2%) under the same conditions and 22-fold higher than the highest value of p-A₀H₁₀₀ (2.4% at −1.1 V) and comparable to the highest values of reported catalysts (Fig. 3c, d and Table S5†).^40–45 Isotope labelling experiments confirmed that all the CO₂RR products originated from CO₂ rather than decomposition of the electrocatalyst (Fig. S16†).

Chronoamperometry tests at −1.3 V showed that the current density and C₂H₄ selectivity of w-A₁₀₀H₀ and p-A₀H₁₀₀ can remain unchanged for ca. 6 h (Fig. 3e and S17†). After chronoamperometry at −1.3 V for 8 h, PXRD showed that there was no obvious change before and after the CO₂RR (Fig. S18†), which revealed that the coordination structure should be maintained; TEM showed that the morphology of the nanosheets was similar to that before catalysis and there was no occurrence of agglomeration or particles (Fig. S4†), which proved that there were no inorganic substances such as Cu or its derivatives present before and after the reaction; XPS combined with X-ray absorption near-edge structure (XANES) showed that the valence state of Cu did not change, and the N 1s region indicated that the intensity of Cu–N did not diminish after the CO₂RR (Fig. S19 and S20†), suggesting that the Cu–N bonds were not broken.^46,47 Therefore, the degraded catalysis performances after 6 h can be ascribed to the falling-off and/or poisoning effects rather than degradation of the catalysts (Fig. S21†), which have been widely observed in the literature.^30,48,49

The operando electrochemical attenuated total reflection Fourier transform infrared (ATR-FTIR) spectra of both p-A₀H₁₀₀ and w-A₁₀₀H₀ showed characteristic peaks (Fig. S22†) of *COOH, *CO, and *CHO (intermediates for CH₄) and CO*–*CHO (intermediates for C₂H₄).^43,47 In particular, comparing the ATR-FTIR spectra of p-A₀H₁₀₀ and w-A₁₀₀H₀ at −1.3 V for 800 s, the peaks of p-A₀H₁₀₀ are significantly weaker than those of w-A₁₀₀H₀ (Fig. S23†). Furthermore, the characteristic peaks of C₂H₄ intermediates in w-A₁₀₀H₀ are significantly stronger than those of CH₄, being consistent with the experimental results.

To identify the roles of the amino group and layer bending, p-A₀H₁₀₀ and w-A₁₀₀H₀ were post-synthetically modified by ligand exchange with Htz or Hatz, respectively, i.e., change x in [Cu(tz)_x%(atz)_100−x%] (Fig. S24, S25 and Table S6†). PXRD patterns of the modified nanosheet products, i.e., p-A₁₂H₈₈, p-A₂₅H₇₅, w-A₂₅H₇₅ and w-A₅₀H₅₀, were similar to those of the parent nanosheets, and the characteristic PXRD peaks did not shift, indicating that the local structures of nanosheets changed little (Fig. S26†). TEM, AFM, and XPS further confirmed the retention of nanosheet morphologies and local coordination structures (Fig. S27–S29†). Note that p-A₂₅H₇₅ and w-A₂₅H₇₅ are supramolecular isomers, which have not been reported for ultrathin nanosheets. PDFT calculations showed that the planar structure of p-A₀H₁₀₀ can be retained when 25% of tz⁻ was replaced by atz⁻, the wavy structure of w-A₁₀₀H₀ can be retained when 75% of atz⁻ was replaced by tz⁻, and higher ligand exchanging ratios resulted in irregular layer deformation, possibly implying some unknown kinetic factors (Fig. S25 and 30†).⁵⁰ These results indicated that the small pores of a planar sql-a network can only accommodate half an amino group, i.e., two pores for one amino group.³³

Electrocatalysis tests clearly demonstrated that p-A_xH_100−x and w-A_xH_100−x preferred the CO₂RR and HER, respectively (Fig. 4a, S31–S36 and Tables S7–S10†). For p-A_xH_100−x, when x increased from 0 to 25, the HER selectivity slightly decreased (<3.4%) and the CO₂RR selectivity slightly increased (<3.7%), indicating that the concentration of amino groups in the planar structures plays a minor role in the selectivity. The isomers p-A₂₅H₇₅ and w-A₂₅H₇₅ offer a straightforward/reliable comparison of the roles of the amino group and the layer shape. Possessing the same chemical compositions and the same concentration of amino groups, w-A₂₅H₇₅ showed 5.3% higher CH₄ selectivity, 20% higher C₂H₄ selectivity, and 25% lower HER selectivity, indicating the critical role of the wavy structure for CO₂RR/HER selectivity. For w-A_xH_100−x, when x increased from 25 to 100, the CO and CH₄ selectivities decreased slightly (<4.7%), whereas the C₂H₄ selectivity increased rapidly (>30%) and H₂ selectivity decreased rapidly (>31%) (Fig. 4a). These results indicated that, when the layers are wavy, the amino groups also play important roles in improving not only CO₂RR/HER selectivity but also C₂H₄ selectivity.

Fig. 4 Selectivity and mechanisms for p-A_xH_100−x and w-A_xH_100−x. (a) CO₂RR/HER selectivity at −1.3 V. (b) Comparison of ΔG_max of the CO₂RR/HER.

Mechanism investigations

The tuneable CO₂RR/HER performances can be elucidated using PDFT calculations, which showed that the rate-determining steps (RDSs) of the CO₂RR (C₂H₄) and HER are CO*–*CO → CO*–*CHO and H₂O*–* → H*–*OH (Fig. S37–S46†), respectively, similar to many literature studies.^30,51–59 The ΔG_max values of the CO₂RR/HER were calculated to be 1.36/1.10 and 1.17/1.34 eV for p-A₀H₁₀₀ and w-A₁₀₀H₀ (Fig. 4b and S37–S39†), meaning that the energy barrier of the CO₂RR is higher than that of the HER for p-A₀H₁₀₀, while w-A₁₀₀H₀ showed an opposite trend, which is consistent with the experimental results. The ΔG_max values of the CO₂RR/HER were 1.32/1.12 eV for p-A₂₅H₇₅, which were slightly lower/higher than those for p-A₀H₁₀₀ (Fig. 4b, S40 and S41†), indicating that increasing the concentration of the amino group in the planar structure has little effect on improving CO₂RR/HER selectivity. For w-A₂₅H₇₅, the ΔG_max values of the CO₂RR/HER were 1.28/1.23 eV, which were significantly lower/higher than those for p-A₂₅H₇₅, indicating that the wavy structure is critical for improving CO₂RR/HER selectivity (Fig. 4b and S40 and S42†).

To further illustrate the role of wavy structure in CO₂RR/HER selectivity, a hypothetical w-A₀H₁₀₀ structure (fixed during simulation, otherwise relaxed to p-A₀H₁₀₀) was constructed to perform PDFT calculations, and the results showed that the ΔG_max values of the CO₂RR/HER were calculated to be 1.30/1.21 eV, which were similar to those of p-A₀H₁₀₀ rather than w-A₁₀₀H₀ (Fig. S43 and S44†). This result indicates that a high CO₂RR/HER selectivity requires not only the wavy structure but also the amino groups.

For the RDSs, the simulated intermediate structures showed that the amino groups interact weakly with the adsorbed CO and H₂O molecules (Fig. 5 and S47†). In addition, the energies of the reactants (i.e., CO*–*CO and H₂O*–*) are quite similar for all five simulated structures, indicating that the amino groups play trivial roles on the electronic structure of Cu(I), being consistent with the XPS results (Fig. S29†). Furthermore, the electrostatic potential (ESP) and the Mulliken population analysis of the five structures in both planar and wavy structures are similar, indicating that they possess similar coordination affinity (Fig. S48 and S49†).^60,61 Therefore, the differences in ΔG_max values should mainly arise from the product structures (i.e., CO*–*CHO and H*–*OH). Similar to the literature results,^55,56,62,63 the free energies of CO*–*CHO and H*–*OH were higher than those of CO*–*CO and H₂O*–*, respectively. For CO*–*CHO, the amino groups can form attractive hydrogen-bonding interactions with the CHO fragments of w-A₁₀₀H₀ (N–H⋯O 3.02 Å, H⋯O 2.00 Å, ∠N–H⋯O 166.7°) and w-A₂₅H₇₅ (N–H⋯O 3.12 Å, H⋯O 2.13 Å, ∠N–H⋯O 161.5°), which decrease the system energies to give low CO₂RR barriers (Fig. 5a and b). In contrast, for H*–*OH, the amino groups showed obvious steric repulsion with the adsorbed H atoms of w-A₁₀₀H₀ (H⋯H 2.05 Å) and w-A₂₅H₇₅ (H⋯H 2.08 Å), which increased the system energies to give high HER barriers (Fig. 5c and d). For planar structures p-A₀H₁₀₀ and p-A₂₅H₇₅, as well as amino-free structure w-A₀H₁₀₀, such attractive/repulsive effects cannot be formed. Therefore, the inversed CO₂RR/HER selectivity from p-A₀H₁₀₀ to w-A₁₀₀H₀ can be explained by the cooperation of the wavy structure and amino groups.

Fig. 5 Key intermediates of the CO₂RR/HER for p-A₀H₁₀₀ and w-A₁₀₀H₀. (a–d) Reactant/product structures of the RDSs of the CO₂RR (a and b) and HER (c and d) for p-A₀H₁₀₀ (a and c) and w-A₁₀₀H₀ (b and d).

Note that w-A₁₀₀H₀ has larger attractive/repulsive interactions for CO₂RR/HER intermediates than w-A₂₅H₇₅, respectively, which can be attributed to the higher curvature degree of the layers (Fig. S50 and S51†). In other words, although experimental techniques such as TEM and AFM cannot distinguish the slightly different curvature degrees of the nanosheet samples, computational simulations indicated that the concentration of amino groups can fine tune the curvature degree and supramolecular microenvironment of the 2D coordination layers, as well as the CO₂RR/HER selectivity.

Conclusions

In summary, a series of ultrathin nanosheets based on isoreticular/isostructural/isomeric 2D CPs have been synthesized. By systematically tuning the concentration of the amino group of the organic ligand, the ultrathin nanosheets adopt either planar or wavy structures, which show predominant electrocatalytic CO₂RR or HER selectivity, respectively, and a high C₂H₄ selectivity of 52% is achieved. Computational simulations showed that amino groups not only play an important role in determining the shape of layer structures but also simultaneously promote the CO₂RR and restrict the HER by interacting with the key reaction intermediates with attractive and repulsive interactions, respectively. These results demonstrate the delicate role of the supramolecular microenvironment for catalysis and the potential of 2D CPs for precise structural modulation and development of new catalysts. This work might also inspire future practical research to solve relatively practical issues in electrode preparation or cell devices.

Data availability

The data supporting this article have been included as part of the ESI,† and more raw data are available from the corresponding authors upon reasonable request.

Author contributions

D. D. Z. and J. P. Z. designed the research. K. Z. performed syntheses and measurements. D. Y. H. and X. W. Z. performed computational simulations. X. X. X., Z. J. L. and H. Y. performed XRD, FTIR and XPS analyses. J. X. W., D. Y. L. and L. L. Z. performed SEM and TEM analyses. L. G. performed AFM analyses. K. Z., D. D. Z. and J. P. Z. wrote the manuscript.

Conflicts of interest

The authors declare no conflict of interest.

Acknowledgements

This work was supported by the National Key Research and Development Program of China (2021YFA1500400) and the National Natural Science Foundation of China (22090061, 21821003, 22071272, 21975290 and 22231012).

Notes and references

1. Y. Y. Birdja, E. Pérez-Gallent, M. C. Figueiredo, A. J. Göttle, F. Calle-Vallejo and M. T. M. Koper, Nat. Energy, 2019, 4, 732–745.
2. P. De Luna, C. Hahn, D. Higgins, S. A. Jaffer, T. F. Jaramillo and E. H. Sargent, Science, 2019, 364, 3506.
3. H. Shen, Z. Gu and G. Zheng, Sci. Bull., 2019, 64, 1805–1816.
4. X.-D. Zhang, T. Liu, C. Liu, D.-S. Zheng, J.-M. Huang, Q.-W. Liu, W.-W. Yuan, Y. Yin, L.-R. Huang, M. Xu, Y. Li and Z.-Y. Gu, J. Am. Chem. Soc., 2023, 145, 2195–2206.
5. D. D. Zhu, J. L. Liu and S. Z. Qiao, Adv. Mater., 2016, 28, 3423–3452.
6. J. Feng, L. Wu, S. Liu, L. Xu, X. Song, L. Zhang, Q. Zhu, X. Kang, X. Sun and B. Han, J. Am. Chem. Soc., 2023, 145, 9857–9866.
7. M. B. Ross, P. De Luna, Y. Li, C.-T. Dinh, D. Kim, P. Yang and E. H. Sargent, Nat. Catal., 2019, 2, 648–658.
8. W. Wang, D. Chen, F. Li, X. Xiao and Q. Xu, Chem, 2024, 10, 86–133.
9. Y. Wang, P. Han, X. Lv, L. Zhang and G. Zheng, Joule, 2018, 2, 2551–2582.
10. A. R. Woldu, P. Talebi, A. G. Yohannes, J. Xu, X. D. Wu, S. Siahrostami, L. Hu and X. C. Huang, Angew. Chem., Int. Ed., 2023, 135, e202301621.
11. Z. Sun, T. Ma, H. Tao, Q. Fan and B. Han, Chem, 2017, 3, 560–587.
12. S. Nitopi, E. Bertheussen, S. B. Scott, X. Liu, A. K. Engstfeld, S. Horch, B. Seger, I. E. L. Stephens, K. Chan, C. Hahn, J. K. Nørskov, T. F. Jaramillo and I. Chorkendorff, Chem. Rev., 2019, 119, 7610–7672.
13. D.-H. Nam, O. S. Bushuyev, J. Li, P. De Luna, A. Seifitokaldani, C.-T. Dinh, F. P. García de Arquer, Y. Wang, Z. Liang, A. H. Proppe, C. S. Tan, P. Todorović, O. Shekhah, C. M. Gabardo, J. W. Jo, J. Choi, M.-J. Choi, S.-W. Baek, J. Kim, D. Sinton, S. O. Kelley, M. Eddaoudi and E. H. Sargent, J. Am. Chem. Soc., 2018, 140, 11378–11386.
14. P. Shao, W. Zhou, Q. L. Hong, L. Yi, L. Zheng, W. Wang, H. X. Zhang, H. Zhang and J. Zhang, Angew. Chem., Int. Ed., 2021, 60, 16687–16692.
15. W. Zhang, S. Liu, Y. Yang, H. Qi, S. Xi, Y. Wei, J. Ding, Z. J. Wang, Q. Li, B. Liu and Z. Chen, Angew. Chem., Int. Ed., 2023, 62, e202219241.
16. H. Zhong, M. Ghorbani-Asl, K. H. Ly, J. Zhang, J. Ge, M. Wang, Z. Liao, D. Makarov, E. Zschech, E. Brunner, I. M. Weidinger, J. Zhang, A. V. Krasheninnikov, S. Kaskel, R. Dong and X. Feng, Nat. Commun., 2020, 11, 1409.
17. J. Li, H. Huang, W. Xue, K. Sun, X. Song, C. Wu, L. Nie, Y. Li, C. Liu, Y. Pan, H.-L. Jiang, D. Mei and C. Zhong, Nat. Catal., 2021, 4, 719–729.
18. P.-Q. Liao, J.-Q. Shen and J.-P. Zhang, Coord. Chem. Rev., 2018, 373, 22–48.
19. C. Wang, Z. Lv, W. Yang, X. Feng and B. Wang, Chem. Soc. Rev., 2023, 52, 1382–1427.
20. Q. Wang and D. Astruc, Chem. Rev., 2019, 120, 1438–1511.
21. Q.-J. Wu, J. Liang, Y.-B. Huang and R. Cao, Acc. Chem. Res., 2022, 55, 2978–2997.
22. J. Lee, O. K. Farha, J. Roberts, K. A. Scheidt, S. T. Nguyen and J. T. Hupp, Chem. Soc. Rev., 2009, 38, 1450–1459.
23. C. Tan, X. Cao, X.-J. Wu, Q. He, J. Yang, X. Zhang, J. Chen, W. Zhao, S. Han, G.-H. Nam, M. Sindoro and H. Zhang, Chem. Rev., 2017, 117, 6225–6331.
24. M. Zhao, Y. Huang, Y. Peng, Z. Huang, Q. Ma and H. Zhang, Chem. Soc. Rev., 2018, 47, 6267–6295.
25. L. Cao and C. Wang, ACS Cent. Sci., 2020, 6, 2149–2158.
26. Y. Quan, G. Lan, Y. Fan, W. Shi, E. You and W. Lin, J. Am. Chem. Soc., 2020, 142, 1746–1751.
27. R.-J. Wei, P.-Y. You, H. Duan, M. Xie, R.-Q. Xia, X. Chen, X. Zhao, G.-H. Ning, A. I. Cooper and D. Li, J. Am. Chem. Soc., 2022, 144, 17487–17495.
28. S. Zhao, Y. Wang, J. Dong, C.-T. He, H. Yin, P. An, K. Zhao, X. Zhang, C. Gao, L. Zhang, J. Lv, J. Wang, J. Zhang, A. M. Khattak, N. A. Khan, Z. Wei, J. Zhang, S. Liu, H. Zhao and Z. Tang, Nat. Energy, 2016, 1, 1–10.
29. J. Huang, Y. Li, R. K. Huang, C. T. He, L. Gong, Q. Hu, L. Wang, Y. T. Xu, X. Y. Tian, S. Y. Liu, Z. M. Ye, F. Wang, D. D. Zhou, W. X. Zhang and J. P. Zhang, Angew. Chem., Int. Ed., 2018, 130, 4722–4726.
30. L. L. Zhuo, P. Chen, K. Zheng, X. W. Zhang, J. X. Wu, D. Y. Lin, S. Y. Liu, Z. S. Wang, J. Y. Liu, D. D. Zhou and J. P. Zhang, Angew. Chem., Int. Ed., 2022, 61, e202204967.
31. J.-P. Zhang, Y.-Y. Lin, X.-C. Huang and X.-M. Chen, J. Am. Chem. Soc., 2005, 127, 5495–5506.
32. D. Chen, Y.-J. Liu, Y.-Y. Lin, J.-P. Zhang and X.-M. Chen, CrystEngComm, 2011, 13, 3827.
33. J.-P. Zhang, Y.-B. Zhang, J.-B. Lin and X.-M. Chen, Chem. Rev., 2012, 112, 1001–1033.
34. W. Ma, S. Xie, T. Liu, Q. Fan, J. Ye, F. Sun, Z. Jiang, Q. Zhang, J. Cheng and Y. Wang, Nat. Catal., 2020, 3, 478–487.
35. L. Cao, T. Wang and C. Wang, Chin. J. Chem., 2018, 36, 754–764.
36. C. F. Holder and R. E. Schaak, ACS Nano, 2019, 13, 7359–7365.
37. G. Liu, W. S. Y. Wong, M. Kraft, J. W. Ager, D. Vollmer and R. Xu, Chem. Soc. Rev., 2021, 50, 10674–10699.
38. Z.-Z. Niu, F.-Y. Gao, X.-L. Zhang, P.-P. Yang, R. Liu, L.-P. Chi, Z.-Z. Wu, S. Qin, X. Yu and M.-R. Gao, J. Am. Chem. Soc., 2021, 143, 8011–8021.
39. K. Lv, C. Teng, M. Shi, Y. Yuan, Y. Zhu, J. Wang, Z. Kong, X. Lu and Y. Zhu, Adv. Funct. Mater., 2018, 28, 1802339.
40. Y. Chen, Z. Fan, J. Wang, C. Ling, W. Niu, Z. Huang, G. Liu, B. Chen, Z. Lai, X. Liu, B. Li, Y. Zong, L. Gu, J. Wang, X. Wang and H. Zhang, J. Am. Chem. Soc., 2020, 142, 12760–12766.
41. J.-N. Lu, J. Liu, L. Zhang, L.-Z. Dong, S.-L. Li and Y.-Q. Lan, J. Mater. Chem. A, 2021, 9, 23477–23484.
42. J. Wang, Y. Zhang, Y. Ma, J. Yin, Y. Wang and Z. Fan, ACS Mater. Lett., 2022, 4, 2058–2079.
43. K. Yao, Y. Xia, J. Li, N. Wang, J. Han, C. Gao, M. Han, G. Shen, Y. Liu, A. Seifitokaldani, X. Sun and H. Liang, J. Mater. Chem. A, 2020, 8, 11117–11123.
44. H.-L. Zhu, J.-R. Huang, P.-Q. Liao and X.-M. Chen, ACS Cent. Sci., 2022, 8, 1506–1517.
45. R. Wang, J. Liu, L.-Z. Dong, J. Zhou, Q. Huang, Y.-R. Wang, J.-W. Shi and Y.-Q. Lan, CCS Chem., 2023, 5, 2237–2250.
46. L. Zhang, X.-X. Li, Z.-L. Lang, Y. Liu, J. Liu, L. Yuan, W.-Y. Lu, Y.-S. Xia, L.-Z. Dong, D.-Q. Yuan and Y.-Q. Lan, J. Am. Chem. Soc., 2021, 143, 3808–3816.
47. H.-L. Zhu, H.-Y. Chen, Y.-X. Han, Z.-H. Zhao, P.-Q. Liao and X.-M. Chen, J. Am. Chem. Soc., 2022, 144, 13319–13326.
48. U. O. Nwabara, E. R. Cofell, S. Verma, E. Negro and P. J. A. Kenis, ChemSusChem, 2020, 13, 855–875.
49. W. Gao, Y. Xu, H. Xiong, X. Chang, Q. Lu and B. Xu, Angew. Chem., Int. Ed., 2023, 62, e202313798.
50. P. Deria, J. E. Mondloch, O. Karagiaridi, W. Bury, J. T. Hupp and O. K. Farha, Chem. Soc. Rev., 2014, 43, 5896–5912.
51. C. Choi, S. Kwon, T. Cheng, M. Xu, P. Tieu, C. Lee, J. Cai, H. M. Lee, X. Pan, X. Duan, W. A. Goddard and Y. Huang, Nat. Catal., 2020, 3, 804–812.
52. N. Danilovic, R. Subbaraman, D. Strmcnik, K. C. Chang, A. P. Paulikas, V. R. Stamenkovic and N. M. Markovic, Angew. Chem., Int. Ed., 2012, 124, 12663–12666.
53. X. Qin, T. Vegge and H. A. Hansen, J. Am. Chem. Soc., 2023, 145, 1897–1905.
54. X. Zou and J. Gu, Chin. J. Catal., 2023, 52, 14–31.
55. S. Chen, Z. Zhang, W. Jiang, S. Zhang, J. Zhu, L. Wang, H. Ou, S. Zaman, L. Tan, P. Zhu, E. Zhang, P. Jiang, Y. Su, D. Wang and Y. Li, J. Am. Chem. Soc., 2022, 144, 12807–12815.
56. J. Jiao, Q. Yuan, M. Tan, X. Han, M. Gao, C. Zhang, X. Yang, Z. Shi, Y. Ma, H. Xiao, J. Zhang and T. Lu, Nat. Commun., 2023, 14, 6164.
57. H. Liu, Q. Huang, W. An, Y. Wang, Y. Men and S. Liu, J. Energy Chem., 2021, 61, 507–516.
58. M. He, W. An, Y. Wang, Y. Men and S. Liu, Small, 2021, 17, 2104445.
59. Z. Q. C. Li, H. M. Sun, Y. j. Yang and C.-P. Li, Chin. J. Struct. Chem., 2022, 41, 2211084–2211099.
60. J. D. Yi, D. H. Si, R. Xie, Q. Yin, M. D. Zhang, Q. Wu, G. L. Chai, Y. B. Huang and R. Cao, Angew. Chem., Int. Ed., 2021, 60, 17108–17114.
61. J. Zhang, Y. Chen, F. Xu, Y. Zhang, J. Tian, Y. Guo, G. Chen, X. Wang, L. Yang, Q. Wu and Z. Hu, Small, 2023, 19, 2301577.
62. X. Mao, W. Gong, Y. Fu, J. Li, X. Wang, A. P. O'Mullane, Y. Xiong and A. Du, J. Am. Chem. Soc., 2023, 145, 21442–21453.
63. J. Sang, P. Wei, T. Liu, H. Lv, X. Ni, D. Gao, J. Zhang, H. Li, Y. Zang, F. Yang, Z. Liu, G. Wang and X. Bao, Angew. Chem., Int. Ed., 2021, 134, e202114238.

---

Footnotes

† Electronic supplementary information (ESI) available. See DOI: https://doi.org/10.1039/d4ta01982b

‡ These authors contributed equally to this work.

---