One-Step Fabrication of Amino-Functionalized Fe₃O₄@SiO₂ Core-Shell Magnetic Nanoparticles as a Potential Novel Platform for Removal of Cadmium (II) from Aqueous Solution

Abstract

Fe₃O₄@SiO₂-NH₂ core-shell magnetic nanoparticles were developed by a rapid one-step precipitation route followed by reverse microemulsion and amine functionalization. In this study, an Fe₃O₄@SiO₂-NH₂ nanoparticle was used to evaluate its adsorption efficiency for the treatment of a synthetic solution of Cd(II) ion. The structural and physicochemical properties of Fe₃O₄@SiO₂-NH₂ nanoparticles were characterized by XRD, SEM-EDAX, TEM, FTIR and TGA. From the TEM analysis, the morphology of Fe₃O₄@SiO₂-NH₂ was found as 100–300 nm. In TGA, the first weight loss was noticed between 373 and 573 K, the second was between 673 and 773 K and the final weight loss took place above 773 K. Batch experimental tests, such as pH, dosage of Fe₃O₄@SiO₂-NH₂, Cd(II) ion concentration, temperature as well as interaction time, were conducted and evaluated. Experimental study data were used for the non-linear forms exhibited by isotherms and kinetics of the sorption procedure. The equilibrium adsorption observations were adequately combined with pseudo-first-order kinetics as well as Freundlich isotherm. Monolayer maximum adsorption capacity was found to be 40.02 mg/g, recorded at pH 6 with an interaction time of 30 min, temperature of 303 K and sorbent dose of 2.0 g/L. The thermodynamic study indicated that the adsorption process was an exothermic, spontaneous reaction (−∆o^o = −15.46–7.81 (kJ/mol)). The as-synthesized sorbent had excellent recyclability, and its adsorption efficiency was maintained after five cycles of reuse. The findings of the study exhibited the magnetic Fe₃O₄@SiO₂-NH₂-nanoparticle as an alternative effective adsorbent in eradicating Cd(II) ions from aqueous solution.

1. Introduction

Water scarcity is one of the world’s biggest problems with respect to the environment. With advancements in urbanization and industrialization, the water environment gets polluted by the direct liberation of toxic pollutants, which results in heavy metal contamination [1,2]. A huge amount of non-biodegradable heavy metals that have not been treated, for example, copper, cadmium, nickel, arsenic, mercury, lead ions and chromium, are discharged from the leather, textile, pigments, paper, glass, steel making, electroplating, battery, mining operations and pharmaceutical sectors [3,4]. These heavy metals are discharged directly into the soil and water streams. Additionally, they also cause serious health effects for aquatic systems and human beings. Heavy metals fall under the category of non-biodegradable metals and are consistent, accumulate in nature and are poisonous even in trace amounts [5]. Cadmium is one of the most toxic heavy metals, causing severe effects on health, such as nausea, abdominal pain, pancreatic cancer, muscle cramps, vomiting and kidney damage. Significant sources of cadmium are the burning of fossil fuels, manufacturing of phosphate fertilizers, metals, batteries, pigments and electroplating [6,7]. The permissible cadmium limit in consumable water is 0.003 mg/L, as per the Bureau of Indian Standards (BIS) [8].

The use of conventional methodologies, such as biological techniques, bioremediation, chemical precipitation and flocculation, have been widely used for removing these ions from wastewater. Conventional methods have impediments, such as tedious usage of power, equipment cost, secondary pollution and reusing issues relying on metals [9]. Innovative advancements, like magnetic separation techniques, are used to solve these problems. Advancements in magnetic materials exploit their potential in various areas, such as material synthesis, biology, environmental protection and textiles [10,11].

At present, magnetic nanoparticles (MNPs) have indicated a more significant role in complete toxic heavy metal removal from wastewater. MNPs have favorable circumstances, for example, huge evacuation limits, high reactivity, high surface area as well as fast kinetics [12,13,14]. In any case, the two most striking difficulties of the MNPs are that they are more susceptible towards oxidation processes as well as the process of agglomeration bringing about difficult reusing, lessening the reaction works and surface area constraints [15,16]. Considering these issues, novel multifunctional magnetic adsorbents with an expanded number of active sites and less auxiliary contamination and poisonous quality have come into the image. Mesoporous silica nanoparticles have a high surface area and are progressively suitable in surface change, favoring improved expulsion of heavy metal ions [17].

The primary issue related to mesoporous silica nanoparticles is the trouble in reusing them and their inclination to aggregation. The core-shell nanoparticles comprise magnetic nanoparticles as a center and external shell silica coating [18]. This empowers better recuperation and separation by the magnet. Nevertheless, the core-shell magnetic nanoparticles have been accounted for as biocatalysts. To expand the expulsion effectiveness of the mesoporous nanoparticles for metal evacuation, the surfaces of the nanoparticles were changed by chemical functional groups. In addition, the hydroxyl group present in the silica coating gives tremendous reaction sites for the amino functionalization of magnetic nanoparticles [19]. Meanwhile, amino groups can work like chelation sites. Hence, molecules containing amino groups can adsorb several metal-positive ions and are capable of being used as adsorbents. The use of superparamagnetic iron oxide nanoparticles (SPIONs) with surface modification possesses a high specific surface area [20]. SPIONs are extraordinarily affected by an external magnetic field. Adsorbents with magnetic properties can be recovered and reused many times, thereby being considered environmentally friendly substances [21,22].

In this work, amino-functionalized silica-coated core-shell magnetic nanoparticles (Fe₃O₄@SiO₂-NH₂) were employed as a novel efficient adsorbent for the removal of Cd(II) from simulated water. The quality of the prepared material was identified through its properties and experimental approach on the removal of Cd(II) ions. Various characterization methods, including scanning electron microscopy (SEM), X-ray diffraction (XRD), transmission electron microscopy (TEM), energy-dispersive X-ray analysis (EDX), thermogravimetric analysis (TGA) as well as Fourier transform infrared spectrophotometry (FTIR), were performed in evaluating the diffraction index, elemental composition and chemical composition of the nanocomposite. The adsorption experiments were directed in batch mode, concerning dependent quantities like Cd(II) ion concentration, pH, interaction time, a dose of Fe₃O₄@SiO₂-NH₂ nanoparticle and temperature, and their optimum values were assessed. The adsorption interaction behavior between the Fe₃O₄@SiO₂-NH₂ nanoparticles and Cd(II) ions was investigated by analyzing sorption kinetics and an isotherm model. Adsorption mechanisms and thermodynamics of Cd(II) ion adsorption onto Fe₃O₄@SiO₂-NH₂ were also investigated. Regeneration and reusability of the Fe₃O₄@SiO₂-NH₂ were also studied by adsorption regeneration cycles.

2. Experimental Study

2.1. Materials

Iron (III) chloride hexahydrate (FeCl₃·6H₂O), iron (II) sulfate heptahydrate (FeSO₄·7H₂O), oleic acid (OA), ammonium hydroxide (NH₄OH, 28%), tetra ethoxy silane (TEOS), 3-aminopropyl trimethoxysilane (APS), Triton X-100, cyclohexane, ethanol and n-hexanol were procured as analytical grade reagents from Loba Chemie India.

2.2. Preparation of Synthetic Cd(II) Ion Solution

Stock cadmium ion (100 mg/L) solution was made by mixing the calculated quantity of cadmium sulfate octahydrate (3CdSO₄·8H₂O) (Merck, India) using DI water. The required test solutions (25–150 mg/L) were formed by using stock cadmium ion solution. The pH of the initial solution was modified with 0.1 M NaOH or 0.1 M HCl solutions utilizing a pH meter device (Elico Model) before mixing with adsorbent. Concentration readings of Cd(II) ions were recorded utilizing an atomic absorption spectrometer (AAS, SL176 Model, Elico Limited, Chennai, India). The deionized (DI) water was used for all purposes.

2.3. Preparation of Fe₃O₄@SiO₂-NH₂ Nanoparticles

2.3.1. Synthesis of Oleic Acid Stabilized Fe₃O₄ Nanoparticles

Oleic acid stabilized Fe₃O₄ nanoparticles were synthesized by the co-precipitation method, which depends upon the concentration of oleic acid. Approximately 11.6 g of FeCl₃·6H₂O and 4.3 g of FeSO₄·7H₂O, dispersed with 400 mL DI water in a nitrogen atmosphere with vigorous agitation at 333 K. After that, the 15 mL of 25% ammonia solution was added, followed by quick dropwise mixing of the 9 mL oleic acid. The resultant solution was centrifuged for 10 min at 6000 rpm to separate the black precipitates of Fe₃O₄ nanoparticles [23]. The final solid was flushed several times using DI water as well as anhydrous ethanol to eliminate the excess oleic acid.

2.3.2. Preparation of Core-Shell Fe₃O₄@SiO₂ Nanoparticles

The obtained oleic acid stabilized Fe₃O₄ nanoparticles were then modified with silica by following steps. First, the mixture of 500 μL of oleic acid, 50 mL of cyclohexane, 8 mL of n-hexanol, 10 mL of TritonX-100, stabilized magnetic nanoparticles stock solution were added with 500 μL of TEOS in a flask, and the resulting solution agitated vigorously. After 30 min of stirring, homogeneous microemulsions were formed. The resultant mixture was added with 150 μL aqueous ammonia to initiate the polymerization reaction [24]. After 24 h of continuous stirring, the silica growth was completed. The black precipitate Fe₃O₄@SiO₂ nanoparticles were collected by the magnetic separation technique. Finally, the obtained Fe₃O₄@SiO₂ nanoparticles were flushed many times using ethanol, as well as water to remove the excess solvents.

2.3.3. Functionalization of Fe₃O₄@SiO₂ Nanoparticles

To achieve amino-functionalization of silica-coated magnetic nanoparticles (i.e., Fe₃O₄@SiO₂-NH₂), 2 mL of 3-aminopropyl trimethoxysilane (APS) were added to the 95 mL ethanol solution. Then, the obtained dispersion was stirred for 3 h at 353 K. The amino silane-functionalized magnetic nanoparticles were gathered by a bar magnet. The resultant nanoparticles were washed many times with DI water [25]. Finally, the obtained material was designated as Fe₃O₄@SiO₂-NH₂ nanoparticles. The nanoparticles were dried using vacuum on 353 K for approximately 12 h. The scheme of preparation of Fe₃O₄@SiO₂-NH₂ nanoparticles is shown in Figure 1.

2.4. Characterization of Fe₃O₄@SiO₂-NH₂ Nanoparticles

The morphological and size determination for Fe₃O₄@SiO₂-NH₂ nanoparticles were analyzed utilizing scanning electron microscope (SEM-EDAX, Hitachi S-3400 Model, Tokyo, Japan) and HR-transmission electron microscope (JEOL JEM2010, HR-TEM, at 200 kV) analyses. The specimens were made ready by dehydrating the samples and placing them on 300 mesh copper grids coated with carbon. XRD investigation was conducted to understand the chemical composition of Fe₃O₄@SiO₂-NH₂ with an XRD analysis sampler, Rikagu laboratory equipment, India, operating voltage of 40 kV, current recorded value 26 MA Cu-Kα2 radiations. FTIR analysis was carried out using amine-functionalized silica-coated magnetic nanoparticles (0.01 g) dehydrated through the night at 333 K, blended with 0.1 g of KBr. The obtained sample was used to check the moieties by FTIR spectra (Shimadzu 8201PC, Kyoto, Japan). In order to investigate the magnetic properties of synthesized Fe₃O₄@SiO₂-NH₂ nanoparticles, particles were dispersed into distilled water in a conical flask. A permanent magnet was kept next to the flask to ensure magnetic separation. In addition, magnetic measurements were performed on the desired conditions of temperature utilizing a vibrating magnetometer sample (VSM, 735VSM, Modl 7410; lake Shore, Westerville, OH, USA) with a peak magnetic field of 31 kOe. Thermal stability was performed to interpret the weight loss strategy utilizing a thermogravimetric analyzer (model Q600 SDT simultaneous DSC–TGA) and heating rate of 283 K per minute under N₂ gas, carried out at 303–1073 K.

2.5. Batch Adsorption Study

Adsorption behavior exhibited by attractive Fe₃O₄@SiO₂-NH₂ nanoparticles toward Cd(II) ions was explored by batch studies. Under controlled conditions, the adsorption nature was studied at different parameters, e.g., initial metal ion concentrations (25–150 mg/L), adsorbent quantity (0.5–3.0 g/L), temperature (303–333 K), pH (2.0–8.0) for the adsorption of Cd(II). Afterward, Fe₃O₄@SiO₂-NH₂ was gathered using a permanent bar magnet. The final Cd(II) concentrations were calculated using an Atomic Absorption Spectrometer device (AAS, SL176 Model, Elico Limited, Chennai, India). Cd(II) removal %, as well as sorption capacity, were calculated with the help of the Equation below:

$$\% \mathrm{Removal}=\left(\frac{{\mathrm{C}}_{\mathrm{o}}-{\mathrm{C}}_{\mathrm{e}}}{{\mathrm{C}}_{\mathrm{o}}}\right)\times 100$$

(1)

Sorption capacity:

$${\mathrm{q}}_{\mathrm{e}}=\frac{{(\mathrm{C}}_{\mathrm{o}}-{\mathrm{C}}_{\mathrm{e}}) \mathrm{V}}{\mathrm{m}}$$

(2)

C_o (mg/L) and C_e (mg/L) denote initial and equilibrium concentrations for the cadmium ion solution, respectively. V denotes the volume of the cadmium ion solution (L), m denotes the mass of the Fe₃O₄@SiO₂-NH₂ nanoparticles (gram).

2.6. Thermodynamic Study

The thermodynamic parameters, for example, the enthalpy change (∆H°), Gibbs free energy change (ΔG°) and standard entropy change (∆S°) were estimated from the following equations (Equations (3)–(5))

The thermodynamic experiment was conducted by reckoning 0.2 g of Fe₃O₄@SiO₂-NH₂ nanoparticles with a series of conical flasks consisting of 100 mL cadmium ion solution, accompanied by various initial concentrations ranging from 25 to 150 mg/L, and temperatures ranging 303–333 K. Fe₃O₄@SiO₂-NH₂ nanoparticles were eliminated through solutions utilizing a bar magnet. Final Cd(II) ion concentration was calculated using AAS.

$${\mathrm{K}}_{\mathrm{c}}=\frac{{\mathrm{C}}_{\mathrm{Ae}}}{{\mathrm{C}}_{\mathrm{e}}}$$

(3)

$${\mathsf{\Delta }\mathrm{G}}^{\mathrm{o}}=-{\mathrm{RTlnK}}_{\mathrm{c}}$$

(4)

$$\log \left(\frac{{\mathrm{C}}_{\mathrm{Ae}}}{{\mathrm{C}}_{\mathrm{e}}}\right)=\frac{{\mathsf{\Delta }\mathrm{S}}^{\mathrm{o}}}{2.303 \mathrm{R}}-\frac{{\mathsf{\Delta }\mathrm{H}}^{\mathrm{o}}}{2.303 \mathrm{RT}}$$

(5)

where C_Ae denotes the amount of cadmium ions attached to the Fe₃O₄@SiO₂-NH₂ (mg/L), K_c denotes equilibrium constant, C_e denotes equilibrium cadmium ion concentration (mg/L), T denotes temperature (K) and R denotes universal gas constant (8.314 J/mol/K).

2.7. Isotherm Modelling

The Langmuir equation is as follows [26]:

$${\mathrm{q}}_{\mathrm{e}}=\frac{{\mathrm{q}}_{\mathrm{m}}{\mathrm{K}}_{\mathrm{L}}{\mathrm{C}}_{\mathrm{e}}}{1+{\mathrm{K}}_{\mathrm{L}}{\mathrm{C}}_{\mathrm{e}}}$$

(6)

The equilibrium parameter is:

$${\mathrm{R}}_{\mathrm{L}}=\frac{1}{1+{\mathrm{K}}_{\mathrm{L}}{\mathrm{C}}_{\mathrm{o}}}$$

(7)

The Freundlich isotherm model is presented as follows [27]:

$${\mathrm{q}}_{\mathrm{e}}={\mathrm{K}}_{\mathrm{F}}{\mathrm{C}}_{\mathrm{e}}^{\raisebox{1ex}{$1$}\!\left/ \!\raisebox{-1ex}{$\mathrm{n}$}\right.}$$

(8)

Temkin adsorption isotherm model is given below [28]:

$${\mathrm{q}}_{\mathrm{e}}=\mathrm{B} \ln (\mathrm{A} {\mathrm{C}}_{\mathrm{e}})$$

(9)

where q_e (mg/g) denotes adsorption capacity for Cd(II) at equilibrium state, K_L is the sorption Langmuir constant (L/mg), q_m denotes maximum cadmium ion adsorption capacity (mg/g), K_F is the Freundlich sorption constant ((mg/g)(L/mg)^(1/n)), n denotes the intensity of adsorption constant (g/L), B = RT/b is the heat of adsorption constant, b denotes heat of adsorption (kJ/mol), A is constant of Temkin isotherm (L/mg).

2.8. Kinetic Modeling

The sorption kinetics confirmation is significant for assessing the efficiency and system of the sorption. The kinetics experiments were conducted at various concentrations (25 to 150 mg/L) with 0.2 g of Fe₃O₄@SiO₂-NH₂ nanoparticles at different time periods (10 to 60 min) on an incubation shaker. The Fe₃O₄@SiO₂-NH₂ nanoparticles were separated by a bar magnet, and using the AAS, the residual amount of Cd(II) was calculated. The quantity of Cd(II) ions adsorbed onto Fe₃O₄@SiO₂-NH₂ nanoparticles at different time intervals q_t (mg/g) was calculated by:

$${\mathrm{q}}_{\mathrm{t}}=\frac{\left({\mathrm{C}}_{\mathrm{o}}-{\mathrm{C}}_{\mathrm{t}}\right)}{\mathrm{m}}\mathrm{V}$$

(10)

where C_t denotes concentration of cadmium ions at a given time t (mg/L), q_t is the amount of Cd(II) ion adsorbed/g of adsorbent at any time t.

Collected kinetic data were analyzed by the pseudo-first-order [29], pseudo-second-order [30] as well as the Elovich kinetic [31] models in explaining sorption processes.

Pseudo-first order kinetic model:

$${\mathrm{q}}_{\mathrm{t}}={\mathrm{q}}_{\mathrm{e}}\left[1-\exp \left(-{\mathrm{K}}_1\mathrm{t}\right)\right]$$

(11)

Pseudo-second order kinetic model:

$${\mathrm{q}}_{\mathrm{t}}=\frac{{\mathrm{q}}_{\mathrm{e}}^2{\mathrm{k}}_2\mathrm{t}}{1+{\mathrm{q}}_{\mathrm{e}}{\mathrm{k}}_2\mathrm{t}}$$

(12)

Elovich kinetic model:

$${\mathrm{q}}_{\mathrm{t}}=\left(1+{\mathsf{\beta }}_{\mathrm{E}}\right)\ln \left(1+{\mathsf{\alpha }}_{\mathrm{E}}{\mathsf{\beta }}_{\mathrm{E}}\mathrm{t}\right)$$

(13)

where q_e and q_t are the quantity of adsorbed Cd(II) ions onto Fe₃O₄@SiO₂-NH₂ nanoparticles (mg/g) at equilibrium and at a given time, t denotes time (min), k₁ denotes pseudo-first-order sorption constant (min⁻¹), k₂ denotes pseudo-second-order sorption constant (g/mg min) as well as k₂·q_e² = h denotes initial sorption rate (mg/g min). α_E denotes the initial sorption rate mg/(g min) and β_E(g/mg) is the desorption constant.

2.9. Adsorption Mechanism Validation

To describe sorption mechanisms, intraparticle diffusion [32], Boyd kinetic [33] and shrinking core models [34] were used, as shown below.

Weber and Morris intraparticle diffusion model:

$${\mathrm{q}}_{\mathrm{t}}={\mathrm{k}}_{\mathrm{p}}{\mathrm{t}}^{\raisebox{1ex}{$1$}\!\left/ \!\raisebox{-1ex}{$2$}\right.}+C$$

(14)

The Boyd kinetic model:

$$-0.4977-\ln \left(1-\frac{{\mathrm{q}}_{\mathrm{t}}}{{\mathrm{q}}_{\mathrm{e}}}\right)=\mathrm{Bt}$$

(15)

The effective diffusivity, D_i (m²/s), was calculated by the following equation:

$$\mathrm{B}=\frac{{\mathsf{\pi }}^2 {\mathrm{D}}_{\mathrm{i}}}{{\mathrm{r}}^2}$$

(16)

k_p denotes the intraparticle diffusion constant (mg/g min^0.5), r denotes Fe₃O₄@SiO₂-NH₂ nanoparticles radius and C denotes boundary layer thickness.

For film diffusion control:

$$\mathrm{X}=\frac{3\mathrm{D}}{\mathsf{\delta } \mathrm{r} \mathrm{C}}\mathsf{\alpha }$$

(17)

Considering particle diffusion control:

$$\mathrm{F}\left(\mathrm{X}\right)=1-3(1-{\mathrm{X})}^{\frac{2}{3}}+2(1-\mathrm{X})=\frac{6\mathrm{D}}{{\mathrm{r}}^2{\mathrm{C}}^{\mathrm{o}}}\mathsf{\alpha }$$

(18)

From the slope of the graph between F(X) vs. α, the diffusivity values are given by:

$$\mathrm{D}=(\mathrm{S}\mathrm{l}\mathrm{o}\mathrm{p}\mathrm{e})\frac{{\mathrm{C}}^{\mathrm{o}}{\mathrm{r}}^2}{6}$$

(19)

where:

$$\mathrm{X} \mathrm{is} \mathrm{the} \mathrm{extent} \mathrm{of} \mathrm{reaction} = \frac{{(\mathrm{C}}_{\mathrm{o}}-\mathrm{C})}{{(\mathrm{C}}_{\mathrm{o}}-{\mathrm{C}}_{\mathrm{eq}})}$$

(20)

$$\mathsf{\alpha }={\displaystyle \underset{0}{\overset{\mathrm{t}}{{\displaystyle \int }}}\mathrm{C} \mathrm{d}\mathrm{t}}$$

(21)

C_o denotes initial cadmium ions (mg/L), C denotes final cadmium ions (mg/L), r denotes Fe₃O₄@SiO₂-NH₂ nanoparticles (m) radius and C^o denotes average cadmium ions site density of the Fe₃O₄@SiO₂-NH₂ nanoparticles (mg/L).

2.10. Reusability/Regeneration Studies

Examining the effective regeneration and possible reuse of adsorbents are two vital factors in industrial operation. An ideal adsorbent has greater potential for cost reduction, practical reusability and excellent adsorbent storage ability. Fe₃O₄@SiO₂-NH₂ nanoparticles possess a lower capacity of adsorption at high pH values; acid treatment is a possible method to achieve effective regeneration of Fe₃O₄@SiO₂-NH₂ nanoparticles [35]. Hence, the sorbent Fe₃O₄@SiO₂-NH₂-adsorbed Cd(II) material was treated with 0.1 M Hydrochloric acid solution for two hours and cleaned using deionized water till the pH was near 7. Later, the nano sorbent was dehydrated using vacuum on 323 K. Regenerated sorbent was utilized for further Cd(II) sorption cycles.

3. Results and Discussion

3.1. Characterization Study

3.1.1. XRD Pattern of Fe₃O₄@SiO₂-NH₂ Nanoparticles

Figure 2a exhibits the X-ray diffraction (XRD) pattern of amino-functionalized Fe₃O₄@SiO₂ nanoparticles. The XRD pattern shows intense diffraction patterns at 2θ = 30.56°, 35.88°, 43.94°, 53.72°, 57.33° and 62.13°, which correspond to the miller indices of the reflecting planes for (220), (311), (400), (422), (511) and (440), respectively. These observed reflections as series go well along with the inverse spinel structure exhibited by Fe₃O₄. The acquired results are well-matched to standard JCPDS File No. 65–3107 [36,37]. The diffraction patterns at around 2θ = 20° correspond to the amorphous silica shell, which covers the core Fe₃O₄ for strengthening the outer structure [38]. From the previous studies [39], it was reported that the 3-aminopropyltrimethoxysilane (APTS) functionalized Fe₃O₄@SiO₂ nanoparticles exhibit a similar spinel structure with the face centered cubic (FCC). Various researchers showed that the (3-aminopropyl)-triethoxysilane (APTES) functionalized Fe₃O₄@SiO₂ nanoparticles exhibit a similar spinel ferrite crystal structure [40,41]. The synthesized amino-functionalized Fe₃O₄@SiO₂ nanoparticles show spinel ferrite patterns [42].

3.1.2. Surface Morphology of Fe₃O₄@SiO₂-NH₂ Nanoparticles

Figure 2b–d depicts the SEM image, EDAX pattern and TEM image of amino-functionalized Fe₃O₄@SiO₂ nanoparticles. The prepared nanoparticle morphological changes were examined utilizing SEM analysis. Meanwhile, peaks corresponding to elements were studied using the EDAX analysis. The in-depth morphological study (TEM) images suggest that the spherical shape of the particles and the Fe₃O₄ was sequentially coated with SiO₂, which confirms the formation of the core-shell structure of amino-functionalized Fe₃O₄@SiO₂ nanoparticles. After functionalizing through the grafting of APS on the surface of Fe₃O₄/silica, core-shell particle shape was preserved [43]. The SiO₂ layer could provide the Fe₃O₄ nanoparticles with a good acid resistance property [44].

3.1.3. FTIR Analysis of Fe₃O₄@SiO₂-NH₂ Nanoparticles

FT-IR spectra were documented in order to characterize the fabrication process and to validate the modification of Fe₃O₄@SiO₂ nanoparticles by the amine group. From Figure 3a, the absorption band at 538.23 cm⁻¹ corresponds to magnetite’s Fe-O vibration [45], and the absence of typical carboxyl peaks in the spectrum corresponds to oleic acid stabilized nanoparticles, obtained by the interaction between carboxyl groups and nanoparticles, which enhance the structural strength of nanoparticles. The bands at 810.25 cm⁻¹ and 1031.81 cm⁻¹ seemed familiar to symmetric stretching vibration, as well as the deformation vibrations, which confirm the silica coating on Fe₃O₄ nanoparticles [46]. The characteristic peak at 965.15 cm⁻¹ corresponds to the silanol group (Si-OH), which confirm the amino-functionalized Fe₃O₄@SiO₂ nanoparticles [47]. The absorption peaks at 3286.55 cm⁻¹, 1632.46 cm⁻¹ and 695.26 cm⁻¹ were attributed to amino group stretching and bending vibration [48]. Absorption peaks at 2919.23 cm⁻¹ correspond to the -CH₂- vibrations in amino-functionalized Fe₃O₄@SiO₂ nanoparticles. This analysis helped to identify the fabrication of the silica shell as an outer layer on the Fe₃O₄ nanoparticles.

3.1.4. Magnetism and Dispersibility Nature of Fe₃O₄@SiO₂-NH₂ Nanoparticles

The magnetization curve of the amino-functionalized Fe₃O₄@SiO₂-NH₂ nanoparticle (VSM) results is shown in Figure 3b. Magnetic properties exhibited by the synthesized nanoparticles were represented by utilizing a magnetization curve. It was observed that the amino-functionalized Fe₃O₄@SiO₂-NH₂ nanoparticles exhibited a superparamagnetic nature [49]. The reductions in the saturation value mainly correspond to the isolation effect of the outer layer of silica [50]. Thus, the obtained amino-functionalized Fe₃O₄@SiO₂-NH₂ nanoparticles led to the simultaneous decrease of coercivity [51]. Immediately after applying the magnet, the gathering of magnetic particles took place, as shown in Figure 3b.

3.1.5. Thermogravimetric and DSC Analysis of Fe₃O₄@SiO₂-NH₂ Nanoparticles

Thermogravimetric analysis (TGA) is a method of thermal study where variations in chemical as well as physical properties in materials are studied with the dependence of a constant rise of temperature or, as a function of time, having non-varying temperature and mass loss. TGA gives data on physical phenomena, like the second-order phase transitions, sublimation, vaporization, adsorption, desorption and absorption [49]. Thermo-gravimetric analysis (TGA), as well as differential scanning calorimetry (DSC) analysis, were mainly performed for investigation of the thermal characteristics of the prepared samples. Figure 3c shows the TGA-DSC curves of amino-functionalized Fe₃O₄@SiO₂-NH₂ nanoparticles. The prepared nanoparticles show an exothermic peak from the DSC pattern at around 503 K, 603 K, 773 K and 953 K, respectively [52]. From the TGA pattern, the first weight loss was noticed between 373 K as well as 573 K, attributed to evaporation by water molecules that were adsorbed [53]. Second weight loss was noticed between 573 K and 773 K due to the dehydration of hydroxyl groups and decomposition of the remaining organic constituent [54]. The final weight loss took place > 773 K.

3.2. Batch Adsorption Study

3.2.1. Impact of pH on Adsorption and Point of Zero Charge (pH_pzc)

The pH of the cadmium ion solution is the vital parameter to be considered in the case of cadmium ion sorption onto Fe₃O₄@SiO₂-NH₂ nanoparticles. The adsorption test was conducted in the Erlenmeyer flasks in a series with pH values ranging from 2 to 8. The pH of solution varied with the addition of 0.01 M hydrochloric acid, as well as sodium hydroxide. Sorption temperature (303 K) and the interaction time (30 min) were kept to achieve the adsorption equilibrium [55]. The adsorbents were recovered from the medium using a magnet. The supernatant was subjected to AAS for analyzing the residual concentration of Cd(II). The pH effect on the sorption method is depicted in Figure 4a. If the pH is low, the removal percentage and q_e were found to be low; this is due to the increase in the number of hydronium ions (H⁺) present in the medium. The amino groups on Fe₃O₄@SiO₂-NH₂ are prone to protonation and deprotonation [56].

$$\mathrm{MNP}-\mathrm{S}-{\mathrm{NH}}_2+{\mathrm{H}}^{+}=\mathrm{MNP}-\mathrm{S}-{\mathrm{NH}}_3^{+}$$

(22)

$$\mathrm{MNP}-\mathrm{S}-{\mathrm{NH}}_2+\mathrm{Cd}\left(\mathrm{II}\right)=\mathrm{MNP}-\mathrm{S}-{\mathrm{NH}}_2\mathrm{Cd}\left(\mathrm{II}\right)$$

(23)

The protonation and deprotonation steps related to MNP-S-NH₂ in the medium are depicted by Equation (22). At the same time, Equation (23) shows the complex product formation that occurs with the help of Cd(II) ions using amino groups, appearing in the outer layer of MNP-S-NH₂.

Uptake capacity seen for the pH 7.0–9.0 range tends to be reduced because of the formation of (Cd(OH)⁺) species. However, if the pH of the sorbate solution turns out to be greater than pH_pzc (point of zero charge), the anions on the sorbent layer tend to be increased with the cation adsorption capacity. The point of zero charge of the Fe₃O₄@SiO₂-NH₂ sorbent was found to be greater than 6.0, which resulted in cadmium ion precipitation as Cd(OH)⁺). Therefore, pH 6.0 was a substantial pH for the Fe₃O₄@SiO₂-NH₂ -cadmium adsorption system.

3.2.2. Impact of Dosage on Adsorption

The achieved optimum condition for the amount of Fe₃O₄@SiO₂-NH₂ adsorbent in removing metal ions is shown in Figure 4b. The amount of Fe₃O₄@SiO₂-NH₂ nanoparticles is pivotal to maximizing the adsorption efficiency. In this research, a freshly prepared Fe₃O₄@SiO₂-NH₂ range, starting with 0.5 g/L till 3 g/L with a Cd(II) concentration of 50 mg/L, was carried out. The information noted through experiments is represented in Figure 4b. As there was a rise in the sorbent dosage of Fe₃O₄@SiO₂-NH₂ nanoparticles, the percentage of removal increased, but the q_e decreased. From this trend, it can be clearly understood that a rise in the number of active sites favors sorption [57]. From the results depicted in Figure 4b, it was observed that 2.0 g/L seems to give ample interchangeable binding sites for the removal of cadmium ions. Beyond this, the removal of cadmium ions was not changed appreciably. Therefore, in the following experiments, the sorbent dosage of Fe₃O₄@SiO₂-NH₂ nanoparticles was fixed at 2 g/L.

3.2.3. Impact of the Amount of Cadmium Ions

Adsorption of Cd(II) onto Fe₃O₄@SiO₂-NH₂ nanoparticles was also performed with different initial Cd(II) ion concentrations (25 mg/L till 150 mg/L) (Figure 4c). Figure 4c shows that equilibrium adsorption capacity q_e rose when the initial cadmium ion concentration increased. However, the removal % was reduced. q_e values were raised, starting with 12.473 till 65.686 mg/g, whereas removal % reduced in the order of 99.785 to 87.582%, corresponding to initial cadmium ion concentrations ranging from 25 mg/L to 150 mg/L. Lower metal ion concentrations give a vital push force for the competing mass transfer resistances [58]. This adsorption behavior showed the surface saturation to be relying upon the initial cadmium ion concentration. The ratio of surface-active sites to the cadmium ions in the medium may be more for lower cadmium ion concentrations. Hence, all the cadmium ions may influence the Fe₃O₄@SiO₂-NH₂ sorbent, and the cadmium ions were expelled from the aqueous medium.

3.2.4. Impact of Interaction Time

Figure 4d exhibits the influence of interaction time seen on Cd(II) ion adsorption. Figure 4d found that removal efficiency, as well as equilibrium adsorption capacity, increased rapidly and then reached a saturated state (approximately 30 min). Nevertheless, increasing the contact time did not show any drastic changes in percentage removal. It was observed that the removal percentage and qe values were higher, which resulted from the high availability of binding sites in the layer of Fe₃O₄@SiO₂-NH₂ nanoparticles. Therefore, the contact time of 30 min was chosen to be the desired value in the following experiments.

However, at a later stage, the rate of removal was minimum, as determined by the intraparticle diffusion of the Fe₃O₄@SiO₂-NH₂ nanoparticles. It was clearly evident that the double stage of the adsorption mechanism took place. The first stage was quantitatively predominant, and the second stage was insignificant.

3.2.5. Impact of Temperature

Temperature has a prominent influence on metal removal by sorption. Similarly, the influence of temperature on the sorption mechanism of cadmium ions by Fe₃O₄@SiO₂-NH₂ nanoparticles was studied in the range of 303 K–333 K and values are portrayed in Figure 4e. Figure 4e shows that the percentage removal lowers with rising temperature. These observations conclude that the cadmium ion adsorption by Fe₃O₄@SiO₂-NH₂ nanoparticles was exothermic. At high temperatures, the molecules in the excited state weaken the bonds between the cadmium ions and the active site for the sorbent. This may be the reason for the negative correlation between cadmium ions and temperature. The maximum adsorption was experienced at 303 K for the Fe₃O₄@SiO₂-NH₂-cadmium system.

3.2.6. Thermodynamic Study

The thermodynamic parameters for the Fe₃O₄@SiO₂-NH₂ nanoparticle-cadmium system were calculated from log K_c vs. 1/T plots (Figure 4f), and the findings are listed in

Table 1. Thermodynamic parameter study for the adsorption of Cd(II) ion onto Fe₃O₄@SiO₂-NH₂ nanoparticles.

Concentration of Cd(II) ion (mg/L)	∆Ho (kJ/mol)	∆So (J/mol K)	∆Go (kJ/mol)
			303 K	313 K	323 K	333 K
25	−134.17	−390.90	−15.467	−9.630	−8.664	−7.810
50	−30.912	−69.115	−8.999	−7.935	−7.320	−6.529
75	−18.631	−35.907	−6.995	−6.682	−6.048	−5.548
100	−9.780	−12.654	−5.948	−5.752	−5.018	−4.755
150	−10.011	−16.159	−4.920	−4.647	−4.296	−3.941

. From Table 1, the negative values of ∆H^o confirm that the adsorption procedure leads to the heat releasing condition, which corresponds to the exothermic nature of the Fe₃O₄@SiO₂-NH₂ nanoparticle-cadmium system. This is possible due to the temperature increase; the cadmium ions move firstly to the previous layer, which creates a tendency of desorbing cadmium ions from the Fe₃O₄@SiO₂-NH₂ nanoparticle surface.

3.3. Modeling Study

3.3.1. Adsorption Isotherm Study

Depicted by Figure 4 and

Table 2. Adsorption isotherm parameters for the adsorption of Cd(II) ion onto Fe₃O₄@SiO₂-NH₂ nanoparticles.

Adsorption Isotherm Model	Parameters	Values	R2
Langmuir	qm (mg/g)	40.02	0.8832
	KL (L/mg)	0.834
	SSE	109.2
	RMSE	5.97
Freundlich	KF ((mg/g)(L/mg)(1/n)))	19.67	0.9451
	n (g/L)	3.091
	SSE	23.56
	RMSE	2.987
Temkin	A	112	0.8045
	B	1.175
	b (kJ/mol)	1.234
	SSE	117.2
	RMSE	5.393

, the Freundlich adsorption isotherm model can well be portrayed by the adsorption equilibrium data. Additionally, it fits more, along with the isotherm data, having high R² in comparison to the Langmuir and Temkin models. This pointed out that nonideal adsorption occurred with a heterogeneous surface of the Fe₃O₄@SiO₂-NH₂ nanoparticle adsorbent, as well as multilayer cadmium adsorption [56]. The Langmuir maximum monolayer adsorption capacity (q_max) of the Fe₃O₄@SiO₂-NH₂ for cadmium ions was calculated to be 40.02 mg/g.

Error functions, such as the root mean square error (RMSE), Chi-square and R² error, were calculated for the optimization of process parameters. The smallest value of the error functions was taken as the best fit model.

$$\mathrm{RSME}=\sqrt{\frac{1}{\mathrm{n}-1}}{\displaystyle \sum }_{\mathrm{i}=1}^{\mathrm{n}}\left({\mathrm{q}}_{\mathrm{e}}-{\mathrm{predictedq}}_{\mathrm{e}}\right)$$

(24)

$$\mathrm{Chi} \mathrm{Square}={ \mathsf{\chi }}^2={\displaystyle \sum }_{\mathrm{i}=1}^{\mathrm{n}}\frac{{({\mathrm{q}}_{\mathrm{e}}-{\mathrm{Predicted} \mathrm{q}}_{\mathrm{e}})}^2}{{\mathrm{Predicted} \mathrm{q}}_{\mathrm{e}}}$$

(25)

$${\mathrm{R}}^2 \mathrm{Error}=\frac{\mathrm{SSR}}{\mathrm{SST}}=\frac{\mathrm{Sum} \mathrm{of} \mathrm{Squares} \mathrm{Regression}}{\mathrm{Sum} \mathrm{of} \mathrm{Squares} \mathrm{Total}}$$

(26)

In these equations, n represent the number of observations. In order to identify the best-fit adsorption model, non-linear models were considered [59]. Although the degree of determination values were close to 0.85 (Table 2) in isotherm models, the error functions for the three models varied considerably.

Table 3. Comparison of Cd(II) ion adsorption capacities of Fe₃O₄@SiO₂-NH₂ nanoparticles on different adsorbents.

Adsorbents	qm (mg/g)	References
Magnetic chitosan	48	[58]
Fe3O4@SiO2-NH2 nanoparticles	40.02	This work
Amino-functionalized MNPs	40.10	[59]
Magnetic nanoadsorbents	36.00	[53]
HA-Fe-PILC	31.34	[54]
Magnetic composites-carbon nanotubes	31.25	[55]
Iron oxide coated sewage sludge	42.40	[56]
Manganese oxide-carbon nanotube	26.24	[57]
Sugar beet pulp	24.3	[58]
Fe3O4@APS@AA-co-CA MNPs	29.6	[59]
oxMWCNT6h	13.5	[60]
Granular sludge-clay	1.53	[61]

depicts the maximum q_m of Fe₃O₄@SiO₂-NH₂ nanoparticles as indicated by a higher potential towards other magnetic adsorbents. This might be due to the formation of adsorption sites for cadmium onto the polymer matrix through adding silica and amino groups. Furthermore, the magnetic nano sorbents displayed a stable q_m of cadmium after reuse. Due to these outcomes, Fe₃O₄@SiO₂-NH₂ nanoparticles are required to be a predominant attractive magnetic nano sorbent for cadmium removal and recovery from aqueous solutions. Above this, taking into account the easy synthesis, reusability as well as separation of MNPs, the Fe₃O₄@SiO₂-NH₂ nanoparticles were better adsorbents than others.

3.3.2. Adsorption Kinetics and Mechanism

Figure 5 showed the adsorption kinetics for Cd(II) ions by Fe₃O₄@SiO₂-NH₂ nanoparticles at 303 K. For ensuring the enhanced interpretation of the adsorption kinetic behavior of Cd(II) ions on the Fe₃O₄@SiO₂-NH₂ nanoparticles, the most typical kinetic models like the pseudo-first, pseudo-second and intraparticle diffusion model, Elovich model, SCM model and Boyd Kinetic model have been well established to elucidate relationships of adsorption rate as well as the adsorption capacities [62]. Results on sorption kinetics for Fe₃O₄@SiO₂-NH₂ nanoparticle Cd(II) removal are portrayed in Figure 5.

Table 4. Adsorption kinetic parameters for the adsorption of Cd(II) ions onto Fe₃O₄@SiO₂-NH₂ nanoparticles.

Kinetic Model	Parameters	Concentration of Cadmium Ion Solution (mg/L)
		25 mg/L	50 mg/L	75 mg/L	100 mg/L	150 mg/L
qe,exp (mg/g)		12.4899	25.4677	35.4566	45.99	65.956
Pseudo-first-order equation	k1(min−1)	0.0943	0.08508	0.08162	0.07375	0.06614
	qe, cal (mg/g)	12.8	25.13	36.63	47.96	69.89
	R2	0.9636	0.9739	0.9663	0.9596	0.9396
Pseudo-second-order equation	k2 (g mg−1 min−1)	0.008046	0.003395	0.002143	0.00135	0.0007472
	qe,cal (mg/g)	14.93	29.88	43.96	58.87	88.2
	R2	0.8858	0.9146	0.9059	0.9064	0.8894
Elovich kinetic model	α (mg/g.min)	8.215	0.6823	0.3036	0.125	0.04648
	β (g/mg)	0.227	1.677	3.087	4.927	8.666
	R2	0.7977	0.8445	0.8374	0.8477	0.8374

depicts calculated values of kinetic models and coefficients of determination (R²) values. The calculated equilibrium adsorption capacity (q_e) value of the pseudo-first-order did not differ much in comparison to the experimental adsorption capacity (q_e,(exp)) value. R² values were found as: pseudo-first-order > pseudo-second-order > Elovich kinetic models. The chemical adsorption principles can be well portrayed by the Elovich model, which explains that the adsorbent possesses a heterogeneous surface [63,64]. Hence, from these findings, it was validated that the pseudo-first-order model is the best apt model to exhibit the Cd(II) ion eradication by Fe₃O₄@SiO₂-NH₂ nanoparticles.

In the solid-liquid sorption technique, the exchange of solutes can be either an external mass transfer, an intraparticle diffusion or a combined method [65,66]. In the case of the removal process under study, Cd(II) is transported through the following sequences below:

• Film-type diffusion, where ion transfer from the bulk portion through the liquid film to the adsorbent surface;
• Intraparticle diffusion characterized by moving through adsorbent pores;
• Adsorption, the ions may be attached to the active sites of the adsorbent.

Even though the intraparticle diffusion model was evaluated more, to convey the adsorption mechanism, it should be analyzed for different metal ion concentrations. With regard to the graph of q_t vs. t^1/2, the first step represents a rapid transfer of Cd(II) ions from the bulk solution to the Fe₃O₄@SiO₂-NH₂ nanoparticle surface. The second step represents the slow diffusion of Cd(II) ions from the external surface into the intra-particle, marking it as the rate-determiner. The slope was defined as the intraparticle diffusion rate constant k_p. Furthermore, a larger intercept represents the surface sorption’s huge contribution. The final step illustrates the equilibrium adsorption of Cd(II) ions in the inner surfaces of Fe₃O₄@SiO₂-NH₂ nanoparticles. Values of k_p and C were calculated from the slope as well as the intercept, respectively, of q_t versus t^1/2 represented in Figure 6a. From the slope of the linear portion of the plot, the intraparticle adsorption parameter k_p was found to be 1.013, 2.212, 3.359, 4.815, and 7.694 mg/g.min^1/2. The boundary layer effect was explained by the surface sorption factor C (mg/g) featured by the intercept of the diffusion plot. In this study, the C factor was found to increase for the initial Cd(II) ion concentrations (

Table 5. Adsorption mechanism parameters for the adsorption of Cd(II) ions onto Fe₃O₄@SiO₂-NH₂ nanoparticles.

Adsorption Models	Parameters	Concentration of Cadmium Ion Solution (mg/L)
		25	50	75	100	150
Intraparticle diffusion model	kp (mg/g min1/2)	1.013	2.212	3.359	4.815	7.694
	C (mg/g)	5.636	9.364	12.58	13.11	13.50
	R2	0.670	0.748	0.741	0.759	0.754
Boyd kinetic model	B	0.101	0.109	0.118	0.125	0.132
	Di (×10−12 m2/s)	5.343	5.766	6.242	6.612	6.983
	R2	0.760	0.883	0.862	0.857	0.867
SCM model	D (×10−9 m2/s)	3.2564	3.1829	3.0978	3.0124	2.7893
	R2	0.751	0.747	0.798	0.747	0.734

) [67]. The slowest step in the sorption of cadmium ions by Fe₃O₄@SiO₂-NH₂ nanoparticles was given by the Boyd kinetic model. The adsorption kinetic data fit well with the Boyd kinetic model, and the results are shown in Figure 6b. The graphs were found to be a straight line; however, they did not pass the origin [68].

The effective diffusion coefficient (D_i) data was computed with Equation (16), and the data are presented in Table 5. Figure 4c represents the shrinking core model, which influences the particle diffusion on the current adsorption system was scrutinized. From these findings, it was also clearly seen that particle diffusion might make changes in the present adsorption system. Diffusivity (D) values were computed utilizing Equation (19), and values are presented in Table 5. Taking the above results from kinetic models into consideration, both film as well as particle diffusion, could be involved in the adsorption of cadmium ions onto the Fe₃O₄@SiO₂-NH₂ nanoparticles.

3.4. Desorption and Reuse of Fe₃O₄@SiO₂-NH₂ Nanoparticles

Figure 7a showcases the desorption kinetics for Cd(II) desorption from Fe₃O₄@SiO₂-NH₂ nanoparticles. Therefore, the desorption of Fe₃O₄@SiO₂-NH₂ molecules can be completed by washing with a high concentration of HCl solution [69]. The adsorption/desorption cycles were continuously carried out nearly five times. Figure 7b depicts that the sorption capacity of Cd(II) ions by Fe₃O₄@SiO₂-NH₂ nanoparticles underwent a reduction from 95 to 80% at the end of five consecutive cycles. Hence, the experimental outcomes confirmed that Fe₃O₄@SiO₂-NH₂ nanoparticles could be reusable and also an efficient sorbent for the successful eradication of removing Cd(II) ions.

4. Conclusions

In this experimental study, economically feasible amino-functionalized Fe₃O₄@SiO₂-NH₂ novel magnetic nano sorbent was prepared by co-precipitation via the silica coating and amine functionalization. Characterization like FT-IR, TEM, SEM and EDX analysis, XRD, VSM and TGA-DSC analyses were performed to validate the magnetic nano sorbent’s structure, surface morphology and potential elements. FT-IR and XRD analysis concluded that the Fe₃O₄@SiO₂-NH₂ nanoparticles have possible functional moieties amorphous in nature. VSM and TGA-DSC studies were performed to validate the magnetic properties and thermal stability of the Fe₃O₄@SiO₂-NH₂ nanoparticles_. Meanwhile, the optimized values on various process parameters were demonstrated: the initial Cd(II) ion concentration of 50 mg/L, pH 6.0, Fe₃O₄@SiO₂-NH₂ dosage 2.0 g/L, the temperature 303 K and the contact time 30 min for maximum removal of Cd(II) ions. The batch sorption studies prove that the pseudo-first-order kinetics and the Freundlich isotherm models were well fitted to the experimental data. The maximum adsorption capacity was found to be 40.02 mg/g. Moreover, the thermodynamic study revealed that the Cd(II) ion removal by Fe₃O₄@SiO₂-NH₂ nanoparticles was viable, exothermic in nature and spontaneous. Furthermore, the acid treatment could easily regenerate the Fe₃O₄@SiO₂-NH₂ nanoparticles, and the sorption property remained unchanged after the completion of five cycles. Therefore, amino-functionalized silica magnetic nano sorbent is one of the efficient adsorbents in removing Cd(II) ions from an aqueous solution. Subsequently, we expect these findings to give a new understanding of the eco-friendly techniques and tailoring of novel adsorbents.