Unraveling the impact of Ag dopant in Zn–In–S colloidal nanocrystals for boosting visible-light-driven photocatalytic CO2 reduction

Jing Wanga, Shenshen Ouyanga, Ye Wanga, Xusheng Wangb, Xiaohui Renc and Li Shi*a
aSchool of Materials Science and Chemical Engineering, Ningbo University, Ningbo, Zhejiang 315211, P. R. China. E-mail: shili1@nbu.edu.cn
bSchool of Materials Science and Engineering, Zhejiang Sci-Tech University, Hangzhou 310018, China
cThe State Key Laboratory of Refractories and Metallurgy, School of Materials and Metallurgy, Wuhan University of Science and Technology, Wuhan 430081, China

Received 6th June 2024 , Accepted 9th August 2024

First published on 9th August 2024


Abstract

The development of durable and effective photocatalysts is significant for realizing efficient photocatalytic CO2 conversion. In this work, heteroatom doped Zn–In–S colloidal nanocrystals are fabricated via a facile method, which can be utilized for photocatalytic CO2 reduction under visible light in the presence of triethanolamine. Among various dopants, Ag shows the most effectiveness for improving the photocatalytic CO2 reduction performance of Zn–In–S colloidal nanocrystals. The optimized Ag doped Zn–In–S colloidal nanocrystals with doping amount of 1.13 wt% exhibit the highest photocatalytic CO2 reduction performance with a CO evolution rate of 30.29 μmol h−1, achieving high selectivity of 96.06%. The photocatalytic mechanism study indicates that increasing the doping amount of Ag in Zn–In–S colloidal crystals would result in the improved visible light harvesting ability, increased charge carrier lifetime and weakened reduction potential of electrons, which exert a synergistic effect on the CO2 photoreduction.


1. Introduction

The excessive consumption of fossil fuels since the last century has released large amounts of carbon dioxide (CO2), and a series of energy crises and environmental problems have received increasing attention.1,2 Great efforts have been made to decrease the level of CO2 in the environment, such as the capture, storage, and direct mineralization of CO2.3–6 Among the various technologies used to convert CO2 into valuable chemical feedstocks, photocatalytic reduction of CO2 is rather promising, because it can take advantage of natural conditions and address a range of environmental energy issues.7–11 CO2 is very stable due to the high dissociation energy of C[double bond, length as m-dash]O bonds and requires efficient photocatalysts to drive the CO2 reduction reaction to form value-added products.3,12,13 To date, large numbers of photocatalysts have been explored for CO2 reduction, however, their photocatalytic activities are still unsatisfactory, largely because of the insufficient absorption of light and sluggish kinetics of separation and transfer of photogenerated electron–hole pairs.14–18 Developing efficient photocatalysts is a critical challenge in this field.16

Semiconductor colloidal nanocrystals have received tremendous attention as photocatalysts for solar energy conversion due to their multifunctional properties, including high dispersibility in solvents, long excited state lifetime, good stability, and superb compositional and morphological tunability.19–21 Among various colloidal nanocrystals, ternary II–III–VI compound colloidal nanocrystals such as Zn–In–S have become one of the most prominent materials because of their remarkable component-dependent optical properties, low-toxicity, and multiple exciton generation properties.22,23 Zn–In–S based materials have been proved to be effective photocatalysts for CO2 reduction. For instance, Yu et al. demonstrated that the Zn vacancy in the ZnIn2S4 photocatalyst could tune the Gibbs free energy of *COOH, which could result in the improved photocatalytic CO2 reduction performance.24 Sun et al. revealed that the Cu–S chemical bond in Cu-substituted ZnIn2S4 was able to effectively activate CO2 and lower the Gibbs free energy for the formation of *COOH, leading to a much improved photocatalytic CO2 reduction performance compared to pristine ZnIn2S4.25 It was found that careful control of the size, shape and composition of Zn–In–S colloidal nanocrystals makes them powerful precursors for modelling multiphase catalysts.26 Doping group I elements (e.g., Ag, Cu) into Zn–In–S colloidal crystals is an effective strategy to tune the electronic structure for optoelectronic applications.27,28 Recent works also indicate that doping Ag into Zn–In–S colloidal crystals can improve the photocatalytic H2 evolution performance. For instance, Gong et al. have demonstrated that doping Ag into Zn–In–S colloidal quantum dots can greatly boost the photocatalytic H2 evolution, and the enhanced photocatalytic activity can be attributed to the synergetic effect of simultaneous bandgap narrowing and charge carrier lifetime elongation.29 However, to the best of our knowledge, the potential roles of the Ag dopant in Zn–In–S colloidal crystals for photocatalytic CO2 reduction have not been explored. It is rather interesting to elucidate the impact of the Ag dopant in colloidal crystals for efficient and selective photocatalytic reduction of CO2.

In this work, Ag doped Zn–In–S colloidal nanocrystals (Ag–ZnInS) are prepared by an aqueous solution synthesis method, which can be used as visible-light-active photocatalysts for photocatalytic CO2 reduction. It is revealed that the doping amount of Ag exerts great effect on the photocatalytic activity and selectivity, and the optimized Ag–ZnInS with doping amount of 1.13 wt% exhibits a remarkable photocatalytic CO production rate of 30.29 μmol h−1 and H2 evolution rate of 1.24 μmol h−1 with the addition of Co(bpy)32+ (bpy = 2′2-bipyridine, abbreviated as CoBPY) as cocatalyst and triethanolamine (TEOA) as a sacrificial agent, corresponding to the CO selectivity of 96.06%, which shows a much higher photocatalytic CO2 reduction performance than non-doped Zn–In–S. Ag–ZnInS also exhibits higher activity than other metal (Cu, Fe, Co and Ni) doped Zn–In–S colloidal crystals. The investigation of the photocatalytic mechanism indicates that gradually increasing the doping amount of Ag in Zn–In–S colloidal nanocrystals leads to the enhanced visible light adsorption ability and prolonged charge carrier lifetime, which are beneficial for photocatalysis. However, increasing the doping amount of Ag would also result in the downshift of the conduction band potential, which reduces the reduction ability of photogenerated electrons. Therefore, the enhanced visible light adsorption ability, prolonged charge carrier lifetime and the downshift of conduction band potential exert competitive effects on the performances of photocatalytic CO2 reduction, and the optimized performance is achieved when the doping amount of Ag is 1.13 wt%.

2. Results and discussion

Ag–ZnInS with different doping amounts of Ag were synthesized via a facile procedure (see experimental sections). Three Ag–ZnInS samples were prepared, which were named as 1Ag–ZnInS, 2Ag–ZnInS and 3Ag–ZnInS. The weight percentages of Ag in Zn–In–S colloidal crystals were measured by inductively coupled plasma optical emission spectrometry (ICP-OES), which were 0.69 wt%, 1.13 wt% and 2.13 wt%, respectively (Table S1). Fig. 1a shows the X-ray powder diffraction (XRD) patterns of Zn–In–S colloidal crystals and Ag–ZnInS. Zn–In–S shows three peaks at 28.4°, 47.7° and 56.1°, which are the typical (008), (110) and (203) planes of the hexagonal phase ZnIn2S4 crystal (ICDD-JCPDS Card No. 72-0773).30 It can also be seen that the typical diffraction peaks do not change significantly after Ag doping, but the positions are slightly shifted to a small angle with the increase of the amount of Ag. Such a blue shift of XRD peaks is ascribed to the fact that the ionic radius of Zn2+ and In3+ is smaller than that of Ag+, which proves the successful doping of Ag into the lattice of Zn–In–S colloidal crystals.29 The diffuse ultraviolet-visible (UV-vis) spectra in Fig. 1b indicate that the light absorption capacity gradually increases as the amount of the Ag dopant increases. The band gap was calculated based on the Kubelka–Munk function, and the value was achieved by extrapolating the tangent line to the x-axis.31 As displayed in Fig. S1, the band gap becomes significantly narrower with the increase of the amount of the Ag dopant. The corresponding band gap is decreased from 3.07 eV of Zn–In–S to 2.55 eV of 3Ag–ZnInS. This result shows that the optical properties of the colloidal crystals can be effectively adjusted with the doping of Ag. As shown in Fig. 1c, the pure Zn–In–S colloidal crystals appear white, while the Ag–ZnInS colloidal crystals show varying degrees of yellow color as the amount of the Ag dopant increases. The as-prepared Ag–ZnInS shows the Tyndall effect in N,N-dimethylformamide (DMF) solution, indicating the colloidal feature (Fig. 1c). Fig. 2a and b show the transmission electron microscopy (TEM) and high-resolution transmission electron microscopy (HRTEM) images of 2Ag–ZnInS, respectively. The significant agglomeration of particles in 2Ag–ZnInS is observed for the TEM characterization under dry conditions, which is mainly attributed to its high surface energy.32 However, in the HRTEM image in Fig. 2b, we are still able to identify several isolated nanocrystals. A measured crystal face spacing of about 0.32 nm corresponds to the (102) plane.33 The energy dispersive X-ray (EDX) in Fig. S2 clearly reveals the S, In, Zn and Ag elements in the prepared samples. The high-angle annular darkfield scanning TEM (HAADF-STEM) and the corresponding elemental mapping images confirm the homogeneous distribution of Ag, Zn, In and S in the crystals (Fig. 2c–g). All these results demonstrate the successful synthesis of Ag–ZnInS.
image file: d4cy00716f-f1.tif
Fig. 1 (a) XRD patterns and (b) UV–vis absorption spectra of Zn–In–S colloidal nanocrystals and Ag–ZnInS colloidal nanocrystals. (c) Photographs of Zn–In–S colloidal nanocrystals and Ag–ZnInS colloidal nanocrystal powders and their Tyndall effect dispersed in DMF.

image file: d4cy00716f-f2.tif
Fig. 2 (a and b) TEM and HRTEM images and (c–g) HAADF-STEM image and the Ag, S, In and Zn elemental mapping images of the 2Ag–ZnInS colloidal nanocrystals.

X-ray photoelectron spectroscopy (XPS) was applied to uncover the electronic states of the colloidal crystals. Fig. 3a–c show the high-resolution XPS spectra of In 3d, Zn 2p and S 2p, respectively. The In 3d spectrum of Zn–In–S displays two peaks at 452.29 eV and 444.70 eV, which are typical for In3+ (Fig. 3a).34 The binding energies of the two peaks at 1044.90 eV and 1021.80 eV correspond to Zn 2p1/2 and Zn 2p3/2, respectively (Fig. 3b).35 The S 2p spectra show two peaks centered at 162.6 eV and 161.3 eV, attributed to S2− (Fig. 3c).36 Fig. 3d shows the Ag 3d spectra of 2Ag–ZnInS, and the two peaks at 374.02 eV and 368.02 eV can be attributed to Ag+,37 indicating that Ag is doped into the Zn–In–S colloidal crystal. Upon Ag doping, the binding energies of In 3d, Zn 2p and S 2p peaks are shifted towards higher binding energies, indicating a shift in the electron density of the colloidal crystals. This shift can be attributed to the interaction between the dopant (Ag) and the host material, which changes the electronic structure.38


image file: d4cy00716f-f3.tif
Fig. 3 XPS spectra of (a) In 3d, (b) Zn 2p, (c) S 2p and (d) Ag 3d for Zn–In–S colloidal nanocrystals and 2Ag–ZnInS colloidal nanocrystals.

The as-prepared colloidal crystals were then used for photocatalytic CO2 reduction reactions. The reaction was carried out under visible light (300 W Xenon lamp) and mild conditions with DMF as solvent, CoBPY as cocatalyst and TEOA as sacrificial reagent. DMF was employed as the reaction solution due to the high solubility of CO2 gas.39 DMF is also an excellent solvent for the well dispersion of Zn–In–S colloidal nanocrystals. CoBPY has been commonly used as a co-catalyst for trapping photogenerated electrons to realize efficient CO2 conversion.40–43 This reaction system only produces CO and H2, which is consistent with previous reports.39,44–47 Fig. 4a shows the photocatalytic CO2 reduction performances of Ag–ZnInS with different doping amounts of Ag. For the bare Zn–In–S colloidal crystals, basically no CO and H2 production is observed, indicating that Zn–In–S colloidal crystals have no photocatalytic activity, which is mainly due to its weak absorption of visible light. It can be seen that the evolution rate of CO exhibits a volcano type curve as the doping amount of Ag increases, and 2Ag–ZnInS shows the highest CO evolution rate of 30.29 μmol h−1 and a moderate H2 evolution rate of 1.24 μmol h−1, corresponding to the selectivity of CO at 96.06%. The hydrogen evolution reaction is recognized as a competing reaction for CO2 reduction, but in our experiments, the H2 evolution rate is much lower than the CO evolution rate. The achieved photocatalytic CO2 reduction activity over the 2Ag–ZnInS sample is much higher than some reported photocatalysts under similar reaction conditions, demonstrating the superiority of this colloidal photocatalyst for the CO2 reduction reaction (Table S2). The 2Ag–ZnInS sample also shows higher photocatalytic performance than other transition metal doped Zn–In–S colloidal crystals, as exhibited in Fig. S3.


image file: d4cy00716f-f4.tif
Fig. 4 (a) Photocatalytic CO2 reduction performances of Ag–ZnInS colloidal nanocrystals with different doping amounts of Ag. (b) Photocatalytic CO2 reduction performances of 2Ag–ZnInS colloidal nanocrystals under different conditions in 5 h. (c) GC-MS of CO obtained from photocatalytic reduction of 13CO2 over 2Ag–ZnInS colloidal nanocrystals. (d) Stability test of photocatalytic CO2 reduction performances over 2Ag–ZnInS colloidal nanocrystals in the presence of CoBPY as a co-catalyst.

The performance of the photocatalytic reduction of CO2 by 2Ag–ZnInS under different reaction conditions was investigated. As shown in Fig. 4b, the CO evolution rate decreases in the absence of CoBPY, demonstrating the important function of CoBPY as a co-catalyst in facilitating the photocatalytic CO2 to CO conversion. When the reaction is carried out under Ar gas, almost no CO is produced and only H2 evolution can be observed. To verify the origin of the produced CO, a 13C-labeled isotope experiment was conducted. Gas chromatogram and mass spectra (GC-MS) was used to measure and analyze the generated CO product. As shown in Fig. 4c, the CO peak in MS gives a m/z = 29, which can be ascribed to 13CO. This result demonstrates that the CO originates from the photocatalytic reduction of CO2.

The time-dependent production of CO and H2 over Ag–ZnInS with the CoBPY co-catalyst is displayed in Fig. S4, which indicates that the evolution rates of CO and H2 is kept almost steady. To further evaluate the stability, the photocatalytic reaction was conducted for 18 hours over the 2Ag–ZnInS photocatalyst (Fig. 4d). A linear increase of CO evolution is observed for the first 10 h, reaching a CO yield of 269.27 μmol. When the photocatalytic reaction continues, the CO evolution rate decreases slightly, which should be ascribed to the consumption of the TEOA sacrificial reagent, because the CO evolution rate can be improved after re-adding 4 ml TEOA directly to the reaction solution. The used 2Ag–ZnInS sample was collected and dried for XRD and XPS characterization. The XRD pattern shows that the crystal structure of 2Ag–ZnInS has no obvious change after the photocatalytic reaction (Fig. S5). The high-resolution XPS spectra of In 3d, Zn 2p, S 2p and Ag 3d of 2Ag–ZnInS before and after the photocatalytic reaction in Fig. S6 show that there are no obvious change of compositions and chemical states, further demonstrating the good stability of 2Ag–ZnInS for the photocatalytic CO2 reduction reaction.

The above results show that the photocatalytic CO2 reduction activities depend on the doping amount of Ag in Zn–In–S colloidal crystals, and the mechanism is discussed below. The band structures of the photocatalysts are determined by ultraviolet photoelectron emission spectroscopy (UPS). The valence band energies (EVB) can be calculated by subtracting the width of the UPS spectra (Fig. 5a–c) by the excitation energy (21.22 eV), which are 6.48 eV, 6.47 eV and 6.46 eV for 1Ag–ZnInS, 2Ag–ZnInS, 3Ag–ZnInS, respectively. The conduction band energy (ECB) is thus calculated from the equation: ECB = EVBEg.48,49 The values of the ECB and EVB can be converted according to the reference standard for which 0 V vs. RHE (reversible hydrogen electrode) equals −4.5 eV vs. evac (vacuum level).48 The band positions of samples are illustrated in Fig. 5d, which shows that the ECB of all the Ag–ZnInS photocatalysts are located above the energy levels of H2 evolution and CO2 reduction to CO. The ECB positions of Ag–ZnInS are significantly affected by the doping amount of Ag, and increasing the amount of Ag results in the gradual downshift of the ECB. It should be noted that the downshift of the ECB could weaken the reduction ability of photogenerated electrons, which would have negative influence on the photocatalytic CO2 reduction performances.46


image file: d4cy00716f-f5.tif
Fig. 5 (a–c) UPS spectra of Ag–ZnInS colloidal nanocrystals with different doping amounts of Ag. (d) Band structure diagram for Ag–ZnInS colloidal nanocrystals.

The charge transfer kinetics was then investigated by photoluminescence (PL) spectroscopy. As shown in Fig. 6a, the as-prepared Zn–In–S and 1Ag–ZnInS have almost no PL signals. With the increased amount of Ag doping, the PL intensity increases and the peak position red shifts. 2Ag–ZnInS and 3Ag–ZnInS exhibit PL peaks at 500.03 nm (2.48 eV) and 531.95 nm (2.33 eV), much smaller than the values of their bandgaps, which indicates that such PL is ascribed to the intrinsic defect states, e.g. the deep donor–acceptor pair states.29 The increase of the PL intensity may be due to the increased density of deep donor–acceptor pair states in Ag–ZnInS with the increasing doping amount of Ag, and the red shift of the PL peak is consistent with experimental results of the red shift of absorption spectra and narrowing of bandgaps.50 To further investigate the mechanism of photocatalytic CO2 reduction, time resolved PL decay spectra were conducted. Fig. 6b shows the PL decay curves of 1Ag–ZnInS, 2Ag–ZnInS and 3Ag–ZnInS, and their fitting parameters are shown in Table S3. With the increased doping amount of Ag, the average lifetime increases gradually, indicating the improved separation efficiency of charge carriers, which is beneficial for photocatalytic CO2 reduction. Therefore, along with the increasing amount of Ag in Ag–ZnInS, the improved light adsorption ability, the prolonged lifetime of charge carriers and the weakened reduction ability of photogenerated electrons exert a competitive effect on the photocatalytic CO2 reduction reaction, and the highest performance is obtained over 2Ag–ZnInS with a mild doping amount of 1.13 wt%.


image file: d4cy00716f-f6.tif
Fig. 6 (a) PL spectra and (b) PL decay spectra of Ag–ZnInS colloidal nanocrystals with different doping amounts of Ag. Schematic illustration of the photocatalytic CO2 reduction process over Ag–ZnInS colloidal nano-crystals (c) in the presence and (d) in the absence of Co(bpy)32+ as a co-catalyst.

The role of the CoBPY cocatalyst in photocatalytic CO2 reduction was then investigated. The Ag 3d XPS spectra of 2Ag–ZnInS with and without the CoBPY co-catalyst were recorded after the photocatalytic CO2 reduction reactions. As shown in Fig. S7, the Ag 3d XPS peaks shift to lower binding energies by 0.1 eV for 2Ag–ZnInS without the CoBPY co-catalyst after the photocatalytic reaction compared with the fresh 2Ag–ZnInS, which indicates that the photogenerated electrons are trapped in the deep donor–acceptor pair states induced by the Ag dopant in the absence of the CoBPY co-catalyst, leading to the reduction of the chemical state of the Ag+ dopant. Such phenomenon can also be observed by the color change of the reaction solution after the photocatalytic reactions (Fig. S8). However, when the photocatalytic reaction was conducted in the presence of the CoBPY co-catalyst, no obvious change of Ag 3d XPS peak positions can be observed before and after the photocatalytic reactions (Fig. S7), which should be ascribed to the fact that the photoexcited electrons trapped in the deep donor–acceptor pair states would be further transferred to the CoBPY co-catalyst and participate in the reaction of CO2 reduction. PL spectroscopy and UV-vis absorption spectrum were utilized to reveal the role of the CoBPY co-catalyst in the photocatalytic CO2 reduction. As shown in Fig. S9, the quenching of PL signals of Ag–ZnInS are observed after the addition of CoBPY, reflecting the efficient electron transfer from the photocatalyst to CoBPY. Moreover, the color of the reaction mixture changes from light yellow to light grey after the photocatalytic reaction (Fig. S8). The enhanced light absorption indicated by the UV-vis absorption spectrum in Fig. S10 is attributed to the existence of Co(bpy)3+, originated from the reduction of the CoBPY cocatalyst upon receiving photogenerated electrons from Ag–ZnInS.51 The asformed Co(bpy)3+ can subsequently convert CO2 and H+ to CO and H2 (Fig. 6c).52 However, when the photocatalytic reaction is conducted in the absence of the CoBPY cocatalyst, the photogenerated electrons are trapped in the deep donor–acceptor pair states and partial electrons participate in the CO2 reduction reaction (Fig. 6d).

3. Conclusions

In summary, we have demonstrated that Ag–ZnInS can be used as visible-light-active photocatalysts for photocatalytic CO2 reduction. The photocatalytic CO2 reduction performances strongly depend on the doping amount of Ag, which exhibits volcano type dependence on the amount of Ag. The optimized Ag–ZnInS with a doping amount of 1.13 wt% exhibits a photocatalytic CO generation rate of 30.29 μmol h−1 and H2 evolution rate of 1.24 μmol h−1 in the presence of CoBPY as a co-catalyst, which are much higher than the pristine and other metal (Cu, Fe, Co and Ni) doped Zn–In–S colloidal crystals. It is revealed that the improvement of photocatalytic performances can be attributed to the synergistic effect of the improved visible light adsorption ability, the prolonged charge carrier lifetime, and the decreased reduction potential of electrons. This work represents a valuable contribution towards the development of efficient photocatalytic materials for CO2 reduction reactions and highlights the potential of Ag–ZnInS in the field of renewable energy and environmental sustainability.

Data availability

The data supporting this article have been included as part of the ESI.

Conflicts of interest

There are no conflicts to declare.

Acknowledgements

The authors thank the financial support from the National Natural Science Foundation of China (No. 22209084), the Yongjiang Talent Project (No. 2021A-142-G), the Ningbo Science and Technology Bureau under Yongjiang 2035 Key Technology Breakthrough Programme (No. 2024Z237), and the K. C. Wong Magna Fund in Ningbo University.

References

  1. J. Agrawal, R. Shahin, C. Singh, S. Singh, R. K. Shukla, S. Mishra, P. Singh, J.-O. Baeg, R. K. Yadav and N. K. Gupta, RSC Sustainability, 2024, 2, 695–700 RSC .
  2. C. W. Jones, A.-H. A. Park and P. Wright, Acc. Chem. Res., 2023, 56, 3545–3546 CrossRef CAS .
  3. A. D. N. Kamkeng, M. Wang, J. Hu, W. Du and F. Qian, Chem. Eng. J., 2021, 409, 128138 CrossRef CAS .
  4. D. Y. Shu, S. Deutz, B. A. Winter, N. Baumgärtner, L. Leenders and A. Bardow, Renewable Sustainable Energy Rev., 2023, 178, 113246 CrossRef CAS .
  5. O. I.-F. Chen, C.-H. Liu, K. Wang, E. Borrego-Marin, H. Li, A. H. Alawadhi, J. A. R. Navarro and O. M. Yaghi, J. Am. Chem. Soc., 2024, 146, 2835–2844 CrossRef CAS PubMed .
  6. L. N. Lammers, Y. Duan, L. Anaya, A. Koishi, R. Lopez, R. Delima, D. Jassby and D. L. Sedlak, ACS Sustainable Chem. Eng., 2023, 11, 4800–4812 CrossRef CAS .
  7. G. Q. Zhao, J. Hu, X. Long, J. Zou, J. G. Yu and F. P. Jiao, Small, 2021, 17, 2102155 CrossRef CAS .
  8. W. Gao, H. Chi, Y. Xiong, J. Ye, Z. Zou and Y. Zhou, Adv. Funct. Mater., 2023, 202312056 Search PubMed .
  9. S. Man, W. Jiang, X. Guo, O. Ruzimuradov, S. Mamatkulov, J. Low and Y. Xiong, Chem. Mater., 2024, 36, 1793–1809 CrossRef CAS .
  10. D. P. H. Tran, M.-T. Pham, X.-T. Bui, Y.-F. Wang and S.-J. You, Sol. Energy, 2022, 240, 443–466 CrossRef CAS .
  11. Y. He, L. Yin, N. Yuan and G. Zhang, Chem. Eng. J., 2024, 481, 148754 CrossRef CAS .
  12. X. Zhang, K. Matras-Postolek, P. Yang and S. P. Jiang, Carbon, 2023, 214, 118337 CrossRef CAS .
  13. W. Zhang, R. Huang, L. Song and X. Shi, Nanoscale, 2021, 13, 9075–9090 RSC .
  14. J. Zhang, J. Jiang, Y. Lei, H. Liu, X. Tang, H. Yi, X. Huang, S. Zhao, Y. Zhou and F. Gao, Sep. Purif. Technol., 2024, 328, 125056 CrossRef CAS .
  15. Z. Zhu, Y. Xuan, X. Liu and Q. Zhu, Nanoscale, 2023, 15, 730–741 RSC .
  16. Z. Wang, G. Zou, J. H. Park and K. Zhang, Sci. China Mater., 2024, 67, 397–423 CrossRef CAS .
  17. J. Wang, Y. Shi, Y. Wang and Z. Li, ACS Energy Lett., 2022, 7, 2043–2059 CrossRef CAS .
  18. L. Shi, P. Wang, Q. Wang, X. Ren, F. Ichihara, W. Zhou, H. Zhang, Y. Izumi, B. Cao, S. Wang, H. Chen and J. Ye, J. Mater. Chem. A, 2020, 8, 21833–21841 RSC .
  19. P. Losch, W. Huang, E. D. Goodman, C. J. Wrasman, A. Holm, A. R. Riscoe, J. A. Schwalbe and M. Cargnello, Nano Today, 2019, 24, 15–47 CrossRef CAS .
  20. C. Gadiyar, A. Loiudice and R. Buonsanti, J. Phys. D: Appl. Phys., 2017, 50, 074006 CrossRef .
  21. H. L. Wu, X. B. Li, C. H. Tung and L. Z. Wu, Adv. Mater., 2019, 31, 1900709 CrossRef PubMed .
  22. J. Selvaraj, A. Mahesh, V. Baskaralingam, A. Dhayalan and T. Paramasivam, ChemistrySelect, 2018, 3, 5993–6008 CrossRef CAS .
  23. X. Wang, J. Damasco, W. Shao, Y. Ke and M. T. Swihart, ChemPhysChem, 2015, 17, 687–691 CrossRef .
  24. Y. Nie, T. Bo, W. Zhou, H. Hu, X. Huang, H. Wang, X. Tan, L. Liu, J. Ye and T. Yu, J. Mater. Chem. A, 2023, 11, 1793–1800 RSC .
  25. L. Xiao, C. Yuan, P. Chen, Y. Liu, J. Sheng, S. Zhang, F. Dong and Y. Sun, ACS Sustainable Chem. Eng., 2022, 10, 11902–11912 CrossRef CAS .
  26. S. Cao, J. Zheng, C. Dai, L. Wang, C. Li, W. Yang and M. Shang, J. Mater. Sci., 2017, 53, 1286–1296 CrossRef .
  27. S. Mukherjee, J. Selvaraj and T. Paramasivam, ACS Appl. Nano Mater., 2021, 4, 10228–10243 CrossRef CAS .
  28. W. Zhang, Q. Lou, W. Ji, J. Zhao and X. Zhong, Chem. Mater., 2013, 26, 1204–1212 CrossRef .
  29. G. Gong, Y. Liu, B. Mao, L. Tan, Y. Yang and W. Shi, Appl. Catal., B, 2017, 216, 11–19 CrossRef CAS .
  30. S. Lu, S. Zhang, L. Li, C. Liu, Z. Li and D. Luo, Chem. Eng. J., 2024, 483, 149058 CrossRef CAS .
  31. V. G. Dileepkumar, P. S. Surya, C. Pratapkumar, R. Viswanatha, C. R. Ravikumar, M. R. Anil Kumar, H. B. Muralidhara, I. M. Al-Akraa, A. M. Mohammad, Z. Chen, X.-T. Bui and M. S. Santosh, J. Environ. Chem. Eng., 2020, 8, 104005 CrossRef CAS .
  32. H. Pang, X. Meng, H. Song, W. Zhou, G. Yang, H. Zhang, Y. Izumi, T. Takei, W. Jewasuwan, N. Fukata and J. Ye, Appl. Catal., B, 2019, 244, 1013–1020 CrossRef CAS .
  33. X. Xin, Y. Li, Y. Zhang, Y. Wang, X. Chi, Y. Wei, C. Diao, J. Su, R. Wang, P. Guo, J. Yu, J. Zhang, A. J. Sobrido, M.-M. Titirici and X. Li, Nat. Commun., 2024, 15, 337 CrossRef CAS PubMed .
  34. Q. Xue, P. Cai, X. Pu, Q. Ai, J. Si, X. Yao, G. Bai, Q. Dong and Z. Liu, Mater. Today Nano, 2024, 25, 100457 CrossRef CAS .
  35. F. Rasool, B. M. Pirzada, M. Misbah Uddin, M. I. H. Mohideen, I. Yildiz, M. Elkadi and A. Qurashi, Int. J. Hydrogen Energy, 2024, 59, 63–73 CrossRef CAS .
  36. P. Su, D. Zhang, X. Yao, T. Liang, N. Yang, D. Zhang, X. Pu, J. Liu, P. Cai and Z. Li, J. Colloid Interface Sci., 2024, 662, 276–288 CrossRef CAS PubMed .
  37. Y. Zhao, X. Fan, H. Zheng, E. Liu, J. Fan and X. Wang, J. Mater. Sci. Technol., 2024, 170, 200–211 CrossRef CAS .
  38. F. Zhou, Y. Zhang, J. Wu, W. Yang, X. Fang, T. Jia, Y. Ling, P. He, Q. Liu and J. Lin, Appl. Catal., B, 2024, 341, 123347 CrossRef CAS .
  39. Q. Guo, F. Liang, X.-B. Li, Y.-J. Gao, M.-Y. Huang, Y. Wang, S.-G. Xia, X.-Y. Gao, Q.-C. Gan, Z.-S. Lin, C.-H. Tung and L.-Z. Wu, Chem, 2019, 5, 2605–2616 CAS .
  40. B. Su, M. Zheng, W. Lin, X. F. Lu, D. Luan, S. Wang and X. W. Lou, Adv. Energy Mater., 2023, 13, 2203290 CrossRef CAS .
  41. R. Wang, P. Yang, S. Wang and X. Wang, J. Catal., 2021, 402, 166–176 CrossRef CAS .
  42. G. Chen, Z. Zhou, B. Li, X. Lin, C. Yang, Y. Fang, W. Lin, Y. Hou, G. Zhang and S. Wang, J. Environ. Sci., 2024, 140, 103–112 CrossRef CAS .
  43. B. Su, H. Huang, Z. Ding, M. B. J. Roeffaers, S. Wang and J. Long, J. Mater. Sci. Technol., 2022, 124, 164–170 CrossRef CAS .
  44. L. Shi, Y. Yan, Y. Wang, T. Bo, W. Zhou, X. Ren and Y. Li, Inorg. Chem. Front., 2023, 10, 2731–2741 RSC .
  45. Y. Wang, Y. Yan, H. Zhang, X. Peng, H. Huang, S. Zhang and L. Shi, J. Colloid Interface Sci., 2024, 658, 324–333 CrossRef CAS .
  46. L. Shi, X. Ren, Z. Zhang, Q. Wang, Y. Li and J. Ye, J. Catal., 2021, 401, 271–278 CrossRef CAS .
  47. Y. Yan, Y. Wang, Z. Zhang, S. Zhang, J. Ye and L. Shi, Chem. Eng. J., 2023, 468, 143639 CrossRef CAS .
  48. S. Hu, W. Zhai, F. Chen and Q. He, Mater. Today Phys., 2024, 40, 101311 CAS .
  49. K. H. Do, D. Praveen Kumar, A. Putta Rangappa, J. Wang, Y. Hong, E. Kim, D. Amaranatha Reddy and T. Kyu Kim, Mater. Today Chem., 2021, 22, 100589 CrossRef CAS .
  50. J. Song, C. Ma, W. Zhang, S. Yang, S. Wang, L. Lv, L. Zhu, R. Xia and X. Xu, J. Mater. Chem. A, 2016, 4, 7909–7918 CAS .
  51. F. Wang, T. Hou, X. Zhao, W. Yao, R. Fang, K. Shen and Y. Li, Adv. Mater., 2021, 33, 2102690 CrossRef CAS .
  52. K. H. Do, D. P. Kumar, A. P. Rangappa, J. Lee, S. Yun and T. K. Kim, J. Mater. Chem. A, 2023, 11, 8392–8403 RSC .

Footnote

Electronic supplementary information (ESI) available. See DOI: https://doi.org/10.1039/d4cy00716f

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