Surface Modifications of Superparamagnetic Iron Oxide Nanoparticles with Polyvinyl Alcohol and Graphite as Methylene Blue Adsorbents

Abstract

Methylene blue (MB) is one of the toxic synthetic dyes that are being discharged heavily into water supplies. Hence, MB removal is one of the most important tasks for a cleaner water supply. By using inexpensive, abundant, and easy-to-synthesize materials, superparamagnetic iron oxide nanoparticles, which were synthesized using the co-precipitation method with polyvinyl alcohol and graphite (SPION/PVA/GR), can be used to adsorb MB. The adsorbent was characterized using FE-SEM, FTIR, XRD, VSM, and BJH. The entrapment efficiency of MB on SPION/PVA/GR after 12 days was 33.96 ± 0.37–42.55 ± 0.39%, at 333.15, 310.15, and 298.15 K, and the initial concentration of MB was 0.017–0.020 mg/mL. The adsorption process can be considered spontaneous, endothermic, chemisorption, heterogeneous, or multilayer adsorption. When releasing MB at 298.15 K and a pH of 3.85 after 7 days, the release percentage ranged from 11.56 ± 0.33 to 22.93 ± 5.06 depending on the initial loading conditions and mainly the releasing temperature following the Higuchi kinetic model. Since this is a novel SPION-based MB adsorbent, optimization, and different forms of adsorbent (i.e., thin film composite) should be further researched.

1. Introduction

Various significant applications, such as drug delivery [1] and water treatment [2] use magnetic nanoparticles. In treating water processes, magnetic nanoparticles help to ease the separation process, especially in solid-liquid phases [3]. As a result, researchers and scientists all over the world are focusing more on magnetic separation. The magnetic property is influenced by the presence of magnetic nanoparticles, such as iron oxide nanoparticles (IONPs). Maghemite, hematite, and magnetite—the superparamagnetic iron oxide nanoparticles—Fe₃O₄ (SPION) are different types of IONPs. The hydrophobic nanoparticles of SPION can be produced using a variety of methods, including hydrothermal, microemulsion, high-temperature decomposition, and co-precipitation, which is the fastest, highest yielding method for magnetite, and easiest to use due to the suppression of magnetite [4]. However, this method has some drawbacks, including agglomeration, which can be reduced by ultrasonication and coating with other materials, leading to weak size control [1,5,6,7].

While removing synthetic color from water during water treatment, SPION can speed up the separation process because of its magnetic capabilities [3]. Despite SPION nanoparticles’ smaller specific surface area and low diffusion resistance, the adsorption capacity of synthetic dyes such as methylene blue, congo red, and methyl orange, as well as the adsorption process, dramatically increases in the presence of carbon-based materials such as graphite (GR), carbon nanotubes, and graphene oxide due to their superior adsorption abilities due to their high porosity structure and large specific surface area [2,8,9]. Hence, the MB-adsorption capabilities are greatly enhanced when mixing SPION with carbon material, as shown in

Table 1. Comparison table between SPION-based MB adsorbents.

Adsorbent	Adsorption Capacity (mg/g)	Ref.
SPION	45.43	[10]
SPION@Carbon sheets	95	[11]
SPION@Graphene	45.27	[12]
SPION@NH2-MWCTNs	178.5	[13]
SPION/expanded graphite	76.2	[14]
SPION/graphene oxide	280.26	[15]
SPION/MWCNT	48.06	[16]
PVA/SA/SPION@KHA gel beads	781.92	[17]

.

The most stable form of carbon is called graphite, which is composed of layers of graphene with covalent and metallic bonds inside each layer and is connected to other layers via a delocalized pi-orbital that produces weak van der Waals interactions. Moreover, compared to other carbon materials, graphite is one of the most economical substances. Therefore, to optimize the adsorption process of methylene blue, one of the most prevalent synthetic carcinogenic and poisonous dyes (producing cancer, mutation, and skin illness) in the textile wastewater sector, SPION must be modified with graphite [18,19]. Hence, methylene blue must be eliminated from wastewater in order to protect the environment and the general public’s health [19].

Despite the facile solid-liquid separation process of magnetic graphite as methylene blue (MB) adsorbents, polymers such as polyacrylonitrile, poly(vinyl pyrrolidone), polyvinylpyrrolidone, especially polyvinyl alcohol (PVA) can be used to enhance the degradation rate of the pollutants and the physical shape of the adsorbents in various forms such as membranes and thin films due to the polymer’s chemical and physical properties of immobilizing the carbon-based composite [20,21,22] Out of these mentioned polymers, PVA was chosen to be used in this composite due to its biocompatibility, affordability, chemical resistance, biodegradability, high structural integrity, environmental friendliness, thermal stability, and non-toxicity properties [23,24,25,26].

The goal of the current work is to assess the possibility of adsorbing and desorbing methylene blue onto SPION/PVA/GR composite, which can be produced using a straightforward, economical, and ecologically friendly approach. Additionally, the future aspect of this work could be creating a thin film composite to adsorb methylene blue. Moreover, this work can be applied further to remove MB from wastewater at a low concentration in a batch process at a wide range of temperatures (298.15–333.15 K). Hence, this is the novelty of this work. Field-emission scanning electron microscopy (FE-SEM), Fourier transform infrared spectroscopy (FTIR), Barrett-Joyner-Halenda (BJH), vibrating-sample magnetometer (VSM), and X-ray diffractometer (XRD) were used to characterize the adsorbent materials. The UV-VIS spectrometer analysis was used to quantify the adsorption process. The adsorption process was carried out at different temperatures and measured in various time increments, which yielded the adsorption isotherm and thermodynamic properties of the adsorbents interacting with the adsorbate via simplified Langmuir, Freundlich, Dubinin-Radushkevich, Temkin, Pyzhev, and Halsey isotherm models. Hence, the mechanism of adsorption can be determined, whether it is physical, exothermic/endothermic adsorption, monolayer/multilayer adsorption capacity, activity coefficient related to mean free energy of adsorption, average free energy of adsorption, spontaneous adsorption, or randomness on the surface. Moreover, an intraparticle diffusion model was also built.

2. Materials and Methods

2.1. Materials

Iron (III) chloride hexahydrate (99% FeCl₃·6 H₂O), iron (II) chloride tetrahydrate (98% FeCl₂·4H₂O), ammonium hydroxide solution (NH₄OH) (28 Wt% NH₃ in H₂O), and hydrochloric acid (37% HCl) were purchased from Xilong Scientific Co., Ltd. (Shantou, China). Methylene blue trihydrate (98.5% MB), graphite (GR), and polyvinyl alcohol (PVA) were purchased from Shanghai Zhanyun Chemical Co., Ltd. (Shanghai, China). All materials were used as received.

2.2. Synthesis

Solution A1—Synthesis of SPION [4]: Using the co-precipitation approach, SPIONs were synthesized [1]. First, 500 mL of 0.7 M NH₄OH was prepared and poured into a three-necked round-bottom flask. N₂ was bubbled through the solution while stirring, and the last neck was plugged with a hole cap to let oxygen release. Next, 10.81 g of FeCl₃·6 H₂O and 3.97 g of FeCl₂·4H₂O were dissolved in 40 mL of DI water and 10 mL 2 M HCl, respectively. The two iron solutions were then mixed, and the entire 50 mL was added dropwise to the flask containing the 0.7 M NH₄OH solution. As soon as the solution turned black, the stirring was reduced. In an N₂ environment, the reaction continued for 30 min. A neodymium magnet was used to capture the particles at the bottom of the flask. After removing the supernatant, DI water was used to wash the particles five times. Then, for 24 h, the particle and DI water mixture was dried in the oven at 80 °C.

Solution A2—SPION solution: 3 g of dried solution A1 was mixed with 200 mL of deionized water for 1 h in a sonication bath at room temperature.

Solution B—PVA solution: 4 g of dried PVA powder into 250 mL of deionized water for 1 h in a sonication bath at room temperature.

Solution C—GR solution: 12 g of dried GR was mixed with 250 mL of deionized water for 1 h in a sonication bath.

Solution D—Synthesis of PVA-coated iron oxide nanoparticles (SPION/PVA): Solution A2 was stirred vigorously with solution B for 1 h using a magnetic stirrer.

Solution E—Synthesis of PVA-coated iron oxide nanoparticles coated graphite (SPION/PVA/GR) composite: Solution D was stirred vigorously with solution C for 1 h. The product was dried in an oven at 80 °C for 1 day.

Solution G—Methylene blue stock solution: 0.05 g of methylene blue (MB) was mixed with 1000 mL of DI water to make a stock MB solution of 0.05 mg/mL.

Solution H—Methylene blue diluted solution: 17, 18, 19, and 20 mL of solution G were mixed with 33, 32, 31, and 30 mL of DI water to make diluted MB solutions of 0.017, 0.018, 0.019, and 0.02 mg/mL, respectively. The pH was kept at 7. This step was repeated three times.

2.3. Adsorption/Loading Experiment

In a 50 mL falcon tube, 50 mL of solution H was mixed with 20 mg of dried solution E for 12 days in an incubator kept at room temperature (298.15 K), 310.15 K, and 333.15 K. The aliquot was analyzed using UV-VIS spectrometry. This step was repeated three times.

2.4. Desorption/Releasing Experiment

After the adsorption experiment, with the aid of a neodymium magnet, the aliquot in each falcon tube was removed. Then, DI water and 2 M of HCl were mixed to create a solution of pH 3.85. The 25 mL of the mentioned solution was then added to each falcon tube. The desorption/release experiment was carried out at 298.15 K. Hence, the loaded adsorbents at 298.15, 310.15, and 333.15 K with initial MB concentrations of 0.017, 0.18, 0.019, and 0.02 mg/mL were used to release MB from the adsorbents for 7 days at 298.15 K at pH = 3.85. The aliquot was analyzed using UV-VIS spectrometry and poured back into the falcon tube. This step was repeated three times.

2.5. Theory

The adsorption process can be quantified using multiple equations such as the loading amount (Equation (1)), loading capacity percent (Equation (2)), entrapment efficiency percent (Equation (3)), and percent release (Equation (4)) [1,4].

$${\mathrm{Q}}_{\mathrm{e}}=\frac{\left({\mathrm{C}}_0-{\mathrm{C}}_t\right)\mathrm{V}}{\mathrm{m}}$$

(1)

$$\%\mathrm{L}\mathrm{C}=\frac{\mathrm{W}\mathrm{e}\mathrm{i}\mathrm{g}\mathrm{h}\mathrm{t} \mathrm{o}\mathrm{f} \mathrm{M}\mathrm{B} \mathrm{a}\mathrm{d}\mathrm{s}\mathrm{o}\mathrm{r}\mathrm{b}\mathrm{e}\mathrm{d} \mathrm{o}\mathrm{n} \mathrm{t}\mathrm{o} \mathrm{t}\mathrm{h}\mathrm{e} \mathrm{p}\mathrm{a}\mathrm{r}\mathrm{t}\mathrm{i}\mathrm{c}\mathrm{l}\mathrm{e}\mathrm{s} \left(\mathrm{m}\mathrm{g}\right)}{\mathrm{W}\mathrm{e}\mathrm{i}\mathrm{g}\mathrm{h}\mathrm{t} \mathrm{o}\mathrm{f} \mathrm{p}\mathrm{a}\mathrm{r}\mathrm{t}\mathrm{i}\mathrm{c}\mathrm{l}\mathrm{e}\mathrm{s} \left(\mathrm{m}\mathrm{g}\right)}\times 100$$

(2)

$$\%\mathrm{E}\mathrm{E}=100\times \frac{\mathrm{W}\mathrm{e}\mathrm{i}\mathrm{g}\mathrm{h}\mathrm{t} \mathrm{o}\mathrm{f} \mathrm{M}\mathrm{B} \mathrm{a}\mathrm{d}\mathrm{s}\mathrm{o}\mathrm{r}\mathrm{b}\mathrm{e}\mathrm{d} \mathrm{o}\mathrm{n} \mathrm{t}\mathrm{o} \mathrm{t}\mathrm{h}\mathrm{e} \mathrm{p}\mathrm{a}\mathrm{r}\mathrm{t}\mathrm{i}\mathrm{c}\mathrm{l}\mathrm{e}\mathrm{s} \left(\mathrm{m}\mathrm{g}\right)}{\mathrm{W}\mathrm{e}\mathrm{i}\mathrm{g}\mathrm{h}\mathrm{t} \mathrm{o}\mathrm{f} \mathrm{M}\mathrm{B} \mathrm{i}\mathrm{n}\mathrm{i}\mathrm{t}\mathrm{i}\mathrm{a}\mathrm{l}\mathrm{l}\mathrm{y} \mathrm{f}\mathrm{e}\mathrm{d} \left(\mathrm{m}\mathrm{g}\right)}$$

(3)

$$\%\mathrm{R}=100\times \frac{\mathrm{W}\mathrm{e}\mathrm{i}\mathrm{g}\mathrm{h}\mathrm{t} \mathrm{o}\mathrm{f} \mathrm{M}\mathrm{B} \mathrm{d}\mathrm{e}\mathrm{s}\mathrm{o}\mathrm{r}\mathrm{b}\mathrm{e}\mathrm{d} \mathrm{o}\mathrm{n} \mathrm{t}\mathrm{o} \mathrm{t}\mathrm{h}\mathrm{e} \mathrm{p}\mathrm{a}\mathrm{r}\mathrm{t}\mathrm{i}\mathrm{c}\mathrm{l}\mathrm{e}\mathrm{s} \left(\mathrm{m}\mathrm{g}\right)}{\mathrm{W}\mathrm{e}\mathrm{i}\mathrm{g}\mathrm{h}\mathrm{t} \mathrm{o}\mathrm{f} \mathrm{M}\mathrm{B} \mathrm{a}\mathrm{d}\mathrm{s}\mathrm{o}\mathrm{r}\mathrm{b}\mathrm{e}\mathrm{d} \mathrm{o}\mathrm{n} \mathrm{t}\mathrm{o} \mathrm{t}\mathrm{h}\mathrm{e} \mathrm{p}\mathrm{a}\mathrm{r}\mathrm{t}\mathrm{i}\mathrm{c}\mathrm{l}\mathrm{e}\mathrm{s} \left(\mathrm{m}\mathrm{g}\right)}=\frac{{\mathrm{M}}_{\mathrm{t}}}{{\mathrm{M}}_{\mathrm{\infty }}}$$

(4)

The adsorption isotherm can be calculated by applying the Langmuir isotherm (Equations (5)–(8)) [27,28] the Freundlich isotherm (Equations (9) and (10)) [29], the Dubinin-Radushkevich (D-R) isotherm (Equation (10)) [28], the Temkin and Pyzhev isotherm (Equations (12)–(14)) [30,31] and the Halsey isotherm (Equation (15)) model [32].

Langmuir assumed that the adsorption and desorption rates are equal at equilibrium when $\mathsf{\theta }$ is in direct proportion to the rate of desorption from the surface [28]. Hence, the Langmuir model assumes that when a single molecule occupies a single surface site, there is no lateral interaction between adjacent adsorbed molecules [28].

$${\mathrm{k}}_{\mathrm{a}}{\mathrm{C}}_{\mathrm{e}}\left(1-\mathsf{\theta }\right)={\mathrm{k}}_{\mathrm{d}}\mathsf{\theta }$$

(5)

$$\mathsf{\theta }=\frac{\mathrm{Q}}{{\mathrm{Q}}_{\mathrm{m}}}=\frac{{\mathrm{K}}_{\mathrm{L}}{\mathrm{C}}_{\mathrm{e}}}{\left(1+{\mathrm{K}}_{\mathrm{L}}{\mathrm{C}}_{\mathrm{e}}\right)}$$

(6)

$${\mathrm{Q}}_{\mathrm{e}}=\frac{{\mathrm{Q}}^0{\mathrm{K}}_{\mathrm{L}}{\mathrm{C}}_{\mathrm{e}}}{1+{\mathrm{K}}_{\mathrm{L}}{\mathrm{C}}_{\mathrm{e}}}$$

(7)

$$\frac{{\mathrm{C}}_{\mathrm{e}}}{{\mathrm{Q}}_{\mathrm{e}}}=\frac{1}{{\mathrm{Q}}^0{\mathrm{K}}_{\mathrm{L}}}+\frac{1}{{\mathrm{Q}}^0}{\mathrm{C}}_{\mathrm{e}}$$

(8)

$${\mathrm{Q}}_{\mathrm{e}}={\mathrm{K}}_{\mathrm{F}}{\mathrm{C}}_{\mathrm{e}}^{1/{\mathrm{n}}_{\mathrm{F}}}$$

(9)

$$\ln {\mathrm{Q}}_{\mathrm{e}}=\ln {\mathrm{K}}_{\mathrm{F}}+\frac{1}{{\mathrm{n}}_{\mathrm{F}}}\ln {\mathrm{C}}_{\mathrm{e}}$$

(10)

If $1<{\mathrm{n}}_{\mathrm{F}}<10$, then the adsorption was favorable [28]. If $\frac{1}{{\mathrm{n}}_{\mathrm{F}}}$ closes to 0 and n is higher than unity (which is 1), then the physical process is favorable [2,33].

$$\ln {\mathrm{Q}}_{\mathrm{e}}=\ln {\mathrm{Q}}_{\mathrm{m}\mathrm{D}\mathrm{R}}-{\mathrm{K}}_{\mathrm{D}\mathrm{R}}{\mathsf{\epsilon }}^2=\ln {\mathrm{Q}}_{\mathrm{m}}-{\mathrm{K}}_{\mathrm{D}\mathrm{R}}{\left[\mathrm{R}\mathrm{T}\ln \left(1+\frac{1}{{\mathrm{C}}_{\mathrm{e}}}\right)\right]}^2$$

(11)

Once obtaining the value of ${\mathrm{K}}_{\mathrm{D}\mathrm{R}}$, the average free energy of adsorption, E (kJ mol⁻¹) can be calculated by $\mathrm{E}={\left(2{\mathrm{K}}_{\mathrm{D}\mathrm{R}}\right)}^{-1}$ [28,34].

$${\mathrm{Q}}_{\mathrm{e}}=\frac{\mathrm{R}\mathrm{T}}{\mathrm{b}}\ln {\mathrm{K}}_{\mathrm{T}\mathrm{P}}{\mathrm{C}}_{\mathrm{e}}$$

(12)

$${\mathrm{Q}}_{\mathrm{e}}={\mathrm{B}}_1\ln {\mathrm{K}}_{\mathrm{T}\mathrm{P}}+{\mathrm{B}}_1\ln {\mathrm{C}}_{\mathrm{e}}$$

(13)

$${\mathrm{B}}_1=\frac{\mathrm{R}\mathrm{T}}{\mathrm{b}}$$

(14)

$$\ln {\mathrm{Q}}_{\mathrm{e}}=\left[\left(\frac{1}{\mathrm{n}}\right)\ln {\mathrm{K}}_{\mathrm{H}\mathrm{a}}\right]-\left(\frac{1}{\mathrm{n}}\right)\ln {\mathrm{C}}_{\mathrm{e}}$$

(15)

Moreover, the intraparticle diffusion rate can be calculated using Weber’s intraparticle diffusion model [16,35]:

$${\mathrm{Q}}_{\mathrm{t}}=\mathrm{I}+{{\mathrm{k}}_{\mathrm{i}}\mathrm{t}}^{1/2}$$

(16)

If I = 0, the adsorption process is intraparticle diffusion. The thermodynamic parameters can be calculated using the equilibrium data obtained at different temperatures [2,28,30].

$$\ln {\mathrm{K}}_0=-\frac{\Delta \mathrm{H}}{\mathrm{R}\mathrm{T}}+\frac{\Delta \mathrm{S}}{\mathrm{R}}$$

(17)

$$\Delta \mathrm{G}=\Delta \mathrm{H}-\mathrm{T}\Delta \mathrm{S}$$

(18)

${\mathrm{K}}_0$ can be determined by plotting $\ln \left(\frac{{\mathrm{Q}}_{\mathrm{e}}}{{\mathrm{C}}_{\mathrm{e}}}\right)$ v. ${\mathrm{Q}}_{\mathrm{e}}$ and extrapolating it to zero. K₀ equals to the exponent of $\ln \left(\frac{{\mathrm{Q}}_{\mathrm{e}}}{{\mathrm{C}}_{\mathrm{e}}}\right)$ when ${\mathrm{Q}}_{\mathrm{e}}$ equals to 0.

The desorption kinetics can be calculated by applying the zeroth-order (Equation (19)), the Higuchi (Equations (20) and (21)), and the Korsmeyer-Peppas (KP) (Equations (22) and (23)) models [36].

$${\mathrm{M}}_{\mathrm{t}}={\mathrm{k}}_0\mathrm{t}$$

(19)

$$\log \left({\mathrm{M}}_{\mathrm{t}}\right)=\log \left({\mathrm{k}}_{\mathrm{H}}\right)+0.5\mathrm{l}\mathrm{o}\mathrm{g}\left(\mathrm{t}\right)$$

(20)

$${\mathrm{M}}_{\mathrm{t}}={\mathrm{k}}_{\mathrm{H}}{\mathrm{t}}^{1/2}$$

(21)

$$\log \left(\frac{{\mathrm{M}}_{\mathrm{t}}}{{\mathrm{M}}_{\mathrm{\infty }}}\right)={\mathrm{l}\mathrm{o}\mathrm{g}(\mathrm{k}}_{\mathrm{K}\mathrm{P}})+{\mathrm{n}}_{\mathrm{K}\mathrm{P}}\mathrm{l}\mathrm{o}\mathrm{g}(\mathrm{t})$$

(22)

$$\frac{{\mathrm{M}}_{\mathrm{t}}}{{\mathrm{M}}_{\mathrm{\infty }}}=\left({\mathrm{k}}_{\mathrm{K}\mathrm{P}}\right)\left({\mathrm{t}}^{{\mathrm{n}}_{\mathrm{K}\mathrm{P}}}\right)$$

(23)

where Equations (19), (20) and (22) are linear models while Equations (21) and (23) are nonlinear models.

For the fitting models, the chi-square test was calculated to determine whether the experimental data fit the fitting model. The chi-square test can be calculated as follows: [30]

$${\mathsf{\chi }}^2=\sum _{\mathrm{i}=1}^{\mathrm{m}}\frac{{\left(\mathrm{e}\mathrm{x}\mathrm{p}\mathrm{e}\mathrm{r}\mathrm{i}\mathrm{m}\mathrm{e}\mathrm{n}\mathrm{t}\mathrm{a}\mathrm{l} \mathrm{v}\mathrm{a}\mathrm{l}\mathrm{u}\mathrm{e}-\mathrm{c}\mathrm{a}\mathrm{l}\mathrm{c}\mathrm{u}\mathrm{l}\mathrm{a}\mathrm{t}\mathrm{e}\mathrm{d} \mathrm{v}\mathrm{a}\mathrm{l}\mathrm{u}\mathrm{e}\right)}^2}{\mathrm{c}\mathrm{a}\mathrm{l}\mathrm{c}\mathrm{u}\mathrm{l}\mathrm{a}\mathrm{t}\mathrm{e}\mathrm{d} \mathrm{v}\mathrm{a}\mathrm{l}\mathrm{u}\mathrm{e}}$$

(24)

If ${\mathsf{\chi }}^2$ is small, the data from the isotherm are similar to the experimental data [30]. On the other hand, if ${\mathsf{\chi }}^2$ is large, the data from the isotherm are different from the experimental data [30].

3. Results and Discussion

3.1. Characterization of SPION/PVA/GR

The SPION/PVA/GR material’s effective fabrication was verified by the FE-SEM, FTIR, and XRD. The morphology of the material may be seen in the FE-SEM photos. The kind of iron oxide nanoparticles and the bonding of SPION/PVA/GR may both be verified by FTIR. Additionally, the XRD examination may demonstrate that the iron oxide nanoparticles exhibit superparamagnetic iron oxide nanoparticle features.

3.2. FE-SEM Analysis

As shown in Figure 1a, the iron oxide nanoparticles (IONPs) were characterized using FE-SEM (Hitachi SU8000) and the agglomeration was visible, similar to previous publications [1], which could be avoided by using an ultra-sonic probe [1].

From the FE-SEM image and ImageJ software v.1.52a, the size distribution (as shown in Figure 1b) and the average size of IONPs were determined to be 29.01 ± 3.90 nm, which is similar to previous publications [1].

After synthesizing IONPs/PVA/GR 3:4:12, the adsorbents were analyzed using the FE-SEM instrument, which yielded the photos shown in Figure 2a.

As shown in Figure 2a, when taking the FE-SEM image of the adsorbent at 5 μm, the IONPs seem to be invisible while the GR is clearly visible. However, in Figure 2b,c, as the magnification increased, the IONPs could be seen clearly on the surface of GR. Moreover, in Figure 2b,c, the IONPs were aggregated. This might be caused by the coating of the PVA, which created the outer shell of the IONPs nanoparticles, leading to the proposed structure of the adsorbents, as shown in Figure 2d. However, the aggregation could be simply caused by the agglomeration nature of IONPs, and the PVA did not coat the IONPs. Hence, further analysis was needed to confirm the structure.

3.3. XRD Analysis

To determine the types of IONPs, XRD analysis was necessary. As shown in Figure 3a, the X-ray diffractograms of IONPs confirmed that the nanoparticles have peaks at 2θ positions of 18.61°, 30.57°, 35.82°, 43.47°, 53.71°, 57.35°, and 63.01°, which corresponded to the magnetite [37], leading to the conclusion that IONPs were SPION.

Based on Figure 3a at a reflective peak 2θ of 35.82°, combining the XRD and the Scherrer equation [38], the SPION size was calculated to be 29.54 nm with a shape factor of 0.89, which was in accordance with the FE-SEM analysis. Moreover, the peaks correspond to their hkl indices of (220), (311), (400), (422), (511), and (440), which are similar to the literature [39,40]. As shown in Figure 3b, for SPION/PVA/GR, the sharp peak at 26.63° and 54.69° indicates that GR exists in the composite, corresponding to their hkl indices of (002) and (004) planes, which is similar to the literature [41,42]. Additionally, as shown in Figure 3b, the SPION peaks have shifted slightly to 18.59°, 30.36°, 35.71°, 43.51°, 57.36°, and 62.94°. Hence, the XRD confirmed that IONPs are SPION, and the adsorbent consists of GR and SPION.

3.4. FTIR Analysis

FTIR is an effective instrument to quantitate and determine the functional groups of the nanoparticles, which confirm the final structure of the material. The FTIR spectra were analyzed using the Brucker Sensor 27 in Germany. As seen in Figure 4, IONPs have the characteristic magnetite peak due to the Fe-O-Fe band splitting into two peaks, corresponding to the first and second bands at 586 and 441 cm⁻¹, which is the Fe-O bond of bulk magnetite [43]. At the wavelengths of 3429 and 1629 cm⁻¹, the peaks corresponded to the bending vibration of absorbed water and surface hydroxyl—O-H stretching mode, C=O stretching vibration, respectively [1,44,45,46] This FTIR analysis confirmed that the IONPs were, in fact, SPION.

As shown in Figure 4, the PVA FTIR spectra shows peaks at 3423, 2923, 1743, 1644, 1457, 1381, 1100, and 851 cm⁻¹, which correspond to the O-H stretching vibration, CH₂ asymmetric stretching vibration, C=O stretching vibrational band attributed to the carbonyl function groups due to the residual acetate groups from the hydrolysis process of polyvinyl acetate, C=O carbonyl stretch, CH₂ bending, C-H dseformation vibration, C=O stretching, and C-C stretching vibration, respectively [47,48,49,50]. As shown in Figure 4, the GR FTIR spectra shows peaks at 3422 and 1644 cm⁻¹, which correspond to the O-H stretching vibration, and C=C [51]. The peaks at 2923, 2853, 1265, and 1059 correspond to the asymmetric stretching vibration of CH₂, the symmetric stretching vibration of CH₂, the C-O stretching of the epoxy group, and the C-O stretching of the alkoxy group, respectively [52]. The FTIR spectra of SPION/PVA/GR in Figure 4 showed the peaks at 3435, 2923, 1724, 1630, 1266, 1059, and 587 cm⁻¹ which matched the peaks of SPION, PVA, and GR, indicating that the adsorbent has been assembled successfully as the proposed structure in Figure 2d.

3.5. BJH Analysis

According to Figure 5a, the adsorption-desorption isotherm demonstrates that the volume of adsorbate uptake begins at 0.1 p/p_o and increases at higher p/p_o.

From Figure 5a, the adsorption-desorption isotherm exhibits type IV isotherm, indicating that the adsorbent has a mesoporous structure with a small amount of micropores [53]. The pores’ dimensions can be between 2 and 50 nm in size [54]. The BJH average pore diameter of the synthesized SPION/PVA/GR sample is summarized in

Table 2. BJH and BET analysis of SPION/PVA/GR sample.

	Adsorption
Surface area (m2/g)	25.3
Pore diameter (Amstrong)	10.3
Pore volume (cm3/g)	0.045

.

As shown in Table 2, the result of BJH and BET indicates the surface area of the initial sample is 25.3 m²/g. The adsorption-desorption isotherm shows that the adsorbate uptake starts at 0.1 p/p_o and the volume adsorbed increases at higher p/p_o. Furthermore, the total pore volume and the mean pore diameter of the SPION/PVA/GR sample were 0.045 cm³/g and 10, Å respectively.

3.6. VSM Analysis

As shown in Figure 5b, IONPs have a magnification (Ms) value of 68.7 emu/g, which is consistent with the Ms values of SPION, according to the literature [55,56].

From Figure 5b, the hysteresis loop shape of SPION/PVA/GR exhibits the superparamagnetism properties. However, the Ms value of the adsorbent dropped to 9.7 emu/g. A possible explanation for this phenomenon is the coating of PVA [57]. Hence, the proposed structure of SPION/PVA/GR is shown in Figure 2d.

3.7. Adsorption

The methylene blue concentration was measured using UV-Vis spectrometry (Jasco V-730, scan speed 40 nm/min, data interval 1 nm, response 0.06 sec, filter exchange step). As the absorbance for methylene blue is at 664 nm, similar to the literature [58], the calibration curve was also obtained.

Via the UV-VIS analysis, the loading amount (${\mathrm{Q}}_{\mathrm{e}}$), percent loading capacity (%LC), and entrapment efficiency (%EE) for the adsorption process of methylene at 273.15, 303.15, and 333.15 K can be seen in

Table 3. The ${\mathrm{Q}}_{\mathrm{e}}$, %LC, %EE of SPION/PVA/GR (3:4:12 w/w/w) adsorbing methylene blue after 12 days.

Initial MB Concentration (mg/mL)	$${\mathbf{Q}}_{\mathbf{e}}$$ (mg/g)	%LC (%)	%EE (%)
333.15 K
0.017	15.15 ± 0.82	1.51 ± 0.08	36.90 ± 1.23
0.018	16.53 ± 1.12	1.65 ± 0.11	37.94 ± 0.31
0.019	18.69 ± 0.82	1.87 ± 0.08	40.08 ± 0.11
0.020	20.88 ± 0.73	2.09 ± 0.07	42.55 ± 0.39
310.15 K
0.017	14.50 ± 1.33	1.45 ± 0.13	35.10 ± 0.20
0.018	16.34 ± 1.43	1.63 ± 0.14	37.78 ± 0.48
0.019	17.82 ± 1.14	1.73 ± 0.11	39.41 ± 0.08
0.020	20.99 ± 1.34	2.10 ± 0.13	41.95 ± 0.14
298.15 K
0.017	14.92 ± 0.67	1.49 ± 0.07	33.96 ± 0.37
0.018	17.05 ± 2.69	1.70 ± 0.27	37.76 ± 0.90
0.019	19.14 ± 0.38	1.91 ± 0.04	39.73 ± 0.21
0.020	19.87 ± 1.68	1.99 ± 0.16	42.30 ± 0.21

.

As shown in Table 3, the loading amount and the loading capacity do not change dramatically as the temperature increases. Comparing the loading amount between temperatures, the adsorption percentage increases slightly as the temperature rises, indicating the process to be endothermic, which is in accord with the $\Delta \mathrm{H}>0$ [59,60]. However, as the temperature increased to 333.15 K, the adsorption capacity decreased slightly. This could be because the adsorption forces between the active sites of the adsorbents and methylene blue decreased [61,62] due to the increase in mobility of methylene blue ions [63]. As the initial methylene blue concentration increased, the loading capacity increased due to the high driving force for mass transfer at a high initial concentration [64].

After 45 h at T = 333.15 K, the UV-VIS peak wavelength of the aliquots shifted from 664 nm to 657–660 nm. This might be caused by the degradation or changes in the structure of methylene blue, which led to the unreliable concentration of the remaining methylene blue in solutions. However, for 298.15 K and 310.15 K, the peak wavelength was 664 ± 2 nm. This indicates that the change in the structure of MB was insignificant.

Comparing the experimental equilibrium adsorption capacities obtained (as shown in Table 1), these values were much smaller compared to some [65,66,67] literature and much greater compared to other literature [64,68].

To determine whether the adsorption process favors higher or lower temperatures, thermodynamic studies were conducted, and the results yielded that the adsorption process was non-spontaneous, and exothermic, and the randomness decreased, as shown in

Table 4. Thermodynamic parameters of SPION/PVA/GR (3:4:12 w/w/w) adsorbing methylene blue after 12 days.

Temperature (K)	$\Delta \mathbf{G}$ (J/mol)	$\Delta \mathbf{H}$ (J/mol)	$\Delta \mathbf{S}$ (J/mol K)
298.15	−90.33	0.39	0.30
310.15	−93.98
333.15	−100.98

.

As shown in Table 4, $\Delta \mathrm{G}<0$, $\Delta \mathrm{H}>0$, and $\Delta \mathrm{S}>0$ shows that the adsorption process was feasible, spontaneous, endothermic, with weak chemical forces between methylene blue and the adsorbents, the randomness increasing on the surface, and some changes occurring in the internal structure of the methylene blue and the adsorbent during the adsorption process [59,60,69,70,71]. As $\Delta \mathrm{G}$ becomes more negative as temperature increases, this indicates that the adsorption process of MB on the adsorbents becomes favorable at higher temperatures via physical force [60,72]. With the $\Delta \mathrm{H}$ values smaller than 40 kJ/mol, the adsorption process can be considered a physisorption process [60,70]. In this case, since the $\Delta \mathrm{H}$ value is smaller than 20 kJ/mol, the physisorption interaction is dominated by Van der Waals forces [73]. The small positive value of $\Delta \mathrm{H}$ also indicates that the adsorption was endothermic and physical, involving weak forces of attraction, weak electrostatic interactions, and the existence of loose bonding between methylene blue and the adsorbents [74,75,76]. Moreover, the positive value of $\Delta \mathrm{H}$ also indicates the occurrence of monolayer adsorption [69]. This result also shows that as the temperature increases, the degree of adsorption increases [70]. Endothermic adsorption may be caused by the stronger interaction between the adsorbent and pre-adsorbed water than the interaction of cationic dyes with the adsorbent [77]. In this case, the methylene blue and water molecules compete for the active sites of activated charcoal, leading to simultaneous adsorption and desoprtion of both types of molecules, resulting in positive $\Delta \mathrm{H}$ [78,79]. Different adsorption isotherm models (Langmuir, Freundlich, Dubinin-Radushkevich, Temkin and Pyzhev, and Halsey) were built, and various adsorption isotherm constants and variables were calculated as shown in

Table 5. Adsorption isotherm of SPION/PVA/GR (3:4:12 w/w/w) adsorbing methylene blue.

Model	Constant	298.15 K	310.15 K	333.15 K
Langmuir	kL (L/mg)	−0.08	−0.08	−0.07
	Q0 (mg/g)	0.19	0.23	0.37
	Average RL	1.00 ± 0.000	1.00 ± 0.000	1.00 ± 0.000
	R2	0.773	0.918	0.828
Freundlich	kF (mg/g)	9.3 × 10−8	2.38 × 10−6	0.000578
	$\frac{1}{{\mathrm{n}}_{\mathrm{F}}}$ (mg/L)	7.91	6.55	4.31
	R2	0.798	0.916	0.871
Dubinin-Radushkevich	kDR (mol2 J2)	90	70	40
	Qm (mg/g)	1066.14	510.76	157.23
	E (kJ mol−1)	5.56	7.14	12.5
	R2	0.796	0.91	0.865
Temkin and Pyzhev	B1	135.62	112.65	75.60
	ln kTP (mg/g)	−2.28	−2.25	−2.16
	R2	0.795	0.882	0.844
Halsey	n	−0.13	−0.15	−0.23
	kHa	0.13	0.14	0.18
	R2	0.798	0.916	0.871

.

Based on the R² values of the isotherm models, which were all greater than 0.5, from Table 5, all the models can be used to fit the experimental values. To determine whether the adsorption of the adsorbate over the adsorbent was favorable, the Langmuir adsorption isotherm (as shown in Figure 6) can be used [2,16] which can be calculated using Equation (25).

$${\mathrm{R}}_{\mathrm{L}}=\frac{1}{1+{\mathrm{K}}_{\mathrm{L}}{\mathrm{C}}_0}$$

(25)

where ${\mathrm{K}}_{\mathrm{L}}$ is calculated from the Equation (7) or (8). If $0<{\mathrm{R}}_{\mathrm{L}}<1$, then the adsorption was favorable [2,16].

As shown in Table 5, the Langmuir adsorption isotherm models (as shown in Figure 5) can confirm that the mechanism of attaching methylene blue onto the surface of SPION/PVA/GR was adsorption linear due to the average R_L = 1 [60,80]. This indicates that MB was adsorbed as a monolayer onto the homogeneous surface of the adsorbent [14].

However, the negative Langmuir isotherm constants show no physical meaning and are unacceptable [81]. Hence, the linearized Langmuir isotherm model should not be considered the best-fitted model for all three temperatures.

After fitting the experimental values with the Freundlich isotherm model, the $\frac{1}{{\mathrm{n}}_{\mathrm{F}}}$ value, which was obtained from the Freundlich isotherm model, as shown in Figure 7, shows the non-favorable physical process.

The $\frac{1}{{\mathrm{n}}_{\mathrm{F}}}$ value which is greater than one shows the adsorption process was cooperative adsorption [82,83]. Moreover, the Freundlich isotherm model also yields values of n_F that are smaller than 1. These values indicate that the bond energies increase with surface density [84]. Moreover, the values of n_F also represent the poor adsorption characteristic [60].

The Freundlich isotherm model determined that the adsorption process was a non-favorable physical process. Hence, to determine whether the adsorption process was chemical and confirm the non-physical adsorption process, the Dubinin-Radushkevich model was built [85]. As shown in Figure 8, since K_DR was less than unity, the adsorbent’s pore structure and the interactions between adsorbent and adsorbate caused the increase in surface heterogeneity [86].

The magnitude of E indicates that the adsorption process was chemical ion-exchange because chemical ion-exchange occurs at a magnitude of E between 8 and 16 kJ/mol and physical adsorption occurs at a magnitude of E less than 8 kJ/mol [87,88,89]. Hence, at 273.15, 310.15, and 333.15 K, the adsorption processes were chemical ion-exchange, chemical ion-exchange, and physical sorption, respectively [90].

The Freundlich isotherm model is quite similar to the Halsey isotherm model in evaluating the multilayer adsorption system and the heterogeneous surfaces with uniform surface heat distribution [91,92] The Freundlich isotherm model describes the exponential distribution of the active sites and their energies [91,92]. However, the Halsey isotherm model not only evaluates the multilayer adsorption system but also describes its condensation at a relatively large distance from the surface [91,92]. Hence, overall, at all three temperatures, the Halsey adsorption isotherm was the only model that did not fit the experimental data the worst, as shown in Figure 9.

As shown in Figure 10, the Temkin-Pyzhev isotherm model shows that all the molecules in the layer decrease linearly with coverage due to adsorbate/adsorbate interactions, and the adsorption is characterized by a uniform distribution of binding energies up to some maximum binding energy [93,94].

As shown in

Table 6. The intraparticle diffusion model after 12 days.

Initial MB Concentration (mg/mL)	I
333.15 K
0.017	14.053
0.018	16.01
0.019	18.333
0.020	20.498
0.017	15.52
310.15 K
0.018	16.35
0.019	17.82
0.020	21.07
298.15 K
0.017	15.63
0.018	17.45
0.019	19.60
0.020	21.85

, the intraparticle diffusion model showed that at 333.15 K, the adsorption was both film diffusion and intra-particle diffusion since $\mathrm{I}\ne 0$ [60].

From the data in Table 6, at 298.15, 310.15, and 333.15 K, the I values showed that the film diffusion and intra-particle diffusion occurred at the same time [95,96,97].

In addition to film diffusion, intra-particle diffusion, and chemisorption, the methlylene blue adsorption mechanism of SPION/PVA/GR could result from electrostatic interactions between the negatively charged surface and the positively charged methylene blue, hydrogen bonds, and the π−π* stacking with the methylene blue aromatic ring [60,70,73,95,96,97]. Additionally, intraparticle diffusion, boundary layer diffusion, and external diffusion can regulate the adsorption processes [60,75,98].

3.8. Desorption

The percentage of release average is given as in

Table 7. The percentage release average of MB from SPION/PVA/GR was 298.15 K after 7 days.

Loaded Temperature (K)	Loaded Initial MB Concentration (mg/mL)
	0.017	0.018	0.019	0.02
298.15	16.89 ± 1.21	22.93 ± 5.06	14.39 ± 1.92	20.25 ± 5.45
310.15	19.54 ± 0.83	19.04 ± 1.49	14.97 ± 0.31	14.31 ± 0.32
333.15	15.36 ± 0.15	14.10 ± 0.15	12.64 ± 0.61	11.56 ± 0.33

.

As shown in Table 7, despite releasing MB at a constant temperature and pH of 3.85, the release percentage varies and depends on the initial loading conditions, such as temperature and initial MB concentration. As the initial loaded MB concentration increases, the release percentage decreases when MB is loaded at 310.15 and 333.15 K. As the loaded temperature increases, the release percentage decreases at the initial loaded MB concentration of 0.02 mg/mL. However, the standard deviation of the release percentage when loaded MB at 298.15 K was much larger than T = 310.15 and 333.15 K. Hence, the highest release percentage occurred when loaded MB was at 310.15 K and 0.017 mg MB/mL.

From Table 7, the percentage of release average can be predicted, as shown in Figure 11 and Figure 12, based on the loading conditions after 7 days. The predicted models can be represented in 3D or 2D. In each model, the predicted equations were generated.

As shown in Figure 11, the calculated/predicted values of the percentage of release were calculated using the following equation:

$$\mathrm{f}\left(\mathrm{x},\mathrm{y}\right)=\mathrm{p}00+\mathrm{p}10\mathrm{x}+\mathrm{p}01\mathrm{y}+\mathrm{p}20{\mathrm{x}}^2+\mathrm{p}11\mathrm{x}\mathrm{y}+\mathrm{p}02{\mathrm{y}}^2+\mathrm{p}30{\mathrm{x}}^3+\mathrm{p}21{\mathrm{x}}^2\mathrm{y}+\mathrm{p}12\mathrm{x}{\mathrm{y}}^2$$

where x, y, p00, p10, p01, p20, p11, p02, p30, p21, and p21 is T_loaded in Kelvin, [MB]_loaded in mg/mL, 16.45, −7.527, −2.278, −0.01926, −1.112, −0.1102, 3.233, 0.05589, 1.59, respectively. The above equation yields R² and root-mean square values of 0.83 and 2.71, respectively.

On the other hand, in Figure 12, the calculated/predicted values of the percentage of release were calculated using the following equation:

$$\%\mathrm{R}\mathrm{e}\mathrm{l}\mathrm{e}\mathrm{a}\mathrm{s}\mathrm{e}=-0.1493577\times {\mathrm{T}}_{\mathrm{L}\mathrm{o}\mathrm{a}\mathrm{d}\mathrm{e}\mathrm{d}}-1057.0489\times {\left[\mathrm{M}\mathrm{B}\right]}_{\mathrm{l}\mathrm{o}\mathrm{a}\mathrm{d}\mathrm{e}\mathrm{d}}+82.3673982$$

where T_loaded and [MB]_loaded in Kelvin and mg/mL, respectively. The above equation yields ${\mathsf{\chi }}^2$ of 3.16.

To determine whether the release temperature or the initial loaded MB concentration affect the percentage of average release, the Taguchi and Factorial methods in Mintab-17 software were used to generate the signal-to-noise (SN) SN ratios (larger is better, as shown in Equation (19)), interaction plots for SN ratios (larger is better), and a Pareto chart of the standardized effects, as shown in Figure 13 [99].

$$\frac{\mathrm{S}}{\mathrm{N}}=-10{\log }_{10}\left(\sum _{\mathrm{i}=1}^{\mathrm{n}}{\mathrm{Y}}_{\mathrm{i}}^2\right)$$

(26)

By using the Factorial method, in Figure 13, the calculated/predicted values of the percentage of release were calculated using the following equation:

$$\%\mathrm{R}\mathrm{e}\mathrm{l}\mathrm{e}\mathrm{a}\mathrm{s}\mathrm{e}=101+0.436\times {\mathrm{T}}_{\mathrm{L}\mathrm{o}\mathrm{a}\mathrm{d}\mathrm{e}\mathrm{d}}+8899\times {\left[\mathrm{M}\mathrm{B}\right]}_{\mathrm{l}\mathrm{o}\mathrm{a}\mathrm{d}\mathrm{e}\mathrm{d}}-31.7\times {\mathrm{T}}_{\mathrm{L}\mathrm{o}\mathrm{a}\mathrm{d}\mathrm{e}\mathrm{d}}\times {\left[\mathrm{M}\mathrm{B}\right]}_{\mathrm{l}\mathrm{o}\mathrm{a}\mathrm{d}\mathrm{e}\mathrm{d}}$$

where T_loaded and [MB]_loaded in Kelvin and mg/mL, respectively. The above equation yields ${\mathsf{\chi }}^2$ of 3.05. As shown in Figure 13a,b, as the temperature decreases, the average release percentage (%R) decreases. On the other hand, no trend was determined for the effects of the initial MB loading concentration on the %R. However, the optimum release conditions were 298.15 K and 0.018 mg/mL MB. As shown in Figure 13b,c, the factor that affects %R the most is temperature since the horizontal bar passed the vertical line on the Pareto charts, which is statistically significant at a 95% confidence level [100], despite some interactions (no parallel lines observed in Figure 13b) between initial loading MB concentration and release temperature [99].

As shown in

Table 8. MB release kinetic models after 7 days at T = 298.15 K and pH = 3.85.

	Korsmeyer-Peppas			0th Order		Higuchi
Initial Loaded MB (mg/mL)	KKP	nKP	${\mathsf{\chi }}^2$	k0	${\mathsf{\chi }}^2$	KH	${\mathsf{\chi }}^2$
Initial Loaded Temperature 298.15 K
0.017	4.81	0.27	1.16	0.00037	0.06	0.0046	0.007
0.018	1.48	0.54	0.02	0.00053	0.02	0.0058	0.00
0.019	0.70	0.61	0.58	0.00039	0.01	0.0043	0.00
0.02	1.02	0.58	0.00	0.00057	0.02	0.0062	0.00
Initial Loaded Temperature 310.15 K
0.017	1.23	0.56	0.93	0.00037	0.06	0.0046	0.007
0.018	1.35	0.54	1.83	0.00053	0.02	0.0058	0.00
0.019	0.76	0.60	1.10	0.00039	0.01	0.0043	0.004
0.02	0.94	0.55	1.08	0.00057	0.02	0.0062	0.00
Initial Loaded Temperature 333.15 K
0.017	1.22	0.51	1.04	0.00037	0.06	0.0046	0.01
0.018	1.35	0.48	1.88	0.00053	0.02	0.0058	0.00
0.019	1.28	0.47	1.59	0.00039	0.01	0.0043	0.00
0.02	1.15	0.47	1.37	0.00057	0.03	0.0062	0.00

and Figure 14, the zeroth order, Higuchi, and Korsmeyer-Peppas released models of MB loaded at different temperatures and different initial MB concentrations released after 7 days at T = 298.15 K and pH = 3.85 were calculated.

As shown in Table 8 and Figure 14, the Korsmeyer-Peppas models yield the release exponent with values of 0.45 < n_KP < 0.89, which indicates that the releasing mechanism is anomalous diffusion or non-Fickian diffusion, which is the combination of diffusion and case-II relaxation [101,102,103,104]. Moreover, with the values of n_KP, the release kinetics are dependent on time. However, with an initial loaded MB concentration of 0.017 mg/mL at a loaded temperature of 298.15 K and an initial loaded MB concentration of 0.018, 0.019, and 0.02 mg/mL at a loaded temperature of 333.15 K, the n_KP was smaller than 0.5, indicating that the releasing kinetic was Fickian diffusion [101]. However, with the Fickian diffusion scenarios, the $chi-squared$ values were all greater than 1 (much greater than 0), indicating that the model did not fit the experimental values well. Overall, the best-fitted kinetic model for releasing MB at 298.15, 310.15, and 333.15 K with a pH of 3.85 is the Higuchi model due to the smallest ${\mathsf{\chi }}^2$ values. The Higuchi models indicate that the diffusion process was based on Fick’s law, which is root-time dependent [105]. If diffusion via water-filled pores in the matrix under constant diffusivity primarily controls the release of the MB, the Higuchi model is applicable [102,106]. In other words, the release of MB was controlled by diffusion through the pores and cracks of the adsorbents [102].

4. Conclusions

By modifying the surface of superparamagnetic iron oxide nanoparticles with polyvinyl alcohol and graphite, the material can be used as methylene blue adsorbents. The entrapment efficiency after 12 days was 33.96 ± 0.37–42.55 ± 0.39%. Thermodynamic studies show that the adsorption process can be considered spontaneous and endothermic. Additionally, the intraparticle diffusion and isotherm models indicate that the adsorption process involves chemisorption, heterogeneous adsorption, and multilayer adsorption. The equilibrium data at 333.15, 310.15, and 298.15 K were best fitted with Freundlich and Halsey isotherm models.

When releasing MB at 298.15 K and a pH of 3.85 after 7 days, the cumulative release percentage was highest at 22.93 ± 5.06%. The release kinetics show that the diffusion process was controlled by diffusion through the pores and cracks of the adsorbents. Additionally, the releasing mechanism can be anomalous diffusion or non-Fickian diffusion, which is the combination of diffusion and case-II relaxation.

However, this research can be further studied by optimizing the ratio between SPION, PVA, and GR to improve the adsorption/desorption capabilities, reusability, exploring the impact of swelling behavior, the coating of PVA on SPION using X-ray photoelectron spectroscopy (XPS), examining the surface of the adsorbents using atomic force microscopy (AFM), and the antimicrobial activities against various bacteria.