English

• Phenol, one of common-used industrial chemicals, is widely applied in the manufacture of pharmaceutical compounds, phenolic resins, dyes and plastics [1-3]. However, conventional three-step cumene production process in current industry suffers from high energy consumption, low conversion rate and large quantities of by-products [4]. Therefore, it is imperative to develop a novel strategy to solve the above shortcomings. Recently, one-step process as an attractive route in phenol production has been developed for the straight and selective oxidation of benzene to phenol, with the aid of environmentally friendly oxidants such as N₂O, O₂ and H₂O₂ [5-10]. Among them, H₂O₂ is commonly considered as a promising oxidant because of its advantages on low cost and environment friendly process with H₂O as the only by-product. However, direct utilization of H₂O₂ as an oxidant often yields unsatisfied benzene-to-phenol efficiency, mainly due to the lack of suitable platforms to enrich hydrogen peroxide and benzene and further promote the oxidizing reaction.

  Based on this, much progress has been made to develop co-catalysts for improving the benzene-to-phenol activity and selectivity with H₂O₂ as oxidant, such as Fe-based MOFs (MIL-101, 30.6% conversion rate) [11], Fe-doped and Cu-grafted ordered silica SBA-15 composite (Cu/Fe-SBA-15, 35.5% conversion rate and 89.8% selectivity) [12], copper single-atom catalyst (Cu-SA/HCNS, 86.0% conversion rate and 96.7% selectivity) [13]. However, there is no catalyst capable of achieving complete conversion of benzene and single selectivity of phenol, despite the importance of these indicators in industrial production.

  Because of its structural diversity and adjustability, metal-organic frameworks (MOFs) can be used as a very promising photocatalyst, which have been widely used in water splitting, CO₂ reduction, degradation of pollutants, and selective oxidation of organics [14-17]. Herein, a novel photocatalyst, CuO@CN composite, has been prepared by high-temperature calcination of precursor synthesizing by in situ loading Cu-based MOFs onto the surface of tubular carbon nitride (TCN) under solvothermal method. The CuO@CN composite material as the catalyst possesses the follow advantages: (1) Metal with the high conductivity is the optimal candidate to modify CN, which can effectively promote the charge separation and transfer for CN. (2) CuO nanoparticles are uniformly loaded on the surface of CN, which is conductive to increase the interfacial contact area and further to enhance the catalytic efficiency. (3) The heterojunction structure of CuO and CN can effectively inhibit the recombination of charge carriers and improve the utilization efficiency of charge carriers [18], thus greatly improving the catalytic activity of the CuO@CN composites. Benefiting from these above advantages, the CuO@CN composite photocatalyst is expected to exhibit excellent catalytic performance in selective oxidation of benzene to phenol, being of a great potential for practical application. This work paves a new avenue for designing and preparing effectively catalyst based on MOFs materials and CN [19-21].

  Firstly, the characterization analyses are carried out to as-prepared composites. According to the scanning electron microscopy (SEM) images (Fig. 1a), the Cu-MOFs features a regular octahedral geometry which consistent with previous reports [22-24]. The supramolecular precursor for TCN has a hexagonal structure with a radius of 30 µm (Fig. 1b). After uniformly loading the Cu-MOFs onto the surface of the TCN rod, the size of the Cu-MOFs is obvious decreased (Fig. 1c). In addition, we synthesized MOFs/TCN loaded with different contents of MOFs. It can be seen from the SEM (Fig. S2 in Supporting information), when the amount of Cu(OAC)₂·3H₂O and H₃BTC increases, the surface of TCN is modified with more MOFs with more small size. After thermal calcination, the obtained CuO@CN exhibits the hollow tubular morphology with uniform filamentous structure in inner surface and solid particles loaded on the outer surface (Fig. 1d). For clarity, magnified images have been collected and show more clearly structural features (Fig. S3 in Supporting information). To further confirm the structure and morphology, transmission electron microscopy (TEM) images of the CuO@CN sample have been carried out. As displayed in Fig. 1e, CuO nanoparticles are uniformly loaded on the surface of CN, and the morphology of Cu-MOFs is well maintained. We can observe that the average particle size of CuO is approximate 15 nm (Fig. S4 in Supporting information). In the high-resolution transmission electron microscopy (HRTEM) of CuO@CN, there is a clear observation of the lattice fringe of 0.232 nm that matches well with the (111) plane of CuO (Fig. 1f). This indicates that CuO nanoparticles have been successfully supported on the surface of CN. The corresponding elemental mappings of CuO@CN composite materials are also delineated. As expected, C, O, Cu and N atoms are equally dispersived in the photocatalyst (Fig. S5 in Supporting information), which further prove the successful loading of CuO on the CN.

  Figure 1

  

  Figure 1.  (a–c) SEM photographs of MOF, TCN and MOFs/TCN. (d) SEM photographs of CuO@CN. (e) TEM photographs of CuO@CN. (f) HRTEM photographs of CuO@CN.

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  Powder X-ray diffraction (PXRD) patterns further certify the above analysis. The PXRD patterns of CuO@CN reveal the simultaneous presence of the CN and CuO nanoparticles (Figs. 2a and b). The peaks located at 2θ values of 32.5° and 35.5° can be indexed to the (110) and (111) facets of CuO, respectively. The low intensity of the diffraction peak of CuO results from the low content of the loaded CuO. Meanwhile, Fourier transmission infrared (FT-IR) spectra (Fig. S1 in Supporting information) are traced to obtain further structural information on the as-synthesized catalysts. The broad peak at 2900~3200 cm⁻¹ attributes to the N-H and O-H bands, due to the presence of residual amino groups and absorbed H₂O molecules, respectively. The absorption band ranging from 1200 cm⁻¹ to 1600 cm⁻¹ is the characteristic vibration signal of the aromatic CN heterocycles [25], indicating that loading CuO nanoparticles did not change the structure of CN.

  Figure 2

  

  Figure 2.  (a) XRD patterns of the synthesized MOFs, TCN and MOFs/TCN. (b) XRD patterns of the synthesized CuO and CuO@CN. XPS spectra of CuO@CN: (c) Cu 2p, (d) O 1s, (e) C 1s and (f) N 1s.

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  To probe the elemental composition and the oxidation state, the systematic analysis on X-ray photoelectron spectroscopy (XPS) of CuO@CN has been subsequently performed. As displayed in Fig. 2c, the Cu 2p spectrum in CuO@CN consists of three peaks located at 934.2 eV and 953.7 eV, attributing to Cu 2p_3/2 and Cu 2p_1/2 of CuO, respectively. The peak at 941.9 eV belongs to Cu 2p_3/2 satellite peak of CuO. These results reveal that CuO is successfully loaded onto the CN surface, consistent with the XRD and TEM results. In Fig. 2d, the high-resolution XPS spectrum of O 1s spectrum is deconvoluted into two main peaks at 530.7 eV and 532.4 eV, which are assigned to Cu-O and C-O bond, respectively. For C 1s spectrum, three main peaks located at 284.65, 288.0 and 289.6 eV have been deconvoluted and assigned to C-C, C-N and C-O bond, respectively (Fig. 2e). The high-resolution XPS spectrum of O 1s and C 1s of pure CN are shown in Figs. S6 and S7 (Supporting information). Fig. 2f shows that N 1s spectrum of CN has three peaks at 398.5, 399.6 and 400.7 eV, which are allocated to the C-N=C, N-(C)₃ and C-N-H bonds. The N 1s spectrum of the CuO@CN shows three pinnacles of C-N=C, N-(C)₃ and C-N-H bonds located at 398.9, 399.5 and 400.3 eV, respectively. It is noticeable that the C-N=C peak of CuO@CN moves towards higher binding energy but C-N-H peak moves towards lower binding energy in comparison to them of CN. These results demonstrate the strong mutual interaction and electronic transfer between CuO and CN, which is beneficial to improve the catalytic activity of composites.

  In the process of photocatalysis, it is significant influence factor that the separation of electron-hole pairs and their rapid migration toward the active center of the catalysts [26-28]. As displayed in Fig. 3a, the photoluminescence (PL) intensity of CuO@CN decreases significantly in comparison with that of CN, which should be evaluated to the rapid transfer of photogenerated electrons from CN to CuO and thus suppressing the recombination of electron-hole pairs, which greatly improves the utilization rate of photogenerated electrons and thus improves the catalytic activity of the catalyst. In the Nyquist plots (Fig. 3b), the diameter of the semicircle for CuO@CN is smaller than those for CN and CuO, suggesting that the CuO@CN composite has the most efficient charge transfer. In other words, CuO nanoparticles anchored on CN can effectively increase visible-light harvesting and promote the separation and transfer of photo-induced electron-hole pairs [29, 30].

  Figure 3

  

  Figure 3.  (a) Steady-state PL spectra of CN and CuO@CN. (b) Nyquist plots of CN, CuO and CuO@CN.

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  Subsequently, the catalytic performance of CuO@CN composite is evaluated by employing selective oxidation of benzene to phenol in one-step process. Without the CuO@CN catalyst, little benzene is converted under the illumination of AM 1.5 for 12 h (Table S1 in Supporting information, entry 1). For the CN as photocatalyst, the conversion rate and the selectivity increase to 8.5% and 94.4%, respectively (Table S1, entry 2). Remarkably, CuO@CN composite exhibits obviously improving photocatalytic performance. Concurrently, CuO nanoparticles anchored on CN can effectively promote the separation and transfer of photo-induced electron-hole pairs. The above results show that CuO and CN have a good synergistic effect. When the reaction was conducted under the illumination of AM 1.5 for 12 h, the conversion and selectivity were increased to 99.9% and 99.1%, respectively, which are significantly higher than those of CN (Fig. 4a and Table S1). Even though in the absence of visible light, the CuO@CN catalyst shows 16.4% of benzene conversion with 98.0% of phenol selectivity in the dark and 63.7% of benzene conversion with 93.1% of phenol selectivity at 80 ℃ for 12 h. The state-of-the-art benzene conversion rate and phenol selectivity indicate that the as-prepared CuO@CN composite is an ideal benzene-to-phenol photocatalyst which is of practical values in industry.

  Figure 4

  

  Figure 4.  (a) Conversion rate and selectivity of CuO@CN at different conditions. (b) The recycle performance of CuO@CN. (c) XRD patterns of CuO@CN and after recycle. (d) Comparison of catalytic activity of CuO@CN with previously reported catalysts for selective oxidation of benzene to phenol [11-13, 31-40].

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  In addition to the remarkable catalytic properties, the high stability of CuO@CN composite is an outstanding advantage for industrial application. Fig. 4b shows that even after five cycles, the conversion rate of benzene and selectivity of phenol still remain high levels, with indiscernible decline in benzene conversion rate and phenol selectivity. After five cycles of reaction, the results of ICP analysis show that the content of copper did not decrease significantly from 1.18% to 0.90% (Table S2 in Supporting information). These results strongly show that CuO@CN composite is a very active and stable catalyst for the oxidation of benzene to phenol. Additionally, the PXRD pattern of CuO@CN photocatalyst shows the unchanged structure after five cycles (Fig. 4c). This further proves that CuO@CN is a promising catalyst for the oxidation of benzene to phenol (Fig. 4d and Table S3 in Supporting information). Furthermore, the application scope of this catalytic system is explored by using a variety of benzene derivatives contain electron-withdrawing or electron-donating substituents under the same reaction conditions. As summarized in Table 1, the CuO@CN composite also exhibits good activity for oxidation of benzene derivatives. When using chlorobenzene and bromobenzene as the substrate, both the conversion rate of benzene and the selectivity of phenol reach up to 99.0% (Table 1, entries 2 and 3). The main products are ortho- and para-substituted phenol. A similar effect is observed on methylbenzene (Table 1, entry 4). When using nitrobenzene with electron-withdrawing substituents as the substrate, there is a little decrease on the conversion rate of benzene (90.5%) with ortho-, meta- and para-substituted phenol as the main products (Table 1, entry 5). The above results indicate that CuO@CN catalyst have good catalytic activity and functional group tolerance for the oxidation of benzene to phenol containing different electron-withdrawing or electron-donating substituents.

  Table 1

  

  Table 1.  Selective oxidation of benzene to phenol.

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  Then, 5, 5-dimethyl-1-pyrroline-N-oxide (DMPO) is used as hydroxyl radical trapping agent [41]. Fig. S8 (Supporting information) shows an EPR spectrum observed during the reaction of benzene with H₂O₂ in the presence of CuO@CN and DMPO under the illumination of AM 1.5 and in the dark. The results show four typical signals for the DMPO-^•OH adduct under AM 1.5 illumination, which confirms the formation of ^•OH radicals during the photocatalytic reaction. This shows that selective oxidation of benzene to phenol over CuO@CN follows a ^•OH radicals mediated oxygenation pathway. Therefore, CuO@CN catalyst has the superior electron trapping ability and can effectively inhibit the recombination of electrons and holes, which is the significant reason to interpret the excellent photocatalytic activity of CuO@CN. Based on the above analysis, the mechanism for photocatalytic selective oxidation of benzene to phenol over CuO@CN has been proposed. First, efficient excitation of CuO@CN by the illumination of AM 1.5 takes place and the photoresponse simultaneously forms electron and hole charge carriers. Then, the photogenerated electrons can react with H₂O₂ to form ^•OH radicals. The last step, the photogenerated ^•OH takes part in the selective oxidation of benzene to phenol. Meanwhile, the holes can directly react with benzene to form phenol [34, 39]. The possible mechanism diagram for photocatalytic selective oxidation of benzene to phenol over CuO@CN is shown in Scheme S1 (Supporting information). Thus, CuO@CN shows a superior performance for the selective oxidation of benzene to phenol.

  In summary, a CuO@CN composite with uniform dispersion of CuO nanoparticles on the surface of CN has been successfully designed and fabricated by the high temperature calcination of Cu-MOFs/TCN precursor. CuO nanoparticles tightly contact with CN, which promotes the transfer of photogenerated electrons from CN to CuO, effectively inhibits the recombination of electrons and holes, as well as shows excellent catalytic activity in the selective oxidation of benzene to phenol. Remarkable, the benzene conversion rate and phenol selectivity achieve 99.9% and 99.1%, respectively, suggesting a great potential for practical application. Our powerful results show that Cu-MOFs/TCN-derived CuO@CN materials would endow them with better change to be applied in more areas of catalysis.

  Declaration of competing interest

  We declare that we have no financial and personal relationships with other people or organizations that can inappropriately influence our work.

  Acknowledgments

  This work was supported by National Natural Science Foundation of China (Nos. 21771061, U2001219, 52103225, 51973051 and 81961138010) and the Outstanding Youth Fund of Heilongjiang Province (No. JQ 2020B002), National Key R & D Program of China (No. SQ2021YFE012298).

  Supplementary materials

  Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.cclet.2022.05.004.

  
  
• 1. [1]

     P. Borah, X. Ma, K.T. Nguyen, Y. Zhao, Angew. Chem. Int. Ed. 51 (2012) 7756–7761. doi: 10.1002/anie.201203275

  2. [2]

     S. Fukuzumi, K. Ohkubo, Asian J. Org. Chem. 4 (2015) 836–845. doi: 10.1002/ajoc.201500187

  3. [3]

     T. Tsuji, A.A. Zaoputra, Y. Hitomi, et al., Angew. Chem. Int. Ed. 56 (2017) 7779–7782. doi: 10.1002/anie.201702291

  4. [4]

     S.S. Niwa, M. Eswaramoorthy, J. Nair, et al., Science 295 (2002) 105–107. doi: 10.1126/science.1066527

  5. [5]

     M.L. Bols, H.M. Rhoda, B.E.R. Snyder, et al., Dalton Trans. 49 (2020) 14749–14757. doi: 10.1039/D0DT01857K

  6. [6]

     C. Ouyang, Y. Li, J. Li, Catalysts 9 (2019) 44. doi: 10.3390/catal9010044

  7. [7]

     Y.Y. Gu, X.H. Zhao, G.R. Zhang, H.M. Ding, Y.K. Shan, Appl. Catal. A: Gen. 328 (2007) 150–155. doi: 10.1016/j.apcata.2007.06.002

  8. [8]

     W. Wang, G. Ding, T. Jiang, et al., Green Chem. 15 (2013) 1150–1154. doi: 10.1039/c3gc00084b

  9. [9]

     D. Wei, L. Huang, H. Liang, et al., Catal. Sci. Technol. 11 (2021) 5931–5937. doi: 10.1039/D1CY00890K

  10. [10]

      P. Basyach, A.K. Guha, S. Borthakur, et al., J. Mater. Chem. A 8 (2020) 12774–12789. doi: 10.1039/D0TA03729J

  11. [11]

      D. Wang, M. Wang, Z. Li, ACS Catal. 5 (2015) 6852–6857. doi: 10.1021/acscatal.5b01949

  12. [12]

      Y. Wu, X. Zhang, F. Wang, et al., Ind. Eng. Chem. Res. 60 (2021) 8386–8395. doi: 10.1021/acs.iecr.1c00388

  13. [13]

      T. Zhang, D. Zhang, X. Han, et al., J. Am. Chem. Soc. 140 (2018) 16936–16940. doi: 10.1021/jacs.8b10703

  14. [14]

      Y. Liu, H. Cheng, M. Cheng, et al., Chem. Eng. J. 417 (2021) 127914. doi: 10.1016/j.cej.2020.127914

  15. [15]

      Y. Liu, C.S. Tang, M. Cheng, et al., ACS Catal. 11 (2021) 13374–13396. doi: 10.1021/acscatal.1c03866

  16. [16]

      H.D. Liu, M. Cheng, Y. Liu, et al., Coord. Chem. Rev. 458 (2022) 214428. doi: 10.1016/j.ccr.2022.214428

  17. [17]

      W. Zhang, Y. Tian, H. He, et al., Nat. Sci. Rev. 7 (2020) 1702–1725. doi: 10.1093/nsr/nwaa021

  18. [18]

      Y. Chen, J.F. Li, P.Y. Liao, et al., Chin. Chem. Lett. 31 (2020) 1516–1519. doi: 10.1016/j.cclet.2019.12.013

  19. [19]

      Q. Li, S.X. Li, J.Q. Sha, et al., ACS Appl. Nano Mater. 4 (2021) 12197–12203. doi: 10.1021/acsanm.1c02693

  20. [20]

      C.C. Wang, X.H. Yi, P. Wang, Appl. Catal. B: Environ. 247 (2019) 24–48. doi: 10.1016/j.apcatb.2019.01.091

  21. [21]

      A. Bavykina, N. Kolobov, I.S. Khan, et al., Chem. Rev. 120 (2020) 8468–8535. doi: 10.1021/acs.chemrev.9b00685

  22. [22]

      M.K. Albolkany, W. Y, W.J. Li, et al., Angew. Chem. Int. Ed. 59 (2020) 21499–21504. doi: 10.1002/anie.202009710

  23. [23]

      T. Wei, M. Zhang, P. Wu, et al., Nano Energy 34 (2017) 205–214. doi: 10.1016/j.nanoen.2017.02.028

  24. [24]

      N. Bhoria, G. Basina, J. Pokhrel, et al., J. Hazard. Mater. 394 (2020) 122565. doi: 10.1016/j.jhazmat.2020.122565

  25. [25]

      X.D. Xiao, Y. Gao, L. Zhang, et al., Adv. Mater. (2020) e2003082.

  26. [26]

      Y. Chen, Z. Zhan, J. Wang, et al., Chin. Chem. Lett. 29 (2018) 437–440. doi: 10.1016/j.cclet.2017.08.028

  27. [27]

      B.G. Wu, L. Zhang, B.J. Jiang, et al., Angew. Chem. Int. Ed. 60 (2021) 4815–4822. doi: 10.1002/anie.202013753

  28. [28]

      Y. Xiao, G. Tian, W. Li, et al., J. Am. Chem. Soc. 141 (2019) 2508–2515. doi: 10.1021/jacs.8b12428

  29. [29]

      Y. Xing, X. Wang, S. Hao, et al., Chin. Chem. Lett. 32 (2021) 13–20. doi: 10.1016/j.cclet.2020.11.011

  30. [30]

      L. Duan, C. Wang, W. Zhang, et al., Chem. Rev. 121 (2021) 14349–14429. doi: 10.1021/acs.chemrev.1c00236

  31. [31]

      L. Balducci, D. Bianchi, R. Bortolo, et al., Angew. Chem. Int. Ed. 42 (2003) 4937–4940. doi: 10.1002/anie.200352184

  32. [32]

      Y. Gu, Q. Li, D. Zang, et al., Angew. Chem. Int. Ed. 60 (2021) 13310–13316. doi: 10.1002/anie.202011164

  33. [33]

      G. Tanarungsun, W. Kiatkittipong, P. Praserthdam, et al., Chemistry 14 (2008) 596–601. doi: 10.1002/chem.200700290

  34. [34]

      J. Li, Y. Xu, Z. Ding, et al., Chem. Eng. J. 388 (2020) 124248. doi: 10.1016/j.cej.2020.124248

  35. [35]

      X. Shi, S. Liu, C. Duanmu, et al., Chem. Eng. J. 420 (2021) 129976. doi: 10.1016/j.cej.2021.129976

  36. [36]

      J.H. Yang, S. G, Y.J. Gao, et al., Energy Environ. Sci. 6 (2013) 793–798. doi: 10.1039/c3ee23623d

  37. [37]

      H. Zhou, Y. Zhao, J. Gan, et al., J. Am. Chem. Soc. 142 (2020) 12643–12650. doi: 10.1021/jacs.0c03415

  38. [38]

      Y. Zhong, G. Li, L. Zhu, et al., J. Mol. Catal. A: Chem. 272 (2007) 169–173. doi: 10.1016/j.molcata.2007.03.015

  39. [39]

      Y. Zhang, S.J. Park, J. Catal. 379 (2019) 154–163. doi: 10.1016/j.jcat.2019.09.032

  40. [40]

      Y. Pan, Y. Chen, K. Wu, et al., Nat. Commun. 10 (2019) 4290. doi: 10.1038/s41467-019-12362-8

  41. [41]

      Z. Wei, F.A. Villamena, L.K. Weavers, Environ. Sci. Technol. 51 (2017) 3410–3417. doi: 10.1021/acs.est.6b05392

• 

  Figure 1  (a–c) SEM photographs of MOF, TCN and MOFs/TCN. (d) SEM photographs of CuO@CN. (e) TEM photographs of CuO@CN. (f) HRTEM photographs of CuO@CN.

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  Figure 2  (a) XRD patterns of the synthesized MOFs, TCN and MOFs/TCN. (b) XRD patterns of the synthesized CuO and CuO@CN. XPS spectra of CuO@CN: (c) Cu 2p, (d) O 1s, (e) C 1s and (f) N 1s.

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  Figure 3  (a) Steady-state PL spectra of CN and CuO@CN. (b) Nyquist plots of CN, CuO and CuO@CN.

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  Figure 4  (a) Conversion rate and selectivity of CuO@CN at different conditions. (b) The recycle performance of CuO@CN. (c) XRD patterns of CuO@CN and after recycle. (d) Comparison of catalytic activity of CuO@CN with previously reported catalysts for selective oxidation of benzene to phenol [11-13, 31-40].

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  Table 1.  Selective oxidation of benzene to phenol.

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