Water pollution caused by water-immiscible pollutants such as BTXs has become a major concern for researchers in recent years. This study presents the synthesis of a hydrophobic photocatalyst, Ag-CuPc-ZnO/Silica Aerogel, prepared using sol-gel and impregnation methods for the degradation of floating benzene. The effect of different percentages of Ag on the photocatalyst performance was studied, and the optimal sample was tested in rectangular and cylindrical photoreactors. The physicochemical properties of the hydrophobic photocatalyst were analyzed using XRD, FESEM, FTIR, BET/BJH, PL, contact angle, and UV-Vis DRS. Our analysis showed that decreasing nanoparticle size led to an increased specific surface area and decreased pore diameter. DRS analysis demonstrated that increasing Ag content led to a decreased bandgap and increased light absorption in the visible light region with CuPc addition. PL analysis indicated a significant decrease in electron-hole recombination with 5% Ag and confirms the efficient charge separation. The 5% wt. Ag sample achieved highest benzene photodegradation efficiency, while the rectangular photoreactor outperformed with superior degradation rates, STY, PSTY, and QY due to uniform light distribution and improved illumination. This study offers valuable insights on hydrophobic photocatalysts for degrading water-immiscible pollutants, emphasizing the need to optimize catalyst performance for efficient wastewater treatment.
Research Article
Synthesis of Ag-Doped CuPc-ZnO/Hydrophobic Silica Aerogel Photocatalyst for Enhanced Photocatalytic Degradation of Floating Benzene: A Comparative Study of Different Photoreactor Geometries
https://doi.org/10.21203/rs.3.rs-3953617/v1
This work is licensed under a CC BY 4.0 License
Journal Publication
published 04 May, 2024
Read the published version in Journal of Sol-Gel Science and Technology →
You are reading this latest preprint version
Floating Pollutants
Ag-CuPc-ZnO nanocomposite
Silica Aerogel
Photoreactor Geometry
Hydrophobic Photocatalyst
Water contamination is a widespread environmental problem that affects human activities and the entire ecosystem worldwide (Kumar et al., 2022). With a growing global population and increasing industrial and agricultural activities, organic pollutants are ubiquitous in watersheds (Panis et al., 2022). These pollutants can cause significant issues, including increased toxicity and oxygen demand in sewage water and reduced light transmission, which can severely influence photosynthesis in marine life(Dutta et al., 2021; Priya et al., 2021). Benzene is a floating pollutant that is discharged into water resources from various sources, including oil refineries, petrochemical plants, and landfill leachate(Joodi et al., 2020). The entry of benzene into water sources causes the destruction of aquatic ecosystems and the death of aquatic animals(Xu et al., 2020). On the other hand, water contamination with benzene endangers human health and leads to damage to the nervous system, liver, kidney, and the occurrence and development of cancer in humans(Rana et al., 2021). Traditional techniques for removing hazardous contaminants from wastewater, such as adsorption and ozonation, have various limitations(Tang et al., 2022; Xie et al., 2016). To address these challenges, advanced oxidation processes (AOPs), thermal distillation, adsorption, ion exchange, and membrane filtration are now being used(Hakki et al., 2018). Advanced oxidation techniques are particularly effective in removing a range of organic pollutants, using strong oxidants to break them down into harmless compounds(Angosto et al., 2020). Various organic molecules can be oxidized using the advanced oxidation process (AOP)(Taoufik et al., 2021). Reactive oxygen and free radical species are potent oxidants capable of initiating advanced oxidation processes (AOPs) and breaking down contaminants into non-toxic, elementary compounds(Hakki & Allahyari, 2022b; Wang & Wang, 2020). Advanced Oxidation Processes (AOPs) encompass a variety of techniques, including wet air oxidation, supercritical water oxidation, Fenton, photocatalytic oxidation, ultrasonic oxidation, electrochemical oxidation, and ozonation, among others.(Pandis et al., 2022; Rayaroth et al., 2022). The mechanisms used in photochemical and photocatalytic process, which rely on light irradiation to transform harmful contaminants into non-toxic ones, make them sustainable treatment technologies with "zero" waste(Al-Nuaim et al., 2023; Pandis et al., 2022).
Nano-oxides such as Fe2O3, ZnO, TiO2, WO3, SiO2, etc. are effective and practical photocatalyst due to their simple production, high surface reactivity, high abundance, non-flammability, and non-toxicity properties(Hakki et al., 2019; Kausar et al., 2022). These nanoparticles can be used alone or doped with different materials to enhance their adsorption capacity. ZnO is a semiconductor with a broadband gap, great exciton binding energy, high carrier mobility, and significant thermal conductivity(Najafidoust et al., 2019).
The study of photocatalysts that operate in aqueous solutions and use semiconductor components to oxidize water at the catalyst surface is a key area of research in heterogeneous photocatalysis(Zhao et al., 2020). Due to its 3D network structure, large porosity, significant specific surface area, poor bulk density, highly low thermal conductivity, and small sound velocity, SiO2 aerogels have received much attention as adsorbents in recent years(Wang et al., 2022; Zhang et al., 2023).
The pure ZnO and Ag-doped ZnO synthesized by Chauhan et al. were made utilizing an environmentally benign process using Cannabis sativa leaves. The nanoparticles were described and evaluated for antibacterial activity and photocatalytic dye degradation. They discovered that Ag-doped nanoparticles demonstrated superior elimination of Congo red and methyl orange when exposed to visible light(Chauhan et al., 2020). Yi et al.(Yi et al., 2020) investigated how increased adsorption properties of tetrapod-like ZnO (T-ZnO) affected its photodegradation activity. They created a novel composite using the sol-gel technique to load silica aerogels (SiO2(AG)) on the surface of T-ZnO. As their model pollutant, they used Nitrobenzene (NB), and they investigated the adsorption and photocatalytic capabilities of T-ZnO and SiO2(AG)/T-ZnO for NB. The decomposition efficiency of rhodamine B, methylene blue, and Escherichia coli utilizing 0, 5, 10, 15, and 20% Fe-doped ZnO (ZnO: Fe) was investigated in the study conducted by Sutanto et al.(Yi et al., 2020) Based on Tauc's plot approach and they determine that 20% Fe-doped ZnO has the maximum transmittance and the lowest energy band gap of 3.21 eV. Ag-ZnO nanoparticles were prepared by Rajendran and Mani using the Sol-gel process, and coated using polyethylene glycol as stabilizer on the substrate. When they investigated Ag-ZnO NPs' photocatalytic activity against ponceau, they found that the maximal degradation rate peaked at 89% after 140 min(Rajendran & Mani, 2020). Armelao et al.(Armelao et al., 2001) created ZnO-doped silica coatings and annealed them at various temperatures to track how the system changed chemically and microstructurally over time. Najafidoust et al.(Najafidoust et al., 2021) synthesized a Fe-ZnO/Silica Aerogel nanocomposite to photodegrade BTX from wastewater. They found that the prepared nanocomposite was highly hydrophobic and exhibited effective photocatalytic activity, allowing it to float on the wastewater and degrade BTX.
This research aims to investigate the influence of Ag doping on the photocatalytic activity of CuPc-ZnO/SA in the photodegradation of benzene. Additionally, the study examines the impact of photoreactor geometry on the efficiency of the photodegradation process. The choice of the reactor design and process conditions heavily affects light distribution in photoreactor and light adsorption by the photocatalytic nanoparticles, thereby influencing the overall efficiency of the photodegradation process.
2.1 Materials
The reagents were zinc acetate dihydrate, ethylene glycol (EG), Silver nitrate, diethanolamine (DEA), copper phthalocyanine (CuPc), ethanol, and Benzene, all from Merck (Germany). Deionized water (DI) was acquired from Tooskashimi Company (Iran). TetraEthyl orthoSilicate (part number 131903), ammonium fluoride ammonium hydroxide purchased from Sigma Aldrich company. All reagents were utilized without further purification.
2.2 Ag-CuPc-ZnO nanoparticles Preparation
AgO-CuPc-ZnO/silica aerogel samples with 2% wt. of CuPc and 2.5-10 % wt. of AgO were synthesized by the double solvent sol-gel technique. First, 1 mole of ZnO precursor was added to 20 mole ethanol as the solvent and mixed at 60°C for 30 min. In another flask, silver nitrate as AgO precursor was dissolved under the continuous stirring in diethylene glycol at 70°C for 15 minutes. Then CuPc was gradually added to the mixture at the mentioned temperature. The prepared mixture and zinc acetate solution were mixed at 60 °C for 60 minutes with vigorous stirring. Then, 1 mole of distilled water was added dropwise into the Ag-CuPc-ZnO sol, along with diethanolamine, to initiate the hydrolysis process. The diethanolamine acted as a stabilizer during this process. The prepared sols containing 2.5, 5, 7.5, and 10 wt.% Ag were aged for 4 h and dried in an oven at 100 °C for 12 h. Finally, all synthesized photocatalytic nanocomposites were annealed at 400 °C for 2 h.
2.3 Hydrophobic silica aerogel preparation
2.3.1 Preparation of the alkaline catalyst solution
To prepare the alkaline catalyst, 1.85 g of ammonium fluoride was entirely dissolved in 100 ml of deionized water. Then, 22.8 ml of ammonium hydroxide was added to the ammonium fluoride solution. Then, in a 50 ml beaker, 7 ml of deionized water and 11 ml of ethanol were mixed, and 1 ml of the prepared solution was added under stirring at 25⁰C for 5 min.
2.3.2 Preparation of silica sol-gel
To prepare the solution, 5 mL of tetraethyl orthosilicate (TEOS) was vigorously mixed with 11 mL of 96% ethanol at 25⁰C for 5 min. The alkaline catalyst solution was then added instantly to the alcoholic TEOS solution while stirring continuously for 10 min. The prepared gel was fully immersed in pure ethanol solution for a day. After the aging process, the prepared gel was grinned and placed on filter paper for solvent replacement. The gel was washed with a hexane solution in ethanol five times and then immersed in pure hexane for 12 h.
2.3.3 Surface modification of silica aerogel
The surface modification procedure involved utilizing a sealed container containing a solution composed of 67 mL of hexane and 7 mL of trimethylchlorosilane (TMCS). To initiate the process, the pulverized gel was introduced into the solution for surface modification. Subsequently, the sealed container was positioned in an oven and kept at a temperature of 60°C for a duration of 6 hours. The hydrophobic aerogel was prepared by drying the gel through a supercritical drying process in pure hexane for 4 hours using a CO2 system after the container had been cooled.
2.4 Impregnation of Ag-CuPc-ZnO over the hydrophobic silica aerogel
To this aim, the prepared hydrophobic silica aerogel was dissolved into ethanol with agitation at 70⁰C. In addition, the prepared Ag-CuPc-ZnO samples were added to the solution and mixed at 70⁰C for 45 min. Finally, ethanol evaporated, and hydrophobic photocatalytic samples were prepared by drying at 100⁰C in the oven. The samples with 2.5%, 5%, 7.5%, and 10% Ag were labelled 2.5%ACZ/SA, 5%ACZ/SA, 7.5%ACZ/SA, and 10%ACZ/SA, respectively.
2.5 Nanocatalyst Characterization Techniques
In this study, In order to study the surface morphologies of ACZ/SA samples, their surface were covered with a layer of gold and specified by a scanning electron microscope (SEM, HITACHI S-109 4160). XRD analysis has been applied to characterize hydrophobic photocatalytic samples' crystalline structure and phase purity. The analysis was carried out using a Siemens D5000 diffractometer, which was equipped with a Cu radiation source (with a wavelength of 0.154056 nm). The scanning speed was set at 0.02 s-1, covering a 2θ range from 10 to 80. To assess the porosity, specific surface area, and pore diameter of the samples, the BELSORP-mini analyzer was employed, utilizing the Brunauer-Emmett-Teller (BET) and Barrett-Joyner-Halenda (BJH) methods. To identify the functional groups present in the prepared samples, Fourier Transform Infrared Spectroscopy (FTIR) analysis was performed using a PerkinElmer Spectrum 65 instrument, covering a wavelength range of 400 to 4000 cm-1. The porosity and specific surface area of the synthesized catalyst were determined using a ChemBET3000 analyser. DRS analysis was performed to determine the bandgap and light absorption spectra of prepared nanophotocatalyst (DRS, Sinco S4100, Korea). To evaluate the thermal stability of the best sample and examine the stability of CuPc (copper phthalocyanine) during the annealing process, thermogravimetric analysis (TGA) was performed. PL analysis was applied to investigate the influence of Ag on the recombination rate in the samples.
2.6 Evaluation of Closed-Batch Photoreactors Performance
The performance of the photocatalytic nanocomposites was studied for the photodecomposition of benzene under visible light irradiation from a 100 W halogen lamp in a closed batch photoreactor with varying geometries. The synthetic benzene wastewater used in the study appeared in two separate phases owing to its non-polarity and immiscibility in water. The experiments were performed using 0.3 g of photocatalyst in 100 mL of synthetic benzene wastewater with an initial benzene concentration of 5% v/v at pH 7. To achieve adsorption/desorption equilibrium between benzene molecules and the surface of the photocatalyst nanoparticles, the synthetic benzene wastewater was subjected to stirring in a light-restricted environment for 1 hour. Subsequently, the lamp was activated and positioned 5 cm above the synthetic benzene wastewater. To avoid benzene evaporation and potential temperature-related effects, the reaction temperature was kept constant at 25◦C using an ice bath. Sampling was carried out each 15 min during the photocatalytic reaction. To determine the percentage of benzene photodegradation, Gas Chromatography (GC) equipped with purge and trap devices was employed after each sampling event. The samples were analyzed using a Varian CP3800 gas chromatograph equipped with a Flame Ionizing Detector (FID). Hydrogen gas, with a flow rate of approximately 15 mL/min was used as the carrier gas, which was generated by an HG-2200B hydrogen gas generator. The injector temperature and detector temperature were set at 150°C and 300°C, respectively. Benzene conversion in the photodegradation process was calculated by Eq. (3):
Conversion (%) = 100 × ((C0 - C) /C0) (1)
Where C0 and C were the initial concentration and the concentration of MO at specified times, respectively. The light intensity of the lamp was determined by using a luxmeter (Extech HD450, England) and compared the measured value with the light intensity calculated by Equations (1) and (2):
Φ (photon / s) = (P×η)/(hc / λ) (2)
E (W/m2) = Φ × (hc / λ) (3)
Under identical conditions, four performance benchmarks were applied to assess the effectiveness of the different closed batch photoreactors. These benchmarks encompassed the rate constant (k), quantum yield (QY), space-time yield (STY), and photocatalytic space-time yield (PSTY) (Hakki & Allahyari, 2022a). By considering the photodecomposition of benzene as a first-order reaction, the rate constant (k, expressed in h-1) for the photocatalytic degradation reaction can be obtained through regression analysis. This analysis involves examining the linear relationship depicted by the plot of ln (C0/C) against the irradiation time (h). For all the applied photoreactors, the STY and PSTY are equal:
STY = k / 6.908 (4)
PSTY = STY / LP (5)
LP = P / V (6)
QY = N / Φ (7)
The variables LP, P, and V in the formulas mentioned above represent the standardized lamp power (measured in kW), the lamp power of the photoreactor (measured in kW), and the volume of the reaction medium in the experimental setup (measured in m3), N and Φ were numbers of decomposed Benzene molecules and photon flux, respectively.
Furthermore, the study also examined various parameters including the initial dye concentration, dosage of photocatalyst, and pH value of the dye solution.
(Figure 1)
(Figure2)
3.1.1 Photocatalytic Activity of ACZ samples
The photocatalytic activity of the nanophotocatalytic composites was studied in the photodegradation of Benzene in a rectangular photoreactor. The photocatalytic activity test results demonstrated a significant enhancement in the photocatalytic performance of the composite photocatalyst upon the introduction of Ag nanoparticles to ZnO. According to fig.3, 5%ACZ sample revealed the highest photocatalytic activity in the photodecomposition of benzene, which decomposed 95.27% of benzene in 90 min. The showed increase in photodegradation efficiency with increasing Ag loading in the photocatalytic composites can be attributed to the synergistic effect of Ag and ZnO in improving the photocatalytic activity. The Ag acts as an electron sink in the photocatalytic composites, trapping the electrons generated by ZnO nanoparticles and consequently preventing electron-hole recombination in the samples. This facilitates the separation of electron-hole pairs, leading to enhanced photocatalytic activity. In addition, the addition of Ag into the ZnO structure influenced the crystalline structure, surface area, and bandgap of the photocatalytic samples, and consequently, improved the photocatalytic activity of the samples. The obtained results from the PL analysis and DRS analysis are in excellent agreement with the findings obtained from the photocatalytic activity test.
(Figure 3)
3.1.2 Photoreactor Geometry
The photoreactor geometry can have a significant impact on the light distribution and light absorption by photocatalysts in the photocatalysis process. In this research, two rectangular photoreactor (15 cm × 10 cm × 6 cm) and cylindrical photoreactor (10 cm diameter and 15 cm height) geometries of photoreactors were applied to evaluate the effect of geometry on light intensity and distribution, and photodegradation efficiency. The photocatalytic treatment of synthetic benzene wastewater was performed with 5% v/v concentration in the presence of 5% ACZ/SA sample under the 100 w halogen lamp irradiation in both rectangular and cylindrical photoreactor. The results showed that the rectangular photoreactor had a photodegradation efficiency of 95.27%, while the cylindrical photoreactor exhibited a lower efficiency of 81.25%. The high benzene removal efficiency in the rectangular photoreactor can be due to the uniform light distribution in the photocatalytic reaction media and its flat bottom and sides that allow for more uniform illumination of the wastewater. While the low photodegradation efficiency in the cylindrical photoreactor compared to the rectangular photoreactor may be due to the curved shape of the walls, which caused non-uniform light distribution. To further evaluate and compare the performance of the photoreactors, the four aforementioned benchmarks were utilized. Table 1 presents a comparison between rectangular and cylindrical photoreactors in terms of reactor volume, lamp power, photocatalyst loading, rate constant, STY, PSTY, and QY for the photodegradation of benzene. Although the rate constant (k) is a useful parameter for quantifying reaction kinetics, it does not account for throughput, as it is dependent on reactor volume. To address this limitation, the space-time yield (STY) can be used, which is defined as the volume of treated wastewater required to decrease the concentration by three orders of magnitude in one day in a 1m3 photoreactor. Computations revealed rectangular photoreactor had the highest STY compared to the cylindrical photoreactor. According to the results the STY of rectangular and cylindrical photoreactors are 6.937 and 4.091 m3 wastewater.m-3 reactor.day-1, respectively. The value of STY is influenced by both the hydrodynamic behavior and the reaction rate constant. In this study, the static flow of wastewater in both photoreactors resulted in a higher STY value for the rectangular photoreactor. This difference can be attributed to the higher rate constant observed in the rectangular photoreactor. Due to the exclusion of electricity considerations in STY, which are crucial in assessing photocatalytic reactions, PSTY is proposed as a more comprehensive benchmark. PSTY takes into account the combined influences of reaction, mass and photon transfer rates, as well as light utilization efficiency, on the volume. As shown in Table 1, the PSTY of the rectangular photoreactor is 13.06 times higher than the PSTY of the cylindrical photoreactor. The high PSTY in the rectangular photoreactor confirms its efficient light distribution and high number of light photons reaching the photocatalytic nanoparticles, enabling effective photocatalytic reactions to perform. The obtained QY results indicated that the QY of the rectangular and cylindrical photoreactors is 0.00739% and 0.00631%, respectively. The rectangular photoreactor demonstrated the highest QY for the removal of benzene, indicating that it is an efficient photoreactor for electrical usage. This suggests that the design of the rectangular photoreactor is more effective than that of the cylindrical photoreactor in maximizing electricity utilization for photocatalytic wastewater treatment. During a photocatalytic reaction, only a fraction of the incident photons are absorbed by the photocatalyst surface, while the remaining photons may be transmitted, scattered, or reflected. Quantum yield (QY) is a measure of the photoreactors efficiency in utilizing the absorbed photons for the photocatalytic degradation of pollutants. In other words, the QY reflects the impact of the photoreactor configuration on both light distribution and photocatalytic efficiency.
(Figure 4)
(Table 1)
3.1.3 XRD Analysis
The XRD patterns of prepared ZnO, 2.5%ACZ/SA, 5%ACZ/SA, 7.5%ACZ/SA, and 10%ACZ/SA nanophotocatalytic composites in the 2θ range of 20-80◦ are demonstrated in fig. 4. According to the fig.4, the XRD strongest peaks revealed at 2θ values of 31.45, 33.94, 35.83, 47.38, 56.35, 62.56, 66.11, 67.44, 68.72, 72.25, and 76.83 are attributed to the lattice planes (1 0 0), (0 0 2), (1 0 1), (1 0 2), (1 1 0), (1 0 3), (2 0 0), (1 1 2), (2 0 1), (0 0 4), and (2 0 2), respectively. As depicted in Fig. 4, the doping of Ag into the ZnO structure caused the partial shift to a larger angle in the region of the (1 0 1) peak, stating that Ag+ was substituted with Zn2+ in the hexagonal wurtzite structure of ZnO. The peaks observed at 2θ values of 37.2, 43.9, and 64.3 are represented the Ag existence in the prepared samples that by increasing the Ag precursor in the solutions the peak intensity of Ag increased. Debye-Scherer's equation was applied to calculate the crystallite size of prepared samples. According to the debye-scherrer's equation the average crystalline size of ZnO, 2.5%ACZ/SA, 5%ACZ/SA, 7.5%ACZ/SA, and 10%ACZ/SA samples were 36.33, 30.41, 27.17, 29.56, and 34.67 nm, respectively. The calculated data indicated that by increasing the Ag concentration to 5% in the sols, the crystallite size decreased to 27.17 nm while by increasing its percentage from 5% to 10% the crystallite size increased to 34.67 nm. The lattice parameters a (the length of the side of the hexagonal unit cell) and c (the height of the unit cell) of the hexagonal structure, as well as the unit cell, were calculated and tabulated in Table 2. According to Table 1, the length of the unit cell decreased by increasing the Ag percentage to 5%. Subsequently, the length of the unit cell increased as the Ag amount in the samples went from 5% to 10%. In contrast, the height of the unit cell decreased with the increasing Ag amount in the samples. The ratios of c/a for ZnO, 2.5%ACZ/SA, 5%ACZ/SA, 7.5% ACZ/SA, and 10% ACZ/SA are 1.63297, 1.63293, 1.632908, 1.63292, and 1.63295, respectively. The results indicate that the c/a ratio decreased as the Ag percentage increased from 2.5% to 5% in the samples and then increased again as the Ag percentage increased from 5% to 10%. The volume of unit cell of ZnO, 2.5%ACZ/SA, 5%ACZ/SA, 7.5%ACZ/SA, and 10%ACZ/SA sample were calculated 5.1952, 5.1931, 5.0737, 5.0768, and 5.0184, respectively. The lattice strain of ZnO, 2.5%ACZ/SA, 5%ACZ/SA, and 7.5% ACZ/SA, and 10% ACZ/SA were 0.29894, 0.30178, 0.330929, 0.3055, and 0.257267, respectively. According to the results, the lattice strain of the samples increased when the Ag percentage was increased to 5% in the nanocomposites. However, by increasing the Ag percentage to 10%, the lattice strain significantly decreased to 0.257267. This reduction in lattice strain in the 10%ACZ/SA sample may be due to the defects and deformation of the ZnO hexagonal structure or the formation of another structure between Ag and Zn. The results indicated that in the 5%ACZ/SA sample, the Ag atoms were appropriately located in the ZnO structure due to the increase in lattice strain. According to Bragg's equation, the interlayer spacing of ZnO, 2.5%ACZ/SA, 5%ACZ/SA, 7.5% ACZ/SA, and 10% ACZ/SA were 0.164874, 0.16599, 0.165402, 0.17436, and 0.1664 nm, respectively. The results indicated that the influence of various Ag dosages on the interlayer spacing in the ZnO hexagonal structure was such that the interlayer spacing in all nanocomposites was higher than pure ZnO. This was due to the placement position of Ag atoms in the ZnO structure.
(Figure 5)
(Table 2)
3.1.4 FESEM Analysis of Photocatalytic Composites
The SEM analysis was utilized to examine the surface morphology and structural features of the synthesized photocatalytic nanocomposites. The FESEM images, as depicted in Fig.8 (a–d), reveal that the particles in all samples exhibit spherical shapes and are uniformly dispersed without any observable cracks. The uniform surface of the samples facilitates maximum absorption of irradiated light, stimulates the energy bandgap, and consequently leads to a high generation of electron-hole pairs. Finally, this results in the formation of active species and facilitates the maximum attack on pollutant molecules. Fig.8 reveals that by increasing the Ag contents in the samples, the particles size decreased, which is consistent with the XRD analysis results. Decreasing in the particle size can be due to the substitution of Zn2+ ions with Ag+ ions in the lattice structure, which caused lattice defects and inhibition of crystal growth. The aggregation of nanoparticles in all samples is due to the presence CuPc. This finding is consistent with our previous research that reported results on the CuPc effect on the Bi2O3- ZnO nanoparticles (Hakki & Allahyari, 2022b).
(Figure 6)
3.1.5 BET Analysis of Photocatalytic Nanocomposites
In studies of catalysts, the BET analysis is a commonly utilized technique for measuring the specific surface area. In this research, N2-adsorption analysis was utilized to study the influence of Ag amount on the pore diameter, specific surface area, and pore volume of the prepared ACZ/SA samples. N2 adsorption/desorption isotherms and pore size distribution graphs of the samples containing the least and highest amounts of Ag (5%ACZ/SA and 10%ACZ/SA samples) are presented in Fig.5. The specific surface area of 5%ACZ/SA and 10%ACZ/SA samples are 78.24 and 71.83 m2/g, respectively. The results had good agreement with XRD and FESEM analysis. According to our last published work (Najafidoust et al., 2021), the prepared silica aerogel had 659.74 m2/g. The findings derived from the BET analysis are in agreement with those obtained through XRD analysis. The results indicate that the increase in the concentration of Ag in the samples results in a reduction in crystal size, causing an increase in the specific surface area. In contrast, the introduction of silica aerogel to the samples leads to an increase in surface area, which has been reported in several prior studies (Gharibshahian et al., 2017; Muradov et al., 2018). Increasing the surface area of the sample led to an increase in the concentration of active sites on its surface(Gharibshahian et al., 2017). Specifically, expanding the surface area of samples based on silica aerogel resulted in a reduction of the pore diameter, while concurrently, the pore volume of the samples increased. As shown in Figure 6, the pore diameter distribution is wide in the 10% ACZ sample, whereas in the 5% ACZ sample, the pore distribution has become narrow. Increasing the silver content of the samples not only led to a reduction in crystal size, but also resulted in a decrease in pore diameter in the prepared nanoparticles, as confirmed by the BET analysis data.
(Figure 7)
3.1.6 Contact Angle Analysis of 5%ACZ/SA Photocatalytic Composite
To evaluate the hydrophobicity of the 5% ACZ/SA sample, contact angle analysis was performed using water as the testing liquid. The results of the analysis showed that the contact angle of the sample was measured to be 105º degrees while the contact angle of pure silica aerogel was reported 144º in our last research (Najafidoust et al., 2021). The results confirmed that the prepared photocatalyst has low affinity to water and can be floated on the wastewater and used for photodegradation of floated and immiscible pollutants with water.
(Figure 8)
3.1.7 DRS analysis
UV-Vis DRS analysis was applied to assess how the Ag content affected the bandgap energy, as well as to evaluate the influence of the CuPc content on the light absorption properties of the samples. The UV-Vis DRS spectra of the ACZ/SA nanocomposite samples and their Tauc plots are demonstrated in Fig. 9 and Fig.10. According to Fig. 9, all the prepared nanocomposites reveal quite similar light absorption profiles and by increasing the amount of Ag to 5% in the samples, the light reflectance has increased in the UV wavelength spectrum region. While, by increasing the amount of Ag to 7.5% and 10% the light reflectance has decreased in the UV wavelength spectrum. That means 5% Ag doping influenced the light absorbance in the samples and moved that to the visible light spectrum region. Conversely, incorporating CuPc into the ZnO structure led to enhanced light absorption in the visible spectrum, as reported in previous publications (Hakki & Allahyari, 2022b; Yarahmadi & Sharifnia, 2014). Due to the synthesized samples being indirect semiconductors, the absorption values were calculated by using the kubelka - Munk function, and the Tauc method (Dolgonos et al., 2016) was applied to determine the bandgap energies of synthesized nanocomposites (Landi Jr et al., 2022). For this purpose, the following equation was used to plot (ɑhʋ) 1/2 versus hʋ (eV) diagram (Tauc plot):
ɑhʋ = A (hʋ-Eg) 1/2 equation
Where ɑ, h, ʋ, Eg, and A are the absorption coefficient, Planck constant, radiation frequency, bandgap and a constant, respectively. The results of bandgap calculating revealed in fig.10. According to the Tauc method, the bandgap energies of 2.5%ACZ/SA, 5%ACZ/SA, 7.5%ACZ/SA, and 10%ACZ/SA samples were 3.15, 2.93, 3.05, and 3.15 eV, respectively.
(Figure 9)
(Figure 10)
3.1.8 Thermal Gravity Analysis (TGA)
To examine the stability of phthalocyanines in the 5% ACZ/SA photocatalytic composite sample and verify the absence of amorphous carbon arising from the reaction materials, TGA analysis was used. As shown in Fig. 12, a slight weight loss (close to 2% by weight) was observed in the temperature range of 470⁰C, which may indicate partial degradation of the structure of the copper phthalocyanine used in the photocatalytic sample at this temperature. However, considering the fact that the photocatalytic samples in this study were calcined at 400⁰C, we can conclude that the copper phthalocyanine in the photocatalytic samples has not been degraded. These results are consistent with the FTIR analysis, in which the functional groups related to copper phthalocyanine were clearly observed. In a study by Mohammad et al., it was found that copper phthalocyanine was not stable at temperatures above 490⁰C in its pure form, while the CuPc/ZnO photocatalyst remained stable at higher temperatures (Mohamed et al., 2019).
(Figure 11)
3.1.9 FTIR analysis
For additional characterization of the nanocomposites, FTIR analysis was conducted, and the outcomes are demonstrated in Figure 7. The peaks that appeared in the fingerprint region below 1000 cm-1 were attributed to metal oxides. Specifically, in this case, the peaks observed between 500-400 cm-1 correspond to the stretching vibration of the Zn-O bond. The observed peaks in the infrared spectra between 900-800 cm-1 for all samples originate from the benzene ring portion of the copper phthalocyanine structure. The vibration modes in this wavenumber range are assigned to out-of-plane C-H bending vibrations of the benzene ring in the phthalocyanine macrocycle(Salehabadi et al., 2020). These peaks confirm the presence of the intact phthalocyanine ring system in these samples. As shown in Figure 4, the peaks observed between 1200-1000 cm-1 in all samples are due to C=N and C-H vibrational modes within the copper phthalocyanine structure (Hakki & Allahyari, 2022b; Yarahmadi & Sharifnia, 2014). The peaks in the 1700-1600 cm-1 range are attributed to C=N vibrations of the phthalocyanine ring. The observed peak at approximately 1400-1200 cm-1 corresponds to C-H bending vibrations within the plane of the phthalocyanine ring. The presence of two merged weak peaks in the range of 2400-2200 cm-1 can be ascribed to the stretching vibration of C≡N bonds in CuPc. This type of peak is commonly observed in the nitrile functional group that exists in the CuPc molecule. The FTIR peaks observed in the range of 3000-2800 cm-1 can be associated with the stretching vibration of C-H bonds present in the CuPc molecule. This type of peak is usually observed in the alkyl and aryl groups that exist within the CuPc structure(Yarahmadi & Sharifnia, 2014). The peak observed at around 3400 cm-1 may correspond to the absorption of the stretching vibration of O-H bonds in copper phthalocyanine or the stretching vibration of Zn-OH bonds in ZnO(Denisenko et al., 2021; Golovnev et al., 2013).
(Figure 12)
3.1.10 Photoluminescence Analysis
PL analysis was used in order to evaluate the defects, optical properties, and electron-hole pair's recombination in the photocatalytic nanocomposites. For this purpose, the photoluminescence properties of the nanocomposites were studied at room temperature applying a 320 nm excitation wavelength of a Xe lamp are depicted in Fig. 9. The photoluminescence (PL) spectrum of all samples exhibited two distinct emission peaks. One of these peaks was observed in the ultraviolet (UV) wavelength region, while the other peak was located in the visible light region. In all samples, a distinctive peak between 420-460 nm was observed, which can be attributed to the electron transition from the donor level of oxygen vacancies to the defect donor level associated with ionized oxygen vacancies and the valence band. The intensity of the generated peak between 420–460 wavelengths has decreased by increasing the Ag content in the samples. According to Fig. 9, 10%ACZ/SA and 5%ACZ/SA samples have the highest and lowest intensity of the mentioned peak, respectively. Peak intensity in the PL spectrum showed the electron-hole recombination rate in the semiconductors in the defined wavelength. This means by decreasing the peak intensity, the electron-hole recombination rate decreased.
(Figure 13)
3.1.11 TEM Analysis
TEM analysis was conducted to further evaluate the 5%ACZ/SA sample. Figure 13 illustrates the TEM image of the 5%ACZ/SA sample, which exhibited the lowest electron-hole recombination rate and the highest photocatalytic activity among the prepared samples. TEM analysis indicates the presence of particles with two distinct shapes: spherical and hexagonal. These particles vary in size, with dimensions below 150 nm. Specifically, the ZnO nanoparticles exhibit a consistent hexagonal shape, while the silica aerogel particles appear to possess a fine spherical morphology.
(Figure 14)
3.1.12 Effect of Wastewater pH on Photodecomposition of Benzene
The pH of the wastewater plays an important role in the photodegradation process, which affects the surface electronic properties and the interaction between pollutant molecules and the photocatalytic nanoparticles' surface(Kazemi Hakki et al., 2021). According to the results, the photodegradation rate of benzene at pH 3, 7, and 9 is 69.37%, 95.27 and 80.25%, respectively. As shown in Fig. 13 neutral pH was optimal for the photodecomposition of benzene and the photodegradation efficiency is the highest. At the lower pH, H+ concentration and positive charge are increased in the solution. By increasing the H+ in the solution, the H+ ions act as a separating layer between the benzene molecules and the photocatalyst surface, which leads to adsorbing fewer benzene molecules on the surface of nanoparticles and consequently, decreasing the photocatalytic degradation efficiency (Najafidoust et al., 2021). On the other hand, decreasing in the benzene photodegradation efficiency at the alkaline pHs is due to the increasing amount of negative charges inside the wastewater solution and affecting the surface properties of the photocatalyst and hindering the adsorption of benzene molecules on the photocatalyst surface(Kataria & Garg, 2017). Variations in the surface charge of photocatalyst nanoparticles have been attributed to the changing point of zero (pzc) charge of metal oxides in response to changes in the pH of wastewater, resulting in the inhibition of benzene molecule adsorption on the photocatalytic composite surface(Kuśmierek et al., 2022). To determine the electronic properties of the photocatalytic composite surface, it is imperative to identify the isoelectric point, which corresponds to the pH value (pHpzc) at which the surface charge of the photocatalyst is neutral. The isoelectric point is a pivotal parameter that assists in comprehending the surface characteristics of the photocatalyst. At pHpzc, the surface charge density is zero, which means that the surface has neither a net positive nor a net negative charge. In photocatalytic wastewater treatment, pHpzc is important because in this pH the surface is not influenced by electric fields, and therefore may be more stable. Figure 14 shows that the pHpzc of the 5% ACZ/SA sample is 7.4. Therefore, optimal photocatalytic activity can be achieved at or near this pH.
(Figure 15)
(Figure 16)
3.1.13 Effect of Initial Photocatalyst dosage on removal of Benzene
The photocatalyst dosage is one of the effective parameters in the photocatalytic wastewater treatment, which can affect the process efficiency. Various photocatalyst concentration (0.5, 1.2, and 2 g/lit) were applied to evaluate the influence of photocatalyst dosage on the photocatalytic elimination of Benzene. The results of the experiments are indicated in Fig.15. The photodegradation process efficiency was the highest at the 1.2 g/l photocatalyst dosage. As shown in fig.15 by increasing the photocatalyst concentration from 0.5 to 1.2 g/l the removal percentage increased from 63.05% to 95.27%, while increasing the photocatalyst concentration to 2 g/l the process efficiency decreased from 95.27% to 74.87%. The results revealed that the photocatalyst dosage should have an optimal amount to achieve the best efficiency. Decreasing the efficiency of the photodegradation process at low photocatalyst dosages is due to the reduced absorption of photons by nanoparticles and low electron-hole generation. Additionally, low photocatalyst concentrations result in less contact between photocatalytic nanoparticles and benzene molecules, lower active species generation, and, consequently, fewer attacks on the benzene molecules, leading to decreased photodegradation efficiency. Conversely, the efficiency of the photodegradation process decreases at high photocatalyst dosages due to the agglomeration of the nanoparticles. This agglomeration leads to decreased light absorption and active phase generation, which in turn decreases the contact area between pollutant molecules and the active phase.
(Figure 17)
3.1.14 Reusability of 5%ACZ/SA Photocatalytic Composite
The reusability and stability of the photocatalyst in the photocatalytic wastewater treatment is significant factor for long-term application of photocatalyst in order to scale up and use in the semi-industry and industry scale. The stability test of the photocatalytic composite was performed over six consecutive periods for the photodegradation of benzene with a 5% v/v concentration in the rectangular photoreactor at pH = 7. After each period of use, the 5%ACZ sample was regenerated and its activity was evaluated. At the end of the stability test, the photocatalytic activity and the reduction rate of the activity were compared to those of the first and last steps. The results of the stability test of prepared photocatalytic composite in benzene photodegradation are depicted in fig.10. The diagrams demonstrate that the photocatalyst retained high photocatalytic activity even after six consecutive cycles of benzene photodegradation. The comparison between the first and last cycles of the stability test reveals that the photocatalytic activity of sample decreased by only 3.8%, indicating that the photocatalyst exhibited good stability during the test.
(Figure 18)
The conclusions indicated from this study are summarized as following:
- Adding Ag to the CuPc-ZnO/SA nanocomposite structure resulted in an increase in the photodegradation efficiency of benzene under visible light irradiation due to the reducing the electron hole recombination according to the PL analysis results. According to the results, the 5%ACZ/SA sample has removed about 95.27% of initial benzene concentration in 90 min.
- The geometry of the photoreactor significantly influences the efficiency of photocatalytic treatment. The value of k, STY, PSTY and QY in the rectangular photoreactor is higher than in the cylindrical photoreactor and this confirmed that the rectangular geometry is more effective than cylindrical geometry in photodegradation of floating pollutants due to its ability to provide uniform light distribution and illumination of the wastewater.
- According to the XRD and FESEM analysis, with increasing the Ag percentage in the samples the crystalline structure and particle size deceased. The substitution of Ag+ ions for Zn2+ ions in the lattice structure resulted in the presence of lattice defects, which ultimately hindered the process of crystal growth.
- The results of BET analysis revealed that increasing the Ag content caused the increasing the specific surface area and decrease in pore diameter in the prepared nanoparticles.
- DRS analysis demonstrated that all samples exhibit light absorption in the visible spectrum. The incorporation of Ag into the ZnO structure resulted in a decrease in the bandgap of the nanocomposites.
- The experiments revealed that the best pH according to the pHpzc of the prepared nanocomposite for photodegradation of benzene is 7 and by increasing the photocatalyst dosage from 1g/lit the process efficiency decreased.
Acknowledgements
The authors gratefully acknowledge Soran University and Nuzhan Nanofannavar Company for their complementary non-financial support.
Ethics approval All authors have read, understood, and have complied as applicable with the statement on “Ethical responsibilities of Authors” as found in the Instructions for Authors.
Data availability The datasets generated during and/or analysed during the current research are available from the corresponding author on reasonable request.
Competing interests The authors have no competing financial and/or non-financial interests.
Funding The authors did not receive support from any organization for the submitted work.
Author Contributions Statement
Hamid Kazemi Hakki: Supervision, Conceptualization, Data curation, Validation, review the manuscript.
Hadi Seyyedbagheri: Methodology, Visualization, Investigation.
Shahla Zubair Ahmed: Writing – original draft, Formal analysis.
Hossein Alinezhad Avalzali: Data curation, Formal analysis.
Aref Ghaderi: Writing – review & grammatical editing, Funding acquisition, Resources.
- Al-Nuaim, M. A., Alwasiti, A. A., & Shnain, Z. Y. (2023). The photocatalytic process in the treatment of polluted water. Chemical Papers, 77(2), 677-701.
- Angosto, J. M., Roca, M. J., & Fernández-López, J. A. (2020). Removal of diclofenac in wastewater using biosorption and advanced oxidation techniques: Comparative results. Water, 12(12), 3567.
- Armelao, L., Fabrizio, M., Gialanella, S., & Zordan, F. (2001). Sol–gel synthesis and characterisation of ZnO-based nanosystems. Thin Solid Films, 394(1-2), 89-95.
- Chauhan, A., Verma, R., Kumari, S., Sharma, A., Shandilya, P., Li, X., Batoo, K. M., Imran, A., Kulshrestha, S., & Kumar, R. (2020). Photocatalytic dye degradation and antimicrobial activities of Pure and Ag-doped ZnO using Cannabis sativa leaf extract. Scientific reports, 10(1), 7881.
- Denisenko, Y. G., Molokeev, M. S., Oreshonkov, A. S., Krylov, A. S., Aleksandrovsky, A. S., Azarapin, N. O., Andreev, O. V., Razumkova, I. A., & Atuchin, V. V. (2021). Crystal structure, vibrational, spectroscopic and thermochemical properties of double sulfate crystalline hydrate [CsEu (H2O) 3 (SO4) 2]· H2O and its thermal dehydration product CsEu (SO4) 2. Crystals, 11(9), 1027.
- Dolgonos, A., Mason, T. O., & Poeppelmeier, K. R. (2016). Direct optical band gap measurement in polycrystalline semiconductors: A critical look at the Tauc method. Journal of solid state chemistry, 240, 43-48.
- Dutta, S., Let, S., Sharma, S., Mahato, D., & Ghosh, S. K. (2021). Recognition and Sequestration of Toxic Inorganic Water Pollutants with Hydrolytically Stable Metal‐Organic Frameworks. The Chemical Record, 21(7), 1666-1680.
- Gharibshahian, M., Mirzaee, O., & Nourbakhsh, M. (2017). Evaluation of superparamagnetic and biocompatible properties of mesoporous silica coated cobalt ferrite nanoparticles synthesized via microwave modified Pechini method. Journal of Magnetism and Magnetic Materials, 425, 48-56.
- Golovnev, N., Molokeev, M., Vereshchagin, S., & Atuchin, V. (2013). Calcium and strontium thiobarbiturates with discrete and polymeric structures. Journal of Coordination Chemistry, 66(23), 4119-4130.
- Hakki, H. K., & Allahyari, S. (2022a). Intensification of photocatalytic wastewater treatment using a novel continuous microcapillary photoreactor irradiated by visible LED lights. Chemical Engineering and Processing-Process Intensification, 175, 108937.
- Hakki, H. K., & Allahyari, S. (2022b). Sonophotocatalytic treatment of wastewater using simulated solar light-driven Bi2O3-ZnO nanophotocatalyst sensitized with copper phthalocyanine. Materials Chemistry and Physics, 288, 126355.
- Hakki, H. K., Allahyari, S., Rahemi, N., & Tasbihi, M. (2018). The role of thermal annealing in controlling morphology, crystal structure and adherence of dip coated TiO2 film on glass and its photocatalytic activity. Materials Science in Semiconductor Processing, 85, 24-32.
- Hakki, H. K., Allahyari, S., Rahemi, N., & Tasbihi, M. (2019). Surface properties, adherence, and photocatalytic activity of sol–gel dip-coated TiO2–ZnO films on glass plates. Comptes Rendus Chimie, 22(5), 393-405.
- Joodi, A., Allahyari, S., Rahemi, N., Hoseini, S., & Tasbihi, M. (2020). ZnO–C3N4 solar light-driven nanophotocatalysts on floating recycled PET bottle as support for degradation of oil spill. Ceramics International, 46(8), 11328-11339.
- Kataria, N., & Garg, V. (2017). Removal of Congo red and Brilliant green dyes from aqueous solution using flower shaped ZnO nanoparticles. Journal of Environmental Chemical Engineering, 5(6), 5420-5428.
- Kausar, F., Varghese, A., Pinheiro, D., & KR, S. D. (2022). Recent trends in photocatalytic water splitting using titania based ternary photocatalysts-A review. International Journal of Hydrogen Energy.
- Kazemi Hakki, H., Shekari, P., Najafidoust, A., Dezhvan, N., & Seddighi Rad, M. (2021). Influence of calcination temperature and operational parameters on Fe-ZSM-5 catalyst performance in sonocatalytic degradation of phenol from wastewater. Journal of Water and Environmental Nanotechnology, 6(2), 150-163.
- Kumar, R., Qureshi, M., Vishwakarma, D. K., Al-Ansari, N., Kuriqi, A., Elbeltagi, A., & Saraswat, A. (2022). A review on emerging water contaminants and the application of sustainable removal technologies. Case Studies in Chemical and Environmental Engineering, 6, 100219.
- Kuśmierek, K., Dąbek, L., & Świątkowski, A. (2022). Removal of phenoxy herbicides from aqueous solutions using lignite as a low-cost adsorbent. Desalin. Water Treat, 260, 111-118.
- Landi Jr, S., Segundo, I. R., Freitas, E., Vasilevskiy, M., Carneiro, J., & Tavares, C. J. (2022). Use and misuse of the Kubelka-Munk function to obtain the band gap energy from diffuse reflectance measurements. Solid state communications, 341, 114573.
- Mohamed, H. H., Hammami, I., Akhtar, S., & Youssef, T. E. (2019). Highly efficient Cu-phthalocyanine-sensitized ZnO hollow spheres for photocatalytic and antimicrobial applications. Composites Part B: Engineering, 176, 107314.
- Muradov, M. B., Balayeva, O. O., Azizov, A. A., Maharramov, A. M., Qahramanli, L. R., Eyvazova, G. M., & Aghamaliyev, Z. A. (2018). Synthesis and characterization of cobalt sulfide nanoparticles by sonochemical method. Infrared Physics & Technology, 89, 255-262.
- Najafidoust, A., Asl, E. A., Hakki, H. K., Sarani, M., Bananifard, H., Sillanpaa, M., & Etemadi, M. (2021). Sequential impregnation and sol-gel synthesis of Fe-ZnO over hydrophobic silica aerogel as a floating photocatalyst with highly enhanced photodecomposition of BTX compounds from water. Solar Energy, 225, 344-356.
- Najafidoust, A., Hakki, H. K., Avalzali, H. A., & Bonab, M. K. A. (2019). The role of Diethanolamine as stabilizer in controlling morphology, roughness and photocatalytic activity of ZnO coatings in sonophotodegradation of methylene blue. Materials Research Express, 6(9), 096401.
- Pandis, P. K., Kalogirou, C., Kanellou, E., Vaitsis, C., Savvidou, M. G., Sourkouni, G., Zorpas, A. A., & Argirusis, C. (2022). Key points of advanced oxidation processes (AOPs) for wastewater, organic pollutants and pharmaceutical waste treatment: A mini review. ChemEngineering, 6(1), 8.
- Panis, C., Candiotto, L. Z. P., Gaboardi, S. C., Gurzenda, S., Cruz, J., Castro, M., & Lemos, B. (2022). Widespread pesticide contamination of drinking water and impact on cancer risk in Brazil. Environment International, 165, 107321.
- Priya, A., Suresh, R., Kumar, P. S., Rajendran, S., Vo, D.-V. N., & Soto-Moscoso, M. (2021). A review on recent advancements in photocatalytic remediation for harmful inorganic and organic gases. Chemosphere, 284, 131344.
- Rajendran, R., & Mani, A. (2020). Photocatalytic, antibacterial and anticancer activity of silver-doped zinc oxide nanoparticles. Journal of Saudi Chemical Society, 24(12), 1010-1024.
- Rana, I., Dahlberg, S., Steinmaus, C., & Zhang, L. (2021). Benzene exposure and non-Hodgkin lymphoma: a systematic review and meta-analysis of human studies. The Lancet Planetary Health, 5(9), e633-e643.
- Rayaroth, M. P., Aravindakumar, C. T., Shah, N. S., & Boczkaj, G. (2022). Advanced oxidation processes (AOPs) based wastewater treatment-unexpected nitration side reactions-a serious environmental issue: A review. Chemical Engineering Journal, 430, 133002.
- Salehabadi, A., Morad, N., & Ahmad, M. I. (2020). A study on electrochemical hydrogen storage performance of β-copper phthalocyanine rectangular nanocuboids. Renewable Energy, 146, 497-503.
- Tang, X., Tang, R., Xiong, S., Zheng, J., Li, L., Zhou, Z., Gong, D., Deng, Y., Su, L., & Liao, C. (2022). Application of natural minerals in photocatalytic degradation of organic pollutants: A review. Science of The Total Environment, 812, 152434.
- Taoufik, N., Boumya, W., Achak, M., Sillanpää, M., & Barka, N. (2021). Comparative overview of advanced oxidation processes and biological approaches for the removal pharmaceuticals. Journal of Environmental Management, 288, 112404.
- Wang, H., Li, X., Zhao, X., Li, C., Song, X., Zhang, P., & Huo, P. (2022). A review on heterogeneous photocatalysis for environmental remediation: From semiconductors to modification strategies. Chinese Journal of Catalysis, 43(2), 178-214.
- Wang, J., & Wang, S. (2020). Reactive species in advanced oxidation processes: Formation, identification and reaction mechanism. Chemical Engineering Journal, 401, 126158.
- Xie, M., Shon, H. K., Gray, S. R., & Elimelech, M. (2016). Membrane-based processes for wastewater nutrient recovery: Technology, challenges, and future direction. Water research, 89, 210-221.
- Xu, J., Zheng, L., Yan, Z., Huang, Y., Feng, C., Li, L., & Ling, J. (2020). Effective extrapolation models for ecotoxicity of benzene, toluene, ethylbenzene, and xylene (BTEX). Chemosphere, 240, 124906.
- Yarahmadi, A., & Sharifnia, S. (2014). Dye photosensitization of ZnO with metallophthalocyanines (Co, Ni and Cu) in photocatalytic conversion of greenhouse gases. Dyes and Pigments, 107, 140-145.
- Yi, Z., Jiang, T., Cheng, Y., & Tang, Q. (2020). Effect of SiO2 aerogels loading on photocatalytic degradation of nitrobenzene using composites with tetrapod-like ZnO. Nanotechnology Reviews, 9(1), 1009-1016.
- Zhang, Y., Zhou, B., Chen, H., & Yuan, R. (2023). Heterogeneous photocatalytic oxidation for the removal of organophosphorus pollutants from aqueous solutions: A review. Science of The Total Environment, 856, 159048.
- Zhao, Y., Zhang, S., Shi, R., Waterhouse, G. I., Tang, J., & Zhang, T. (2020). Two-dimensional photocatalyst design: A critical review of recent experimental and computational advances. Materials Today, 34, 78-91.
No competing interests reported.