Chemical co-precipitation synthesis of manganese ferrite (MnFe 2 O 4 ) nanoparticles as a magnetic adsorbent of lead

Abstract

Herein, MnFe₂O₄ binary oxides, including various percentages of Fe₃O₄ were synthesized using the chemical co-precipitation method. In order to determine the physicochemical properties, Fourier transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD), and energy-dispersive X-ray spectroscopy (SEM-EDX) analyses were used. Adsorbent dosage, pH of the solution, contact time, and adsorbate concentration were optimized during the adsorption process. It was found that the Langmuir isotherm model is the best kinetic model for adsorption. Finally, the mean adsorption energy, reproducibility, and spontaneity of the adsorbent were also estimated, which showed that the physical adsorption mechanism is dominant.

Keywords

Manganese ferrite nanoparticles adsorption langmuir isotherm lead removal

1 Introduction

Heavy metals are discharged into the environment through various industries such as electroplating, metal surface treatment, mining operations, chemical manufacturing, tanneries, wood processing, batteries, and pesticides, etc [1]. Heavy metals have an atomic weight of between 63.5 u and 200.6 u, and their specific gravity is at least 5.0 g cm^–3 [1]. The examples are including arsenic, mercury, aluminum, zinc, chromium, and iron, which are released into the ecosystem by both natural and artificial sources such as mining, industrial evacuation, the exhaust of automobiles [2]. Unlike organic pollutants, toxic heavy metals are non-biodegradable and tend to accumulate in living organisms and cause poisoning and even cancer [1].

Lead (Pb^2 +) as heavy metal, is a particularly toxic ingredient in effluent with the potential of causing irreversible health effects [3]. Therefore, the removal of this heavy metal from industrial wastewater is a necessity, especially in developing countries. Various methods have been used to remove heavy metals, which generally include; ion exchange, membrane filtration, coagulation and flocculation, flotation, electrochemical treatment, and adsorption [4]. Among the various methods applied to remove heavy or trace metals, chemical co-precipitation techniques are commonly used for industrial effluent treatment because of their facility and low cost for a high volume of separation [5].

In chemical precipitation, the chemical reactants react with heavy metal ions dissolved in water to form insoluble particles which can be separated from water by filtration [6]. In the ion exchange technique, the heavy metal ion in the wastewater is replaced by a harmless cation in the ion exchanger (e.g. strongly and weakly acidic resins, natural zeolites, etc.) [7]. The membrane filtration methods used to eliminate heavy metals from the wastewater are ultrafiltration, reverse osmosis, nanofiltration, and electrodialysis. In these methods, depending on the type of pollutant, membranes with different characteristics such as different pore sizes, semi-permeability, and electrically charged surfaces are used [8]. Coagulation is a process that causes colloids to accumulate into small aggregates called “flocs” by neutralizing the forces that keep them apart. In the flocculation process, the suspended particles are agglomerated with the help of polymers and are therefore ready to be separated through filtration, straining, or floatation [5]. In the flotation method, the air micro-bubbles bring the suspended particles in the wastewater to the surface, and then the accumulated particles are easily separated [9]. In electrochemical treatment, heavy metal ions are electrodeposited on the surface of the cathode electrode and are recovered as an elemental metal from the surface [10].

Adsorption is a mass transfer method in which pollutants are transferred from the liquid phase to the surface of solid material and physically or chemically bonded to it [9]. The adsorption method has advantages over other methods, which include high efficiency, cost-effectiveness, flexibility in design and operation, producing high quality treated effluents, and adsorbent recovery in some cases [1]. So far, selective adsorption of heavy metals has been done using various materials such as carbon nanotubes, activated carbon, biological materials, polymer resins, and minerals [11]. However, the effectiveness of using nanomaterials with a large active area to adsorb heavy metals, especially lead, has been reported [12, 13]. Lead can cause problems such as damage to the fetal brain, diseases of the kidneys, circulatory system, and nervous system [8].

Chen et al. synthesized new nanomaterials of orthohexagonal iron oxide for efficient removal of lead (II), which were doped with cobalt (Co-Fe₂O₃) or Nickel (Ni-Fe₂O₃) ions [12]. They showed that the lead adsorption capacity in the doped state is greater than that in the pristine one (Fe₂O₃). Zhang et al. demonstrated that monodispersed and spherical Fe₃O₄@SiO₂–NH₂ nanomaterials, which are eco-friendliness and recoverable, can be a potential adsorbent for Pb(II) removal [14]. Cao et al. synthesized MgO nanostructures with high surface area and high adsorption capacity for Pb(II), with a maximum capacity of 1980 mg/g [9]. TiO₂-Fe₂O₃ binary oxides containing different percentages of Fe₂O₃ were synthesized by Abebe et al. and introduced as a good adsorbent for the lead metal [15].

An important class of nanoparticles is magnetic metal ferrite nanoparticles, which are obtained by coupling a metal with a ferrite molecule. Ferrite’s magnetic property makes it easy to recover from the solutions by a magnet. Metal ferrite is denoted as M(Fe_xO_y) where M denotes any metal which makes divalent bonds. Tu et al [16]. Proposed ZnFe₂O₄ nanoparticles were fast and efficient for Mo removal from solutions with an adsorption capacity of 62.5 mg g^–1. Tu et al [17] showed that copper ferrite (CuFe₂O₄), a new type of nanoparticle produced from industrial sludge, is effective for Pb removal from aqueous solutions. Their results specified that about 90% of lead was removed/recovered from aqueous solutions at a pH of 4.5 and 298 K. in another study [18], Mn-Zn ferrite (Mn_0.67Zn_0.33Fe₂O₄) was synthesized using the powder of waste dry batteries as starting raw materials and employed for removing As (V), Cd (II), and Pb (II) with high removal efficiencies.

Since reactive nanoparticles have been shown to provide a potentially cheap and effective solution for environmental remediation, ferrite manganese nanoparticles are widely used for metal remediation due to their excellent chemical stability, remarkable inherent biocompatibility, low toxicity, and tunable magnetic properties [19]. Hence, this work reports the usage of manganese ferrite nanoparticles for the removal of Pb heavy metal from water sources. Furthermore, the effects of pH of the solution, adsorbent dosage, contact time, and concentration of adsorbate were optimized for adsorbing lead heavy metal.

2 Experimental

2.1 Synthesis of manganese ferrite and its characterization

Adsorption of Pb^2 + from aqueous solution by MnFe₂O₄ was examined in batch experiments. The MnFe₂O₄ were synthesized by catalytic chemical vapour deposition process, MnFe₂O₄ were dispersed in an ultrasonic bath (Bandelin Sonopuls). Functionalization of MnFe₂O₄ was realized by the wet chemical treatment method. Equilibration of the experiments was done on a rotary shaker. Then, the obtained solution was filtered to separate the residue from the solution, finally, the nano-adsorbent was separated magnetically from solution.

The following chemicals were used for the synthesis of manganese ferrite nanoparticles; Manganese (II) chloride tetrahydrate (MnCl₂·4H₂O, Merck), Iron (II) chloride tetrahydrate (FeCl₂·4H₂O, Merck), Iron (III) chloride hexahydrate (FeCl₃·6H₂O, Merck), and Ammonia solution 25% (NH₄OH, Merck). All reagents were used as received without further purification.

In the co-precipitation method, reagents were prepared according to the literatures. This process involves the precipitation of Fe^2 + and Fe^3 + salt (e.g., chlorides, sulfates, and nitrates) aqueous solutions by addition of a base (e.g., NaOH) [20]. For this purpose, an aqueous solution of precursors (MnCl₂, FeCl₂, and FeCl₃) with a preset stoichiometry was prepared by an overhead stirrer (IKA Nanostar 7.5 digital). The temperature of the solution is then raised to 80°C. While the solution was stirred at 450 rpm, ammonia was gradually added to the solution for 20 minutes to adjust the pH and precipitate the dark brown manganese ferrite particles.

The resulting precipitate was collected by a magnet and washed several times by deionized water to get rid of impurities involved in the reaction before being dried at 60°C for 12 h. The product is then calcinated in an oven to remove water from its surface structure. Subsequently, the material was characterized by X-ray diffraction spectroscopy (XRD), scanning electron microscopy (SEM), and Fourier-transform infrared spectroscopy (FTIR).

2.2 Investigation of Pb^2 + adsorption by manganese ferrite

The adsorption of Pb^2 + by manganese ferrite was investigated by altering some technical parameters such as pH of the solution, adsorbent dosage, contact time, and concentration of adsorbate.(pH range: 3, 4, 5, 6, and 7 contact time range: 30, 60, 90, and 120 adsorbent range: 0.003, 0.005, 0.008, 0.010, 0.012, and 0.015 and adsorbate concentration of range: 10, 25, 50, and 75).

2.3 Desorption study

A desorption study was performed using Pb^2 + ion-loaded powder obtained using optimized values after the sorption experiment. For this purpose, 0.0001 kg of Pb^2 + ion-loaded binary oxide powder was added into six 0.050 L of Erlenmeyer flasks with approximately 0.03 L of distilled water. The pH of the solution was regulated to 2, 4, 6, 8, 10 and 12 by acid and base.

3 Results and discussion

3.1 XRD analysis

Figure 1 shows the XRD diffraction spectra of Fe₃O₄ and MnFe₂O₄ species. The sharpness of the peak on Fe₃O₄ and MnFe₂O₄ shows that they have crystalline structures. The particle size was determined using Equation 1 (Debye-Scherrer equation): $D = \frac{K λ}{β cos θ}$ (1) where K,λ, and θ is the constant value (0.9), the wavelength of X-ray (0.1550 nm), and the line of broadening (in radian), respectively. β is the Bragg angle (β= G –g), where G and g are the line width and instrument line broadening, respectively (in radians) [21]. Among the different percentages of Fe₃O₄ precipitated into MnO₂ lattice, the optimized particle size value is found to be 30.15 nm (Table 1). The effects of Fe₃O₄ loading were reported in Table 1. The results reveal that with the increase of loading of Fe₃O₄, particle size increases, and then it further decreases with the increase of the Fe₃O₄ percentage to 8. Also this paper applied values and investigated their effect on the nanoparticle structure is (Fig. 1). During this process, the temperature increases, the nanoparticle structure improves, and finally, the adsorption performance increases.

Fig. 1

XRD spectra of corresponding metal oxide nanoparticles.

Fig. 2

XRD spectra of corresponding metal oxide nanoparticles.

Table 1

Percentage composition and XRD results of the as-synthesized powders

Fe₃O₄ (%)	MnFe₂O₄ (%)	2θ (degree)	β (degree)	θ (radian)	D
100	0	25.314	0.3982	0.2209	20.05
96	4	24.812	0.2291	0.2165	34.92
92	8	25.010	0.2646	0.2182	30.15
88	12	25.170	0.2333	0.2196	34.15
0	100	36.755	0.6619	0.3207	12.08

3.2 SEM-EDX analysis

Figure 3 shows the SEM-EDX images of the synthesized manganese ferrite nanoparticles. The observed nanoparticle size is in the range of 30 to 50 nm. Based on Fig. 3, a spherical shape of approximately equal size is observed. The EDX spectrum reveals the appearance of Fe, Mn, C, and O atoms, such that the carbon atom is from the standard used during analysis. The purity of the powder is confirmed by the presentation of only the three elements without any others. The zero charge (pzc) values of MnFe₂O₄ nanoparticles prepared at pH 9.0, 9.5, 10.0, and 10.5 were 5.58, 6.13, 6.69, and 5.18, respectively.

Fig. 3

SEM-EDX spectra of corresponding metal oxide nanoparticles.

3.3 FT-IR analysis

To better identification of synthetic products and confirmation of the obtained results, FTIR was taken from synthetic samples in the range of 400 to 4000 cm^–1. Figure 4 shows the FT-IR spectrum of manganese ferrite nanoparticles. According to Fig. 4, the band that appeared at 690 cm^–1 is attributed to the Mn-O bending vibration mode. Generally, the broadband stretched from 560–580 cm^–1 is due to Mn-O-Mn and Mn-O bending vibration mode. The two bands that appeared at 542 (α –Fe₃O₄) and 460 (γ-Fe₃O₄) are assigned to bending vibrations of the Fe–O bond. The peak at 1455 in the FT-IR spectrum of Fig. 4 shows the presence of water and tensile bonds between water and oxygen. The spectra of both MnO₂ and MnO₂-Fe₃O₄ are almost similar, showing the good precipitation of Fe₃O₄ in the MnO₂ lattice. The strong and broad absorption band appeared around 3420 cm^–1 and the medium band at 1640 cm^–1 are related to the hydroxyl (OH) and water (H₂O) stretching vibrations absorbed on the adsorbent surface, respectively, which are very essential for the adsorption process [22].

Fig. 4

FT-IR spectrum of corresponding metal oxide nanoparticles.

3.4 Parameter optimization

The effects of various parameters such as pH of the solution, contact time, dose, and agitation speed for sorption of Pb²⁺ ion are investigated and corresponding results are shown in Fig. 5. During pH optimization, the greatest sorption was observed under the alkaline pH range (Fig. 5a). Due to the presence of H⁺, the acidic pH causes the more positive the surface of metal oxides, so that repulsive interaction exists between the iron oxides and Pb²⁺ ion, In alkaline pH value, the presence of OH^– causes the surface to be more negatively charged and hence, the interactions become attractive [23]. On dosage optimization (Fig. 5(b)), up to an optimum point (0.2 g), the sorption efficiency was found to be high, which is due to the availabilities of high sorption sites [24]. With further increasing adsorbent dosage, it does not significantly change, because the total number of the adsorbate becomes insignificant. From Fig. 5(c), as the speed of agitation enhances, diffusion of Pb²⁺ ions towards the adsorbent surface also elevates. After the optima (98 rpm) with further increasing agitation speed, the adsorbate starts to desorb from the surface. The effect of contact time on the uptake capacity of Pb^2 + ions by Mn-Fe₂O₄ nanoparticles can be seen in Fig. 5(d). In the first few minutes, the uptake of Pb^2 + ion is fast as initially more sites of adsorbent are available for adsorption of metals. As time passes the maximum number of sites is occupied by the ions and the adsorption process slows down. In the end, the equilibrium time (100 min) of adsorption occurs due to the saturation of the adsorbent.

Fig. 5

The effect of a) pH, b) adsorbent dose, c) agitation speed and d) contact time for Pb^2 + ion adsorption onto Mn-Fe₂O₄ nanoparticle.

3.5 Adsorption isotherms

Adsorption isotherm of single metal ions solutions

The adsorption equilibrium isotherm is important for describing how the adsorbate molecules distribute between the liquid and the solid phases when the adsorption process reaches an equilibrium state. The adsorption isotherms of single cation solutions of Pb^2 +, Cu^2 +, Cd^2 + and Ni^2 + on the MnFe₂O₄ are shown in Fig. 6. Equilibrium uptake increased with heavy metal concentrations. This is a result of the increase in the driving force from the concentration gradient. In the same conditions, if the concentrations of heavy metals in solutions are higher, the active sites of the MnFe₂O₄ are surrounded by many more heavy metal ions and the process of adsorption would be carried out sufficiently. The experimental data for single component solutions containing Pb^2 +, Cu^2 +, Cd^2 + and Ni^2 + ions could be approximated by Langmuir and Freundlich isotherm models.

Fig. 6

Diagram of Pb²⁺ ion adsorption by manganese ferrite nanoparticles: a) Langmuir isotherm and b) Freundlich isotherm.

Adsorption isotherms show the correlation between the concentration of adsorbent in the solution and the amount of adsorbed material at a constant temperature. Langmuir isotherm accounts for the surface coverage by balancing the relative rates of adsorption and desorption (dynamic equilibrium), while Freundlich isotherm gives an expression, which describes the surface heterogeneity and the exponential distribution of active sites as well as their energies [25]. The linear equations for Langmuir and Freundlich isotherms can be expressed as Equations 2 and 3, respectively [26, 27]: $\frac{c_{o}}{q_{e}} = \frac{1}{b q_{m}} + \frac{C_{e}}{q_{m}}$ (2) $log q_{e} = log k_{f} + \frac{1}{n} + log C_{e}$ (3) where C_o and C_e are the initial Pb²⁺ ion (adsorbate) and adsorbate equilibrium concentration in solution (mg/L), respectively, while q_e is the amount of adsorbate aggregated per gram of the adsorbent, q_max is the maximum uptake corresponding to the site saturation, k_f stands for the distribution coefficient and reveals the quantity of adsorbate adsorbed onto adsorbent for unit equilibrium concentration and $\frac{1}{n}$ is the ratio of adsorption and desorption rates. The value of n is between 1 and 10, showing the adsorption process becomes acceptable [28]. If the value of n is greater than one, a physical adsorption process occurs; while if it is less than one, the adsorption process is driven by chemical one. The extracted sorption constant values are presented in Table 2. The value of n obtained is found to be 1.558, showing the domination of the physical adsorption process as well as the presence of high binding affinity between adsorbate and absorbent. The sorption isothermal behavior based on concentration optimization results is shown in Fig. 6. Based on R² values, the Langmuir sorption isotherm model fits the sorption data relatively better than the Freundlich model due to the higher R² value (R² = 0. 8876).

Table 2

Langmuir and Freundlich parameters for lead adsorption on manganese ferrite nanoparticles

Parameter	Langmuir equation	Freundlich equation
b(l/mg)	0.376	–
q_m(mg/g)	192.3	–
n	–	1.558
k_f	–	45.62

3.6 Kinetics of adsorption

To survey time-dependent experimental data, the linear form of the pseudo-first and pseudo-second-order kinetic equations is defined as Equations 4 and 5, respectively. $log (q_{e} - q_{t}) = log q_{e} - \frac{k_{1} t}{2.303}$ (4) $\frac{t}{q_{1}} = \frac{1}{k_{2} q_{e}^{2}} + \frac{t}{q_{e}}$ (5) where q_e and q_t are the amounts of adsorbate adsorbed on the adsorbent at equilibrium and at various times, t (mg/g), respectively. k₁ is pseudo-first-order rate constant (1/min), and k₂ is pseudo-second-order rate constant (g/mg.min). The results of the kinetics of the adsorption study are shown in Fig. 7. The correlation coefficient (R²) in the pseudo-second-order model is higher than the pseudo-first-order model, which indicates that the pseudo-second-order model has more efficiency for fitting lead removal from aqueous solutions compared to the pseudo-first-order model. Moreover, it is possible to mention that the reaction is totally under the control of surface/adsorption-reaction [29].

Fig. 7

Plot of Pb²⁺ ion adsorption using manganese ferrite nanoparticles a) pseudo-first-order kinetics and b) pseudo-second-order kinetics.

3.7 Desorption efficiency

Desorption efficiency was calculated using the Equations 6: $% Desorption efficacy = \frac{desorbed}{adsorbed} \times 100$ (6) where desorbed denotes the amount of the lead ion that was removed from the loaded powder after desorption study and adsorbed is the value of Co–Ce for each recovery process. Figure 7 shows the reproducibility/desorption studies. Figure 8 shows based on the obtained results, with increasing pH, the amount of desorption of Pb²⁺ decreases, such that 83% of adsorbed lead ions were desorbed.

Fig. 8

Effect of pH on desorption of Pb²⁺ ion.

4 Conclusion

In this work, MnO₂-Fe₃O₄ oxide nanoparticles, including the different percentages of Fe₃O₄ was synthesized using the co-precipitation method. The precipitation of iron oxides on manganese oxides was confirmed by SEM-EDX, FTIR, XRD, analyses. The obtained approximate particle size for precipitated binary oxide was found to be 0.5394 nm. The effect of various factors such as (pH, adsorbent dose, and contact time) on the adsorption experiment was studied. It is found that Langmuir adsorption isotherm, as well as pseudo-first-order kinetics, fit the adsorption mechanism well. The obtained results showed the removal of heavy metals using manganese ferrite (MnFe₂O₄) nanoparticles and provide a practical solution for wastewater treatment.

References

and Wang

Removal of heavy metal ions from wastewaters: a review, J Environ Manage 92 (2011), 407–418.

Yadav

, Gupta

and Sharma

R.K.

Advances in water purification techniques, Elsevier (2019), 355–383.

Pinho

and Ladeiro

Phytotoxicity by lead as heavy metal focus on oxidative stress, J Bot 2012 (2012), 1–10.

Qasem

N.A.A.

, Mohammed

R.H.

and Lawal

D.U.

Removal of heavy metal ions from wastewater: a comprehensive and critical review, NPJ Clean Water 4 (2021), 1–15.

Vidu

, Matei

, Predescu

A.M.

, Alhalaili

, Pantilimon

, Tarcea

and Predescu

Removal of heavy metals from wastewaters: A challenge from current treatment methods to nanotechnology applications, Toxics 8 (2020), 101.

Wang

L.K.

, Vaccari

D.A.

, Li

and Shammas

N.K.

Chemical precipitation, in Physicochemical treatment processes, 1st ed: Springer (2005), 141–197.

Dąbrowski

Hubicki

, Podkościelny

and Robens

, Selective removal of the heavy metal ions from waters and industrial wastewaters by ion-exchange method, Chemosphere 56 (2004), 91–106.

Barakat

New trends in removing heavy metals from industrial wastewater, Arab J Chem 4 (2011), 361–377.

Kurniawan

T.A.

, Chan

G.Y.

, Lo

W.H.

and Babel

Physico–chemical treatment techniques for wastewater laden with heavy metals, Chem Eng Sci 118 (2006), 83–98.

10.

Kongsricharoern

and Polprasert

Electrochemical precipitation of chromium (Cr⁶⁺) from an electroplating wastewater, Water Sci Technol 31 (1995), 109.

11.

Martinez-Vargas

, Martínez

A.I.

, Hernández-Beteta

E.E.

, Mijangos-Ricardez

, Vázquez-Hipólito

, Patiño-Carachure

, Hernandez-Flores

and López-Luna

Arsenic adsorption on cobalt and manganese ferrite nanoparticles, J Mater Sci 52 (2017), 6205–6215.

12.

Chen

, Lu

, Xiao

, Gu

, Yao

, Xing

, Asiri

A.M.

, Alamry

K.A.

, Wang

and Wang

Enhanced removal of lead ions from aqueous solution by iron oxide nanomaterials with cobalt and nickel doping, J Clean Prod 211 (2019), 1250–1258.

13.

Cao

C.Y.

, Qu

, Wei

, Liu

and Song

W.G.

Superb adsorption capacity and mechanism of flowerlike magnesium oxide nanostructures for lead and cadmium ions, ACS Appl Mater Interfaces 4 (2012), 4283–4287.

14.

Zhang

, Zhai

, Li

, Xiao

, Song

, An

and Tian

Pb (II) removal of Fe3O4@ SiO2–NH2 core–shell nanomaterials prepared via a controllable sol–gel process, Chem Eng Sci 215 (2013), 461–471.

15.

Abebe

and Ananda Murthy

Synthesis and characterization of Ti-Fe oxide nanomaterials for lead removal, J Nanomater 2018 (2018), 1–11.

16.

Y.J.

, Chan

T.S.

, Tu

H.W.

, Wang

S.L.

, You

C.F.

and Chang

C.K.

Rapid and efficient removal/recovery of molybdenum onto ZnFe₂O₄ nanoparticles, Chemosphere 148 (2016), 452–458.

17.

Y.J.

, You

C.F.

, Chen

M.-H.

and Duan

Y.P.

Efficient removal/recovery of Pb onto environmentally friendly fabricated copper ferrite nanoparticles, J Taiwan Inst Chem Eng 71 (2017), 197–205.

18.

Y.J.

, You

C.F.

and Chang

C.K.

Conversion of waste Mn–Zn dry battery as efficient nano-adsorbents for hazardous metals removal, J Hazard Mater 258 (2013), 102–108.

19.

Islam

, Haque

, Kumar

, Hoq

, Hyder

and Hoque

S.M.

Manganese ferrite nanoparticles (MnFe₂O₄): Size dependence for hyperthermia and negative/positive contrast enhancement in MRI, Nanomaterials 10 (2020), 2297.

20.

, Mendoza-Garcia

, Li

and Sun

Organic phase syntheses of magnetic nanoparticles and their applications, Chem Rev 116 (2016), 10473–10512.

21.

Saravanan

, Aviles

, Gracia

, Mosquera

and Gupta

V.K.

Crystallinity and lowering band gap induced visible light photocatalytic activity of TiO₂/CS (Chitosan) nanocomposites, International Int J Biol Macromol 109 (2018), 1239–1245.

22.

Mahdavi

, Ahmad

M.B.

, Haron

M.J.

, Gharayebi

, Shameli

and Nadi

Fabrication and characterization of SiO₂/(3-aminopropyl) triethoxysilane-coated magnetite nanoparticles for lead (II) removal from aqueous solution, J Inorg Organomet Polym Mater 23 (2013), 599–607.

23.

Ofomaja

A.E.

, Unuabonah

E.I.

and Oladoja

N.A.

Competitive modeling for the biosorptive removal of copper and lead ions from aqueous solution by Mansonia wood sawdust, Bioresour Technol 101 (2010), 3844–3852.

24.

Tan

K.L.

and Hameed

B.H.

Insight into the adsorption kinetics models for the removal of contaminants from aqueous solutions, J Taiwan Inst Chem Eng 74 (2017), 25–48.

25.

Ayawei

, Ebelegi

A.N.

and Wankasi

Modelling and interpretation of adsorption isotherms, J Chem 2017 (2017), 1–23.

26.

Dąbrowski

Adsorption—from theory to practice, Adv Colloid Interface Sci 93 (2001), 135–224.

27.

Boparai

H.K.

, Joseph

and O’Carroll

D.M.

Kinetics and thermodynamics of cadmium ion removal by adsorption onto nano zerovalent iron particles, J Hazard Mater 186 (2011), 458–465.

28.

Horsfall

Jr and Spiff

A.I.

Effects of temperature on the sorption of Pb²⁺ and Cd²⁺ from aqueous solution by Caladium bicolor (Wild Cocoyam) biomass, Electron J Biotechnol 8 (2005), 43–50.

29.

Yang

, Masse

, Rouelle

, Aubry

, Li

, Roux

, Journaux

, Li

and Coradin

Magnetically recoverable iron oxide–hydroxyapatite nanocomposites for lead removal, Int J Environ Sci Technol 12 (2015), 1173–1182.

Chemical co-precipitation synthesis of manganese ferrite (MnFe 2 O 4 ) nanoparticles as a magnetic adsorbent of lead

Abstract

Keywords

1 Introduction

2 Experimental

2.1 Synthesis of manganese ferrite and its characterization

2.2 Investigation of Pb2 + adsorption by manganese ferrite

2.3 Desorption study

3 Results and discussion

3.1 XRD analysis

References

2.2 Investigation of Pb^2 + adsorption by manganese ferrite