Schiff-Based Modified Bentonite Clay Composites for Wastewater Treatment: Experimental and DFT-Based Analysis

Abstract

A new bentonite clay composite was synthesized by modifying bentonite clay and Schiff base (SB). The purpose of the composite was to eliminate methylene blue (MB) from wastewater. To characterize its efficacy, several spectroscopic techniques (UV-Visible spectroscopy, FTIR, SEM, and XRD) were used. The interactions between the adsorbent dose, pH, initial dye concentration, and contact duration were also tested to evaluate the adsorption capacity of the adsorbent. The results demonstrated that changes in the modification led to a considerable increase in adsorption capacity, with a maximum monolayer adsorption capacity of 258 mg/g being achieved at pH 11. Based on the batch experiments, molecular dynamics simulations, and DFT studies, the pseudo-second-order model described the sorption of MB on the bentonite clay composite the best. It was found that the adsorption of MB on the bentonite clay composite primarily followed a monolayer adsorption mechanism. Using the Langmuir isotherm model, the experimental results were consistent, indicating the monolayer adsorption mechanism. Finally, this study demonstrated that the bentonite-SB adsorbent had enormous promise for the elimination of methylene blue (MB) from wastewaters, as evidenced by the electron density mapping within the molecular electrostatic potential plot and the electrostatic potential graphing within the iso-surface plot.

1. Introduction

Water pollution is increasing day by day and becoming a serious issue due to urbanization and industrialization in the modern era. Water pollution has become a major problem in many developing countries [1,2,3]. It occurs as a result of contaminants being discharged into water bodies without being properly treated, either directly or indirectly [4,5]. The main reasons for water pollution are industrial wastes, domestic sewage, marine dumping, the oil industry, nuclear wastes, and underground storage leaks [6,7]. The incorporation of these organic pollutants into the water has caused many diseases, such as cancer, lung diseases, skin problems, allergies, and many more [8,9]. The pollutants that are present in wastewater are mostly heavy metal ions, dyes, and organic and inorganic pollutants [10,11].

Organic pollutants such as dyes are among the most prevalent types of water contaminants since their use is widespread across various industries, such as paintings, papers, textiles, leather, plastics, etc. The presence of dyes in minute quantities, even in a range of 1.0 mg/L in water, is highly visible. Due to the change in the color of contaminated water, the transmission of sunlight through water is totally or partially blocked, consequently affecting the whole aquatic ecosystem [12]. Dyes can also act as hormonal disrupters in human life. Among the various kinds of dyes, methylene blue (MB) is one of the most important ones. It is a heterocyclic compound with the chemical formula C₁₆H₁₈N₃SCl·3H₂O and it is widely used in dyeing, medicine, and many other industries. However, it may cause burns to the eyes, resulting in a permanent loss of eyesight. When inhaled, it may cause respiratory problems, whereas when ingested, it may cause dizziness, nausea, vomiting, confusion, sweating, diarrhea, and convulsions [13]. Therefore, it is essential to remove these organic contaminants before discharging them into the environment for the preservation of both aquatic and human life [14,15,16,17].

The methods used for the elimination of organic pollutants include precipitation, filtration, ion exchange, flotation, reverse osmosis, electrolysis, and membrane separation [18,19]. Furthermore, these technologies consume a lot of energy and produce hazardous sludge or other waste products that need to be disposed of [20]. Sometimes, these processes may recreate lethal metal sludge. However, adsorption is one of the most ideal methods for wastewater treatment. The superiority of the adsorption method over others is due to mild adsorption conditions, simplicity, energy saving, low cost, good adaptability, easy operation, and high treatment efficiency [21,22,23]. Several adsorbents are used to eliminate organic pollutants, such as activated carbons (ACs), zeolites, clay minerals, metal–organic framework, and Schiff bases, from the water [24]. However, Schiff bases are one of the most extraordinary adsorbents to remove organic contaminants from drinking water as a result of their adsorption capacity and excellent reusability [25]. Due to their ease of synthesis and versatility, Schiff bases are among the most extensively used ligands. (RHC = NR’) is the general formula for Schiff bases, and R and R’ can be replaced with alkyl, cycloalkyl, aryl, or heterocyclic groups [26]. The Schiff base drew a lot of attention as an adsorbent because of its large surface area and the presence of azomethine (C=N) donor groups, which have a greater capability for ion exchange with metal ions [27].

Clay minerals, such as montmorillonite, bentonite, and kaolinite, are used as an adsorbent due to low-cost, high-adsorption sites [28,29]. However, natural bentonite has limited adsorption capacity, poor selectivity, and regeneration capabilities. In contrast to the earlier published modifying agents, which are toxic and have certain deleterious properties, this work describes the modification of bentonite using a Schiff base since it is less toxic and ecologically benign. There is no published research on the adsorption of organic contaminants using Schiff-base-modified bentonite (Schiff base was made by condensing salicylaldehyde (5 mmol) and o-phenylenediamine (10 mmol) in methanol solution under the N₂ environment). Several studies have been conducted on bentonite composites that have minimal affinity for removing MB from wastewaters, but none have been carried out on bentonite loaded with a Schiff base for superior MB removal.

The objective of this work was to overcome the research gap by investigating batch adsorption and Schiff-base-modified bentonite for the elimination of organic contaminants. To symbolize cationic colored dyes, the well-known thiazine dye methylene blue was used. Also investigated in consignment mode were the influences of important adsorption limitations, such as initial concentration, pH, adsorbent dosage, and contact time. The adsorption processes of MB using Schiff-base-modified bentonite as the adsorbent were finally examined using theoretical analyses and experimental data fitting with an adsorption equilibrium isotherm and kinetic models.

2. Materials and Methods

2.1. Materials

Bentonite clay was purchased from the University of Faisalabad. All the chemicals, including salicylaldehyde, o-phenylenediamine, methylene blue, and ethanol, were purchased from Sigma Aldrich and used as received. For the preparation of the stock solution of methylene blue as well as for the batch adsorption experiments, distilled water was used.

2.2. Preparation of Schiff Base (SB)

First, we prepared the Schiff base via the reaction of salicylaldehyde and o-phenylenediamine, which involved the use of an organic solvent. Thus, 20 mL of ethanol was added to a beaker, and we added 2 mL of o-phenylenediamine and 4 mL of salicylaldehyde and used a magnetic stirrer to stir the solution (30–40 min). The yellow-colored precipitates were formed, washed with chilled water, and then filtered and vacuum-dried at 85 °C. The scheme of preparation of the Schiff base is given in Figure 1 [30].

2.3. Purification of Bentonite Clay

To purify the clay, a mixture of 30 g of clay and 500 mL of distilled water was prepared. The solution was stirred for 24 h at room temperature and then subjected to centrifugation at 4000 rpm for 20 min. As the impurities had a lower density than the clay, they settled at the bottom of the centrifuge tube. The resultant high-quality Bt was later dried at 105 °C for 48 h to form the Bentonite–SB composite [31].

2.4. Synthesis of Bentonite Clay Composite (Bentonite–SB)

Modification of bentonite clay was performed using the reported method with slight modifications [30]. Bentonite clay was modified with Schiff base at different impregnation ratios of 5%, 10%, 15%, and 20%. Bentonite–SB W/W was prepared by adding the Schiff base solution in ethanol and followed by a magnetic stirrer for 3 h. Then, it was dried in an oven for 24 h at 100 °C. The dried material was crushed with a pestle and mortar and converted into fine powders. A brief schematic representation of the whole work is presented in Figure 2 [12,30].

2.5. Characterization

The sensitized bentonite clay composite’s surface shape and elemental analyses were examined using a scanning electron microscope (SEM). Using Fourier-transform infrared spectroscopy, functional groups in materials were investigated (IRSpirit-T, Shimadzu). Bentonite clay composite, the sample after MB adsorption, and all impregnation ratios’ FTIR spectra were recorded and examined for this study. A UV-Visible spectrophotometer was employed to determine the concentration of pollutants (Cecil 7400S). X-ray diffraction (XRD) measurements were used to examine the crystallinity and phase of the adsorbent in a range of 5–80° (2).

2.6. Batch Adsorption Study

The experimental setup consisted of an ES 20 orbital shaker incubator, which was operated in batch mode using a 100 mL Erlenmeyer flask. The flask was shaken at a speed of 120 rpm for a duration of 120 min. To adjust the pH levels, solutions of 1 M NaOH and 1 M HCl were utilized. Adsorption of MB (100 mL) at varied starting concentrations with optimal adsorbent dosage was examined to examine what effect various parameters had (0.5 g). All studies were conducted at pH 11 except for the pH effect parameter. Each experiment was repeated three times, and accuracy and repeatability were confirmed. A UV-Visible spectrophotometer model Cecil 7400S with a maximum absorbance wavelength of 664 nm was used to determine the dye concentration. Equations (1) and (2) were used to calculate adsorption capacity q_E (mg/g) and the removal efficiency (%).

$${ \mathrm{q}}_{\mathrm{E}}=\frac{\left({\mathrm{C}}_{\mathrm{o}}-{\mathrm{C}}_{\mathrm{T}}\right)\mathrm{V}}{\mathrm{W}}$$

(1)

$$\mathrm{Removal} \mathrm{Efficiency} \left(\%\right)=\frac{{\mathrm{C}}_{\mathrm{o}}-{\mathrm{C}}_{\mathrm{E}}}{{\mathrm{C}}_{\mathrm{o}}}$$

(2)

Here, C_E and C_o are equilibrium concentrations and initial concentrations (mg/g) of adsorbate, W is the quantity of adsorbent (g), and V is the volume of solution (L).

2.7. Adsorption Isotherm

The interaction between the adsorbate and adsorbent can be understood by analyzing the adsorption isotherm, which plots the correlation between the amount of dye adsorbed onto the adsorbent surface and the quantity of dye present in the solution at equilibrium. These isotherm models not only help to determine the adsorption mechanism but also assist in analyzing the adsorption equilibrium data. In this study, both the Freundlich and Langmuir adsorption isotherm models were used to analyze the adsorption equilibrium data. The Langmuir model is based on the homogenous surface of the adsorbent and the monolayer adsorption process. Methylene blue was adsorbed from an aqueous solution using sensitized bentonite, which served as a long-lasting biosorbent. The linear form of the Langmuir model is given in Equation (3).

$$\frac{{\mathrm{C}}_{\mathrm{E}}}{{\mathrm{Q}}_{\mathrm{E}}}=\frac{1}{{\mathrm{K}}_{\mathrm{L}}{\mathrm{q}}_{\mathrm{m}}}+\frac{1}{{\mathrm{q}}_{\mathrm{m}}}\mathrm{Ce}$$

(3)

In this context, C_E represents the equilibrium concentration of the adsorbate in milligrams per liter (mg/L). The Langmuir constant is represented by K_L, while the maximum monolayer adsorption capacity is denoted as qm, and the equilibrium adsorption capacity is Q_E, which is measured in milligrams per gram (mg/g).

Table 1. Parameters of pseudo-first- and pseudo-second-order models.

Pseudo-First Order Model	Co (mg/L)	QE (mg/g) (exp)	QE (mg/g) (cal)	K1 (min−1)	R2
	100	89.214	333.461	0.001972	0.82878
Pseudo-Second Order Model	Co (mg/L)	QE (mg/g) (exp)	QE (mg/g) (cal)	K2 (g·mg−1min−1)	R2
	100	89.214	102.300	0.006369	0.96543

presents the data obtained through the Langmuir isotherm. The intercept and slope of the Langmuir isotherm’s fit line are utilized to calculate Q_E, K_L, and q_m.

The Freundlich adsorption isotherm is predicated on the assumption that the adsorption process on the heterogeneous surface is due to the occurrence of a multi-layer adsorption process. The aqueous solution is treated with modified bentonite clay composite to get rid of the methylene blue. The Freundlich isotherm’s linear form is illustrated in Equation (4).

$${\mathrm{Lnq}}_{\mathrm{e}}=\frac{1}{\mathrm{n}}\mathrm{lnCe}+{\mathrm{LnK}}_{\mathrm{F}}$$

(4)

Freundlich constant KF (L/mg), adsorption strength constant n, and adsorption favorability 1/n, related to the degree of surface heterogeneity, are all constant numbers.

2.8. Adsorption Kinetics

To gain insight into the mechanisms and properties of adsorption, researchers often scrutinize kinetic models. During the experiment, the solution’s concentration was recorded at several intervals, and Equation (1) was employed to determine the adsorption capacity at each point in time. The pseudo-first-order and pseudo-second-order models are commonly utilized in adsorption processes.

Pseudo 1st is given by Equation (5)

$$\ln (\frac{{\mathrm{q}}_{\mathrm{e}}}{{\mathrm{q}}_{\mathrm{e}}-{\mathrm{q}}_{\mathrm{T}}})=\frac{{\mathrm{K}}_1\mathrm{t}}{2.303}$$

(5)

The adsorption capacity at a specific time t is represented by q_T, while the equilibrium adsorption capacity is represented by q_E. The pseudo-first-order adsorption rate constant is denoted by K₁, which is measured in inverse minutes (1/min).

The pseudo 2nd kinetic model is given by Equation (6).

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

(6)

K₂ serves as the pseudo-second-order constant, while q_E (mg/g) and q_T (mg/g), respectively, represent the adsorption capabilities at equilibrium and time t.

2.9. Density Functional Theory (DFT) Analysis of MB

Gaussian 09 program at the B3LYP/6-311G(d,p) was used for DFT calculations of MB to measure the lowest-energy geometries as well as the protonated and non-protonated form [32]. The BIOVIA Materials Studio’s adsorption finder module was employed to determine the lowest-energy configurations for the adsorption of methylene blue onto the bentonite–SB surface. Monte Carlo (MC) simulation was used in conjunction with a simulated annealing approach to accomplish this task. The water molecules were then placed inside the lowest-energy boxes, and the molecular dynamics simulation was run. FORCITE module carried out the optimization procedure and the molecular dynamics simulation.

3. Results

3.1. SEM Analysis

The scanning electron microscope provides information about the surface morphology before and after modification. The SEM images of pure bentonite (a and b) and bentonite–SB composite (c and d) are shown in Figure 3. The smooth fluffy layered structure of pure bentonite is converted into an uneven rugged layered structure in modified bentonite and which depicted that the insertion of the Schiff base into bentonite made it more suitable for the adsorption of MB [33,34,35].

3.2. XRD Analysis

X-ray diffraction showed the crystalline nature of the modified bentonite clay because the peaks are still narrow and sharp. XRD patterns of the pure bentonite and bentonite–SB are shown in Figure 4. Clear sharp peaks indicate the crystalline nature of the bentonite and relatively lower peak intensities of bentonite–SB. A sharp peak at 26.37° of the diffraction angle is the property of a crystalline substance that is bentonite while the same diffraction for bentonite–SB, but it is feeble, which is the sign of preferred orientation, showing the insertion of SB into the layers of bentonite. The d-spacing of both materials was calculated using Bragg’s equation at a peak position of 26.37° for bentonite and 26.14° for bentonite–SB. This shift in the diffraction angle is due to the change in the basel space from 3.377 for unmodified to 3.406 for Schiff base modified, confirming that the immobilization of the ligand successfully occurred [36].

3.3. FTIR

In order to determine the functional groups, Fourier-transform infrared spectroscopy was performed. The FTIR spectra of Schiff base (SB), pure bentonite, and bentonite clay composite (bentonite–SB), before and after adsorption, are shown in Figure 5a. The peaks at 1680 cm⁻¹ and 1584 cm⁻¹ were attributed to (C=N) and (C=C), confirming the presence of a Schiff base or imine group in the modified bentonite, hence, indicating the successful synthesis of a bentonite–Schiff base composite (Figure 5b). The peak between 954 and 860 cm⁻¹ was suggested for the aromatic ring. The band at 796 cm⁻¹ was attributed to the bending and deformation of the Si-O bond. At 870 cm⁻¹, the band corresponding to Al–Al–OH was observed, confirming the bentonite clay. A clear peak at 1465 cm⁻¹ is due to the presence of (-CH₂-) stretch. Moreover, the broadening of peaks at 1680 cm⁻¹ and 796 cm⁻¹ also indicates the adsorption of dye onto the modified sample. As a result, it is assumed that bentonite–SB can efficiently absorb MB [37].

3.4. Effect of Various Parameters on Adsorption

3.4.1. Effect of Adsorbent Dosage

The adsorbent dosage has a significant impact on the adsorption process. By varying the adsorbent dosage from 0.5 g/L to 2.5 g/L in the 100 mL of dye solution, the impact of the adsorbent dosage was assessed. As seen in Figure 6a, the adsorption efficiency was increased from 87.64% to 99.92% when increasing the adsorbent dosage. After that, it became constant, indicating that 2.0 g of the adsorbent is adequate for extreme pollutant removal. As a result, all studies were conducted by using 2.0 g of an adsorbent dose. There may be more adsorption sites, which could explain the rise in the adsorption rate. As the dose is raised, the surface area of the adsorbent dosage rises, and, thus, the adsorption rate increases. However, the lack of MB binding sites prevents further augmentation or a poor increase in the adsorption rate [18].

3.4.2. Effect of pH

The most important factor in adsorption studies is the effect of solution pH. We investigated the impact of pH on the rate of adsorption by varying the pH from 3.0 to 12.0. The results are displayed in Figure 6b, which indicates that pH 11 is the pH at which the most MB dye solution may be removed. At pH 3, the rate of MB removal was the lowest. From pH 3 to pH 12, the adsorption percentage increased from 84.62% to 93.48%. Then, it almost immediately became constant. In alkaline environments, MB removal through adsorption is more effective. This is due to conflict between the cations of the MB dye and the H⁺ ions that are present when the pH is acidic. The H⁺ ions occupy the adsorbent’s active sites and prevent the dye (MB) from being absorbed. However, when the pH is alkaline, both the amount of adsorption competition and the concentration of H⁺ ions drop, improving the effectiveness of adsorption. Therefore, pH 11 was used for all experiments.

3.4.3. Effect of Initial Concentration of Dye

The adsorption process is highly dependent on the initial dye concentration, as illustrated in Figure 6c, which depicts the impact of increasing the dye concentration from 100 mg/L to 600 mg/L while holding other variables constant. The efficiency of the adsorption process declined from 94.32% to 83.31%. The large number of active sites available on the bentonite–SB adsorbent resulted in a high initial sorption rate. However, as methylene blue quickly transferred from the aqueous solution to the adsorbent surface, the sorption rate gradually decreased. This may be due to the dye molecules saturating all active sites on the adsorbent’s surface and penetrating its pores, causing the sorption rate to decline.

3.4.4. Effect of Contact Time

A crucial factor in the adsorption process is contact time. As evidenced by the increase in contact duration, adsorption increases (Figure 6d). In the first 20 min of contact, the adsorption efficiency rose quickly and reached 86.43%; however, as the contact time grew (from 40 to 80 min), the efficiency climbed gradually. At 100 min, the efficiency was roughly 93.9%, and at 120 min, it increased to its maximum value. There may have been enough active sites on the surface of an adsorbent to account for the high initial adsorption rate, but as time goes on, these sites progressively fill up and clog the sorption sites. As a result, the adsorption speed gradually rises, reaching a constant level after 120 min.

3.5. Adsorption Isotherm

In order to understand the interaction mechanisms between the adsorbent and adsorbate, adsorption isotherms play a crucial role. To determine the adsorption mechanism of methylene blue on the adsorbent, this study employed the Freundlich and Langmuir models. The obtained R2 values for the Langmuir and Freundlich isotherms were 0.9995 and 0.9580, respectively. These results indicate that the parameters of the adsorption isotherm are consistent with those of the Langmuir isotherm. The Langmuir isotherm is based on the assumption of monolayer adsorption on a uniform surface. The isothermal plots for the Langmuir and Freundlich isotherms are presented in Figure 7a,b, respectively. These two images’ adsorption mechanisms were explained using the Langmuir isotherm.

3.6. Adsorption Kinetics

The experimental data suggested that the pseudo-second-order model was a more appropriate fit compared to the pseudo-first-order model (Figure 8). According to the pseudo-second-order kinetics model, the adsorption mechanism involves chemisorption, where the adsorbent and adsorbate share or exchange electrons, leading to the formation of a stable bond. This type of adsorption usually occurs at high surface coverage and may be the predominant adsorption mechanism in this study.

3.7. Adsorption Mechanism

The bentonite–SB’s capacity to adsorb methyl blue (MB) was analyzed using Monte Carlo (MC) and molecular dynamics (MD) simulations. The principles of MC and MD simulations were described by Frenkel and Smit. The MC simulation was used to identify the MB desorption sites on the bentonite–SB, while the MD simulation was employed to investigate the impact of solvent molecules, particularly water, on MB adsorption. The MD simulation involved evaluating the lowest-energy structures obtained from the MC simulation in the presence of explicit water.

Figure 9a shows the dry solution’s MB adsorption on the bentonite–SB surface (no solvent). Numerous hydrogen bonds have been formed between the MB molecule and the hydroxide or –Si-O groups on the bentonite–SB surface as a result of the MB molecule’s numerous HB donor and acceptor sites. The sulfur group’s lone pairs and nitrogen atoms produced HBs along with OH on the bentonite–SB surface.

As depicted in Figure 9a, to ascertain if the MB can have non-covalent interactions to the metal ions (Al⁺²) of the adsorbent through non-covalent interactions, the two-layer model rather than the bentonite–SB is utilized. The surface model was utilized to analyze the adsorption of MB. The metal ions have a variety of free connections in the two-layer model. Metal ions with discrete free connections can be found around each edge of a single sheet. For instance, there are no free bonds, two free bonds, and three free bonds on metal ion-containing edges, respectively. The functional groups in MB molecules have also been observed to bind to one another intramolecularly through hydrogen bonds.

In the presence of water, the adsorption of methyl blue (MB) on the surface of bentonite–SB was examined using molecular dynamics (MD) simulations, as demonstrated in Figure 9b. The hydroxyl groups and HO-Al groups of the MB molecule formed hydrogen bonds (HBs) with the bentonite–SB surface when it adsorbed in water (as seen in Figure 9b). However, the primary and tertiary amine groups did not create HBs with the bentonite–SB surface. Figure 9b shows the coordination connections between the MB molecule and Al⁺³ atoms in water. HBs were observed both intra- and intermolecularly between the functional groups of the MB molecule and the water molecules in both water systems. Consequently, the MD simulation confirmed that, even in the presence of water, MB interacts with bentonite–SB [38].

3.8. Examining the Adsorption Mechanism Using DFT Analysis

The DFT calculations were performed using the Gaussian 09 program at the B3LYP/6-311G (d,p) to measure the lowest-energy geometries as well as the protonated and unprotonated forms of MB to understand the adsorption mechanism [35]. Methylene blue’s (MB) optimized structure and its molecular electrostatic potential (MEP) are displayed in Figure 10a. According to the MEP study, the areas with higher and lesser potential were denoted by blue and red colors, respectively. MB’s MEP is displayed in Figure 10b, and the N atom of phenothiazine is shown as having a lower potential and is colored red, which is a potential site for electrophilic attachment with metal ions of modified bentonite. The N atom of dimethyl amine benzene is shown as having a lower potential and is colored blue, depicting a potential site for nucleophilic attack by OH groups of bentonite–SB. Hence, the MEP study showed that electrophilic interaction may occur in nitrogen of methylene blue, and nucleophilic interaction was at the dimethyl amine group. In this case, HOMO functions as an electron donor and is constrained at the bonds C-H, C-C, and C-N, whereas LUMO acts as an electron acceptor and is restricted at the site of the bond C=C inside the ring. As a result, the electronic transition of the ring bond (C=C) to the LUMO stimulates the formation of additional pyrimidine bonds (C–N and C–C). The energy gap, which is represented by the difference in energy between HOMO and LUMO, analyzes reactivity and stability, typically with the lowest electronic energy level excitation of a molecule. As a result, an electronic level transition takes place from the ground state to the first excited level of the state, which illustrates how an electron is stimulated from the HOMO level to the LUMO level. In this case, a lower energy gap may be stimulated more easily than a bigger energy gap. In light of this, a reduced energy gap reveals the cause of intracharge transition in molecules as well as chemical activity. Because of the bigger energy band gap, which generates better kinetic stability and lower chemical reactivity, this prevents electrons from moving to the higher-level LUMO while removing them from the lower-level HOMO. Therefore, any practical reaction must have a very small energy gap. The computed transition energy level for the MB molecule from HOMO to LUMO is 0.05359 eV (Figure 10c,d). While the benzene atoms in dimethylamine were at a greater potential and might be the target of a nucleophilic attack, the nitrogen atom in phenothiazine was at a lower potential and could be the target of an electrophilic attack. The MEP of MB is depicted in Figure 10b. The MEP analysis revealed nucleophilic interaction in the dimethylamine group and electrophilic contact in the nitrogen of methylene blue. The DFT study’s findings further demonstrate that the adsorption process is spontaneous because of the dominant electrostatic contact between modified bentonite and MB [39].

4. Conclusions

Water pollution is a growing problem globally, due to increased industrialization and population. To address this issue, a new adsorbent, called a bentonite clay composite (bentonite–SB), was developed by modifying bentonite clay and incorporating a Schiff base for the removal of MB from wastewater. The optimal conditions for MB adsorption onto bentonite–SB were determined to be at pH 11, a dosage of 0.5 g, dye concentration of 200 mg/L, and 2 h of interaction time. The effectiveness of adsorption was found to increase with an increase in adsorbent dosage, initial dye concentration, and contact time. The prepared adsorbent was characterized using UV-Vis, FTIR, SEM, and XRD techniques, while isotherm modeling and kinetic investigation were conducted to evaluate the adsorption mechanism. The kinetic analysis showed that the pseudo-second-order model best fits the adsorption process, and the maximum monolayer adsorption capacity of 258 mg/g was achieved at pH 11. The DFT study identified the active site of MB, showing that both the adsorbent and adsorbate have interaction sites. Overall, the results showed that bentonite–SB is an excellent and cost-effective adsorbent for MB removal from wastewater.