Synthesis of the novel CuAl
2O
4–Al
2O
3–SiO
2nanocomposites for the removal of pollutant dye and antibacterial
applications
A. Saffar1 · H. Abbastabar Ahangar1 · Arsham Aghili2 · S. A. Hassanzadeh‑Tabrizi2 · Farham Aminsharei3 · H. Rahimi1 · J. Alikhani Kupai1
Received: 16 August 2020 / Accepted: 26 September 2020
© Springer Nature B.V. 2020
Abstract
CuAl2O4–Al2O3–SiO2 nanocomposites with different amounts of CuAl2O4 (40, 50, 60 and 70 wt. %) were synthesized by the sol–gel method and characterized by XRD, FTIR, FESEM, EDS and TEM analyses. The nanocomposites were applied for removal of methylene blue (MB) as a cationic dye from aqueous solution. The relation between removal percentages with variables such as adsorbent dosage (0.01, 0.03 and 0.05 g), adsorbent type (0, 30, 50, 70 and 100 wt. % related to CuAl2O3 in CuAl2O4–Al2O3–SiO2), pH (4, 7 and 10) and initial MB concentration (5, 10, 20 and 30 mg/L) was investigated. The maximum removal efficiency of MB was 96 wt. % in the optimized conditions (0.01 g of adsorbent, 50 wt. % of CuAl2O3, pH = 10 and MB = 10 mg/L). Moreover, an obvious decrease in the amount of Escherichia coli in a medium was observed by the addition of the title nanocomposite to the medium indicating its beneficial antibacterial activity.
Keywords CuAl2O4–Al2O3–SiO2 nanocomposites · Adsorbent · Antibacterial
Introduction
Metal aluminate spinels have been widely used in many industries such as biomedi- cal applications, the pigments, ceramics, optical materials and catalysts due to their resistance to acids and alkalis, lower sintering temperatures, increased hardness,
* A. Saffar
1 Department of Chemistry, Najafabad Branch, Islamic Azad University, Najafabad, Iran
2 Young Researchers and Elite Club, Najafabad Branch, Islamic Azad University, Najafabad, Iran
3 Department Safety, Health and Environment, Najafabad Branch, Islamic Azad University, Najafabad, Iran
improved ductility, availability and hydrophobicity [1]. The crystal structure of spi- nel type aluminate follows MAl2O4 (where M (Mg, Co, Zn, Cu) is a divalent metal cation) formula and consists of tetrahedral sites (A) and octahedral sites (B) in which 32 oxygen ions are packed in a unit cell and between the layers of oxygen ions exist interstices. Among these aluminates, CuAl2O4 is considered as the most promising and environmentally friendly strategy for antibacterial application with minimum metal toxicity. It is well known that the Cu leaching can be considerably decreased with the formation of CuAl2O4 through the sintering a mixture of CuO and Al2O3 [2–4]. Therefore, CuAl2O4 spinel shows a good antibacterial activity accompanied by Cu ions immobilization through its intrinsic structure. The antibacterial activ- ity can be attributed to the inhibition of enzymatic activity that leads to bacterial cell wall damage due to the opposite charge between bacterium and material sur- face. Different methods have been used to synthesize nano-CuAl2O4 spinel, such as coprecipitation [5, 6], hydrothermal synthesis [7], sol–gel method [8], microemul- sion [9], sonochemical [10], Pechini route [11] and microwave combustion [12].
Al2O3–SiO2 mixed oxides are important ceramic materials that, as inorganic sup- ports, have received particular attention due to their low thermal conductivity, low dielectric constant, robust chemical and thermal stability and oxidation resistance.
The high efficiency of Al2O3–SiO2–CuO nanocomposites as an adsorbent for dye removal was previously reported. To the best of our knowledge, there is no report about adsorption and antibacterial properties of CuAl2O4–Al2O3–SiO2 nanocom- posites which have been synthesized by sol–gel method. Therefore, in this research, CuAl2O4–Al2O3–SiO2 nanocomposites were synthesized by sol–gel method fol- lowed by calcination for dye removal methylene blue as a cationic dye. The obtained nanocomposites were characterized by Fourier transform infrared (FTIR) spectros- copy, X-ray diffraction (XRD), field emission scanning electron microscopy (FE- SEM), energy-dispersive spectrometry (EDS) and TEM. In addition, the antibacte- rial property of the CuAl2O4–Al2O3–SiO2 nanocomposites was tested by comparing the growth of Escherichia coli (E.coli) and S. aureus in culture medium.
Experimental
Materials and the synthesis of nanocomposites
All chemicals were purchased from Sigma–Aldrich and Merck and used without any purification. Tetraethyl orthosilicate (TEOS), copper nitrate (Cu (NO3)2·3H2O), aluminum nitrate (Al (NO3)3·9H2O) were used as Si, Cu and aluminum precursors, respectively. Al2O3–SiO2–CuAl2O4 nanocomposites with 30, 50 and 70 wt. % of CuAl2O4 were synthesized using the sol–gel approach.
The necessary amount of HCl (37 wt. %) was added to dilute TEOS in etha- nol/water, and the mixture was refluxed in 75 ℃ for 2 h (TEOS/C2H5OH/H2O/
HCl molar ratio was 1:22:13:7.9 × 10–4). Then, dissolved Cu (NO3)2·3H2O and Al (NO3)3·9H2O in ethanol/water were added to the mixture and refluxed at 75 ℃ for another 2 h. The resulting mixture was aged at room temperature for 24 h and dried in an oven for 24 h at 100 ℃. Then, they were calcined to 900 ℃ at a heating
rate of 10 ℃/min, and they were kept at this temperature for 5 h. The nominal con- tent of CuAl2O4 was 0, 30, 50 and 70 wt. %, and the corresponding nanocompos- ites were denoted as Al2O3–SiO2, CuAl2O4 40 wt. %Al2O3–SiO2, CuAl2O4 50 wt%
Al2O3–SiO2 and CuAl2O4 70 wt. %–Al2O3–SiO2. For comparison, pure CuAl2O4 nanocomposites were also prepared with the same procedure.
Characterization
The surface morphology of the nanocomposites was observed by field-emission scanning electron microscopy (Cam scan MV2300) and transmission electron microscopy (TEM, JEM-100CX, Japan). The crystal structures were examined by X-ray diffractometer (XRD, Philips X’Pert–PRO, PW3050/60 diffractometer).
Fourier transform infrared spectroscopy was recorded by the JASCO Model FT/
IR-6300 spectrometer using KBr as the reference sample within the wavelength range of 400–4000 cm−1.
Adsorption experiments
The dye removal experiment was conducted at room temperature as batches by user- friendly software with scanning and time course capacities; versatile data process- ing; Optizen 3220UV Spectrophotometer at a wavelength of 665 nm. Typically, a stock solution (1 g/L) of MB dye was prepared in deionized water, and then experi- mental solutions with different initial concentrations (5–30 mg/L) were obtained by successive dilutions. The required amount of CuAl2O4–Al2O3–SiO2 nanocomposite was added into the 10-mL dye solution and stirred for the predefined time. After that, the suspension was centrifuged and the supernatant was analyzed by ultravio- let–visible light (UV–Vis) spectroscopy to calculate the residual dye concentration.
The removal of dye percentage (R) was calculated using the following equation:
where C0 is the initial concentration and Ct is the concentration of the dye at time t [13].
Adsorption isotherms
Adsorption isotherms were performed to investigate the interactions between the adsorbate and adsorbent by applying Freundlich and Langmuir sorption isotherms [14]. Freundlich isotherm was used for abnormal adsorption on a heterogeneous sur- face with the following equation:
where KF is Freundlich equilibrium constant indicating the adsorption capacity and n is Freundlich constant showing the dependence of the absorbed material on the (1) Rwt% = ((C0−Ct)∕C0) ×100
qe=KFC (2)
(1
n
)
e
adsorbent surface. qe is the solved material amount on the adsorbent weight (mg/g), and Ce is the concentration of the absorbed material after completion of the adsorp- tion in the solvent and in the equilibrium state [14, 15].
Langmuir isotherm was used for adsorption on homogenous surface in monolayer form (single layer) with the following equation:
where KL is the Langmuir constant; qe (mg/g) and qm are related to the sorption capacity at equilibrium and maximum conditions, respectively; n is the heterogene- ity factor and Ce is concentration of the solution at equilibrium [11, 16].
Adsorption kinetics
To investigate the adsorption mechanism, the dye adsorption constants can be meas- ured by the pseudo-first-order kinetic equation and the pseudo-second-order kinet- ics. The adsorption kinetics can be described by pseudo-first-order kinetics:
In this equation, qeq and q are the amount of dye adsorbed at equilibrium and the amount of dye adsorbed at t, respectively, in mg/g and Kl is the pseudo-first-order adsorption equilibrium constant. In this equation, if log (qe − q) is plotted in terms of t for different experimental conditions, a straight line is obtained which can be used to obtain the Kl constant and the R2 correlation coefficient [3].
The adsorption kinetics can also be explained by the pseudo-second-order kinet- ics model.
So that, q is the amount of dye adsorbed at equilibrium in mg/g and K2 is the equi- librium rate of the pseudo-second equilibrium rate [3, 16, 17]. If the pseudo-quad- ratic equation is applicable, the graph of t/q versus t from the above equation should show a linear relationship. q and K2 are determined from the slope and intersection the point of the graph, respectively.
Antibacterial activity
To investigate antibacterial activity, CuAl2O4 (50 wt%)–Al2O3–SiO2 nanocomposite was applied against gram-positive (S. aureus) and gram-negative (E. coli) bacteria (the American Type Culture Collection (ATCC), USA) through the disk diffusion method (DDM). The Muller-Hinton agar was used with the addition of the agar to obtain 4-mm-thick layer; after that, inoculums of organisms are added and dried at 37 ºC for 30 min. The test disks are incubated at 37 °C for 24 h to determine antibac- terial potential of the prepared disk by measuring the inhibition zone [2].
(3) qe=qmKLCe∕(KLCe+1)
(4) ln(qeq−q) =ln qeq− K1t
2.303
t (5) q= 1
K2q2eq+ 1 qeqt
Results and discussion XRD diffraction
CuAl2O4–Al2O3–SiO2 nanocomposites were prepared by sol–gel method followed by calcination in an electric oven at a rate of 10 ℃/min for calcination at 900 ℃ for 5 h. In addition, Al2O3–SiO2 sample was prepared in order to investigate the effect of the presence of CuAl2O4 on the Al2O3–SiO2 support. The Al2O3–SiO2 sample is completely amorphous without any crystalline phase (Fig. 1a).
The phases identified in CuAl2O4–Al2O3–SiO2 nanocomposite are related to the copper spinel aluminate phase (JCPDS 01-1153), the monoclinic structure of the copper oxide phase (CuO) (JCPDS 09–0376) and also the mullite phase (JCPDS 15-0776) (Fig. 1b). In Fig. 1b, the peaks at 2θ values 31.261º, 36.831 º, 44.821 º, 55.671 º, 59.361 º and 65.281 º are related to (220), (311), (400), (422), (511) and (440) planes of the CuAl2O4 crystal, respectively.
It is clear that the peak intensity of mullite phase decreases with increasing the percentage of copper spinel aluminate phase. The basic amorphous (Al2O3–SiO2) phase that penetrated more with the alumina in the spinel phase led to the higher content of mullite phase in the lower 30 wt. % of CuAl2O4 [18, 19]. In addition, the presence of CuO phase in the samples indicating not fully this transformation at 900 ºC. Pure CuAl2O4 phase only appears at high temperature, while this phase is accompanied by CuO phase at low temperature. The obtained results showed the formation of CuAl2O4 phase delayed with compositing due to the distribution
Fig. 1 XRD patterns of the calcined at 900 ºC. a Al2O3–SiO2. b CuAl2O4–Al2O3–SiO2 nanocomposites.
c Peak shifting in XRD patterns
of particles on the Al2O3–SiO2 substrate and the lower interaction with each other supported with published data [20, 21]. It is interesting that the increase of mullite phase also affects the CuO phase intensity. The size of their crystals was measured by Debye-Shearer equation to investigate the effect of different amounts of compos- ite components on the size of CuAl2O4. Figure 1c also shows the peak displace- ment corresponding to the spinelic phase of CuAl2O4. It was observed that there a very small shift to the right (higher 2θ) due to the higher penetration of aluminum (smaller radii) into the CuAl2O4 structure and it replaces the atoms of the host net- work Cu (radii); as a result, diffraction occurs at higher angles. The size of the spinel crystallite generally decreased with the decreasing CuAl2O4 indicating that the com- posite base of Al2O3–SiO2 may be somewhat desirable (Fig. 2).
Scanning electron microscopy (FE‑SEM) and TEM image
Figure 3 shows a FE-SEM image of an Al2O3–SiO2 sample with its corresponding EDS analysis. The Al2O3–SiO2 nanoparticles are small, uniform and agglomerated (Fig. 4). The particle size is measured to be 12 to 25 nm, each of which is likely to consist of several crystals. Also, its EDS analysis only shows the presence of the elements of silicon, aluminum and oxygen without any trace of impurities. The com- position of Al2O3–SiO2 nanocomposite has been considered as a good potential for catalyst support due to its fine particle size, high surface area and good properties.
This catalyst support can be used for immobilization of catalyst particles to reduce their mobility and favoring the chemical and mechanical stabilization [22].
In CuAl2O4 (30 wt. %)–Al2O3–SiO2, the particles are almost spherical and very tightly coupled together and amorphous. The average diameter of the particles in the agglomerates is from 17 to 30 nm, which are composed of smaller particles. Their EDS analysis also shows the energies of the corresponding elements, i.e., copper, aluminum, silicon and oxygen, and no impurities were observed (Fig. 3).
The particles of CuAl2O4 (50 wt. %)–Al2O3–SiO2 nanocomposite become larger with no particular shape, but they are more spherical than that of CuAl2O4
Fig. 2 Crystallite size of different CuAl2O4 (wt. %)–Al2O3–SiO2 nanocomposite
(30 wt. %)–Al2O3–SiO2 nanocomposite. The particles are generally crystalline, and the amorphous state is not observed. Their particle sizes were measured from 20 to 35 nm with uniformly distribution.
By increasing the percentage of copper aluminate to 70 wt. %, the particle adhesion and agglomeration of the particles increased and consisted of larger agglomerates. Also, the particle size distribution from 30 to 40 nm was less uni- form than the pre-cast samples and their shape tended to be polygonal. It must be mentioned that the pure CuAl2O4 sample shows larger particle size from 35 to 50 nm with more particle agglomeration. In general, the shape of the particles is also polygonal and is larger than that of the obtained nanocomposite.
The high agglomeration of particles can be attributed to their high specific sur- face area that lead to an increase in their surface energy. The particles tend to stick together to reduce their surface energy [23]. On the other hand, the higher dispersion and separation of CuAl2O4 particles occur with increasing wt. % Al2O3–SiO2 cata- lyst support, leading to the reduction of the particle size of nanocomposite.
TEM image of 50 wt. % CuAl2O4–Al2O3–SiO2 was used for a more detailed examination (Fig. 4).
Fig. 3 FE-SEM images and EDS spectra of the CuAl2O4 (wt. %)–Al2O3–SiO2 nanocomposite and Al2O3–SiO2
The nanoparticles can be seen in approximate sizes of 20–25 nm, and the distribution of particles is uniform. Its agglomeration value was also relatively high. TEM images show that the agglomerates are composed of smaller parti- cles. The use of the sol–gel method as well as aluminum oxide-silicon oxide as a catalyst support for the production of CuAl2O4–Al2O3–SiO2 nanocomposite has many advantages as well as particle size reduction by using it supported with published data [20, 24]. Much attention has been paid to the research on the size and agglomeration of nanoparticles. In Table 1, the particle size obtained in this study is compared with the results of other researchers.
The finer nanoparticles were obtained by using sol–gel method, catalyst sup- port and higher calcination temperature. These obtained results can provide a more active surface, especially for catalytic applications. It must be mentioned
Fig. 4 TEM image of CuAl2O4 (50 wt%)–Al2O3–SiO2 nano- composite
Table 1 The comparison of CuAl2O4 particle size
Sample Method Average particle size
(nm) Calcination tempera-
ture (°C) Ref
Al2O3/SiO2-
50%CuAl2O4 Sol–gel 20 900 This study
CuAl2O4 Sol–gel 35 900 This study
CuAl2O4 Sol–gel 35 800 [7]
CuAl2O4 Precipitation 20 700 [25]
CuAl2O4 Sol–gel 20 700 [4]
that the CuAl2O4–Al2O3–SiO2 nanocomposite as an aluminate spinel has higher thermal stability supported with published data [1, 3].
FTIR Spectra
Figure 5 shows the FTIR spectra of CuAl2O4–Al2O3–SiO2 before and after calci- nation at 900 ºC. The dried sample at 100℃ before calcination shows the adsorp- tion bands at 3390 and 1665 cm−1 can be attributed to the stretching and bending vibrations of the O–H group of the adsorbed water on its surface, respectively [20, 22]. The adsorption band at the wavenumber of 2460 cm−1 is due to the presence of adsorbed CO2 molecules from the air. A strong adsorption band in the wave number 1378 cm−1 is related to the asymmetric NO3−stretching vibrations of nitrate ions in the sample [13].
It was observed that the strong adsorption band at 1079 cm−1 and two weak adsorption bands at 827 and 470 cm−1 are related to asymmetric and symmetric stretching and bending vibrations of Si–O–Si bonding, respectively [7]. Also, the stretching vibrations (937 cm−1) of the Al–O bond in the range of 1200–1000 cm−1 overlap with the Si–O adsorption bands (1089 cm−1) [15, 26]. The adsorption band at about 600 cm−1 is related to the Cu–O–H bond. It must be mentioned calcined sample at 900 ºC shows adsorption bands of water due to moisture adsorption on the surface sample before testing.
Investigate the process of dye adsorption
It is well known that the process of color adsorption is related to the type of adsor- bents, the specific surface of adsorbents, the size of the adsorbent particles, their surface charge and their morphology. Therefore, dye adsorption was performed using synthesized samples with different wt. % CuAl2O4 to understand its effect on the final powder performance.
Fig. 5 FTIR spectra of CuAl2O4 (50 wt%)–Al2O3–SiO2 nanocomposite a before and b after calcination
Solution pH
In order to investigate the effect of initial pH of the solution, three solutions of methylene blue (MB) as a the cationic dye prepared with a concentration of 10 ppm and their adsorption on three pH was measured on 0.01 g of CuAl2O4 (50 wt. %)–Al2O3–SiO2 nanocomposite at pH = 4, 7 and 10 after 120 min (Fig. 6a).
pH is one of the important factors that influence the color structure and sur- face charge on the adsorbent. The pH of the solution affects the chemistry of the aquatic environment and the adsorbent surface bonds. It has been reported that the adsorption reaction with cationic dyes is mainly via the interaction between hydrogen bonds and van der Waals forces [27]. As the pH increased, the adsorp- tion percentage on the sample increased indicating the presence of opposite charges between the surface of nanocomposite or adsorbent and MB. At low pH, high concentrations of H+ on the surface of adsorbent led to the formation of more positive charges on its surface; the adsorption capacity of adsorbents is greatly reduced at low pH. In other words, excess hydrogen ions compete with cationic dye molecules to adsorb onto active sites of adsorbent. As the pH of the solution increases, the number of positively charged sites decreases, meaning that the number of negative charge sites increases. As the surface area of the adsor- bent becomes more negatively charged, the interaction between the adsorbent and the cationic dye molecules increases. Therefore, the adsorption capacity of cati- onic dye (MB) on the adsorbent increases with increasing pH value [28].
Fig. 6 The effect of a. pH, b. the adsorbent type, c. the adsorbent dosage, d. the initial MB concentra- tion on the removal of MB (the optimum condition: pH = 10, t = 120 min, adsorbent dosage = 0.01 g, MB = 10 ppm)
Adsorbent type
The effect of CuAl2O4 content on dye adsorption from aqueous solution at 10 ppm and pH = 10 was investigated (Fig. 6b). The amount of adsorbent at this stage was 0.01 g for all samples. It was adsorbed that the adsorption capacity is increased sharply in the first 40 min and then proceeds at a slower rate until it reaches to the equilibrium. As these sites become more occupied, the performance of the adsorbent will decrease. However, the discordant behavior was observed in the Al2O3–SiO2 sample of 30 wt. % CuAl2O4 during the first 20 min. As you can see, the adsorption was very low during this time and even lower than that of pure copper aluminate and Al2O3–SiO2 samples. This behavior was probably due to the very strong agglomera- tion of the particles that partially disintegrated during the first 20 min due to rotation during the adsorption process of the agglomerates, and their adsorption has returned to the usual trend.
In general, the effect of contact time on the efficiency of the adsorption process showed with the increasing contact time the efficiency of the adsorption process improved and increased. The adsorption of a significant portion of the contaminants occurred in the early times and then reached a constant value. Increasing the con- tact time has no effect on the rate of adsorption. The fast adsorption can be attrib- uted to the adsorption on the outer surface, which is different from the adsorption inside the pores, since the access to specific adsorption sites on the outer surface is easier and faster for the contaminant. Many vacant surface sites are available for adsorption, but over time, the remaining vacant sites have difficulty in adsorbing contaminants which may be due to the barrier forces between the adsorbed mol- ecules on the solid adsorbent surface and the liquid mass. The adsorption capacity of nanocomposites increased with increasing copper aluminate content up to 50 wt.
%. The high adsorption of this sample can be attributed to the high surface area of the powder, the lower agglomeration and the appropriate distribution of CuAl2O4 on the surface of Al2O3–SiO2. However, the wt. % CuAl2O4 increased from 50 to 70 wt.
%, the adsorption decreased because of the accumulation and growth of crystals that reduce the specific surface area and inaccessibility of active sites on the surface.
Adsorbent dosage
The amount of adsorbent in adsorption processes is one of the most important characteristics of adsorption systems due to the high cost of adsorbent supply.
The amount of adsorbent used to remove various contaminants often depends on the adsorbent properties regarding particle size, specific surface area, pores and so on. By increasing the amount of adsorbent from 0.01 to 0.03 g, the adsorption rate increased from 96 wt. % to 98 wt. %, but after that, the adsorption decreased (Fig. 6c). In general, the adsorbent increases as the active sites on the surface of the powder particles increase the interactions between the adsorbent and the methylene blue molecules. However the adsorbent level exceeds 0.03 g the active and available surface area of the particles decreases, and the adsorption efficiency decreases due
to the agglomeration of the particles in the aqueous medium. The active and avail- able surface area of the particles decreases, and the adsorption efficiency decreases.
Initial dye concentration
To investigate the effect of initial dye concentration, the adsorption process was car- ried out at initial concentrations of methylene blue 5, 10, 20 and 30 mg/L using 0.01 g of 50 wt. % CuAl2O4–Al2O3–SiO2 nanocomposite (Fig. 6d). After separa- tion of the adsorbent and the amount of residual dye obtained, and the percentage of adsorption, it was found that at the concentration of 10 mg/L, the highest rela- tive percentage of adsorption occurred. At the concentration of 5 ppm, the high- est amount of adsorption is about 100 wt. % due to the higher active sites at the nanopowder surface compared to the number of dye molecules. But by increasing the concentration to 10 ppm, the adsorption was about 98 wt. % and by increasing the concentration of dye, the adsorption rate decreased. This decrease is due to the decrease in the ratio of active surface area of the adsorbent to the amount of dye molecules [13].
Finally, the obtained results were compared with other works to improve MB dye removal (Table 2). Their physical and chemical characteristics led to the difference removal performance of MB dye. Among the main factors that influence the adsorp- tion are surface area and initial solution pH.
Adsorption isotherms and kinetics
One of the most important factors for an adsorption system is the prediction of adsorption rate. The adsorption kinetics depends on the physical and chemical prop- erties of the adsorbent, which affects the adsorption mechanism. Figure 7a shows the adsorption kinetic curve based on the pseudo-first-order kinetic model for meth- ylene blue adsorption or 10 ppm concentration on 0.01 g of Al2O3–SiO2-50 wt. % CuAl2O4 composite. As can be seen, the correlation coefficient for the pseudo-first- order kinetic model was 0.984. In Fig. 7b, the adsorption kinetic curve is plotted based on the pseudo-quadratic model for methylene blue adsorption at a concentra- tion of 10 ppm.
According to the obtained equations, the correlation coefficient for the adsorp- tion kinetic curve based on pseudo-second-order model was 0.9605. The correlation
Table 2 Removal of methylene
blue by various adsorbents Adsorbent Adsorption
capacity (mg/g) pH Reference Al2O3/SiO2-50%CuAl2O4 10.0 10 This study
Natural Jordanian Tripoli 16.6 8 [29]
NaOH-treated fly ash 4.5 7 [30]
NaOH-treated fly ash 12.8 8 [25]
Gypsum 36.0 7.5 [31]
coefficient obtained from the pseudo-first-order model is higher than the pseudo- second-order model. It can then be said that the pseudo-first-order kinetic model provides a better fit for the methylene blue dye adsorption process on the CuAl2O4 (50 wt. %)–Al2O3–SiO2 nanocomposite.
In the next step, different adsorption models were investigated to determine the adsorption model using the determined adsorption capacity. Adsorption is a mass transfer process in which different compounds are competing for equilib- rium. The primary effective forces in the attraction between the adsorbents are the gravity force and the electrostatic repulsion which can be physical or chemi- cal. It is important to establish the proper relationship for the equilibrium curve and to optimize the design of a surface adsorption system to remove the color compound. The equilibrium adsorption isotherms are expressed by plotting the color concentration in the solid phase versus the concentration of this compound in the soluble phase [15–17]. From the linear diagram log (qe) versus log (Ce), 1/n can be determined, which denotes the type of isotherm; if 1/n = 0, it is irrevers- ible, if 0 < 1/n < 1, it is desirable, and if 1 < 1/n, it is undesirable. The isotherm curve based on the Freundlich equation for methylene blue dye adsorption is shown in Fig. 7c. As can be seen from the figure, the correlation coefficient of the Freundlich equation for the methylene blue dye adsorption is 0.952, which is not very close to one. Figure 7d shows the isotherm curve based on Langmuir equa- tion for methylene blue dye adsorption. As can be seen, the correlation coefficient
Fig. 7 Linear fit of experimental data obtained using a the pseudo-first-order model, b the pseudo- second-order model, c the Freundlich isotherm, d the Langmuir isotherm (mads = 0.01 g, C0 = 10 ppm, V = 10 mL, pH = 10, T = rt)
obtained for this equation is very close to one which proves that the adsorption mechanism follows the Langmuir isotherm model. The basic characteristic of the dimensionless Langmuir equation is called the equilibrium parameter, which is defined as follows:
RL represents the type of isotherm. For optimum adsorption 1 > RL > 0, for unde- sirable adsorption RL > 1, for linear adsorption RL = 1 and for irreversible adsorp- tion is R = 0. As can be seen, the correlation coefficient (R2 = 0.9959) is very close to one which proves that the adsorption mechanism follows the Langmuir isotherm model. The obtained result confirmed the adsorption of MB onto CuAl2O4 (50 wt.
%)–Al2O3–SiO2 nanocomposite via monolayer adsorption.
Antibacterial activity
Antimicrobial assays of CuAl2O4–Al2O3–SiO2 disk are carried out by agar well diffusion method against two types bacterial strains (gram-positive and gram- negative) through the measuring the clearance/inhibition zone (Fig. 8). The antimicrobial properties of the nanocomposite can be attributed to the directly interaction of between nanocomposite and the microbial cells by the different mechanisms such as interruption cell membrane morphology, disruption/penetra- tion of the cell envelope or oxidation cell components. Although this reactive oxygen species (ROS) or dissolved metal ions led to further damage on the bac- teria, metals release may cause severe environmental contamination and irrevers- ible health. By immobilization of copper in the nanospinel structure, the envi- ronmental challenge decreased, while a small amount of antimicrobial Cu2+ ions can still be potentially released. It can cause the destruction of the bacterial outer membranes by ROS [1–3].
(6) RL= 1
1+bC0
Fig. 8 The plates of antibacterial activity of CuAl2O4 (50 wt%)–Al2O3–SiO2
Conclusion
A feasible and effective sol–gel method was used to CuAl2O4 (wt. %)–Al2O3–SiO2 nanocomposite. The nano-CuAl2O4 spinel particles were exposed on the sur- face of the Al2O3–SiO2 matrix. These nanocomposites possessed negative surface charge suitable for the adsorption of cationic MB leading to 58wt% decoloration.
The CuAl2O4 (50 wt. %)–Al2O3–SiO2 nanocomposite was chosen as an effective adsorbent with optimum conditions adsorbent dosage, dye concentration, time and pH to be 0.01 g, 10 ppm, 120 min and 10, respectively. The isotherm adsorption data well matched by Langmuir equation with R2 > 0.9959. In addition, its anti- bacterial activity showed that E. coli bacteria’s activity was more susceptible to be inhibited by the disk compared to S. aureus. The obtained results demonstrate that CuAl2O4–Al2O3–SiO2 can be a good candidate to be used as a suitable adsorbent for wastewater treatment.
Acknowledgements The authors would like to express their personal thanks to Islamic Azad University, Najafabad, Iran.
Compliance with ethical standards
Conflicts of interest The authors declare that there are no competing financial interests.
References
1. M. Han, Z. Wang, Y. Xu, R. Wu, S. Jiao, Y. Chen, S. Feng, Mater. Chem. Phys. 215, 251 (2018) 2. M. Ansari, A. Bigham, H. Abbastabar Ahangar, Mater. Sci. Eng. C 105, 110084 (2019).
3. Z. Wang, K. Liang, S.W. Chan, Y. Tang, J. Hazard. Mater. 371, 550 (2019)
4. Y. Xu, Z. Lin, Y. Zhenga, J.P. Dacquin, S. Royer, H. Zhang, Sci. Total Environ. 651, 2585 (2019) 5. F.Z. Akika, M. Benamira, H. Lahmar, M. Trari, I. Avramova, S. Suzer, Surf. Interfaces. 18, 100406
(2020)
6. F. Z Akika, M. Benamira, H. Lahmar, A. Tibera,, I. Avramova, Ş. Suzer, M. Trari. J. Photochem.
Photobiol., A 364, 542 (2018).
7. S.W. Lu, T. Copeland, B.I. Lee, W. Tong, B.K. Wagner, W. Park, F. Zhang, J. Phys. Chem. Solids 62, 777 (2001)
8. B.K. Kwak, D.S. Park, Y.S. Yun, J. Yi, Catal. Commun. 24, 90 (2012) 9. J. Chandradass, K.H. Kim, J. Ceram. Process. Res. 11, 150 (2010)
10. W. Lv, Z. Luo, H. Yang, B. Liu, W. Weng, J. Liu, Ultrason. Sonochem. 17, 344 (2010) 11. M. Naderi, A. Shamirian, M. Edrisi, J. Sol-Gel Sci. Technol. 58, 557 (2011) 12. C. Ragupathi, J.J. Vijaya, R.T. Kumar, L.J. Kennedy, J. Mol. Struct. 1079, 182 (2015) 13. H.V. Tran, L.T. Hoang, C.D. Huynh, Chem. Phys. 535, 110793 (2020)
14. E. Alver, A.Ü. Metin, F. Brouers, Int. J. Biol. Macromol. 154, 104 (2020) 15. F.L. Motta, S.R. Stoyanov, S J.B. P.oares, Chemosphere. 194, 837 (2018).
16. X. Qi, Q. Zeng, T. Su, Y. Huang, J. Shen, J. Hazard. Mater. In Press. (2020).
17. G.B. Kunde, B. Sehgal, A.K. Ganguli, J. Hazard. Mater. 374, 140 (2019)
18. A. Nezam, A. Saffar-Teluri, S.A. Hassanzadeh-Tabriz, Res. Chem. Intermed. 42, 4999 (2016) 19. S.A. Hassanzadeh-Tabrizi, R. Pournajaf, A. Moradi-Faradonbeh, S. Sadeghinejad, Ceram. Int. 42,
14121 (2016)
20. M. Salavati-Niasari, F. Davar, M. Farhadi, J. Sol-Gel Sci. Technol. 51, 48 (2009)
21. J. Yanyan, L. Jinggang, S. Xiaotao, N. Guiling, W. Chengyu, G. Xiumei, J. Sol-Gel Sci. Technol. 42, 41 (2007)
22. M.M. Motlagh, S.A. Hassanzadeh-Tabrizi, A. Saffar-Teluri, Ceram. Int. 40, 16177 (2014) 23. R. Pournajaf, S.A. Hassanzadeh-Tabrizi, M. Ghashang, Ceram. Int. 40, 4933 (2014)
24. I. Mindru, D. Gingasu, L. Patron, G. Marinescu, J.M. Calderon-Moreno, S. Preda et al., Ceram. Int.
42, 154 (2016)
25. S. Wang, Y. Boyjoo, A. Choueib, Chemosphere 60, 1401 (2005)
26. M.I. Mobarakeh, A. Saffar-Teluri, S.A. Hassanzadeh Tabrizi, Res. Chem. Intermed. 41, 6625 (2015).
27. S.K. Das, J. Bhowal, A.R. Das, A.K. Guha, Langmuir 22, 7265 (2006) 28. M. Auta, B.H. Hameed, Chem. Eng. 237, 352 (2014)
29. A.S. Alzaydien, Am. J. Environ. Sci. 5, 197 (2009)
30. R. Wanchanthuek, A. Thapol, J. Environ. Sci. Technol. 4, 552 (2011)
31. M.A. Rauf, I. Shehadeh, A. Ahmed, A. Al-Zamly, Sci. Eng. Technol. 31, 604 (2009)
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