Green synthesis of CuO nanoparticles using Peganum harmala extract for photocatalytic and sonocatalytic degradation of reactive dye and organic compounds

Abstract

The present study was performed to evaluate the effectiveness of photocatalytic and sonocatalytic processes for the removal of reactive blue 5 dye and organic compounds of textile effluent in the presence of copper oxide nanoparticles (CuO NPs). CuO NPs were synthesized using Peganum harmala seed extract. The structure of NPs was confirmed using SEM, TEM, XRD, EDX, and FTIR techniques. The tests were carried out in a batch system to assess factors affecting the dye removal efficiency, including contact time, pH, NPs dosage, and initial dye concentration. The experimental results showed that the photocatalytic process (98.42%) produced a higher degradation percentage than the sonocatalytic process (76.16%). While, the dye removal efficiency was not significant in the dark conditions (without UV or US waves). The maximum removal of reactive blue 5 dye under photocatalytic and sonocatalytic conditions occurred at the presence of 0.15 g of CuO NPs and dye concentration of 40 and 60 mg/L, respectively. The kinetic data followed a pseudo-second-order model in both photocatalytic and sonocatalytic processes with a correlation coefficient higher than 0.99. Isotherm studies showed that the Langmuir model was the best isothermal model to describe the adsorptive behavior of CuO NPs in a dark condition. The results obtained from GC-MS showed that the photocatalytic process had a degradation efficiency of over 87% in the removal of organic compounds.

Keywords

Green synthesis kinetics photocatalytic degradation reactive blue 5 sonocatalytic degradation

1 Introduction

Dye-contaminated effluent of textile industries is one of the major and most serious environmental concerns for the safety of land and aquatic ecosystems [1]. Reactive dyes, owing to their light color and better coloration property, are widely used in industries. These dyes are highly water-soluble, which facilitates their entry into wastewater [2]. Some studies have shown that the entry of reactive dyes into aquatic ecosystems, even at concentrations less than 1 mg/L, might result in serious threats to aquatic animals due to the reduced penetration of sunlight and water-soluble oxygen [3, 4]. Also, the presence of these dyes in drinking water is very dangerous for human health due to the formation of toxic and potentially carcinogenic compounds such as aromatic amines during the dye decomposition process [4 –7]. One of the most important and most commonly used reactive dyes, which is used in the textile industry for dying clothes, is the reactive blue 5 dye. It is an ordinary azo dye with a molecular weight of 774.15 g/mol and a molecular formula of C₂₉H₂₀ClN₇O₁₁S₃ that, like all azo dyes, has one or multiple –N = N–bonds in its chemical structure [8]. These dyes, due to their complex structure and high molecular weight, are highly resistant to biodegradation [9].

Various biological and physiochemical approaches, such as membrane filtration [10], biological degradation [11], adsorption [12], ozonation [13], ionic exchange [14], etc., have been utilized for wastewater treatment. The results of these methods are not satisfactory as they transform pollutants from the liquid to the solid phase. In recent years, reports have indicated that the advanced oxidation processes (AOPs) are suitable for the oxidation of a wide range of resistant organic compounds [15]. Today, the focus is put, among all types of the AOPs, on photocatalytic oxidation due to its high efficiency in the removal of resistant pollutants, low cost, suitable removal speed, lack of secondary pollution, and ease of use [15, 16].

In the photocatalytic process, radiation of photons (UV) on the semiconductors results in the excitation of electrons in the semiconductor, leading to the formation of electron-hole pair and, thereby, further synthesis of reactive oxygen species (ROS). The ROSs, due to their high oxidative properties, can decompose the organic compounds that are resistant to CO₂, H₂O, and other by-products [17, 18]. Furthermore, in the sonocatalytic process, the use of the chemical effect of the ultrasonic (US) waves results in the degradation of the organic compounds [18]. The US waves cause the formation of the nucleation cycle, growth, and collapse of the microbubbles in liquids. The collapse of bubbles creates a hot local point with a temperature of nearly 5000 K and a pressure of ∼500 bar [19]. Under such conditions, the water molecules are decomposed and highly reactive radical species such as hydroxyl (^•OH), hydrogen (^•H), and oxygen (^•O), which play a major role in the non-selective oxidation of pollutants, especially dyes, are formed [18, 20].

Metallic semiconductors, such as TiO₂, ZnO, ZnS, and CdS, have been widely used in wastewater treatment [21]. However, to date, a few studies have been conducted on the effect of CuO NPs on the efficiency of the photocatalytic and sonocatalytic processes in the removal of organic pollutants. CuO NPs possess a monoclinic crystalline structure with a large surface area, high thermal conductivity, and high stability. In this structure, each Cu atom with four oxygen atoms is in a square flat configuration [22]. CuO nanostructures as a p-type semiconductor with a narrow band gap (1.2 eV) are safe and environmentally friendly compounds [23]. Due to the high energy absorption, they are used in the construction of solar cells [24]. In addition, they have diverse applications including semiconductors, biosensors, gas sensors, photodetectors, lithium-ion batteries, photocatalysts, etc. [25, 26]. Different morphological forms of CuO NPs can also greatly influence the photocatalytic degradation efficiency of azo dyes in aqueous media [26].

Today, the green synthesis of nanomaterials has rapidly increased due to its cost-effectiveness and environmental compatibility [27]. Among the biosynthesis methods of CuO NPs, the use of plants has been highly regarded since they are highly rich in polyphenols [28, 29]. In this synthesis method, the use of botanical compounds minimizes or eliminates the chemical interventions, resulting in a really green process with no environmental pollution [28].

In this study, CuO NPs were synthesized for the first time using P. harmala extract according to the search performed in available electronic sources. The synthesized NPs were then confirmed by X-ray diffraction (XRD), energy dispersive X-ray (EDX) analysis, scanning electron microscopy (SEM), transmission electron microscopy (TEM), and Fourier-transform infrared spectroscopy (FTIR). Then, the efficiencies of the photocatalytic and sonocatalytic processes were explored in the presence of CuO NPs considering the influences of pH, initial dye concentration, NPs dosage, and contact time on the removal of the reactive blue 5 (RB5) dye. Langmuir, Freundlich, and Temkin isotherms at the dark condition, as well as pseudo-first-order and pseudo-second-order, Elovich, and intraparticle diffusion kinetic models were explored in the next steps. Finally, organic compounds in textile industry effluent were removed under optimal conditions.

2 Experimental

2.1 Materials

All the used chemicals were at analytical grades. CuO NPs were synthesized using CuCl₂.2H₂O (Riedel-de Haën, Germany). Double-distilled water (Atlas Shimi, Iran) was also used throughout the experiments. A stock solution was prepared using the RB5 dye (C₂₉H₂₀ClN₇O₁₁S₃) (Meghmani Chemicals Ltd., India). The pH was adjusted using 0.01 N solutions of NaOH and HCl (Merck, Germany). Then, n-hexane was used for liquid-liquid extraction and experiments on the textile industry effluent.

2.2 Preparation of the plant extract

P. harmala was collected from the Moghan region in Ardabil province, the northwest of Iran, its seeds were separated from its pod, thoroughly washed several times with double-distilled water, and ground well. The ground material was sieved and dried at room temperature for 24 h. Then, 10 g of dried seeds were mixed with 100 mL double-distilled water and stirred (RH Digital KT/C, IKA Co., Germany) at 400 rpm at 80°C for 30 min until reaching a brownish extract. The cooled extract was filtered (Whatman No. 40, England) and stored at 4°C.

2.3 Synthesis of CuO NPs

For the synthesis of CuO NPs, 1.5 g of copper chloride dihydrate (CuCl₂.2H₂O, Riedel-de Haën Co., Germany) was dissolved in 100 mL of distilled water and stirred for 5 min. The blue solution was mixed with 10 mL of P. harmala seed extract containing reductants and stirred at 70°C for 6 h until its color changed from pale blue to dark green. To separate the solid component from the liquid phase, the sample was centrifuged (EBA 20, Hettich Co., Germany) at 5000 rpm for 30 min. The precipitate was dried at 80°C in an oven (UFE 500, Memmert Co, Germany) for 12 h, followed by calcination (F47, Shimi Fan Co., Iran) at 400°C for 2 h until reaching black CuO NPs (Fig. 1).

Fig. 1

Green synthesis of CuO NPs using P. harmala seed extract.

2.4 Characterization methods

The synthesized CuO NPs were confirmed by XRD, SEM, TEM, FTIR, and EDX tests. The XRD analysis (PW1730, Philips, Netherlands) was employed to evaluate the crystal structure of the samples and their mean particle size. The morphology and structure of the NPs were examined by a SEM (Philips XL30, Germany) and a TEM (CM120, Netherlands). The elemental composition of the samples was explored by EDX or EDS techniques (MIRA3, TESCAN, Czech Republic). Finally, FTIR (Bruker Tensor 27 FTIR, Germany) in a range between 400 and 4000 cm^–1 was applied to identify the functional groups of the samples.

2.5 Reactor design

A wooden chamber was used to design a discontinuous photocatalytic reactor. To provide the light source (energy), a UVC lamp (15 w, Hitachi Co., Japan) with a wavelength of 256 nm was attached to the sidewall of the wooden chamber. A quartz tube located 2 cm away from the energy source was employed to transfer the solution. The required oxygen was supplied by a quartz tube attached to an oxygen tank (Fig. 2a). An ultrasonic bath (2200ETH, SONICA Co., Italy) with a capacity of 3 L and a frequency of 40 kHz was utilized in the sonocatalytic process (Fig. 2b).

Fig. 2

Image and simple schematic of (a) photocatalytic and (b) sonocatalytic reactors.

2.6 Photocatalytic degradation of the dye

The main solution of the RB5 dye was prepared at a concentration of 1000 mg/L. Then, 50 mL of the dye solution with an initial concentration of 100 mg/L and a pH of 2 was prepared from the original solution and mixed with 0.09 g of CuO NPs in an ultrasonic bath for 5 min to make a suspension. It was then transferred into a quartz tube and exposed to UVC for 30 min. At 5-min intervals, 5 mL of the solution was withdrawn and transferred to a centrifuge to separate the solid component at 6000 rpm for 20 min. Finally, light absorption was measured using a UV-Vis spectrophotometer (DR5000, HACH Co., United States) in the 590 nm region (the wavelength of maximum absorbance). The samples were analyzed to determine the optimal value of parameters including dose of NPs, pH, initial concentration, and contact time. For this end, the desired amount of CuO NPs (0.03, 0.06, 0.09, 0.12, and 0.15 g) in each step was added to 50 mL of dye solution with the desired concentration (40, 60, 80, 100, 120, and 150 mg/L). Then, it was exposed to ultraviolet radiation for the desired contact time (5, 10, 15, 20, 25, 30, 35, 40, and 45 min) [30 –32].

2.7 Sonocatalytic degradation of dye

First, 50 mL of the sample at a concentration of 100 mg/L and pH 2 was mixed with 0.09 g of NPs on a magnetic stirrer at 1000 rpm for 15 min to achieve a suspension. The sample was transferred to an ultrasonic bath at a frequency of 40±5 kHz for 30 min. In the next step, the NPs were separated by centrifugation.

2.8 Computational steps

The effects of different values of pH, dye concentration, nanoparticle dose, and contact time were assessed by repeating the experiments while changing one parameter and keeping the others constant. Equations 2 were used to determine the efficiency and the removal rate of the RB5 dye, respectively [33]. $R (%) = \frac{c_{0} - c_{t}}{c_{0}} \times 100$ (1) $q = \frac{c_{0} - c_{t}}{m} \times V$ (2) where R shows the dye removal percentage, C₀ and C_t denote the initial and secondary dye concentrations (mg/L), respectively, q indicates the adsorption capacity (mg/g), V represents the solution volume (L), and m is the adsorbent mass (g).

2.9 Effluent sampling, identification and degradation of organic compounds

The optimal experimental conditions (pH, contact time, and optimum CuO NPs dosage) obtained from the removal of the RB5 dye were evaluated to remove organic compounds from the treatment plant effluent. Regarding the higher efficiency of the photocatalytic process than the sonocatalytic one, the photocatalytic removal of organic compounds was investigated under optimal conditions. To obtain samples, the effluent samples were collected during the peak operation hours from the main outlet of the wastewater treatment plant of the Textile Factory in Ardabil province. The samples were kept at 4°C. The organic compounds of the samples were explored by a CG-MS device (7890A, Agilent Co., USA) operating with helium at a flow rate of 1 ml/min. The type of the applied column was HP-5MS (30 m with an internal diameter of 0.25 mm) and a constant phase thickness of 0.25μm at 50–250°C, 5°C/min. The ionization energy was 70 eV. As the aqueous phase cannot be used in GC-MS, 20 mL of effluent with 20 mL of normal hexane (equal ratio) was transferred to an Erlenmeyer flask and stirred at room temperature for 24 h to achieve liquid–liquid extraction. The solution was then placed in a decanter funnel for 12 h to completely separate the aqueous phase from the organic one. Finally, effluent compounds were detected by GC-MS, and the contaminant removal percentages were reported after reading chromatograms.

3 Results and discussion

3.1 Characterization of the CuO NPs

3.1.1 XRD pattern

The XRD patterns of the synthesized CuO NPs were examined in Xpert Highscore software. Figure 3 shows the XRD pattern of CuO NPs which is in line with the standard JCPDS card No. of 05–0661. The peaks observed at 32.67°, 35.57°, 38.76°, 49.04°, 53.75°, 58.27°, 61.73°, 66.34°, 68.11°, 72.52°, and 75.37° were assigned to (110), (002), (111), (202), (020), (202), (113), (311), (113), (311), and (004), which are consistent with the monoclinic structure of CuO. The intensity and narrow width of the peaks indicate the crystalline nature of the NPs. Based on the Debye-Scherer formula (Eq. 3), the mean size of the crystallites was calculated from the width and position of the main peak in the XRD pattern as 33 nm. $D = K λ / β cos θ$ (3)

Fig. 3

XRD pattern of CuO NPs.

In this formula, D is the average crystallite size, K shows the crystal shape factor (approximately 0.9), λ denotes the wavelength of the X-ray source (1.54 Å), β is the peak width at half maximum height (FWHM), and θ is the diffraction angle [34].

3.1.2 SEM and TEM analysis

SEM and TEM investigations of CuO NPs showed spherical and densely synthesized NPs (Fig. 4a and 4b). In the spherical state, the surface-to-volume ratio of NPs increased significantly. This makes the synthesized semiconductor more efficient as a photocatalyst because it reduces the losses of the electron-hole pair due to the trapping of each of the charge carriers in a spherical state. The aggregation shown in the images is due to the lack of complete abrasion of the NPs after calcination. Moreover, the investigation of the SEM image shows that the average size of the NPs varied from 22 to 41 nm, which is in good agreement with the XRD results. The diameter distribution of CuO NPs in the histogram curve obtained from TEM results showed that the diameter size of the obtained NPs was in the range of 5–40 nm, which is consistent with the results of the Debye-Scherer equation and the SEM image (Fig. 5). In some places, the increase in the diameter of CuO NPs can be attributed to adhesion or so-called agglomeration.

Fig. 4

(a) SEM and (b) TEM images of CuO NPs.

Fig. 5

Histogram of Particle size distribution curve of CuO NPs.

3.1.3 EDX analysis

EDX spectroscopy was utilized to explore the purity of NPs and their elemental composition. The intensity of the peaks evidences the formation of high-purity CuO NPs (Fig. 6a). Weak signals related to chlorine and carbon were in the spectrum due to the use of copper chloride and biomaterials in the synthesis process [33]. According to the results, Cu and O with the respective weight percentages of 22.62 and 77.38 and atomic percentages of 46.27 and 53.73 are the main elements constituting the sample. In addition, EDX mapping was performed to observe distributions of the elements in the CuO NPs. As it can be seen in Fig. 6b, the indicated elements, demonstrate uniform distributions.

Fig. 6

(a) EDX pattern and (b) elemental mapping of CuO NPs.

3.1.4 FTIR studies

The FTIR spectrum indicates the vibrational bands and their relationships with the chemical compositions [35]. The FTIR spectra of the samples were obtained at the wavenumbers of 400–4000 cm^–1 (Fig. 7a and 7b). Two broad peaks at 3451 and 3343 cm^–1 indicate the stretching vibrations of hydroxyl functional groups [36]. Two weak peaks at 2852 and 2924 cm^–1 are attributed to the asymmetric and symmetric stretching vibrations of C-H [36, 37]. The 1639 cm^–1 band belongs to the stretching vibration of C = C [38], and the bands shown in 1380 and 1458 cm^–1 are related to the bending vibrations of C-H (Alkan group) [39]. The strong peaks observed at 465, 529, and 587 cm^–1 are attributed to Cu-O stretching vibrations and confirm the formation of CuO NPs (Fig. 7b) [40, 41]. The FTIR spectrum analysis of P. harmala extract revealed the presence of various chemical constituents (Fig. 7a). The broad band at 3448 cm^–1 shows the symmetric O–H stretching of the hydroxyl group, polyphenols, and alcohols. The absorption band at 2931 cm^–1 in the spectrum of P. harmala extract is attributed to the C–H group stretching. The band at 1628 cm^–1 corresponds to the C = O stretch of flavonoids [42]. The peak at 1413 cm^–1 is assigned to the C = C group of alkenes. The absorption peak at 1041 cm^–1 is corresponding to the C–O stretch of polysaccharides. The FTIR spectrum of CuO NPs shows that flavonoids and phenolic groups in P. harmala seed extract act as the stabilizer and reducing agents and activate the formation of CuO NPs [43].

Fig. 7

(a) FT-IR spectrum of P. harmala extract and (b) FT-IR spectrum of CuO NPs.

3.2 Effect of pH

The pH of a solution is one of the prominent factors in its dye absorption rate in aqueous media [31]. In this study, the removal efficiency of RB5 dye in the presence of CuO NPs is depicted at the pH range of 2–12 (Fig. 8). In photocatalytic and sonocatalytic oxidation, the highest dye removal (62.89% and 36.27%, respectively) was achieved at pH 2. However, the degradation efficiency was reduced to 19.7% at pH 2 in a dark (without UV or US waves). The radical species such as hydroxyl (^•OH) and superoxide (^•O₂^–) produced in the photocatalytic and sonocatalytic processes combine with the dye molecules and cause their degradation [45, 46]. The effect of pH on the removal process mainly depends on the type of contaminant and the pH of zero point of charge (pH_zpc) of the catalyst [47], which can significantly affect the electrostatic interactions between the catalyst and the dye molecules [48]. Gupta et al. [49] reported the pH_zpc of CuO NPs as ∼6.9 [49]. Therefore, the electric charge on the surface of the catalyst will be positive at solution pH levels below pH_zpc, leading to higher electrostatic adsorption of the anionic RB5 dye molecules (with a negative charge) on the positively-charged catalyst [50]. With increasing pH and performing experiments in neutral and alkaline environments, the percentage of dye degradation decreased with a steep slope. The negative ions at the adsorbent surface increased at higher pHs, promoting a repulsive force between the dye and the catalyst surface, hence, declining the removal efficiency [51]. The UV-vis spectra of RB5 dye removal by CuO NPs at different pH values for adsorption, sonocatalytic, and photocatalytic processes is shown in Fig. 9a–c, respectively.

Fig. 8

The effect of pH on the efficiency of photocatalytic, sonocatalytic, and adsorption processes (CuO NPs dosage: 0.09 g, initial dye concentration: 100 mg/L, contact time: 30 min).

Fig. 9

The UV-vis spectra of RB5 dye removal by CuO NPs at different pH values for (a) adsorption, (b) sonocatalytic, and (c) photocatalytic processes.

Figure 10 shows the mechanism of the photocatalytic process. By UV irradiation, electrons from the valence band (VB) are transferred to the conduction band (CB), thereby forming electron-hole pairs. The electron-hole pair reacts with the electron (e^–) acceptor and electron-donor molecules to form Reactive Oxygen Species (ROS) such as superoxide radical (^•O₂^–), hydrogen peroxide (H₂O₂), and hydroxyl free radical (^•OH). Simultaneously, the electron holes (h⁺) can react with H₂O to yield hydroxyl radicals (^•OH). These ROS possess superior redox ability, which can react with organic compounds and break them down into CO₂, H₂O, and other inorganic compounds [52, 53]. The main reactions of the RB5 dye removal by photocatalytic and sonocatalytic processes in the presence of CuO NPs are given in Equations 4 –17. $CuO NPs \overset{hv (UV or US)}{\to} e^{-} + h^{+}$ (4) $H_{2} O + h^{+} \to O H^{o} + H^{+}$ (5) $O_{2} + e^{-} \to O_{2}^{o -}$ (6) $O_{2}^{o -} + H^{+} \leftrightarrow {HO}_{2}^{o}$ (7) $H_{2} O \leftrightarrow H^{+} + O H^{-}$ (8) $O H^{-} + h^{+} \to O H^{o}$ (9) ${HO}_{2}^{o} + O_{2}^{o -} \to {HO}_{2}^{-} + O_{2}$ (10) ${HO}_{2}^{o} + H^{+} \to H_{2} O_{2}$ (11) $H_{2} O_{2} + e^{-} \to O H^{o} + O H^{-}$ (12) $H_{2} O \to))) H^{o} + O H^{o}$ (13) $2 O H^{o} \to H_{2} O_{2}$ (14) $H^{o} + O_{2} \to {HO}_{2}^{o}$ (15) $2 {HO}_{2}^{o} \to H_{2} O_{2} + 1 / 20_{2}$ (16) $Reactive blue 5 dye + (h^{+} or O_{2}^{o -} or H_{2} O_{2}) \to degradation product \to C O_{2} + H_{2} O$ (17)

Fig. 10

Schematic diagram representing the photocatalytic degradation mechanism of CuO NPs.

3.3 The effect of nanoparticle dosage

Figures 11 12 illustrate the influence of CuO NPs doses on the removal efficiency of RB5 dye and its concentration variation (C/C₀) as a function of UV and US exposure times. Tests were performed in two stages. Before starting the photocatalysis and sonocatalysis reactions, the adsorption of the reactive blue 5 dye on the CuO NPs in darkness was tested for 20 min. The highest removal efficiency of dye in darkness was obtained in the NPs dose of 0.15 g, which was equal to nearly 22%. By reaching the equilibrium state in dark conditions over the 20 min period, the effect of UV and US waves in the presence of the CuO NPs on the degradation efficiency of dye was tested. The experiments were repeated by changing the catalyst content from 0.03 to 0.15 g. The removal efficiency in both methods increased by enhancing the amount of CuO NPs, suggesting the direct dependence of RB5 dye removal on the concentration of CuO NPs. In the photocatalytic and sonocatalytic processes, the maximum removal of dye was obtained at a CuO NPs dose of 0.15 g, pH 2, and initial dye concentrations of 100 mg/L, 86.11%, and 61.2%, respectively. The improvement in the dye removal efficiency by enhancing the content of NPs can be assigned to the rise in the active sites on the catalyst and the increased level of adsorbent access for dye adsorption [54], which is consistent with the results of Kakarndee and Nanan (2018) [55]. In both processes, the slope of the dye removal was faster in the early minutes of the process, followed by reaching an equilibrium over time. Also, according to the obtained results, the removal efficiency exhibited no significant difference in the case of exposure to the UV and US waves in the absence of CuO NPs (control solution) so that the highest removal efficiency over the 45 min period was obtained equal to 10.4% and 3.6% for the photolysis and sonolysis processes, respectively. The dye degradation speed in the presence of nanoparticles along with the radiation of the UV and US waves was significantly increased compared to the use of each of them lonely [56].

Fig. 11

(a) Effect of different amounts of CuO NPs on photocatalytic removal efficiency and (b) the plot of the C/C₀ against time (t) using different photocatalysts (optimal pH 2, initial dye concentration: 100 mg/L, contact time: 45 min).

Fig. 12

(a) Effect of different amounts of CuO NPs on sonocatalytic degradation efficiency and (b) the plot of the C/C₀ against time (t) using different doses of CuO NPs (optimal pH 2, initial dye concentration: 100 mg/L, contact time: 45 min).

3.4 Effect of dye concentration

The effect of RB5 concentrations on the efficiency of photocatalytic and sonocatalytic processes was explored in the range of 40–150 mg/L (Fig. 13). In both processes, the dye degradation efficiency decreased with raising dye concentration, which is in line with the results presented by Fatima et al. (2020) [57]. One possible reason could be the coverage of the active sites of the catalyst with dye ions at high dye concentrations, resulting in a decrease in the production of hydroxyl radicals (^•OH) [58]. With increasing the initial concentration of the dye, the production of the intermediate products also increases due to the dye decomposition, which may compete with the dye molecules in the decomposition process [59]. The highest removal rate was 98.42% in photocatalytic oxidation (UV/CuO) at a concentration of 40 mg/L, while it was 76.16% at 60 mg/L for the sonocatalytic process (US/CuO).

Fig. 13

The effect of RB5 dye concentration on (a) the photocatalytic, and (b) sonocatalytic degradation (pH 2, CuO NPs dosage: 0.15 g, contact time: 45 min).

3.5 Reusability test

The test of reusability of the CuO NPs in the photocatalytic and sonocatalytic processes for the degradation of the reactive blue 5 dye was performed in 12 cycles (Fig. 14). After each stage of the removal process, the nanoparticles were separated by centrifuge and then completely washed with water and ethanol [18]. Based on the obtained results, the dye degradation efficiency in cycle 12 for the photocatalytic and sonocatalytic processes was obtained equal to 89.7% and 73.1%, respectively (Table 1). Comparing the dye degradation rates from cycle 1 to cycle 12 in both processes indicates no significant difference before and after recycling the CuO NPs. This indicates the high chemical stability of this catalyst, which makes it suitable for the treatment of dye sewage [18].

Fig. 14

Recycling tests of the CuO NPs for photocatalytic and sonocatalytic degradation under optimal conditions (pH 2, CuO NPs dosage: 0.15 g, dye concentration: 40 mg/L, contact time: 45 min).

Table 1

Evaluation of CuO NPs stability after photocatalytic and sonocatalytic degradation

Removal of dye %
Cycles	1th	2th	3th	4th	5th	6th	7th	8th	9th	10th	11th	12th
UV/CuO NPs	98.4	98.5	98.7	94.2	95.2	92.2	91.6	96.9	91.1	89.7	87.3	89.7
US/CuO NPs	76.2	75.4	71.1	68.2	66.1	74.9	73.4	65.8	65.3	72.1	74.6	73.1

3.6 Adsorption isotherm

Isotherm models are one of the important factors in the design of adsorption systems. The adsorption isotherm indeed describes the relationship between the adsorbent and the adsorbate. Therefore, it is always an important factor in determining the absorber capacity and optimization of its application. Langmuir, Freundlich, and Temkin’s adsorption models were considered to assess the adsorption isotherms corresponding to the adsorption of the RB5 dye by CuO NPs in the dark (Fig. 15). Table 2 lists their linear equations and the calculated parameters. Comparing the correlation coefficients, the adsorption of RB5 on CuO NPs is most consistent with the Langmuir model (R² = 0.982) (Fig. 15a). According to Fig. 15b and 15c, the R² values below 0.9 indicate that the Freundlich and Temkin isotherms are not suitable for describing the removal process in the dark. Similarly, Ferghali et al. (2013) studied the adsorption of lead ions from aqueous solutions using CuO nanostructures and confirmed the adherence of the adsorption process to the Langmuir model [60]. A dimensionless coefficient, called the resolution index (R_L), can be obtained based on K_L (Equation 18), which helps to predict the absorption process. R_L > 1 suggests improper adsorption, while R_L= 1 and R_L= 0 represent linear and irreversible adsorption processes, respectively. 0 < R_L< 1 is indicative of a desirable adsorption process [61]. R_L ranged between 0 and 1 indicating the desirable adsorption of the dye by CuO NPs (Table 2). $R_{L} = \frac{1}{1 + (K_{L} C_{0})} ∥$ (18)

Fig. 15

Reactive blue 5 dye adsorption isotherms in the darkness based on (a) Langmuir, (b) Freundlich, and (c) Temkin models.

Table 2

Isotherm constants calculated for adsorption of RB5 dye by CuO NPs in the dark conditions

Langmuir				Freundlich			Temkin
$\frac{1}{q_{e}} = \frac{1}{q_{m}} + \frac{1}{K_{L} q_{m} C_{e}}$				$ln q_{e} = ln K_{F} + \frac{1}{n} ln C_{e}$			q_e = B_T ln K_T + B_T ln C_e
q _m	K _L	R _L	R ²	K _F	n	R ²	B _T	K _T	R ²
13.14	0.692	0.035	0.982	7.741	6.75	0.8	1.52	2.53	0.809 this work
21.2	0.990	–	0.996	0.150	0.90	0.92	–	–	- [44]

q_m: the maximum capacity of reactive blue 5 dye adsorbed as a monolayer coverage (mg.g^–1). K_L: The Langmuir constant (L.mg^–1). C_e: the equilibrium concentration (mg.L^–1). K_F: the Freundlich constant (mg^1–1/n.L^1/n.g^–1). n: The Freundlich constant related to adsorption intensity. B_T: The Temkin constant (J.mol^–1). K_T: the equilibrium binding constant corresponding to the maximum binding energy (L.mg^–1).

3.7 Reaction kinetics

The kinetics of the reaction should be explored to achieve the factors affecting the reaction rate [62]. In this research, the linear forms pseudo-first-order, pseudo-second-order, intraparticle diffusion, and Elovich models were used to fit the kinetic models to the experimental findings (Fig. 16). The results of the calculated parameters for the kinetic models are listed in Table 3. According to the diagrams and linear correlation coefficients (R²), the obtained data are most consistent with the pseudo-second-order model for both photocatalytic and sonocatalytic processes (R² = 0.995 and R² = 0.991, respectively) (Fig. 16b), indicating the suitability of this model for describing the kinetic behavior of CuO NPs for the absorption of the RB5 dye. These results are in line with those of Naghizadeh Asl et al. (2016) who examined the adsorption of organic dyes from an aqueous solution by CuO NPs [63].

Fig. 16

Kinetic models of (a) pseudo-first-order, (b) pseudo-second-order, (c) intraparticle diffusion, and (d) Elovich for RB5 dye removal.

Table 3

Kinetic constants calculated for the removal of RB5 dye by CuO NPs

Pseudo-first-order			Pseudo-second-order			Intraparticle diffusion			Elovich
ln(q_e - q_t) = ln q_e - k₁t			$\frac{t}{q_{t}} = \frac{1}{k_{2} q_{e}^{2}} + \frac{t}{q_{e}}$			q_t = k_dift^0.5 + C			$q_{t} = \frac{1}{β} ln (α β) + \frac{1}{β} ln t$
q _e	k ₁	R ²	q _e	k ₂	R ²	C	k _dif	R ²	α	β	R²
8.04	0.17	0.966	8.04	0.02	0.995	5.82	0.19	0.973	49.24	0.67	0.984 ^*
11.18	0.27	0.968	11.18	0.06	0.991	6.48	0.68	0.989	44.32	0.66	0.941 ^**

^*Parameters calculated for the photocatalytic degradation. ^**Parameters calculated for the sonocatalytic degradation. q_e: the amount of reactive blue 5 dye adsorbed at an equilibrium time (mg.g^–1). q_t: the amount of reactive blue 5 dye adsorbed at a particular time, t (mg.g^–1). k₁: the overall rate constant for pseudo-first-order kinetic model (min^–1). k₂: the overall rate constant for pseudo-second-order kinetic model (g.mg^–1.min^–1). α: the initial adsorption rate (mg.g^–1.min^–1). β: the extent of surface coverage (g.mg^–1). k_dif: the intraparticle diffusion rate constant (mg.g^–1. min^–0.5). C: the thickness of boundary layer (mg.g^–1).

3.8 Removal of organic compounds from the textile effluent

Organic compounds in the textile effluent sample were identified by GC-MS (Table 4). The chromatogram of the effluent sample before the removal process is shown in Fig. 17. The initial effluent sample contained Decane, Undecane, Dodecene, Naphthalene, decahydro-2,3-dimethyl, 2-methylmethylenecyclohexane, decahydro-1,5-dimethyl, Tridecane, Tetradecane, and Hexadecane, which constituted 73% of the sample. Due to the higher efficiency of photocatalytic oxidation than the sonocatalytic process in the dye removal from synthetic effluents, the performance of the photocatalytic process on real effluent was evaluated under optimal conditions.

Table 4
Organic compounds identified in the effluent by GC-MS

Row Compound Retention time (min) Frequency percentage

1 Benzene, ethyl- 4.663 0.81

2 XYLENE 4.838 2.25

3 Benzene, 1,2-dimethyl- 5.396 0.64

4 Nonane 5.499 0.66

5 Decane 8.253 5.08

6 4-Pentyloxy-2,3-dicyanophenyl 4-Pentylcyclohexanecarboxylate 10.747 0.47

7 Undecane 11.227 9.39

8 Pentane, 2-isocyano-2,4,4-trimethyl- 11.370 0.84

9 1,2,3,5-tetramethylcyclohexane 12.205 0.74

10 Naphthalene, decahydro-2,6-dimethyl- 13.203 0.56

11 Cyclopentane, (2-methylbutyl)- 13.391 0.59

12 3-Propoxyamphetamine 13.475 0.45

13 trans,trans-1,10-Dimethylspiro[4.5]decane 13.598 0.79

14 Naphthalene, decahydro-1,6-dimethyl- 13.650 0.58

15 Naphthalene, decahydro-1,6-dimethyl- 13.903 1.3

16 Dodecane 14.162 19.49

17 Naphthalene, decahydro-1,6-dimethyl- 14.344 2.99

18 Naphthalene, decahydro-2,3-dimethyl- 14.518 3.84

19 Naphthalene, decahydro-2,6-dimethyl- 14.609 1.69

20 2-methylmethylenecyclohexane 14.927 5.39

21 Naphthalene, decahydro-1,5-dimethyl- 15.076 10.72

22 Tridecane 16.961 7.21

23 Benzene, trimethyl(1-methylethyl)- 17.447 0.65

24 4-tert-Butyl-1,2-dimethylbenzene 17.700 0.57

25 Tetradecane 19.611 6.99

26 Hexadecane 24.484 5.38

27 Decane, 2-methyl- 28.883 0.84

Row	Compound	Retention time (min)	Frequency percentage
1	Benzene, ethyl-	4.663	0.81
2	XYLENE	4.838	2.25
3	Benzene, 1,2-dimethyl-	5.396	0.64
4	Nonane	5.499	0.66
5	Decane	8.253	5.08
6	4-Pentyloxy-2,3-dicyanophenyl 4-Pentylcyclohexanecarboxylate	10.747	0.47
7	Undecane	11.227	9.39
8	Pentane, 2-isocyano-2,4,4-trimethyl-	11.370	0.84
9	1,2,3,5-tetramethylcyclohexane	12.205	0.74
10	Naphthalene, decahydro-2,6-dimethyl-	13.203	0.56
11	Cyclopentane, (2-methylbutyl)-	13.391	0.59
12	3-Propoxyamphetamine	13.475	0.45
13	trans,trans-1,10-Dimethylspiro[4.5]decane	13.598	0.79
14	Naphthalene, decahydro-1,6-dimethyl-	13.650	0.58
15	Naphthalene, decahydro-1,6-dimethyl-	13.903	1.3
16	Dodecane	14.162	19.49
17	Naphthalene, decahydro-1,6-dimethyl-	14.344	2.99
18	Naphthalene, decahydro-2,3-dimethyl-	14.518	3.84
19	Naphthalene, decahydro-2,6-dimethyl-	14.609	1.69
20	2-methylmethylenecyclohexane	14.927	5.39
21	Naphthalene, decahydro-1,5-dimethyl-	15.076	10.72
22	Tridecane	16.961	7.21
23	Benzene, trimethyl(1-methylethyl)-	17.447	0.65
24	4-tert-Butyl-1,2-dimethylbenzene	17.700	0.57
25	Tetradecane	19.611	6.99
26	Hexadecane	24.484	5.38
27	Decane, 2-methyl-	28.883	0.84

Fig. 17

Chromatogram of the effluent sample before the removal process.

The chromatogram of the effluent sample exposed to UV waves in the presence of CuO NPs is shown in Fig. 18. Besides, the frequency percentages of the identified organic compounds and their removal efficiencies are listed in Table 5. According to the results, compounds such as 2 methylmethylenecyclohexane, naphthalene, decahydro-1,5-dimethyl, hexadecane, and decahydro-2,3-dimethyl were completely (100%) eliminated in this process. Cyclic hydrocarbons are often degraded due to high pressure and instability in the face of hydroxyl radicals. Organic compounds such as Tetradecane, Decane, Tridecane, Dodecene, and Undecane were eliminated at the rates of 96.2, 94.0, 90.6, 88.3, and 87.7, respectively. In a study by Nouri-Dodaran et al. (2018), acceptable results were obtained in the removal of organic compounds from effluent using the photocatalytic process [64].

Fig. 18

Chromatogram of effluent sample after photocatalytic oxidation in the presence of CuO NPs.

Table 5

Frequency percentages and removal rates of compounds in effluent under the photocatalytic process

Compound	Frequency percentage	Removal percentage	Structure
Undecane	17.8	87.7
Dodecene	38.4	88.3
Tridecane	12.1	90.6
Decane	4.8	94
Tetradecane	5.3	96.2
Naphthalene, decahydro-2,3-dimethyl	–	100
Hexadecane	–	100
2-methylmethylenecyclohexane	–	100
Naphthalene, decahydro-1,5-dimethyl-	–	100

4 Conclusions

In this work, CuO NPs were synthesized for the first time using P. harmala seed extract and confirmed by XRD, EDX, SEM, TEM, and FTIR techniques. Then, the photocatalytic and sonocatalytic degradation of the RB5 dye and organic compounds were explored in experiments. The adsorption efficiency of RB5 by CuO NPs in dark conditions was low compared to photocatalytic and sonocatalytic processes. The synergistic effect of CuO NPs and ultraviolet waves was more effective in removing the RB5 dye (degradation efficiency of 98%) than CuO NPs and ultrasonic waves (76%). The use of CuO NPs in combination with UV and US waves produces electron-hole pairs, which leads to more production of oxygen radicals, resulting in quick oxidation of the dye molecules. Increasing the NPs value from 0.03 to 0.15 g increased the degradation efficiency. The efficiency declined with an increase in the dye initial concentration from 40 to 150 mg/L. The degradation efficiency of over 87% was obtained by the removal of organic compounds from the real effluent using the photocatalytic process. The data obtained from investigating kinetic models were well fitted in a pseudo-second-order model with a correlation coefficient of above 0.99. Equilibrium data obtained in the dark condition fitted very well with the Langmuir isotherm (R² = 0.982) model compared to the Freundlich (R² = 0.800) and Temkin (R² = 0.809) models. Overall, the use of CuO NPs as the photocatalyst is effective and efficient and can be potentially used for the continuous removal of organic compounds from effluents. Accordingly, it is a promising and cost-effective method for the removal of other dyes from textile effluent.

Footnotes

Acknowledgments

This article was derived from PhD degree thesis in the Islamic Azad University, Science and Research Branch, Tehran.

Authors’ contributions

All authors had contributions to the writing, review, and final approval of the paper.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Conflicts of interest

On behalf of all authors, the corresponding author states that there is no conflict of interest.

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