Abstract

Chromium Cr(III) is considered as a toxic pollutant in industrial wastewater. Photocatalytic processes can be used as an efficient method for the treatment of heavy metal wastewaters. This study was conducted to synthesize copper (II) oxide (CuO) with dendrite, leaf and feather morphologies. Synthesized CuO with dendrite and leaf morphologies were characterized by XRD, SEM, and BET/BJH and CuO with feather morphology by XRD, SEM, BET/BJH, FTIR, TEM and DRS techniques. Parameters such as morphology CuO, the contact time (h), and adsorbent dosage (g) in adsorption of Cr(III) and morphology CuO, pH and initial concentration of Cr(III) in the photocatalytic oxidation were investigated. The results demonstrate that CuO feather at 24 h contact time with 0.1 g adsorbent with an adsorption efficiency of 57.24% has the highest efficiency compared to CuO of dendrite and leaf. Oxidation results demonstrate that CuO feather at 2 h with 0.1 g adsorbent dosage and pH = 7 had 89.14% removal efficiency. Also, oxidation results demonstrate that CuO feather at 2 h with 0.1 g adsorbent dosage and pH = 8 had 99.99% removal efficiency, which indicates the high efficiency of the feather.

INTRODUCTION

Nowadays, with population growth and the proliferation of industries, industrial wastewater pollutant materials' production has increased. Meanwhile, heavy metals, due to their high toxicity and low degradation, threaten the health of human beings and nature. Chromium is found in industrial wastewater both as Cr(III) and in Cr(IV) types (Martinson & Reddy 2009; Yu et al. 2012; Arfaoui et al. 2015). Cr(III) is found in industries such as glass, ceramics, photography, dyeing, textiles and the production of animal waste adhesives. Some contaminants in industrial wastewater lead to damage in DNA and cause carcinogenicity and mutagenicity (Rahman et al. 2013; Yang et al. 2015; Rajar et al. 2017). Also, chromium causes renal dysfunction and creates severe allergies even at low concentrations. Regarding the dangers of chromium in the wastewater of various industries, removal of Cr(III) prior to discharge to surface water resources is essential. Hence, many methods have been used to remove Cr(III) from aqueous solutions, including electrochemical deposition, ion exchange, membrane separation, and adsorption processes. However, these methods had some disadvantages and limitations like high lead cost, excess sludge production during the process, and the defective removal of chromium and failure to reach the standard for discharge to water resources (Suryanarayana 1995; Sabbaghan et al. 2015; Soomro et al. 2016; Yao et al. 2016). Among various physical and chemical approaches, photocatalysis has received extensive attention for removal of organic dyestuffs. This is thanks to the rapid development of nanostructured oxide semiconductors which can efficiently utilize abundant solar light as a driving energy source (Xiang et al. 2013; Tang et al. 2016). Photocatalysis processes are an appropriate alternative for removal Cr(III) that has drawn attention in recent years. Because of some reasons such as the lower cost, satiety from strong oxidizing agents and there being no dangerous wastes in products, these processes could be considered as high performance procedures. Nowadays, CuO nanostructures play an essential role in the industrial world. Because of its semiconductor properties, this metal oxide has many functions in the electronic industry. This product is widely used as a catalyst in the petrochemical, glass, ceramic, and sanitary industries. Also, many studies on using of this nanomaterial in textile, water and sewage industries, medical sciences, pharmaceuticals, lasers, and other optical instruments have been performed (Ozin & Arsenault 2003; Khayati & Janghorban 2012; Mallakpour & Aalizadeh 2013; Jayaprakash et al. 2014; Mallakpour & Madani 2015). The unique properties of CuO nanoparticles mean this nanoparticle is suitable for many functions as an antioxidant, antimicrobial, semiconductor, heterogeneous catalyst, lithium battery, solar cell, high-temperature superconductor, and solid and gas sensor. Other functions of CuO that can be mentioned are its use in textile manufacturing, nanowires, microelectronics, nanofluids, and electrochemical tubes. Also, CuO nanoparticles are used as high-performance adsorbents to remove and treat water containing arsenate and arsenate ions (Chen et al. 2003; Yoshimur & Byrapp 2008; Shi et al. 2013; Yang et al. 2013). CuO nanoparticles with a bandgap of 1.2 eV, due to its high catalytic and photochemical properties, toxicity, and low cost have been widely used to remove pollutant materials from aqueous media. So far, many methods have been developed to synthesize CuO nanostructures such as thermal oxidation of copper, thermal degradation, hydrothermal, aqueous reactions, laser, electric arc discharge; electron beam lithography, solid-liquid-steam synthesis, and solid-liquid-solution synthesis. In this study, different morphologies of CuO including dendrite, leaf and feather were synthesized by hydrothermal methods. The adsorption and photocatalytic oxidation of Cr(III) was studied with synthesized copper oxides. Parameters such as morphology CuO, contact time (h), adsorbent dosage (g) in adsorption, pH and initial concentration of Cr(III) in photocatalytic oxidation were investigated.

MATERIALS AND METHODS

Chemicals

Copper (II) nitrate (Cu (NO3)2.3H2O), copper (II) chloride (CuCl2.2H2O), polyethylene glycol (PEG 200 & 2000), hexamethylenediamine (HMDA), sodium hydroxide (NaOH), hydrochloric acid (HCl), chromium (III) chloride (CrCl3.6H2O), and hydrogen peroxide (H2O2 (35%)) were purchased from Merck.

Synthesis of CuO dendrite

1.2 g Cu (NO3)2 was added to 58 mL distilled water (solution 1). Next, 2 mL of PEG 200 was added to solution 1 (solution 2). Then 0.4 g of NaOH was added to solution 2 and it was placed in a magnetic stirrer for 30 minutes. After that, the solution was placed in an autoclave at 80 °C and in the oven for 14 h. Finally, the precipitate was washed and dried at 60 °C for 7 h in an oven.

Synthesis of CuO leaf

0.6 g of Cu (NO3)2 was added to 25 mL distilled water (solution 1). 1.45 g of HDMA was added to 25 mL distilled water (solution 2). Solution 2 was added drop wise to solution 1. Then, the solution was placed in a heater for 30 minutes at 80 °C. After that, it was placed in an autoclave at 140 °C for 6 h. Lastly, the precipitate was washed and then dried at ambient temperature.

Synthesis of CuO feather

0.16 g of CuCl2 and 0.2 g of PEG 2000 were added to 50 mL distilled water (solution 1). Next, 0.25 g of NaOH was added to 5 mL distilled water (solution 2). Then, solution 2 was added to solution 1 and it was placed in an autoclave for 24 h at a temperature of 140 °C. Finally, the precipitates were washed and placed in an oven at 80 °C for 2 h.

Cr(III) adsorption

50 mL Cr(III) solution with concentrations of 50 ppm were mixed with different adsorbent masses of 0.02, 0.05, and 0.1, and 0.2 g of CuO dendrite, CuO leaf and CuO feather was poured into an Erlenmeyer flask at 200 rpm at 12, 24 and 48 h. Then the desired solution was centrifuged and analyzed by ICP-OES at 267 nm.

The percentage of Cr(III) adsorption capacity is calculated as follows:  
formula
(1)
where A0 is the initial adsorption of the solution and Af is its final adsorption in the reaction.

Reactor

The photoreactor that was used in this study is a batch device. The four sides of this device are four UVC lamps of 16 watts, so that light can easily be applied to all parts of the sample. The sample container is located in the center of the device and has a magnet, so the samples were mixed easily.

Cr(III) photocatalytic oxidation

200 ml of Cr(III) solutions 50–450 mg/L (Miretzkya & Fernandez Cirelli 2010) with 0.1 g of CuO dendrite, CuO leaf and CuO feather and 1 µL of H2O2 at pH 3, 6, 7, 8 and 13 in cell quartz were poured and then the samples were put in a 64 watt photoreactor for 2 h. After this time, the samples were centrifuged and analyzed by ICP-OES at 267 nm.

Studies on adsorption isotherms

In this study, experimental data adsorption equilibrium with 2, 3 and 4 parameter isotherms (Saadi et al. 2015) for CuO feather were studied. Curve expert software was used for obtaining irregularities of isothermic equations and calculating the qe, the number of concentrations, and equilibrium adsorption capacity that are used for describing the results. Isotherms are shown in the Supplementary Data S1:  
formula
(2)
where qe is the equilibrium adsorption capacity (mg/g), C0 is the initial concentration of metal in solution (mg/L), Ce is the concentration of metal in solution (mg/L), V is the amount of solvent (L) and W is the adsorbent weight (g).

Error functions

Nonlinear regression is one of the most suitable tools for determining the quantitative ratios of adsorption distributions, mathematical analysis of adsorption systems, and for comparing the compatibility of theoretical assumptions of an isotherm model. Due to the error in the parameter estimation based on the change of an equation and the deviation in matching the results, several important mathematical error functions such as sum square error (ERRSQ), hybrid fractional error function (HYBRID), sum of absolute error (EABS), average relative error (ARE), Marquardt's percent standard deviation (MPSD), nonlinear chi square error and residual root mean square error (RMSE) (Saadi et al. 2015) were investigated. As computational technology develops, progress in nonlinear isotherm modeling has been greatly facilitated. Unlike linear models, nonlinear regressions usually minimize the error distribution (between empirical data and proposed isotherms) based on their convergence. In this study, three types of error are used to determine and evaluate the isotherm fitting models with experimental data. S2 demonstrates the error functions (Elmi Fard et al. 2016).

(S1 and S2 are shown in the Supplementary Data.)

RESULT AND DISCUSSION

Characterization of CuO dendrite, leaf, and feather particles

Figure 1 demonstrates the X-ray diffraction pattern of the CuO dendrite, leaf, and feather particles. Peaks 2θ = 32.5, 35.5, 39, 46, 49, 58, 61.5 and 66.68 indicate that the results of the particles contain CuO crystals.

Figure 1

XRD patterns of the CuO with different morphologies.

Figure 1

XRD patterns of the CuO with different morphologies.

SEM analysis was used to identify and investigate the morphology of the surface of CuO particles. Figure 2 demonstrates SEM images with the morphology Figure 2 a(i) and a(ii) of CuO dendrite, b(i) and b(ii) CuO leaf, and c(i) and c(ii) CuO feather. Based on the results, the CuO is formed and it has some special morphologies.

Figure 2

SEM images of the CuO with different morphologies, a(i) and a(ii) of CuO dendrite, b(i) and b(ii) CuO leaf, and c(i) and c(ii) CuO feather.

Figure 2

SEM images of the CuO with different morphologies, a(i) and a(ii) of CuO dendrite, b(i) and b(ii) CuO leaf, and c(i) and c(ii) CuO feather.

Due to the high amount of CuO feather particles, and efficient reaction, additional studies were performed on it. TEM analysis was used to determine the particle size and morphology of CuO feather particles (Figure 3).

Figure 3

TEM images of CuO feather with (a) 500 nm and (b) 150 nm.

Figure 3

TEM images of CuO feather with (a) 500 nm and (b) 150 nm.

Through the use of the BET method, the surface area of the CuO particles was determined. The BJH method is used to determine the mean diameter of the cavities and the total volume of the cavities were determined. The adsorption/desorption nitrogen isotherms provide the porosity structure properties (Figure 4). The results are obtained from the determination of surface area of the synthesized samples as demonstrated in Table 1. Based on the results, the highest surface area related to feather and the lowest surface area related to leaf morphology.

Table 1

Results of BET/BJH analysis for CuO different morphology

MorphologyVm (cm3 (STP)g1)aS, BET (m2 g1)CTotal pore volume (cm3 g1)Mean pore diameter (nm)VP (cm3 g1)rP, peak (Area) (nm)aP (m2 g1)
Dendrite 3.6852 16.04 54.814 0.1759 43.854 0.1771 1.29 17.235 
Leaf 3.0004 13.059 35.306 0.07278 22.292 0.074662 1.29 15.704 
Feather 4.1288 17.97 23.271 0.087952 19.577 0.090604 1.29 21.015 
MorphologyVm (cm3 (STP)g1)aS, BET (m2 g1)CTotal pore volume (cm3 g1)Mean pore diameter (nm)VP (cm3 g1)rP, peak (Area) (nm)aP (m2 g1)
Dendrite 3.6852 16.04 54.814 0.1759 43.854 0.1771 1.29 17.235 
Leaf 3.0004 13.059 35.306 0.07278 22.292 0.074662 1.29 15.704 
Feather 4.1288 17.97 23.271 0.087952 19.577 0.090604 1.29 21.015 
Figure 4

N2 adsorption–desorption isotherms of CuO with different morphologies.

Figure 4

N2 adsorption–desorption isotherms of CuO with different morphologies.

In Figure 5, the FTIR spectra for CuO feather are shown. In the CuO feather, the three characteristic bands observed at 409.50, 500.74, and 606.98 cm−1 could be assigned to the Cu-O stretching vibration. In the CuO, the three characteristic bands seen at 409.50, 500.74, and 606.98 cm−1 could be assigned to the Cu-O stretching vibration. The peak at 3,423.49 cm−1 was related to the O-H stretching bond.

Figure 5

FTIR spectra of CuO feather.

Figure 5

FTIR spectra of CuO feather.

Determination of the optical bandgap (Eg) in the semiconductor is a key issue in understanding the extent of electronic properties and it usually involves some analytical approximation in experimental data reduction and modeling of the light absorption processes. In the past decade, several studies have focused on the optical properties of a semiconductor. The bandgap property of the synthesized CuO feather was evaluated using a Tauc plot established on UV-vis absorption spectra (Raciti et al. 2017).

The equation is as follows:  
formula
(3)
where h is the Planck constant, ν is the applied frequency, α is the absorption coefficient, Eg is the bandgap, and A is a proportional constant. The bandgap values for CuO feather of 1.51 (eV) were determined by the Tauc method. The diagram is shown in Figure 6.
Figure 6

Band gap energy of CuO feather.

Figure 6

Band gap energy of CuO feather.

Effect of CuO morphology on adsorption and photocatalytic oxidation of Cr(III)

The surface area properties of catalysts are one of the most important characteristics of them. Therefore, CuO with different morphologies were studied with various surface characteristics in this experiment. Based on the results, the lowest efficiency is related to dendrite and the highest efficiency is related to feather morphology. Table 2 demonstrates the results of adsorption and photocatalytic oxidation by CuO dendrite, CuO leaf and CuO feather morphologies. The outcomes have shown that CuO feather at 24 h contact time with 0.1 g adsorbent and an adsorption efficiency of 57.24% has the highest efficiency compared to CuO with dendrite and leaf morphologies. Also, oxidation results have shown that CuO feather at 2 h with 0.1 g adsorbent dosage and pH = 7 had 89.14% removal efficiency. Based on the results, by changing the morphology of CuO, the effective surface area and type of pores for adsorption and interaction with UVC light were significantly different.

Table 2

The effect of CuO morphology on adsorption and photocatalytic oxidation of Cr(III)

MorphologyTime (h)Adsorption (%)Time (h)Oxidation (%)
Dendrite 24 39.18 65.29 
Leaf 24 44.51 77.40 
Feather 24 57.24 89.14 
MorphologyTime (h)Adsorption (%)Time (h)Oxidation (%)
Dendrite 24 39.18 65.29 
Leaf 24 44.51 77.40 
Feather 24 57.24 89.14 

Effect of contact time in Cr(III) adsorption by CuO with different morphologies

The results of the equilibrium time for removal of the Cr(III) by CuO dendrite, CuO leaf and CuO feather adsorbents showed that, in the first 12 h, the decrease of Cr(III) concentration followed by the adsorption process occurs with a rather steep slope, due to the highly active sites on the adsorbent surfaces at the beginning of the adsorption process. It is shown that during the second 12 h, adsorption takes place with a lower slope, because of reduction in the available active sites on the surface and more slow penetration and diffusion of the molecules through the adsorbent pores. After 48 h, occupied places on the adsorbent surface prevent adsorption of more molecules. In this case, the amount of adsorbed ions reaches the equilibrium state. For this reason, the equilibrium time is 24 h (Figure 7).

Figure 7

Effect of contact time for CuO with different morphologies.

Figure 7

Effect of contact time for CuO with different morphologies.

Effect of CuO adsorbent dose with different morphologies in Cr(III) adsorption

The effect of changes in the amount of adsorbent dosage in the adsorption of Cr(III) has an essential role in the adsorption processes efficiency. The effect of adsorbent mass on process efficiency in the same conditions is shown in Figure 8. It can be concluded that adsorption of Cr(III) increased with increase in the adsorbent mass from 0.02 g up to 0.1 g. Using greater amounts of adsorbent mass does not have a significant effect on adsorption due to partial coagulation of copper oxide particles.

Figure 8

Effect of CuO dosage for different morphologies.

Figure 8

Effect of CuO dosage for different morphologies.

Effect of pH in photocatalytic oxidation Cr(III) by CuO with different morphologies

One of the most important factors that have an effect on photocatalytic reactions is pH, which affects the surface charge of catalyst particles. The effect of pH on the efficiency of Cr(III) removal was evaluated by changes in the initial pH (3, 6, 7, 8 and 13). To change the pH of the solutions, HCl (1 M) and NaOH (1 M) were used. The results have shown that pH changes have a significant effect on process efficiency. Zeta potential results for CuO feather at different pHs are shown in Table 3.

Table 3

Zeta potential for CuO feather at different pH

MorphologypH = 3pH = 6pH = 7pH = 8pH = 13
Feather −1.49 (mV) −19.9 (mV) −24.6 (mV) −25.2 (mV) −16.7 (mV) 
MorphologypH = 3pH = 6pH = 7pH = 8pH = 13
Feather −1.49 (mV) −19.9 (mV) −24.6 (mV) −25.2 (mV) −16.7 (mV) 

The zeta potential is an indication of the surface potential, and so determines the magnitude of the electrical double layer repulsion. The total interaction between particles is the sum of the electrical double layer and the van der Waals interaction, which is determined by the magnitude of the Hamaker constant of the material.

The results of the pH effect on the adsorption rate showed that the highest efficiency occurs at pH = 8, and by decreasing and increasing the pH of the solution, the efficiency decreases. This result can be interpreted that decreasing the pH leads to increase in the hydrogen ion (H+), and increasing the pH leads to increase in the hydroxyl ion (OH) in the aqueous solution, and causes a competition with Cr(III) in the adsorption to functional CuO groups. Consequently, by increasing the hydrogen and hydroxyl ions, the free space for Cr(III) on the adsorbent decreases and leads to a decrease in efficiency. The highest and lowest Cr(III) removal efficiency was obtained from CuO dendrite, CuO leaf and CuO feather at pH = 8 and pH = 3 respectively (S3). At pH 8, the zeta potential for CuO dendrite, CuO leaf and CuO feather is −15.4, −21.8 and −25.2 mV respectively.

Effect of Cr(III) concentration on the photocatalytic oxidation of CuO with different morphologies

The effect of changes in the initial concentration of Cr(III) on the removal efficiency at different concentrations of 50–450 mg/L was investigated. The obtained results indicate that the rate of removal of Cr(III) is significantly decreased by increasing the initial concentration. With an increasing concentration of Cr(III), the active sites in CuO are blocked and saturated, which decreases the efficiency. According to the results, CuO feather had the highest adsorption capacity compared to the other two morphologies. CuO feather, leaf and dendrite had adsorption capacities of 197.56, 147.49 and 105.68 (mg/g), respectively.

The results for Cr(III) removal are shown nonlinearly for CuO dendrite, CuO leaf and CuO feather (S4). In S5, S6 and S7 the isothermic results for CuO feather are shown. Isothermic studies have shown that the Fritz-Schlunder (IV) equation, with a correlation coefficient of 0.999 and the lowest error rate, had the highest correlation by experimental data.

(S3, S4, S5, S6 and S7 are shown in Supplementary Data).

CONCLUSIONS

The present study was conducted to synthesize copper oxides with dendrite, leaf and feather morphologies. Then, their adsorption and photocatalytic properties were investigated in effective oxidation of Cr(III). The results show that CuO feather at 24 h using an adsorbent dosage of 0.1 g had an adsorption efficiency of 57.24%, It can be concluded that the highest efficiency in different morphologies belongs to feather. Also, based on the photocatalytic oxidation results, CuO feather at 2 h using an adsorbent dosage of 0.1 g and pH = 8 had a removal efficiency of 99.99%, which indicates the high efficiency of synthesized catalyst. Isothermic studies have shown that the Fritz-Schlunder (IV) equation with a correlation coefficient of 0.999 and the lowest error rate had the highest correlation by experimental data.

SUPPLEMENTARY DATA

The Supplementary Data for this paper is available online at http://dx.doi.org/10.2166/wst.2019.313.

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Supplementary data