## Abstract

The adsorption behavior of lead(II) using a new magnetic adsorbent is investigated. The facile synthesis of MnFe2O4 was carried out using the co-precipitation method. The different parameters that affected the adsorption process were investigated such as contact time, metal ion concentration, pH, temperature, and the adsorbent dosage. The maximum lead(II) sorption capacity was found to be 75.75 (mg/g) and obtained using 1 g/L MnFe2O4 when pH equals 5.3, a temperature of 25 °C, and contact time as 60 min. The adsorption isotherm study indicated that the Langmuir model was the best model that described the adsorption process using 1 g/L MnFe2O4. Based on the values of correlation coefficient data (R2), the kinetic adsorption parameters were well defined by the second-order kinetic model. Furthermore, the temperature effect findings have been confirmed that the removal of lead ions was endothermic. The desorption efficiency reached more than 88% when used 0.01 M NaOH as an eluent.

## HIGHLIGHTS

• The sorption behavior of lead(II) by new magnetic sorbent was investigated using MnFe2O4 nanoparticles.

• The maximum sorption capacity of lead(II) was found to be 75.75 (mg/g).

• The second-order kinetic model described the kinetic sorption process and the Langmuir model, the sorption process.

• The desorption efficiency reached more than 88% when used 0.01 M NaOH as an eluent.

### Graphical Abstract

Graphical Abstract
Graphical Abstract

## INTRODUCTION

Natural lead is composed of a mixture of four stable isotopes: lead-204 (1.4%); lead-206 (24.1%); lead-207 (22.1%); and lead-208 (52.4%). Lead isotopes are the end products of each of the three naturally occurring radioactive elements: lead-206 for the uranium series, lead-207 for the actinium series, and lead-208 for the thorium series. There are 43 other isotopes of lead; all are radioactive, so that the removal of lead ions from the aqueous solutions is considered a critical task (Morton-Bermea et al. 2011). Water pollution is considered a global problem that affects millions of people rapidly, increasing in the fields such as industry and agriculture (Qiu 2010). The wastewater treatment is an important task because of the vicious spread of common diseases of wastewater such as cancer, kidney failure, typhoid fever, diarrhea, and liver hepatitis (Zou et al. 2016; Zare et al. 2018).

The wastewater treatment was taken from industrial effluent, wastewater, and sewage before being exhausted from water resources (Salem & Awwad 2014; Chen et al. 2019). Unfortunately, the presence of large amounts of heavy toxic metals in these effluents causes the biggest challenge in the purification of water, where it can cause death when reaching more than the allowable concentration limit in the human body (Afroze & Sen 2018; Wang et al. 2020). Lead is considered to be a long-term contaminant of these heavy metals. It is produced from the burning of fossil fuels and the mining operations in the atmosphere. It has many uses and applications, such as battery manufacturing, pesticide, ammunition, pigments, glassware, and metal products (Yao et al. 2016; Mohammad et al. 2017). Very low concentration of lead may prevent the synthesis of red blood cells, while above the lead upper limit causes damage to the nervous, reproductive, and cardiovascular systems (Long et al. 2014; Li et al. 2019b).

Consequently, it is essential to find effective treatments to reduce the lead ions in the wastewater and prevent lead toxicity. Various chemical separation techniques have been employed for the effective removal of the toxic heavy metals from the wastewater, such as coagulation, chemical precipitation, reduction, evaporation, cementation, reverse osmosis, ion exchange, and ultrafiltration (Demey et al. 2018; Son et al. 2018; Zhu et al. 2018; Li et al. 2019a; Brinza et al. 2020). Nonetheless, these procedures have numerous technical and economic limitations in the range of 1–100 mg/L to eliminate lead(II) ions from the dilute solutions (Vafajoo et al. 2018).

Various types of adsorbents, such as activated charcoal, zeolites, clays, apatite, and chitosan, have been used in this respect for the removal of lead(II) ions (Ziagova et al. 2007; Xu et al. 2019). Modified magnetic nanoparticles (MNPs) are considering efficient adsorbents for the removal of both the heavy metals and the organic pollutants because of their ease of separation from the aqueous solution under an external magnetic field, beside their advantages such as the nontoxicity, small diffusion resistance, and large surface area (Oliveira et al. 2003; Hu et al. 2007; Razmara et al. 2019). Combining the adsorption and magnetic properties enables these compounds to have an effective strategy for magnetic separation technology. The magnetic adsorption techniques are simple, quick, cheap, and automated (Donia et al. 2008; Zeraatkar Moghaddam et al. 2018). In recent years, this technique has received much more attention (Zhou et al. 2014; Zeraatkar Moghaddam et al. 2018). Recently, it is exciting to eliminate these metals using various magnetic ferrite nanoparticle adsorbents (Reddy & Yun 2016; Kefeni et al. 2017).

The novel contribution to the earlier publications is the facile synthesis of the MnFe2O4 by the co-precipitation method. Then, the characterizations of synthesized MNPs were carried out using the available spectroscopic tools such as transmission electron microscopy (TEM), scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FT-IR), and X-ray diffraction (XRD). The synthesized MNPs have been tested to remove lead(II) ions from an aqueous solution utilizing the magnetic separation technique. Various parameters affecting the adsorption of lead(II) ion process, such as the adsorbent weight, contact time, pH, and initial lead(II) ion concentration, have been examined to assess their impact on the adsorption efficiency, and desorption studies were also carried out to reuse the adsorbent.

## MATERIALS AND METHODS

### Chemicals and reagents

Lead(II) nitrate, cesium(I) nitrate, and cobalt(II) nitrate were obtained from Sigma-Aldrich and were prepared by dissolving in deionized water. The effecting parameters, such as contact time, pH, temperature, and sorbent mass that influence the sorption process, have been investigated by dissolving 0.128 g of lead nitrate into 1,000 mL of deionized water to get the standard lead(II) solution (80 mg/L), whereas to study the effect of the initial metal concentration, the stock solution of lead nitrate (500 mg/L) was prepared. With suitable dilutions, different concentrations from lead(II) were obtained.

### Synthesis of magnetic MnFe2O4 nanoparticles

The magnetic MnFe2O4 nanoparticles MNPs were synthesized by the co-precipitation method according to Yakout et al. (2018). The process is to mix manganese nitrate and ferric nitrate with special weight ratios into 250 mL deionized until the temperature of the solution becomes 323 K for 2 h. Then the pH was adjusted up to pH ≈ 10 using 0.01 M NaOH solution. After cooling, deionized water was thoroughly washed with the obtained MNPs (MnFe2O4) until a pH value of 7 was reached.

### Analysis methods

The synthesized MnFe2O4 nanoparticles have been characterized using the available spectroscopic tools such as the SEM, XRD, and TEM in addition to FT-IR to demonstrate the morphological characteristics of the synthesized adsorbent and elemental composition of the materials, respectively.

The adsorption of MnFe2O4 has been investigated using the analytical grade standard solutions composed of lead nitrate, cesium nitrate, and cobalt nitrate (100 mg/L). The batch studies were performed by varying the adsorbent mass, pH, contact time, temperature, and initial metal ion concentration.

The batch adsorption experiments were done using a thermostatic turning shaker utilizing 125 mL conical flasks under the optimum conditions of (pH 5.3, shaking rate: 400 rpm, temperature: 25 °C, and 1 g/L MNPs). The precipitate can be isolated by the outside magnetic field. The atomic absorption spectroscopy (AAS) (Model S4, Thermo Electron Corporation) was used for the determination of different samples of lead(II) ion concentrations in the aqueous phase before and after batch experiments to calculate the uptake percent and the amount of lead(II) transferred from the aqueous into the solid phase under the optimum conditions. The pH of the initial lead(II) solution was adjusted by 0.01 M HNO3 and 0.01 M NaOH. The removal efficiency and the amount of lead(II) ions removed by the MnFe2O4 were calculated as follows:
(1)
(2)
where Cj (mg/L) and Ce (mg/L) represent the initial and final concentrations of lead(II) ions, respectively. Qe (mg/g) represents the removed amount of the MnFe2O4 nanoparticles at the equilibrium concentration, M (g) is the mass of MnFe2O4 nanoparticles, and V (L) is the volume of the lead(II) ion solution.
The desorption studies were carried out by washing the filtered solids with deionized water, removing the excess lead-stacked ferrite nanoparticles, and evacuating the unadsorbed lead(II) ions joining the conical flask and adsorbent. The dry lead-loaded MNPs were then agitated with a solution (NaOH, 5 mL of 0.01 M) for 1 day and then, after the magnetic isolation process, the lead concentration was measured in the aqueous phase using AAS. The decanted lead(II) solutions were diluted and acidified by adding 0.2% of HNO3 for measuring the concentration of metal after desorption equilibrium was achieved. The concentration of lead(II) ions desorbed from the MnFe2O4 nanoparticles was calculated by the following equation:
(3)
To confirm the correlation between theoretical data (derived from the isotherm and kinetic models) and experimental data, nonlinear regression root-mean-square error (RMSE) (Equation (4)), the sum of squared error (SSE) (Equation (5)), and chi-squares (χ2) (Equation (6)) can be calculated as follows (Yakout et al. 2019):
(4)
(5)
(6)
where Qe,exp and Qe,m refer to the experimental and calculated values of lead(II) absorbed per unit mass of MnFe2O4 nanoparticles. In contrast, the nd represents the number of data points in each treatment period. The smaller values of RMSE, SSE, and χ2 better fit the curve (Abbas et al. 2018).

### Preliminary investigation

The main task in this section was to investigate the removal effectiveness of the synthesized MNPs MnFe2O4 toward different toxic ions such as cesium(I), cobalt(II), and lead(II) from aqueous solutions as promising potential adsorbents. In this concern, the removal efficiency, %R for cesium, cobalt, and lead ions were calculated, and the results are shown in Figure 1. MnFe2O4 nanoparticles removed lead(II) ions from the solution more than other metal ions.

Figure 1

Removal efficiency (%) for different metal ions using MnFe2O4 nanoparticles. (Adsorbent mass: 1 g/L; initial concentration, Cj: 100 mg/L; and temperature, T: 25 °C pH 5.3.)

Figure 1

Removal efficiency (%) for different metal ions using MnFe2O4 nanoparticles. (Adsorbent mass: 1 g/L; initial concentration, Cj: 100 mg/L; and temperature, T: 25 °C pH 5.3.)

## RESULTS AND DISCUSSION

### Characterization of MNPs

To determine surface areas of MnFe2O4 sample, nitrogen adsorption/desorption isotherm was measured at 77 K on an automatic adsorption instrument (Quantachrome Instruments, Model Noval1000e series, USA) in relative pressure ranging from 10−6 to 0.999. Before the measurement, the sample was powdered to shorten the time required for reaching equilibrium in the isotherm study and degassed at 250 °C under nitrogen flow for 24 h. The cross-sectional area, i.e., the area occupied by an adsorbate molecule in a completed monolayer for the molecule at 77 K, was taken as 16.2 Å2.

The surface area of the adsorbent sample was obtained using standard methods, pore-volume, and pore size distribution, which were subsequently calculated from the N2 adsorption data using NOVA Win 2.0 software.

The specific surface area of MnFe2O4 was 145 m2/g. Image of the prepared MNPs utilizing SEM was obtained, as appeared in Figure 2(a). The surface morphology study of MnFe2O4 showed that several ultra-fine particles with a diameter of about 10 nm are agglomerated. It is evident that the prepared material displays the uniform distribution of the crystals of MnFe2O4. It can be seen from the surface topography that there is grain between the particles. The particle size of the compound is around 10 nm.

Figure 2

(a) SEM image of MnFe2O4 nanoparticles, (b) XRD spectra of MnFe2O4 nanoparticles, (c) TEM image of MnFe2O4 nanoparticles, and (d) FT-IR spectra of the MnFe2O4 nanoparticles.

Figure 2

(a) SEM image of MnFe2O4 nanoparticles, (b) XRD spectra of MnFe2O4 nanoparticles, (c) TEM image of MnFe2O4 nanoparticles, and (d) FT-IR spectra of the MnFe2O4 nanoparticles.

The MnFe2O4 specimen's XRD patterns displayed in Figure 2(b) demonstrate that spinel MnFe2O4 can match all diffraction peaks with JCPDS database no. 38-0430. The mean crystallite size (L) was assessed from the full width at half maximum (FWHM) at (311) plain of MnFe2O4 nanoparticles utilizing Scherrer's formula in the following equation:
(7)
where λ refers to the radiation wavelength (0.154056 nm for Cu Kα), whereas L represents the crystallite size, β is the FWHM measured in radians, and θ is the corresponding diffraction peak angle. The average particle size of MnFe2O4 nanoparticles was found to be ≈8.7 nm. The XRD pattern (Figure 2(b)) shows that the prepared product largest peak at 2θ = 35° in the present case may be due to the presence of MnFe2O4 and no other phase occurred. The crystalline phase formation is confirmed.

The TEM micrograph of MnFe2O4 nanoparticles and the corresponding selected area electron diffraction pattern are shown in Figure 2(c). From the TEM image, the nanoparticles of specimens were spherical with the size ranging from 3 to 10 nm and the average particle of 8 nm that agrees well with that obtained from the XRD results given from Equation (7).

The FT-IR spectrum of MnFe2O4 is presented in Figure 2(d). The spectrum shows two major absorption bands under 1,000 cm−1, a typical feature of ferrites. The absorption peaks at 420 and 580 cm−1 may be attributed to the Fe–O and Mn–O stretching vibrations of MnFe2O4. The band at 3430 cm−1 may be assigned to the stretching vibration of O–H surface water molecules or hydroxyl groups, and the crystalline phase formation is confirmed from XRD results (Huang et al. 2019).

### Determination of point zero charge

Point zero charge (pHpzc) of MnFe2O4 nanoparticles was determined using the solid addition method by adding 1 g of the MnFe2O4 nanoparticles in 45 mL of 0.01 M of KNO3 solutions in various locked conical flasks. The pH value is varied between 2 and 10 using (0.1 M) HCl or (0.1 M) NaOH and kept overnight under stirring at a temperature of 25 °C. The final pH (pHf) was measured and plotted versus the initial pH (pH0). The pHpzc of MnFe2O4 nanoparticles was determined at which the pHf equals pH0 (Abbas et al. 2014). From Figure 3, the pHpzc of MnFe2O4 nanoparticles was found to be 6.5.

Figure 3

Plot for the determination of pHpzc for the MnFe2O4 nanoparticles. (Sorbent mass: 1 g and temperature, T: 25 °C.)

Figure 3

Plot for the determination of pHpzc for the MnFe2O4 nanoparticles. (Sorbent mass: 1 g and temperature, T: 25 °C.)

### Effect of initial pH on sorption

The effect of pH on lead(II) removal percentage (R%) at 25 °C is represented in Figure 4. The percentage lead(II) removal was increased, as the pH of the aqueous solution increased from 2 to 6.3 at adsorbent mass and lead(II) concentration of 1 g/L and 80 mg/L, respectively. The removal percentage of lead increased from 30 to 98.8% at pH values of 2 and 6.3, respectively. This phenomenon occurred due to the charge of the surface is neutral at pHpzc, which is 6.5 for manganese ferrite nanoparticles. Below the pHpzc, the surface of MnFe2O4 nanoparticles is positively charged, and lead(II) results in electrostatic repulsion. At pH higher than pHpzc, the surface of MnFe2O4 nanoparticles is negatively charged, increasing the adsorption with positively charged lead(II) species (Selambakkannu et al. 2018).

Figure 4

Effect of pH on the sorption of lead(II) ions on MnFe2O4 nanoparticles. (Sorbent mass: 1 g/L; initial concentration, Cj: 80 mg/L; temperature, T: 25 °C; pH 1–7; and t = 60 min.)

Figure 4

Effect of pH on the sorption of lead(II) ions on MnFe2O4 nanoparticles. (Sorbent mass: 1 g/L; initial concentration, Cj: 80 mg/L; temperature, T: 25 °C; pH 1–7; and t = 60 min.)

Moreover, it was clear that at low pH values, the adsorption of lead(II) ions onto MnFe2O4 nanoparticles was low due to the competition between lead(II) ions and hydronium ion (H3O+). At high pH values, the sorption of lead(II) ions was increased because of a reduction in hydronium ion concentration (Zhang et al. 2013; Chen et al. 2020). Experiments were performed with a pH value of less than 6 because lead(II) ions would precipitate to form Pb(OH)2 at a higher pH value of more than 6 (Kosa et al. 2012).

### Effect of sorbent mass

The effect of the MnFe2O4 nanoparticle mass on the percentage of lead(II) ions adsorbed from aqueous mediums was investigated in the adsorbent mass range (0.2–1.4 g/L), lead(II) concentrations of 80 mg/L, a pH value of 5.3, and a temperature of 25 °C (Figure 5). The figure shows that the percentage of lead(II) ions increased gradually with an increase in the adsorbent mass of MnFe2O4 nanoparticles and increasing the masses of MnFe2O4 nanoparticles from 0.2 to 1.4 g/L increased the percentage of adsorption of lead(II) ions from 35 to 100%. This increase in the percentage of adsorption of lead(II) ions may be attributed to the increase in the adsorption sites toward the metal ions and, consequently, the surface area of the adsorbent (Hassan Mohamed et al. 2020).

Figure 5

Effect of sorbent mass of MnFe2O4 nanoparticles. (Sorbent mass: 0.2–1.4 g/L; initial concentration, Cj: 80 mg/L; temperature, T: 25 °C; pH 5.3; and t: 60 min.)

Figure 5

Effect of sorbent mass of MnFe2O4 nanoparticles. (Sorbent mass: 0.2–1.4 g/L; initial concentration, Cj: 80 mg/L; temperature, T: 25 °C; pH 5.3; and t: 60 min.)

## MODELING STUDY

### Sorption kinetics

The adsorption of lead(II) ions by MnFe2O4 nanoparticles expanded with the expansion of time, and equilibrium was attained after 60 min (Figure 6(a)). Different kinetic sorption models were investigated to estimate the experimental data and understand the adsorption mechanism, including pseudo-first-order kinetic model, pseudo-second-order kinetic model, and intra-particle diffusion model.

Figure 6

(a) Effect of contact time on the adsorption of lead(II) ions onto MnFe2O4 nanoparticles, nonlinear pseudo-first-order, pseudo-second-order, intra-particle diffusion, and Elovich kinetic plot model fitting (sorbent mass: 1 g/L; pH: 5.3; initial concentration, Cj: 80 mg/L; temperature, T: 25 °C). (b) Linear fitting curves of pseudo-first-order, (c) pseudo-second-order, (d) intra-particle diffusion, and (e) Elovich kinetic plot sorption kinetic model for lead(II) ion sorption on MnFe2O4 nanoparticles.

Figure 6

(a) Effect of contact time on the adsorption of lead(II) ions onto MnFe2O4 nanoparticles, nonlinear pseudo-first-order, pseudo-second-order, intra-particle diffusion, and Elovich kinetic plot model fitting (sorbent mass: 1 g/L; pH: 5.3; initial concentration, Cj: 80 mg/L; temperature, T: 25 °C). (b) Linear fitting curves of pseudo-first-order, (c) pseudo-second-order, (d) intra-particle diffusion, and (e) Elovich kinetic plot sorption kinetic model for lead(II) ion sorption on MnFe2O4 nanoparticles.

#### Pseudo-first-order kinetic model

The linear form of the pseudo-first-order kinetic model can be represented by the Lagergren rate in the following equation (Hassan Mohamed et al. 2020):
(8)
where K1 (1/min) is the pseudo-first-order rate constant, Qe (mg/g) refers to the amount of lead(II) ions adsorbed at equilibrium, and Qt (mg/g) is the amount of lead(II) ions adsorbed at any time.

The slope and intercept of the plot of log(QeQt) against time were used to determine K1 and Qe, respectively (Figure 6(b)).

The results showed that the calculated adsorption capacity (Qe,cal) has a lower value than the amount of experimental adsorption capacity (Qe,exp). Consequently, the kinetic behavior of lead(II) ions on MnFe2O4 nanoparticles could not be explained by the pseudo-first-order kinetic model (Hassan & Aly 2019). Other parameters from the linear regression plot are recorded in Table 1.

Table 1

Kinetics parameters for the adsorption of lead(II) ions by the MnFe2O4 nanoparticles

ModelParameterValue
Pseudo-first-order model Qe,exp (mg/g) 77.48
K1 (1/min) 0.0463
Qe,cal (mg/g) 30.24
R2 0.935
RMSE 1.817
SSE 2.702
χ2 0.0381
Second-order model K2 (mg/mg·min) 0.00437
H0 (mg/g·min) 27.382
Qe,cal (mg/g) 79.11
R2 0.999
RMSE 1.713
SSE 2.402
χ2 0.0335
Intra-particle parameters Kint (mg/g·min0.53.32
I 51.34
R2 0.957
RMSE 2.07
SSE 3.99
χ2 0.164
Elovich equation α (mg/g·min) 3,786.8
1/β (mg/g) 6.985
R2 0.872
RMSE 12.38
SSE 125.49
χ2 1.592
ModelParameterValue
Pseudo-first-order model Qe,exp (mg/g) 77.48
K1 (1/min) 0.0463
Qe,cal (mg/g) 30.24
R2 0.935
RMSE 1.817
SSE 2.702
χ2 0.0381
Second-order model K2 (mg/mg·min) 0.00437
H0 (mg/g·min) 27.382
Qe,cal (mg/g) 79.11
R2 0.999
RMSE 1.713
SSE 2.402
χ2 0.0335
Intra-particle parameters Kint (mg/g·min0.53.32
I 51.34
R2 0.957
RMSE 2.07
SSE 3.99
χ2 0.164
Elovich equation α (mg/g·min) 3,786.8
1/β (mg/g) 6.985
R2 0.872
RMSE 12.38
SSE 125.49
χ2 1.592

#### Pseudo-second-order kinetic model

The linear form of the pseudo-second-order kinetic model can be represented in the following equation (Chigondo et al. 2019):
(9)
where K2 (mg/g·min) is the equilibrium rate constant [(H0 = 1/K2Qe2) is the initial rate of sorption)]. To compute parameters and the constant of the pseudo-second-order kinetic model, it was utilized the plot of t/Qt vs. time as shown in Figure 6(c). According to the findings in Table 1, the sorption of lead(II) ions onto MnFe2O4 nanoparticles followed the pseudo-second-order model, where the data achieved for Qcal were mainly close to the experimental data. The value of the correlation coefficient (R2) attained by the pseudo-first-order model was less than that attained by the pseudo-second-order model.

### Intra-particle diffusion model

For the solid–liquid adsorption process, the movement of adsorbate from the aqueous medium to the adsorbent particles in a batch process is generally characterized by either the boundary layer (film) or the intra-particle (pore) diffusion or both (Gad & Youssef 2018). In this work, the data of adsorption were also analyzed in terms of an intra-particle diffusion mechanism. The intra-particle diffusion kinetic (Weber–Morris diffusion model) is shown in the following equation (Abd El-Magied et al. 2016):
(10)
where Kint (mg/g·min0.5) is the intra-particle diffusion rate constant and I (mg/g) is a constant related to the thickness of the boundary layer. The value of Kint and I is obtained from the slope and intercept of the line plotted in Qt vs. t0.5, respectively.

The fitting data of the intra-particle diffusion model gives a nonlinear relationship, and the value of I computed (I ≠ 0) implies that this model does not participate in the adsorption process, as presented in Figure 6(d). And consequently, the intra-particle diffusion model was not valid for the adsorption kinetics.

### Elovich model

The Elovich model was used to compute the initial rate of the adsorption and the desorption. The Elovich equation can be written as in the following equation (Kumar et al. 2019):
(11)
where the constant β (g/mg) is related to the activation energy and the extent of surface coverage, and α (mg/g·min) is the initial sorption rate of the Elovich equation. The coefficients of the Elovich model are computed from the slope and the intercept of plotting of Qt vs. ln t (Figure 6(e)) and tabulated in Table 1. The higher value of α than β confirms that the adsorption of lead(II) ions onto MnFe2O4 may be considered a physical phenomenon, which further suggests that the adsorption rate was higher than that of the desorption.

The adsorption capacities of MnFe2O4 nanoparticles were measured at a pH value of 5.3 with sorbent mass 1 g/L of MnFe2O4 and lead(II) ion concentration (40–280 mg/L). Different isotherm models (Langmuir, Freundlich, and Dubinin–Radushkevich (D–R)) have been developed for assessing the equilibrium adsorption data (Hajialigol & Masoum 2019). Figure 7 shows the nonlinear fitting of the sorption equilibrium data for lead(II) ions onto the MnFe2O4 nanoparticles at different temperatures (Figure 7(a), 7(b), and 7(c), respectively) such as Langmuir, Freundlich, and D–R adsorption isotherm models.

Figure 7

(a) Adsorption equilibrium isotherms for lead(II) ion removal onto MnFe2O4 at a temperature of 25 °C, nonlinear fitting to Langmuir, Freundlich, and D–R isotherm models. (b) Adsorption equilibrium isotherms for lead(II) ion removal onto MnFe2O4 at a temperature of 40 °C, nonlinear fitting to Langmuir, Freundlich, and D–R isotherm models. (c) Adsorption equilibrium isotherms for lead(II) ion removal onto MnFe2O4 at a temperature of 55 °C, nonlinear fitting to Langmuir, Freundlich, and D–R isotherm models. (Sorbent mass: 1 g/L; initial concentration, Cj: 40–280 mg/L; temperature, T: 25–55 °C; pH 5.3; and t = 60 min.)

Figure 7

(a) Adsorption equilibrium isotherms for lead(II) ion removal onto MnFe2O4 at a temperature of 25 °C, nonlinear fitting to Langmuir, Freundlich, and D–R isotherm models. (b) Adsorption equilibrium isotherms for lead(II) ion removal onto MnFe2O4 at a temperature of 40 °C, nonlinear fitting to Langmuir, Freundlich, and D–R isotherm models. (c) Adsorption equilibrium isotherms for lead(II) ion removal onto MnFe2O4 at a temperature of 55 °C, nonlinear fitting to Langmuir, Freundlich, and D–R isotherm models. (Sorbent mass: 1 g/L; initial concentration, Cj: 40–280 mg/L; temperature, T: 25–55 °C; pH 5.3; and t = 60 min.)

### Langmuir isotherms

The Langmuir equation predicted the presence of monolayer coverage of the sorbate molecules above a homogeneous solid surface without any interaction among the adsorbed species (Tahar et al. 2018). The linearized form of the Langmuir adsorption isotherm equation can be expressed by the equation:
(12)
where Ce (mg/L) is the equilibrium concentration of lead(II) ions in solution, Qe refers to the equilibrium quantity of lead(II) ions adsorbed onto MnFe2O4 nanoparticles at equilibrium, QM (mg/g) is the maximum adsorption capacity, and b (L/g) is a constant related to the adsorption intensity. The maximum adsorption capacity (QM) is the monolayer coverage of adsorbent with adsorbate, and b is the energy of adsorption that changes with temperature (Faheem et al. 2020).

The linear plots presented in Figure 8(a) of Ce/Qe against Ce designate the Langmuir isotherm applicability on the lead(II) ion sorption capacity of MnFe2O4 nanoparticles. The values of the Langmuir constants are given in Table 2. The adsorption capacity (QM) for MnFe2O4 nanoparticles is 75.75 (mg/g).

Table 2

Characteristic parameters of the experimental data according to the Langmuir, Freundlich, and D–R models for the adsorption of lead(II) ions onto MnFe2O4 nanoparticles at different temperatures

Isotherm modelsParameter25 °C40 °C55 °C
Langmuir QM (mg/g) 75.75 94.07 106.38
b (L/g) 0.0836 0.114 0.1562
RL 0.0949 0.0720 0.0543
R2 0.998 0.997 0.998
RMSE 1.5054 4.3692 6.21
SSE 1.6188 13.63 25.37
χ2 0.0265 0.1795 0.298
Freundlich KF (mg/g) 19.349 22.451 31.133
N 3.7074 3.410 4.05071
R2 0.959 0.945 0.962
RMSE 6.2513 11.346 10.29
SSE 27.913 91.957 75.742
χ2 0.4479 1.2161 0.9242
D–R Qs (mg/g) 0.3615 0.4713 0.5167
KDR (mol2/kJ20.0130 0.0123 0.0079
E (kJ/mol) 6.196 6.3757 7.940
R2 0.996 0.983 0.980
RMSE 1.1286 4.0201 4.3271
SSE 0.90981 11.5439 13.374
χ2 0.01500 0.1536 0.1593
Isotherm modelsParameter25 °C40 °C55 °C
Langmuir QM (mg/g) 75.75 94.07 106.38
b (L/g) 0.0836 0.114 0.1562
RL 0.0949 0.0720 0.0543
R2 0.998 0.997 0.998
RMSE 1.5054 4.3692 6.21
SSE 1.6188 13.63 25.37
χ2 0.0265 0.1795 0.298
Freundlich KF (mg/g) 19.349 22.451 31.133
N 3.7074 3.410 4.05071
R2 0.959 0.945 0.962
RMSE 6.2513 11.346 10.29
SSE 27.913 91.957 75.742
χ2 0.4479 1.2161 0.9242
D–R Qs (mg/g) 0.3615 0.4713 0.5167
KDR (mol2/kJ20.0130 0.0123 0.0079
E (kJ/mol) 6.196 6.3757 7.940
R2 0.996 0.983 0.980
RMSE 1.1286 4.0201 4.3271
SSE 0.90981 11.5439 13.374
χ2 0.01500 0.1536 0.1593
Figure 8

(a) Langmuir, (b) Freundlich, and (c) D–R plots of lead(II) ion adsorption. (Sorbent mass: 1 g/L; initial concentration, Cj: 40–280 mg/L; temperature, T: 25–55 °C; pH 5.3; and t = 60 min.)

Figure 8

(a) Langmuir, (b) Freundlich, and (c) D–R plots of lead(II) ion adsorption. (Sorbent mass: 1 g/L; initial concentration, Cj: 40–280 mg/L; temperature, T: 25–55 °C; pH 5.3; and t = 60 min.)

The dimensionless separation factor (RL) reveals whether the process of adsorption was favorable or not. RL can be computed from the following equation, which was derived from the Langmuir model.
(13)
where Cj (mg/L) is the initial concentration of lead(II) ions. The RL values in Table 2 were found to be between 1 and 0, indicating that the adsorption of lead(II) ions onto MnFe2O4 nanoparticles was favorable.

### Freundlich model

Freundlich isotherm describes heterogeneous adsorbent surface energies by multilayer adsorption and is described by linear form as in the following equation (Hassan Mohamed et al. 2020):
(14)
where KF is constant related to the theoretical sorption capacity of the adsorbent, and n is constant related to the intensity of the adsorption.

According to the model of Freundlich (Figure 8(b)), the adsorption data at different temperatures were investigated. The constants KF and n are calculated and represented in Table 2. Values of n lying between 1 and 10 confirm that the adsorption was favorable (Selvi et al. 2001).

The adsorption isotherm data of lead(II) onto MnFe2O4 nanoparticles fitted well by the Langmuir model, with higher values of correlation coefficient R2 than the Freundlich model.

### D–R isotherm

The D–R isotherm was related to understanding the adsorption mechanism of pollutants with a data of Gaussian energy, the D–R was described by linear form as in the following equation (Daniel Abraham et al. 2020):
(15)
where KD–R (mol2/kJ2) is a constant related to the sorption energy, Qs (mg/g) is the maximum sorption capacity, and ε represents the Polanyi potential and can be calculated using the following equation as follows:
(16)
where T (K) is the temperature in Kelvin and R (kJ/mol·K) is the ideal gas. E (kJ/mol) is the energy of adsorption to transfer 1 mol of the sorbate from infinity in the solution to the surface of the solid. It can be described by the following equation:
(17)

The plots of ln Qe versus ε2 give straight lines as shown in Figure 8(c) with slopes and intercepts equal to β and ln Qs, respectively. Because in physical adsorption, increasing the temperature reduces the amount of adsorption at 25, 40, and 55 °C. The computed values of means free energy, E, of the adsorption for lead(II) were found to be 6.196–7.940 kJ/mol (Table 2), when the value of the energy of adsorption below 8 kJ/mol the adsorption proceeds via chemisorption mechanism. (Selim et al. 2018; Wang et al. 2018).

### Thermodynamic parameters

The thermodynamic parameters, such as enthalpy change (ΔH°), entropy change (ΔS°), and the free energy change (ΔG°) were computed using the following equation:
(18)
where ΔS° (J/mo1·K) is standard entropy, ΔH° is (kJ/mol) standard enthalpy, R (8.314 J/mol·K) is the ideal gas, T (K) is the temperature in Kelvin, and KL (L/g) is the distribution coefficient. The sorption experiments were carried out at 298, 313, and 328 K for lead(II) concentration of 100 mg/L. The values of ΔS° and ΔH° were computed from the slope and intercept of the linear regression of ln KL vs. 1/T (Figure 9). Values of ΔG° (kJ/mol) were computed by the following equation:
(19)
Figure 9

Van't Hoff plots of lead(II) ion sorption. (Sorbent mass: 1 g/L; pH: 5.3; initial concentration, Cj: 80 mg/L; temperature, T: 25–55 °C; and t: 60 min.)

Figure 9

Van't Hoff plots of lead(II) ion sorption. (Sorbent mass: 1 g/L; pH: 5.3; initial concentration, Cj: 80 mg/L; temperature, T: 25–55 °C; and t: 60 min.)

The values of ΔG°, ΔH°, and ΔS° are reported in Table 3. The positive value of entropy of adsorption ΔS° reflects the affinity of the sorbent MnFe2O4 nanoparticles toward lead(II), and the positive value of enthalpy change ΔH° and the negative values of free energy change (ΔG°) at all temperatures confirmed that the adsorption process of lead(II) ions was endothermic and thermodynamically spontaneous (Foroutan et al. 2018).

Table 3

Thermodynamic parameters of lead(II) sorption onto MnFe2O4 nanoparticles at different temperatures

Temperature (K)KL (L/g)ΔG° (kJ/mol)ΔH° (kJ/mol)ΔS° (J/mol·K)
298 0.55 −1.47
313 0.43 −2.791 24.12 86.89
328 0.228 −4.078
Temperature (K)KL (L/g)ΔG° (kJ/mol)ΔH° (kJ/mol)ΔS° (J/mol·K)
298 0.55 −1.47
313 0.43 −2.791 24.12 86.89
328 0.228 −4.078

The effect of natural organic matter (NOM) on the adsorption of lead(II) onto MnFe2O4 nanoparticles was discussed using the local canal's surface water. Figure 10 shows the isotherm tests of lead(II) adsorption onto MnFe2O4 nanoparticles using natural water compared to double distilled water. The Langmuir–Freundlich constants are listed in Table 4. As can be seen, the presence of the NOM increases lead(II) adsorption. NOM could adsorb onto the surfaces of the MnFe2O4 nanoparticles and then promote the adsorption of lead(II) due to its binding with lead(II) (Yang et al. 2011; Sun et al. 2012).

Table 4

QM (mg/g) 75.75 124.52
b (L/g) 0.0836 0.06
n 3.7074 2.7055
R2 0.998 0.967
QM (mg/g) 75.75 124.52
b (L/g) 0.0836 0.06
n 3.7074 2.7055
R2 0.998 0.967
Figure 10

Effect of NOM on lead(II) adsorption. (Adsorbent mass: 1 g/L; pH: 5.3; Cj: 40–280 mg/L; temperature, T: 25 °C; and t: 60 min.)

Figure 10

Effect of NOM on lead(II) adsorption. (Adsorbent mass: 1 g/L; pH: 5.3; Cj: 40–280 mg/L; temperature, T: 25 °C; and t: 60 min.)

### Regeneration of MnFe2O4 nanoparticles

Desorption and sorbent recovery are the essential features of the sorbent in reasonable applications. As shown in Figure 11, the desorption of lead(II) from stacked adsorbent was examined using various eluents such as NaOH, Na2CO3, Na3PO4, and deionized water.

Figure 11

Figure 11

The findings revealed that the desorption of lead(II) ions from MnFe2O4 nanoparticles was obtained using 0.01 M NaOH, and the desorption percent achieved 88%. The desorption test was performed in a low concentration of alkaline media and using a very low concentration of 0.01 M of NaOH pH around 6 for applications purposes, especially wastewater treatment beside the Pb(II) ions formed more stable complex Pb (OH)2 (Equation (20)) (Awad et al. 2019; Chen et al. 2020).
(20)

### Comparative study

Table 5 includes a relative report about the adsorption capacity compared with other announced adsorbents. From Table 5, it is clear that the adsorption capacity of MnFe2O4 nanoparticles is more noteworthy than that of the most existing adsorbents. Therefore, MnFe2O4 nanoparticles could be a promising material used in lead(II) removal from leaden aqueous media. The cost, including the transport, preparation, and further recovery of the MnFe2O4 nanoparticles, is assessed under various conditions. While numerous researchers have stated as ‘low-cost sorbents for removal of lead’, although even several commercial adsorbents have been closely studied for the removal of lead(II), the actual costs are not stated in the literature. The cost of MnFe2O4 nanoparticles as $/g of lead(II) removed was found at approximately$1.3.

Table 5

Comparison of the sorption capacities of lead(II) onto various sorbents

Hydroxyapatite/chitosan nanocomposite 196.10 Mohammad et al. (2017)
Pretreated clinoptilolite 122.40 Günay et al. (2007)
Carbon nanotubes 12.41 Li et al. (2005)
Phosphatic clay 35.82 Singh et al. (2006)
Co/Bi-LDH 143.4 Jaiswal & Chattopadhyaya (2017)
Manganese oxide-coated carbon nanotubes 78.74 Wang et al. (2007
MWCNTs/PAAM 29.71 Yang et al. (2011
MnFe2O4 nanoparticles 75.75 Present work
Hydroxyapatite/chitosan nanocomposite 196.10 Mohammad et al. (2017)
Pretreated clinoptilolite 122.40 Günay et al. (2007)
Carbon nanotubes 12.41 Li et al. (2005)
Phosphatic clay 35.82 Singh et al. (2006)
Co/Bi-LDH 143.4 Jaiswal & Chattopadhyaya (2017)
Manganese oxide-coated carbon nanotubes 78.74 Wang et al. (2007
MWCNTs/PAAM 29.71 Yang et al. (2011
MnFe2O4 nanoparticles 75.75 Present work

The bold value denotes the maximum sorption capacity, QM (mg/g) value obtained in the present work.

However, the exhausted MnFe2O4 nanoparticles loaded with lead(II) ions can be regenerated by 0.01 M NaOH. After the fourth regeneration time, it can be dried and used in construction, safe and economical disposal of the adsorbed lead(II).

## CONCLUSION

This study reveals that MnFe2O4 nanoparticles are an effective adsorbent for removing lead(II) ions from laden aqueous media. The co-precipitation technique was used to synthesize the MnFe2O4 nanoparticles. The XRD analysis has demonstrated the development of spinel structures of the nanoparticles. The TEM analysis showed that the ferrite particles distributed have a truly uniform structure, and the particle size of the sample is around 8.7 nm.

From the experimental section, we concluded that the percentage removal of lead(II) steadily increases with increasing agitation time, temperature, adsorbate mass, and pH. The adsorption kinetics confirmed that the sorption followed pseudo-second-order kinetics. The lead(II) ion sorption onto MnFe2O4 nanoparticle result followed well with Langmuir and Freundlich isotherm models, but Langmuir isotherm is the best fitted than Freundlich isotherm. The positive value of ΔH° shows the endothermic nature of the process, and the negative value of ΔG° indicates that the sorption process was thermodynamically spontaneous. The presence of NOM increases lead(II) adsorption. Also, the desorption of lead-adsorbed MnFe2O4 nanoparticles was conducted using 0.01 M NaOH as eluent, and desorption efficiency was found to be more than 88% for four runs.

This study concluded that MnFe2O4 MNPs would be a promising, cost-effective, efficient, and renewable adsorbent for the treatment of lead(II) ions from contaminated wastewater.

## ACKNOWLEDGEMENT

The authors would like to thank the Nuclear Research Center, the Egyptian Atomic Energy Authority, to support this work.

## DATA AVAILABILITY STATEMENT

All relevant data are included in the paper or its Supplementary Information.

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