Abstract

Mass production of nanomaterials to remove pollutants from water still faces many challenges, mainly due to the complexity of the synthesis methods involved and the use of dangerous reagents. The green method of preparation of nanomaterials from plants can effectively solve these problems. Fe,Cu oxide nanocomposites (Fe-Cu-NCs) were synthesized by a green and single-step method using loquat leaf extracts, and were used as an adsorbent for removal of Norfloxacin (NOR) and Ciprofloxacin (CIP) from aqueous solution. The synthesized adsorbent showed excellent adsorption properties for NOR and CIP. The experimental equilibrium data fitted the Redlich-Peterson and Koble-Corrigan models well and the maximum adsorption capacities of Fe-Cu-NCs calculated by the Langmuir model for NOR and CIP were 1.182 mmol/g and 1.103 mmol/g, respectively, at 293 K. Additionally, the morphologies and properties of Fe-Cu-NCs were characterized by transmission electron microscopy (TEM), scanning electron microscopy X-ray energy-dispersive spectroscopy (SEM-EDS), X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD) and Fourier transform infrared spectroscopy (FTIR) analysis and the adsorption mechanism of NOR and CIP onto Fe-Cu-NCs was discussed. Thermodynamic parameters revealed that the adsorption process was spontaneous and endothermic. This study indicated that Fe-Cu-NCs are a potential adsorbent and provide a simple and convenient strategy for the purification of antibiotics-laden wastewater.

INTRODUCTION

Antibiotics are widely used in medicine, animal husbandry and aquaculture to prevent and treat bacterial infectious diseases (Zheng et al. 2013). But in recent years, antibiotics have been abused all over the world and released to surface water through different routes, such as hospital and industrial antibiotic waste, human and animal metabolic waste, agricultural activities (Anthony et al. 2018). Water containing trace amounts of antibiotics can indirectly affect human health by causing a decline of the body's immune system (Kong et al. 2016). Quinolones, the most widely used antibiotics class, have been classified among the most important synthetic antibiotics used in human and veterinary medicine (Homem & Santos 2011). Norfloxacin (NOR) and Ciprofloxacin (CIP) are synthetic, broad-spectrum antibacterial agents of the fluoroquinolones family. Factors including the sewage discharge of drug manufacturers, effluents from hospitals and incomplete metabolism in animals are major causes of the omnipresence of NOR and CIP residues in aquatic ecosystems (Wan et al. 2018). Therefore, it is necessary to explore effective techniques for antibiotic removal from wastewaters.

Adsorption is considered to be one of the effective methods for the treatment of contaminants, due to its features of low cost, easy operation, strong practicability and high efficiency (Wan et al. 2018). Over the past decade, numerous attempts have been made to develop low-cost and effective adsorbents, including nanomaterials or nanocomposites for the removal of contaminants from water. Compared with the traditional materials, nanostructured adsorbents exhibit much higher efficiency and faster removal rate in water treatment (Zhang et al. 2016).

So far, nanomaterials, including carbon nanomaterials (Jha et al. 2019), magnetic nanomaterials (Gutiérrez et al. 2018), polydopamine microspheres (Wan et al. 2018), metal oxide nanomaterials (Khandare & Mukherjee 2019) have been studied. Among these nanomaterials, metal oxide nanomaterials are the most commonly used and can be readily synthesized by various chemical and physical methods. However, the physical and chemical methods are generally expensive and have a high energy consumption. Moreover, the reducing agents used in the preparation process are mostly toxic and corrosive chemicals, and the nanomaterials obtained have a definite impact on the environment (Wang et al. 2014). Hence, it is imperative to develop a green and efficient preparation method for nanoadsorption.

Green nanotechnology involves the development of novel and environmentally friendly methods for the preparation of nanomaterials (Singh et al. 2017). Thus, the green synthesis of metal nanoparticles, including microbial and plant synthesis, is considered to be a greener, safer and more cost-effective method to replace chemical and physical production methods. Particularly, plant extracts are promising for the synthesis of nanoparticles since they are cheap, simple to use and scalable.

Considerable efforts have been made to develop plant synthesis methods for the rapid and large-scale fabrication of nanomaterials without the use of dangerous reagents. It has been found that plant extracts that contain the most abundant chemical constituents, such as reducing sugars, phenols, flavonoids and proteins, could serve as the reducing and capping agents for the synthesis of nanoparticles (Makarov et al. 2014). For instance, CuO nanoparticles for the effective removal of As(III) were synthesized from Tamarindus indica pulp extracts (Singh et al. 2017); iron nanoparticles for the removal of hexavalent chromium were synthesized using Eichhornia crassipes extracts (He et al. 2018); Fe,Cu-based nanoparticles for the removal of malachite green were synthesized using Parthenocissus quinquefolia leaf extracts (Zhang et al. 2018). These researchers demonstrated that green synthesis is feasible, and provides a basis for the synthesis of metal oxide nanoparticles from plant extracts for contaminant removal (Luo et al. 2015).

Loquat (Eriobotrya japonica) is a large evergreen shrub that contains a high amount of polyphenols or related antioxidants; these could serve as both reducing and capping agents (Awwad et al. 2013), so loquat leaf is a good material for the preparation of metal oxide nanoparticles. CuO and Fe2O3 are very stable oxides in normal environmental conditions (Singh et al. 2017), and Fe2O3 has a high reaction surface area and high removal rate, favorable properties and non-toxicity (Nalbandian et al. 2016). Thus in the current study, Fe,Cu oxide nanocomposites (Fe-Cu-NCs) were chosen as an adsorbent for the adsorption of NOR and CIP from aqueous solution. To our knowledge, the preparation of Fe,Cu oxide nanocomposites using loquat leaf extracts has not previously been reported in the literature.

In this study, Fe-Cu-NCs were synthesized from loquat leaf extracts and used as the adsorbent for the removal of NOR and CIP. The adsorption kinetics, isotherms and thermodynamic properties of Fe-Cu-NCs for NOR and CIP removal were explored. Furthermore, the adsorption mechanism is discussed according to the results of adsorption experiment.

MATERIALS AND METHODS

Materials and reagents

Ferric chloride hexahydrate (FeCl3·6H2O) and cupric chloride dihydrate (CuCl2·2H2O) were purchased from Shanghai Macklin BioChem Technology Co. Ltd (Shanghai, China); Norfloxacin (C16H18FN3O3, 319.33 g/mol, ≥98%) and Ciprofloxacin (C16H18FN3O3, 367.82 g/mol, ≥98%) were obtained from Haizhengshenghua Biotechnology Limited (Henan Province, China). Oxalic acid (ethanedioic acid) was purchased from Tianjin Kermel Chemical Reagent Company (Tianjin, China). All chemicals used in this study were analytical grade.

PREPARATION METHODS

Preparation of loquat leaf extracts

Fresh loquat leaves were washed with distilled water and dried to constant weight at 323 K. Then 70 g dried loquat leaves were added to 1 L of deionized water and heated for 150 min at 333 K under sealed conditions. The extracts were filtered and stored in the refrigerator for further use.

Synthesis of adsorbents

Oxalic acid (0.02 mol) was added to 150 mL of the extracts of loquat leaf under vigorous stirring at ambient temperature. After 30 min, 70 mL of FeCl3 and CuCl2 premixed solution (0.095 mol/L) was added dropwise to the extracts over a 3 hour period under continued vigorous stirring. The color of the solution changed from clear to atrovirens (dark brown) and the reaction mixture was stirred for another 1 hour. The precipitated mass was then separated by centrifugation (10,000 rpm for 4 min) and washed with deionized water three times. Finally, the product was freeze-dried and stored.

Synthesis mechanism of Fe-Cu-NCs

Loquat leaf extracts contain a potent array of polyphenolic compounds that may act as reducing agent: first the hydroxyl groups of the polyphenolic compounds formed the complex with the Cu2+ and Fe3+ and then reduced them to Cu and Fe. These metallic copper and iron atoms reacted with the available oxygen in the atmosphere to form the most stable oxides i.e. CuO and Fe2O3 (Singh et al. 2017). The preparation mechanism diagram is shown in Figure 1.

Figure 1

Schematic illustration of plausible synthesis mechanism.

Figure 1

Schematic illustration of plausible synthesis mechanism.

Characterization analysis

Scanning electron microscope (SEM) (Zeiss Merlin Compact) equipped with an X-ray energy-dispersive spectrometer (EDS) (Bruker Nano GmbH Berlin, Germany) and a transmission electron microscope (TEM) (FEI Tecnai G2 F20) were employed to analyse the surface structure and morphology of samples. The structural composition of Fe-Cu-NCs were measured by X-ray diffraction (XRD) (Bruker D8 Advance). X-ray photoelectron spectroscopy (XPS) (Thermo Escalab 250 XI) was employed to determine the surface chemical elemental composition. Fourier transform infrared spectroscopy (FTIR) (PE-1710 spectrophotometer, USA) was employed to identify the surface functional groups of Fe-Cu-NCs. The specific surface area and pore size distributions of Fe-Cu-NCs was determined by nitrogen adsorption–desorption isotherms at 77 K using a surface area analyzer (NOVA1200e, USA). The point of zero charge (pHPZC) of Fe-Cu-NCs was determined using the salt addition method; the value obtained pHPZC was 3.74.

Adsorption experiments

Batch adsorption experiments were carried out in a 50 mL Erlenmeyer flask, containing 5 mg of Fe-Cu-NCs and 20 mL diluted NOR or CIP solutions, that was subjected to shaking in a mechanical constant temperature vibrator. After 180 min adsorption equilibrium, the mixture was centrifuged at 10,000 rpm for 3 min. The effect of initial pH on the removal of NOR or CIP was analyzed in the pH range of 2–12. The adsorption kinetic experiments were conducted with initial concentrations of NOR and CIP of 0.313, 0.470 and 0.626 mol/L at 293 K, respectively. Samples were taken periodically, until an adsorption equilibrium was reached. Equilibrium isotherm experiments were performed with different initial concentrations of NOR or CIP solution (ranging from 0.063 to 0.783 mmol/L) for 180 min at 293, 303 and 313 K. The effect of ionic strength was studied with different salt concentrations (varying from 0 to 0.1 mol/L) of NaCl and CaCl2. All the experiments were carried out under identical conditions and repeated three times. The remaining concentration of NOR and CIP were measured by ultraviolet-visible spectrophotometer (TU-1810, Puxi General Instrument Co. Ltd, Beijing, China) both using wavelengths of 276 nm.

Data analysis

The adsorption capacity qt (mmol/g) and the removal efficiency η of NOR or CIP were determined by the following equations:  
formula
(1)
 
formula
(2)
where qt (mmol/g) is the adsorption capacity. C0 (mmol/L) and Ct (mmol/L) are the NOR or CIP concentrations in the solution at the start and any time t, respectively. V (L) is the volume of the NOR or CIP solution, and m (g) is the mass of the adsorbent. η is the removal efficiency.
The degree of fit of the kinetic and isotherm models was evaluated by relative standard deviation ARS, which is defined as follows:  
formula
(3)
where n is the number of data points, and qexp and qcal (mmol/g) are the experimental and calculated adsorption capacities, respectively.

RESULTS AND DISCUSSION

Characterization of adsorbents

Morphology analysis

The surface morphology of Fe-Cu-NCs samples was characterized by SEM (Figure 2), which revealed the successful synthesis of Fe-Cu-NCs. It is clearly evident that the nanocomposites appear spheroidal, with a diameter ranging from 100 to 200 nm, and they tend to form a homogeneous size distribution. TEM images (Figure 2(c)) showed that the Fe-Cu-NCs were polydispersed particles and the surface of Fe-Cu-NCs was capped with organic matter. The organic matter capping on the surface of nanocomposites played a crucial role in preventing their aggregation, improving their dispersion and stability (Weng et al. 2017; Zhang et al. 2018).

Figure 2

(a), (b) SEM images of Fe-Cu-NCs; (c) TEM images of Fe-Cu-NCs; (d) EDS analysis of Fe-Cu-NCs.

Figure 2

(a), (b) SEM images of Fe-Cu-NCs; (c) TEM images of Fe-Cu-NCs; (d) EDS analysis of Fe-Cu-NCs.

To further understand the element composition of Fe-Cu-NCs, the localized elemental information of Fe-Cu-NCs was determined by EDS, as shown in Figure 2(d). There are intense peaks of C, O, Fe and Cu, confirming the presence of Fe and Cu. The signals of elemental C and O originated from the polyphenol groups and other C-, O-containing molecules in loquat leaf extracts (Weng et al. 2017). The weight composition of C and O is more than that of Fe and Cu, which may be attributed to the fact that the surface of Fe-Cu-NCs was coated with biomolecules of loquat leaf extracts (Weng et al. 2017).

XPS and XRD analysis

Figure 3 shows the XPS patterns of Fe-Cu-NCs. In Figure 3(a), due to the low content of copper, the characteristic peak of Cu 2p was not shown in the spectra. Figure 3(b) shows the spectra of Fe and Cu of Fe-Cu-NCs: the core levels of Fe 2p3/2 and Fe 2p1/2 were 711.3 eV and 725.85 eV, respectively, corresponding to Fe3+, and consistent with the peaks reported for iron oxide (Fang et al. 2011; Luo et al. 2015). As shown in Figure 3(c), there were three C peaks on the C 1s curves, corresponding to C-C, C-O and C = O, respectively, implying that biomolecules were attached to the surface of Fe-Cu-NCs (Awwad et al. 2013). Additionally, the O 1s XPS spectrum was further analysed in Figure 3(d), where components were attributed respectively to OH (531.25 eV) and C-O (532.75 eV) (Grosvenor et al. 2004). The presence of O 1s and C 1s implied that some biomolecules and oxalates formed a strong coating on the surface of Fe-Cu-NCs by chemical bonding (Khandare & Mukherjee 2019).

Figure 3

XPS spectra of the Fe-Cu-NCs: (a) widescan; (b) Fe 2p and Cu 2p spectrum; (c) C 1s spectrum; (d) O 1s spectra.

Figure 3

XPS spectra of the Fe-Cu-NCs: (a) widescan; (b) Fe 2p and Cu 2p spectrum; (c) C 1s spectrum; (d) O 1s spectra.

XRD data were collected in the 2θ range of 5–90°, and the pattern is shown in Figure 4. It can be seen that the whole pattern is deficient in distinctive diffraction peaks, suggesting that the synthesized Fe-Cu-NCs are mainly amorphous in nature, as previously reported for the eucalyptus extract synthesized nanoparticles (Wang et al. 2014). A broad shoulder peak at around 2θ = 25° can be ascribed to organic molecules adsorbed from the loquat leaf extracts as a capping or stabilizing agent (Wang et al. 2014).

Figure 4

XRD analysis of the Fe-Cu-NCs.

Figure 4

XRD analysis of the Fe-Cu-NCs.

FTIR analysis

The FTIR spectra of Fe-Cu-NCs is shown in Figure 5. A obvious peak at 3,332 cm−1 is attributed to O-H stretching vibration (Mohan Kumar et al. 2013). One prominent peak at 1,627 cm−1 indicates the O-H and C = C stretching vibration of an aromatic ring, which is thought to be related to polyphenols or sugars/glycosides originating from the loquat leaf extracts (Awwad et al. 2013). The peaks at 1,275 cm−1 and 820 cm−1 are ascribed to C = O of the carboxylic acid and C-C stretching modes, respectively (Zhang et al. 2018), then the band at 1,075 cm−1 is mainly produced by O-H bending vibration and C-O-C stretching vibration. Finally an absorption band around 613 cm−1 corresponds to Fe-O stretches of iron oxides (Yadav et al. 2015).

Figure 5

FTIR spectra of Fe-Cu-NCs and Fe-Cu-NCs after adsorption of NOR and CIP.

Figure 5

FTIR spectra of Fe-Cu-NCs and Fe-Cu-NCs after adsorption of NOR and CIP.

Figure 5 also shows FTIR spectra of Fe-Cu-NCs adsorption of NOR or CIP. In comparison with FTIR spectra of Fe-Cu-NCs, the band at 1,627 cm−1 has shifted to a lower wavelength, revealing an interaction between −OH groups and the CIP or NOR molecules, thus it can be reasonably inferred that the CIP or NOR adsorption process occurs via electrostatic interactions (Zhang et al. 2018). In addition, several new bands appeared, corresponding to NOR or CIP. For the Fe-Cu-NCs adsorbed with NOR, the new peak at 1,185 cm−1 belonging to the C-F bonds proved the presence of NOR on the adsorbents. FTIR analysis not only strongly confirmed that the molecular structure of Fe-Cu-NCs contains C = C, C-H, Fe-O and oxygen containing functional groups, but also confirmed the adsorption of NOR or CIP onto Fe-Cu-NCs.

BET analysis

Nitrogen adsorption-desorption isotherm with BET analysis was used to determine the specific surface area of Fe-Cu-NCs. As can be seen in Figure 6, the curve was characteristic of type-IV isotherm accompanying a H4 type hysteresis loop (Zhang et al. 2018), which was ascribed to capillary condensation, indicating the existence of a mesoporous matrix in the samples (Sai Saraswathi et al. 2017). The BET surface area of the Fe-Cu-NCs was 13.38 m2/g and the pore volume was 0.055 cm3/g. The as-prepared mesoporous structure had a narrow pore size distribution range and the average pore diameter was 1.54 nm. In addition, the desorption curve of the isotherm has a prominent point, indicating that the pore size of the material was heterogeneous and disordered.

Figure 6

Nitrogen adsorption and desorption isotherms and pore volume distributions of Fe-Cu-NCs.

Figure 6

Nitrogen adsorption and desorption isotherms and pore volume distributions of Fe-Cu-NCs.

ADSORPTION EXPERIMENTS

The effect of pH value and adsorption mechanism

Solution pH is a critical factor during the adsorption process, because the change of pH of the aqueous solution influences the speciation of NOR or CIP and the surface charge of Fe-Cu-NCs (Yuan et al. 2019). NOR and CIP are amphoteric molecules and there are two proton-binding sites (carboxyl and piperazinyl groups) that can be present as cations, zwitterions and anions at different pH values (Meng et al. 2018). As shown in Figure 7, the adsorption capacity of NOR onto Fe-Cu-NCs was increased from 0.21 mmol/g to 1.015 mmol/g when the pH values were raised from 2 to 7. Conversely, as the pH increased from 7 to 11, the adsorption capacity of NOR onto Fe-Cu-NCs was decreased from 1.015 mmol/g to 0.692 mmol/g and the adsorption efficiency was decreased by 31.8%. It can be seen that the optimal pH value for the adsorption of NOR onto Fe-Cu-NCs was 7, and the adsorption capacity did not decrease significantly when the pH values were raised from 7 to 11. This result indicates that the adsorption of NOR onto Fe-Cu-NCs is suitable for neutral or weakly alkaline conditions.

Similarly, the adsorption capacity of CIP onto Fe-Cu-NCs was increased from 0.201 mmol/g to 0.817 mmol/g when the pH values were raised from 2 to 8. By contrast, when the pH values were increased from 8 to 11, the adsorption capacity of CIP onto Fe-Cu-NCs was decreased from 0.817 mmol/g to 0.709 mmol/g, and then the adsorption efficiency was only reduced by 13.2%. Thus the optimal pH value for the adsorption of CIP onto Fe-Cu-NCs was 8.

Figure 7

(a) The effect of pH on the NOR adsorption and the distribution coefficient of NOR; (b) the effect of pH on the CIP adsorption and the distribution coefficient of CIP.

Figure 7

(a) The effect of pH on the NOR adsorption and the distribution coefficient of NOR; (b) the effect of pH on the CIP adsorption and the distribution coefficient of CIP.

As shown in Figure 7, taking NOR as an example, when pH < pKa1, the cation (NOR+) is the dominant species in the aqueous solution due to the protonation of the piperazinyl nitrogen. When pKa1 < pH < pKa2, NOR existed mainly as a zwitterion (NOR±) due to the deprotonation of the carboxylic group and the protonation of the peripheral piperazine. When pH > pKa2, the anion (NOR-) state is due to the increasing deprotonation of carboxylic groups in solution.

The pHPZC is an important parameter of adsorbents, as it characterizes the acidic and basic properties of adsorbents beyond a definite pH value. The pHPZC value was determined to be 3.74. When pH < pHPZC, the NOR cation was the dominant species in solution and the surface of the Fe-Cu-NCs also contained positive charges. Therefore the electrostatic repulsion between the adsorbent and adsorbate reduced the adsorption capacity. At pKa1 < pH < pKa2, the removal efficiency of NOR was increased by its zwitterionic form, and NOR in zwitterionic form was more hydrophobic than its cation or anion form (Yang et al. 2012). In addition, NOR could form hydrogen bonds with the hydroxyl groups on the surface of Fe-Cu-NCs via its piperazinyl group, carboxyl group and fluorine group (Liu et al. 2019). Moreover, the hydroxyl groups of Fe-Cu-NCs could act as n-electron-donors and the delocalized π bond of the aromatic ring of NOR could serve as an π-electron acceptor due to the strong electron-withdrawing capability of the fluorine group on benzene ring (Yang et al. 2012). At pH > pKa2, the NOR existed as anionic form, so it and the negative charge on the Fe-Cu-NCs surface repelled each other, resulting in a decrease in adsorption capacity.

In addition to the electrostatic effect, metal surface complexation is responsible for another main mechanism of NOR adsorption in aqueous solutions. NOR is likely to form an energetically favorable mononuclear bidentate complex (i.e., a six-membered ring) with the Fe atom and the Cu atom (Liu et al. 2011). The adsorption mechanism of CIP onto Fe-Cu-NCs is similar to that of NOR, and both their adsorption mechanisms are shown in Figure 8.

Figure 8

Schematic illustration of the adsorption mechanism of (a) NOR and (b) CIP onto Fe-Cu-NCs.

Figure 8

Schematic illustration of the adsorption mechanism of (a) NOR and (b) CIP onto Fe-Cu-NCs.

Adsorption kinetics study

The experimental kinetic data for NOR or CIP adsorption onto Fe-Cu-NCs are shown in Figure 9. It can be seen that the rate of NOR adsorption onto the Fe-Cu-NCs was rapid during the first 10 min, and the adsorption capacity of NOR reached 57.9% of the equilibrated adsorption when the initial concentration was 0.470 mmol/L at 293 K. Under the same conditions, the CIP uptake reached 64.8% of the equilibrated adsorption amounts during the first 10 min. The experimental results support the fact that the initial stage of adsorption is a rapid process. However, due to the decrease in the number of the adsorption sites, the increasing trend slowed down until a state of equilibrium was reached after 180 min for both NOR and CIP (Al-Musawi et al. 2017). It can be seen that NOR or CIP adsorption amounts at equilibrium (qe) were increased from 0.906 to 1.153 mmol/g and from 0.592 to 0.871 mmol/g with an increase in the initial NOR or CIP concentrations from 0.313 to 0.626 mmol/L, respectively, suggesting that the greater concentration gradient could overcome mass transfer resistances during the adsorption process (Sepehr et al. 2014). Compared with the kinetic experimental data of NOR and CIP at the same concentration, the adsorption capacity of NOR is higher than that of CIP, which may be attributed to the lower molecular weight of NOR relative to CIP.

Figure 9

(a) Adsorption kinetic curves for the adsorption of NOR onto Fe-Cu-NCs; (b) adsorption kinetic curves for the adsorption of CIP onto Fe-Cu-NCs; (c) fitting curves of intra-particle diffusion for NOR adsorption; (d) fitting curves of intra-particle diffusion for CIP adsorption.

Figure 9

(a) Adsorption kinetic curves for the adsorption of NOR onto Fe-Cu-NCs; (b) adsorption kinetic curves for the adsorption of CIP onto Fe-Cu-NCs; (c) fitting curves of intra-particle diffusion for NOR adsorption; (d) fitting curves of intra-particle diffusion for CIP adsorption.

In order to investigate the mechanism of the adsorption process of NOR and CIP onto the Fe-Cu-NCs, the experimental kinetic data were fitted according to the pseudo-first-order model, pseudo-second-order model, double-constant rate equation, Elovich model, and the intra-particle diffusion model. These model are described by the following equations:  
formula
(4)
 
formula
(5)
 
formula
(6)
 
formula
(7)
 
formula
(8)
where qt and qe (mmol/g) are the adsorption capacities at time t (min) and at equilibrium, respectively. The k1 (min−1) and k2 (g/(mmol/min)) are the rate constants of pseudo-first-order model and pseudo-second-order model, respectively. A (mmol/(g/min)) is the initial adsorption rate of the Elovich model and B (g/min) is the extent of surface coverage. The α and ks are the correlation constants of the double-constant rate equation. kt (mg/(g min1/2)) is the intra-particle diffusion rate constant and C is related to the boundary layer thickness.

The corresponding parameters obtained from fitted models are shown in Table 1. A higher value of R2 and a smaller value of ARS indicated the higher accuracy of kinetic models: it can be seen that the adsorption process of Fe-Cu-NCs for NOR and CIP were fitted best to the double-constant rate equation and Elovich model. The Elovich model describes a series of adsorption processes on heterogeneous adsorbing surfaces, such as bulk or interfacial diffusion and surface activation and deactivation (Sun et al. 2019), so it indicated that the adsorption process of NOR or CIP onto Fe-Cu-NCs was heterogeneous. The double-constant rate equation is derived from the Freundlich equation. The kinetic rate constant ks reflects the adsorption rate, and the higher the ks value is, the faster the adsorption reaction. The intercept α reflects the adsorption capacity, and the larger the intercept is, the stronger the adsorption capacity (Sun et al. 2019).

Table 1

Kinetic parameters for the adsorption of NOR and CIP onto Fe-Cu-NCs

T/KNORCIP
C0/(mmol/L) 0.313 0.470 0.626 0.313 0.470 0.626 
Pseudo-first order 
 k1 × 10/(min−11.552 1.728 2.037 4.794 3.944 4.170 
 qe(exp)/(mmol/g) 0.906 1.038 1.153 0.592 0.787 0.871 
 qe(cal)/(mmol/g) 0.749 0.882 0.981 0.500 0.647 0.718 
 R2 0.811 0.848 0.850 0.849 0.825 0.840 
 ARS 0.226 0.199 0.186 0.146 0.162 0.152 
Pseudo-second order 
 k2/(g/(mmol·min)) 0.273 0.263 0.278 1.223 0.765 0.748 
 qe(cal)/(mmol/g) 0.806 0.953 1.056 0.532 0.692 0.766 
 R2 0.911 0.936 0.938 0.924 0.912 0.920 
 ARS 0.158 0.132 0.122 0.105 0.117 0.108 
Double-constant rate equation 
 a 0.321 0.406 0.481 0.316 0.382 0.436 
 Ks 0.196 0.183 0.170 0.119 0.134 0.128 
 R2 0.999 0.998 0.998 0.997 0.996 0.997 
 ARS 0.015 0.021 0.02 0.022 0.025 0.022 
Elovich equation 
 A 0.948 1.503 2.413 13.857 7.789 11.905 
 B 8.477 7.480 7.087 18.629 13.059 12.242 
 R2 0.992 0.996 0.997 0.992 0.990 0.991 
 ARS 0.054 0.034 0.028 0.035 0.041 0.036 
Intra-particle diffusion 
 kt1/(mmol/(g·min0.5)) 0.063 0.082 0.087 0.026 0.039 0.044 
 C1/(mmol/g) 0.292 0.344 0.418 0.323 0.387 0.437 
 R 0.998 0.998 0.997 0.996 0.999 0.996 
 kt2/(mmol/(g·min0.5)) 0.031 0.032 0.033 0.015 0.023 0.025 
 C2/(mmol/g) 0.472 0.616 0.719 0.392 0.473 0.535 
 R 0.978 0.999 0.997 0.971 0.996 0.992 
T/KNORCIP
C0/(mmol/L) 0.313 0.470 0.626 0.313 0.470 0.626 
Pseudo-first order 
 k1 × 10/(min−11.552 1.728 2.037 4.794 3.944 4.170 
 qe(exp)/(mmol/g) 0.906 1.038 1.153 0.592 0.787 0.871 
 qe(cal)/(mmol/g) 0.749 0.882 0.981 0.500 0.647 0.718 
 R2 0.811 0.848 0.850 0.849 0.825 0.840 
 ARS 0.226 0.199 0.186 0.146 0.162 0.152 
Pseudo-second order 
 k2/(g/(mmol·min)) 0.273 0.263 0.278 1.223 0.765 0.748 
 qe(cal)/(mmol/g) 0.806 0.953 1.056 0.532 0.692 0.766 
 R2 0.911 0.936 0.938 0.924 0.912 0.920 
 ARS 0.158 0.132 0.122 0.105 0.117 0.108 
Double-constant rate equation 
 a 0.321 0.406 0.481 0.316 0.382 0.436 
 Ks 0.196 0.183 0.170 0.119 0.134 0.128 
 R2 0.999 0.998 0.998 0.997 0.996 0.997 
 ARS 0.015 0.021 0.02 0.022 0.025 0.022 
Elovich equation 
 A 0.948 1.503 2.413 13.857 7.789 11.905 
 B 8.477 7.480 7.087 18.629 13.059 12.242 
 R2 0.992 0.996 0.997 0.992 0.990 0.991 
 ARS 0.054 0.034 0.028 0.035 0.041 0.036 
Intra-particle diffusion 
 kt1/(mmol/(g·min0.5)) 0.063 0.082 0.087 0.026 0.039 0.044 
 C1/(mmol/g) 0.292 0.344 0.418 0.323 0.387 0.437 
 R 0.998 0.998 0.997 0.996 0.999 0.996 
 kt2/(mmol/(g·min0.5)) 0.031 0.032 0.033 0.015 0.023 0.025 
 C2/(mmol/g) 0.472 0.616 0.719 0.392 0.473 0.535 
 R 0.978 0.999 0.997 0.971 0.996 0.992 

To better understand the adsorption process, the intra-particle diffusion model was applied to get further insights into the adsorption behavior of NOR and CIP onto Fe-Cu-NCs. As shown in Figure 9(c) and 9(d), the adsorption process can be divided into two adsorption stages for the same initial concentration. The first stage can be attributed to a rapid diffusion of NOR or CIP through the solution to the external surface of Fe-Cu-NCs. The second stage involves the internal diffusion of NOR or CIP molecules into the interior of the adsorbent particles. As can be seen from Table 1, the kt1 value of the intra-particle diffusion model was higher than the corresponding kt2, and boundary layer effect constant C2 was higher than the corresponding C1. These results indicated that in the first stage, the mass transfer of NOR or CIP molecules from the bulk solution to the Fe-Cu-NCs surface dominated the initial adsorption process, because not only was the intra-particle diffusion rate relatively fast, but also the boundary layer effect seemed weak. At the second stage, steric hindrance exerted by NOR or CIP molecules to the Fe-Cu-NCs surface caused viscous drag to the adsorption process (Wang & Yan 2011). The fitting curves of the intra-particle diffusion were multi-linear and did not pass through the origin, indicating that intra-particle diffusion is not the only rate-limiting step for the process of adsorption (Sepehr et al. 2014). Moreover, the parameters kt1 and kt2 of NOR were greater than that of CIP, implying that the mass transfer resistance of NOR was smaller.

Adsorption isotherm study

The adsorption isotherms of NOR and CIP from the solution onto Fe-Cu-NCs are presented in Figure 10, and the relevant model parameters are listed in Table 2. It can be seen that the adsorption capacity of NOR and CIP increased with increasing solution temperature. When the temperature was increased from 293 to 313 K, the adsorption capacity of NOR was increased from 1.199 to 1.412 mmol/g, and that of CIP was increased from 0.993 to 1.118 mmol/g. This was due to the acceleration of originally slow adsorption or the creation of some new active sites on the adsorbent surface (Meng et al. 2018). This finding indicated that the process of adsorbing NOR and CIP molecules is apparently endothermic in nature. In addition, the initial concentration of NOR or CIP was positively correlated with the adsorption concentration when the temperature was kept constant. As can be seen from Figure 10, the maximum adsorption capacity of NOR onto Fe-Cu-NCs is greater than that of CIP, which is consistent with the kinetic results.

Table 2

Parameters of adsorption isotherm for NOR and CIP onto Fe-Cu-NCs

Isotherm modelsNORCIP
 293 K 303 K 313 K 293 K 303 K 313 K 
Langmuir 
 qm,cal/(mmol/g) 1.182 1.271 1.421 1.103 1.202 1.246 
 qm,exp/(mmol/g) 1.199 1.284 1.412 0.993 1.073 1.118 
 KL/(L/mmol) 38.072 43.599 49.520 9.461 9.058 9.792 
 R2 0.979 0.985 0.993 0.952 0.958 0.966 
 ARS 0.098 0.098 0.091 0.218 0.224 0.203 
Freundlich 
 KF/((mmol/g)(L/mmol)1/n) 1.880 1.526 1.655 1.282 1.401 1.491 
1/n 0.255 0.267 0.259 0.397 0.407 0.407 
 R2 0.957 0.978 0.970 0.997 0.998 0.999 
 ARS 0.280 0.197 0.222 0.040 0.030 0.032 
Koble-Corrigan 
 A 8.779 14.050 29.457 0.876 1.038 1.409 
 B 5.862 9.447 19.254 −0.357 −0.297 −0.064 
 n 0.611 0.677 0.796 0.317 0.343 0.395 
 R2 0.995 0.995 0.997 0.997 0.998 0.999 
 ARS 0.076 0.062 0.026 0.046 0.037 0.035 
Redlich-Peterson 
 A 91.917 97.958 95.222 1.343 × 105 1.312 × 105 502.615 
 B 66.885 67.478 61.280 1.048 × 105 0.936 × 105 337.867 
 g 0.849 0.875 0.923 0.604 0.593 0.600 
 R2 0.998 0.997 0.997 0.996 0.998 0.999 
 ARS 0.051 0.041 0.042 0.040 0.030 0.027 
Dubinin-Radushkevich 
 qm/(mmol/g) 1.242 1.345 1.515 1.008 1.093 1.152 
 Ea/(kJ/mol) 7.271 7.499 7.698 5.385 5.298 5.354 
 R2 0.994 0.996 0.995 0.954 0.958 0.967 
 ARS 0.055 0.057 0.057 0.185 0.198 0.177 
Isotherm modelsNORCIP
 293 K 303 K 313 K 293 K 303 K 313 K 
Langmuir 
 qm,cal/(mmol/g) 1.182 1.271 1.421 1.103 1.202 1.246 
 qm,exp/(mmol/g) 1.199 1.284 1.412 0.993 1.073 1.118 
 KL/(L/mmol) 38.072 43.599 49.520 9.461 9.058 9.792 
 R2 0.979 0.985 0.993 0.952 0.958 0.966 
 ARS 0.098 0.098 0.091 0.218 0.224 0.203 
Freundlich 
 KF/((mmol/g)(L/mmol)1/n) 1.880 1.526 1.655 1.282 1.401 1.491 
1/n 0.255 0.267 0.259 0.397 0.407 0.407 
 R2 0.957 0.978 0.970 0.997 0.998 0.999 
 ARS 0.280 0.197 0.222 0.040 0.030 0.032 
Koble-Corrigan 
 A 8.779 14.050 29.457 0.876 1.038 1.409 
 B 5.862 9.447 19.254 −0.357 −0.297 −0.064 
 n 0.611 0.677 0.796 0.317 0.343 0.395 
 R2 0.995 0.995 0.997 0.997 0.998 0.999 
 ARS 0.076 0.062 0.026 0.046 0.037 0.035 
Redlich-Peterson 
 A 91.917 97.958 95.222 1.343 × 105 1.312 × 105 502.615 
 B 66.885 67.478 61.280 1.048 × 105 0.936 × 105 337.867 
 g 0.849 0.875 0.923 0.604 0.593 0.600 
 R2 0.998 0.997 0.997 0.996 0.998 0.999 
 ARS 0.051 0.041 0.042 0.040 0.030 0.027 
Dubinin-Radushkevich 
 qm/(mmol/g) 1.242 1.345 1.515 1.008 1.093 1.152 
 Ea/(kJ/mol) 7.271 7.499 7.698 5.385 5.298 5.354 
 R2 0.994 0.996 0.995 0.954 0.958 0.967 
 ARS 0.055 0.057 0.057 0.185 0.198 0.177 
Figure 10

Adsorption isotherms for the adsorption of NOR (a) and CIP (b) onto Fe-Cu-NCs.

Figure 10

Adsorption isotherms for the adsorption of NOR (a) and CIP (b) onto Fe-Cu-NCs.

To better describe the adsorption behavior, the experimental data were examined with Langmuir, Freundlich, Koble-Corrigan, Redlich-Peterson and Dubinin-Radushkevich models. These models can be described by the following equations:  
formula
(9)
 
formula
(10)
 
formula
(11)
 
formula
(12)
 
formula
(13)
where Ce (mmol/L) is the equilibrium concentration of the solution and qe (mmol/g) is the equilibrium adsorption capacity. qm (mmol/g) is the theoretical maximum adsorption capacity and KL (L/mmol) is the Langmuir constant related to rate of adsorption. KF ((mmol/g) (L/mmol)1/n) and nF are the Freundlich constants that give a measure of adsorption capacity and adsorption intensity, respectively. E (kJ/mol) is the energy of adsorption of the Dubinin-Radushkevich model. AR, BR and g are the Redlich-Peterson parameters and nKC is an indicator of the adsorption intensity of the Koble-Corrigan model.

From Table 2, based on the high correlation coefficient R2 and low relative standard deviation ARS, the adsorption isotherm models fitted to the equilibrium data of NOR on Fe-Cu-NCs were in the following sequence: Redlich-Peterson > Koble-Corrigan > Dubinin-Radushkevich >Langmuir > Freundlich. Both the Redlich-Peterson model and the Koble-Corrigan model contain three parameters and combine the characteristics of the Langmuir and the Freundlich isotherms models. According to the data in Table 2, the constant g of the Redlich-Peterson model was close to 1, indicating that the NOR adsorption process was approaching the Langmuir model (Wan et al. 2018). The Koble-Corrigan model also fitted the experimental data better and the parameter nKC of Koble-Corrigan model was between 0 and 1 (0.611–0.796), indicating that the adsorption of NOR onto Fe-Cu-NCs was more complex. It can be seen that the correlation coefficient of the Langmuir model (R2: 0.979–0.993) was higher than that of the Freundlich model (R2: 0.957–0.970) and the values of qm,cal obtained by the Langmuir model were closer to the values of qm,exp. It was verified that the Langmuir model could better describe NOR adsorption onto Fe-Cu-NCs. The maximum qm obtained from the Langmuir model were found to be 1.199 to 1.412 mmol/g as the temperature increased from 293 K to 313 K, which were higher than most of the adsorbents previously reported (Table 3).

Table 3

Comparison of maximum adsorption capacities of NOR and CIP on different adsorbents

MaterialsAdsorbatesqm(mmol/g)References
Polydopamine microspheres NOR 0.961 Wan et al. (2018)  
Layered chalcogenide NOR 0.733 Li et al. (2018)  
Magnetic copper-based metal organic frameworks NOR 1.606 Wu et al. (2018)  
Magnetic biochar NOR 0.520 Liu et al. (2019)  
Fe,Cu oxide nanocomposites NOR 1.182 This work 
Magnetic copper based metal-organic frameworks CIP 1.463 Wu et al. (2018)  
Layered chalcogenide CIP 0.694 Li et al. (2018)  
CoFe2O4/Activated carbon@Chitosan CIP 0.513 Malakootian et al. (2018)  
Montmorillonite CIP 1.033 Wu et al. (2010)  
Fe,Cu oxide nanocomposites CIP 1.103 This work 
MaterialsAdsorbatesqm(mmol/g)References
Polydopamine microspheres NOR 0.961 Wan et al. (2018)  
Layered chalcogenide NOR 0.733 Li et al. (2018)  
Magnetic copper-based metal organic frameworks NOR 1.606 Wu et al. (2018)  
Magnetic biochar NOR 0.520 Liu et al. (2019)  
Fe,Cu oxide nanocomposites NOR 1.182 This work 
Magnetic copper based metal-organic frameworks CIP 1.463 Wu et al. (2018)  
Layered chalcogenide CIP 0.694 Li et al. (2018)  
CoFe2O4/Activated carbon@Chitosan CIP 0.513 Malakootian et al. (2018)  
Montmorillonite CIP 1.033 Wu et al. (2010)  
Fe,Cu oxide nanocomposites CIP 1.103 This work 

The Dubinin-Radushkevich model can be applied to distinguish physical or chemical adsorption based on the adsorption free energy. Application of the Dubinin-Radushkevich model gave the adsorption free energies of 3.87, 4.11 and 4.32 kJ/mol at 293 K, 303 K and 313 K, respectively. The values were lower than 8.00 kJ/mol, indicating that NOR adsorption onto Fe-Cu-NCs was dominated by physisorption (Martins et al. 2015).

The adsorption isotherm models fitted the equilibrium data of CIP onto Fe-Cu-NCs in the following sequence: Koble-Corrigan > Redlich-Peterson > Freundlich > Dubinin-Radushkevich > Langmuir. The Koble-Corrigan model and the Redlich-Peterson model fitted the experimental date better. The constant g of the Redlich-Peterson model was far less than 1, indicating that the CIP adsorption process had the behavior of the Freundlich model. According to the values of R2 and ARS, the Freundlich model was more suitable for describing the adsorption behavior of CIP onto Fe-Cu-NCs. The values of 1/nF (0.397–0.407) were less than 0.5, indicating a favorable adsorption for CIP onto Fe-Cu-NCs. For the Dubinin-Radushkevich model, the values of Ea were 2.92, 3.15 and 3.23 kJ/mol at 293 K, 303 K and 313 K, respectively, indicating that the CIP adsorption onto Fe-Cu-NCs was also dominated by physisorption.

The effect of ionic strength

As shown in Figure 11, the adsorption of NOR and CIP onto Fe-Cu-NCs decreased with increasing ionic strength. The adsorption amounts of NOR and CIP onto Fe-Cu-NCs were reduced by 0.522 and 0.296 when the CaCl2 concentration increased from 0 to 0.1 mol/L in aqueous solution, respectively. Conversely, with the increase of NaCl concentration from 0 to 0.1 mol/L, the adsorption amounts of NOR and CIP showed no obvious change, with reductions of 0.149 and 0.045, respectively. These results would be due to the fact that the adsorption capacity of antibiotics onto Fe-Cu-NCs was affected by the competitive adsorption of Na+ and Ca2+ ions in solution. The increase of ionic concentration can reduce the active sites of the adsorbent, which confirmed the existence of electrostatic interactions between NOR or CIP and the Fe-Cu-NCs (Wan et al. 2018). Ca2+ had a stronger inhibitory effect on adsorption, not only because of its higher positive charge, but also because of its complexation effect with NOR or CIP. Furthermore, Ca2+ was easily combined with the oxygen atom of the carbonyl group and one of the two oxygen atoms of the carboxyl group on the NOR or CIP to form a stable six-membered ring, which may have restricted the positive contribution of hydrogen bonding to the adsorption process, thus leading to a reduction in NOR or CIP adsorption (Al-Mustafa 2002).

Figure 11

Effects of ionic (Na+ and Ca2+) concentration on NOR and CIP adsorption onto Fe-Cu-NCs.

Figure 11

Effects of ionic (Na+ and Ca2+) concentration on NOR and CIP adsorption onto Fe-Cu-NCs.

Stability of adsorption properties of Fe-Cu-NCs

As shown in Figure 12, the stability of Fe-Cu-NCs as adsorbents was studied. It was found that the change of adsorption capacity of CIP onto Fe-Cu-NCs was slight, indicating that the Fe-Cu-NCs were stable over an extended time period. The organic matter capping on the adsorbent surface and the added oxalic acid played an important role in the stability of the Fe-Cu-NCs. (Zhang et al. 2018).

Figure 12

CIP adsorption capacity of Fe-Cu-NCs stored for 1–28 days.

Figure 12

CIP adsorption capacity of Fe-Cu-NCs stored for 1–28 days.

Adsorption thermodynamic study

The Gibbs free energy change (ΔG), enthalpy change (ΔH) and entropy change (ΔS) were calculated using the following equations:  
formula
(14)
 
formula
(15)
where Kc is the thermodynamic equilibrium constant. T (K) is temperature in Kelvin, and R is the universal gas constant (8.314 J/(mol K)).

For the adsorption of NOR onto Fe-Cu-NCs, the positive values of ΔH and ΔS were 2.72 kJ/mol and 22.5 J/(mol K), respectively. The value of ΔH was less than 40 kJ/mol, which indicated that the adsorption process was endothermic in nature and controlled by physical adsorption (Zhou et al. 2017). The ΔG values were −3.87, −4.11, −4.32 kJ/mol at 293, 303 and 313 K, respectively, indicating that the NOR adsorption process was feasible and spontaneous. The negative value of ΔG decreased with increasing solution temperature, indicating that the adsorption of NOR onto Fe-Cu-NCs became more favorable at higher temperatures (Ponnusamy et al. 2010).

For the adsorption of CIP onto Fe-Cu-NCs, the values of ΔH and ΔS were 1.6 kJ/mol and 15.5 J/(mol K), respectively. The ΔG values were −2.92, −3.15, −3.23 kJ/mol at 293, 303 and 313 K, respectively. The process of adsorption was also an endothermic and spontaneous process.

CONCLUSIONS

In this study, Fe-Cu-NCs were successfully synthesized from loquat leaf extracts and used in the adsorption process of NOR and CIP from aqueous solution. SEM, TEM, XPS, XRD and FTIR verified the spherical structure and possible surface composition of biomolecules and surface functional groups of the Fe-Cu-NCs, which provided a basis for the excellent adsorption capacity. The results of kinetic study showed the adsorption process fitted the double-constant rate equation and the Elovich model well, and both film diffusion and intra-particle diffusion control the adsorption process. The equilibrium data suggested that the NOR and CIP adsorption onto Fe-Cu-NCs was favorable and dominated by physisorption. In addition, the thermodynamic parameters (ΔG, ΔH, and ΔS) indicated that the adsorption of NOR and CIP onto Fe-Cu-NCs was spontaneous and endothermic. The adsorption performance of the Fe-Cu-NCs for NOR and CIP may be attributed to electrostatic interaction, hydrogen bonding, hydrophobic interaction, n-π electron donor–acceptor (EDA) interactions and surface complexation. In this study, Fe-Cu-NCs showed good stability and high adsorption, and their synthesis process is green and harmless. Thus, Fe-Cu-NCs are considered to be a potential and excellent adsorbents for the removal of antibiotic wastewater. They provide a new insight into applications for the remediation of other pollutants.

ACKNOWLEDGEMENTS

This work was supported by the Henan Science and Technology Department in China (No. 162300410016) and program of biomass resources processing and efficient utilization of outstanding foreign scientists' workroom (GZS2018004).

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