Introduction

Many industrial and domestic pollutants do not meet water quality standards, posing a significant ecological challenge worldwide1. Among the primary contaminants affecting global sustainability are pesticides, heavy metals, pharmaceuticals, and synthetic dyes that enter aquatic systems2. The aromatic structure of organic dyes contributes to their chemical stability, rendering them resistant to biological degradation3. Exposure to anionic dyes in water can result in serious health effects in humans, including nausea, vomiting, skin irritation, genetic mutations, and damage to the liver and kidneys4.

Reactive dyes such as Bemacid Blue (BB) and Congo Red (CR) are particularly hazardous due to their potential to cause respiratory issues through the inhalation of airborne dye particles. In certain individuals, repeated exposure may lead to respiratory sensitization, a condition characterized by an exaggerated immune response upon subsequent exposure5,6. Some reactive, and disperse dyes are also known skin sensitizers. Textile manufacturing further exacerbates the issue, with approximately 0.08 to 0.15 m³ of water required to produce one kilogram of fabric. Daily processing of 12 to 20 tons of textiles may result in the discharge of 1000 to 3000 m³ of wastewater7,8. These effluents pose significant environmental and public health risks, as they often contain persistent and toxic substances, including carcinogenic and non-biodegradable dyes9.

A wide range of methods exists for remediating water contaminated with various pollutants10, among which coagulation–flocculation11, advanced oxidation processes12, adsorption, and membrane filtration13 are the most commonly employed. Among these, adsorption is particularly favored due to its operational simplicity, high efficiency14, and capacity to eliminate a broad spectrum of contaminants15.

Over the past few decades, numerous studies have explored the use of low-cost materials as sorbents for synthetic dyes, which represent a major component of textile industry effluents16. Its simplicity, cost-effectiveness, and high efficiency make it an attractive technique for wastewater treatment, especially in low-income and developing regions. However, most investigations have focused on single-dye systems, which do not accurately represent real wastewater matrices, typically composed of multiple dyes and inorganic salts. Consequently, the nature and extent of potential intermolecular interactions during the sorption process remain poorly understood17.

To bridge this gap, new sorbents must be evaluated in systems that better reflect actual industrial effluents, including mixtures of dyes and the presence of inorganic salts commonly used in the dyeing process. Such modeling studies are essential to advance the application of sorption from an experimental concept to a scalable and practical solution for industrial wastewater treatment18,19.

Bentonite clays are distinguished by their two-layer crystal structure, consisting of silicate sheets intercalated with exchangeable cations such as calcium (Ca²⁺) and magnesium (Mg²⁺), which confer a high specific surface area and cation exchange capacity20. When subjected to acid or thermal activation across a broad temperature range, these clays undergo structural modifications that expose additional porosity and surface charge21, significantly enhancing their adsorption capacity for various pollutants. A review of the literature reveals numerous studies focused on the application of bentonites, whether raw or modified, in fields such as catalysis, contaminant removal22, and industrial wastewater treatment23.

This study aims to acid-activate bentonite clay in order to improve its adsorption performance in binary dye systems involving BB and CR. A set of advanced analytical techniques was used to characterize the activated clay, including thermogravimetric analysis (TGA), differential thermal analysis (DTA), scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), Brunauer–Emmett–Teller adsorption analysis (BET), and infrared spectroscopy (IR). The adsorption behavior of BB and CR was investigated through both single-component and binary kinetic studies, while possible synergistic effects in dye uptake were analyzed using isothermal models based on initial concentrations. The extended Langmuir and extended Sips isotherms were employed to fit the equilibrium data in the binary system. Special emphasis was placed on infrared spectroscopic analysis to elucidate the adsorption mechanisms of the dyes on the modified bentonite surface.

Materials and methods

Material

The bentonite clay used in this study was sourced from western Algeria and had the following chemical composition: SiO₂ (60.49%), Al₂O₃ (11.27%), Fe₂O₃ (22.7%), CaO (3.60%), MgO (2.29%), K₂O (2.28%), Na₂O (1.55%), and TiO₂ (0.3%).

A mass of 10 g of raw bentonite was first weighed using an analytical balance, then placed in an Erlenmeyer flask containing 200 ml of 8 N hydrochloric acid (corresponding to a solid/solution ratio of 1/20, or 5% by mass/volume). The suspension thus prepared was then kept under continuous agitation at 70 °C for 4 h using a heated magnetic stirrer to ensure complete contact between the clay and the acid24. After treatment, the suspension was subjected to vacuum filtration, and the recovered solid was washed several times with distilled water to remove all acid residues. The clay, treated and then washed, was left overnight in an oven at 110 °C to dry. The final product was designated B-8 N. The following reactions are representative of the interactions between the 2:1 clay and hydrochloric acid.

Alumina (Al2O3) reaction:

$$Al_{2} O_{3} {\text{ }} + {\text{ }}6HCl{\text{ }}Al_{2} Cl_{3} {\text{ }} + {\text{ }}H_{2} O$$
(1)

Reaction with Iron Oxide (Fe2O3):

$$Fe_{2} O_{3} {\text{ }} + {\text{ }}6HCl{\text{ }}2FeCl_{3} {\text{ }} + {\text{ }}3H_{2} O$$
(2)

Magnesium oxide (MgO) reaction:

$$MgO{\text{ }} + {\text{ }}2HCl{\text{ }}MgCl_{2} {\text{ }} + {\text{ }}H_{2} O$$
(3)

Characterization

Differential thermal analysis and thermogravimetric analysis (DTA-TGA) were performed using a Netzsch STA 449 Jupiter system, with a programmed temperature increase from 10 °C to 1000 °C per minute. Scanning electron microscopy (SEM) images were captured using a JEOL JSM microscope at 5000× magnification, both before and after the adsorption process, employing a 15 kV secondary electron detector. Energy dispersive spectroscopy (EDS) was conducted with the same instrument. Infrared (IR) spectroscopy was carried out using KBr pellets and a Shimadzu Prestige 21 spectrometer operating over the spectral range of 400 to 4000 cm⁻¹. The specific surface area of the clay was determined by nitrogen adsorption measurements, using Micromeritics Gemini V11503 equipment under pre-established experimental conditions. Zeta potential measurements were conducted as a function of pH using the SZ-100V2 nanoparticle analyzer from Horiba.

Process of adsorption

The experimental procedure consisted of preparing a mixture of the two dyes, BB and CR, illustrated in Fig. 1a and b, respectively. A volume of 20 mL from this mixture, adjusted to pH 6.4, was treated with 20 mg of the adsorbent material. After a predetermined contact time, the mixture was centrifuged, and the residual concentrations of the dyes were determined using a Shimadzu 1240 UV-visible spectrophotometer. The absorbance measurements were recorded at wavelengths of 498 nm for CR and 604 nm for BB. The corresponding experimental conditions are summarized in Table 1. The concentrations of CR and BB remaining after adsorption were calculated using Eqs. (4) and (5).

Fig. 1
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The chemical structure of (a) Bemacid Blue dye (BB) and (b) Congo Red dye (CR).

Table 1 Experiments and parameters for the adsorption of CR and BB dyes by B-8 N in single-and binary modes.
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A batch adsorption method was employed to evaluate the adsorption capacity of B-8 N towards a mixture of anionic pollutants under the conditions specified in Table 1. This included the azo dye Congo Red and Bemacid Blue, with characteristic absorbance wavelengths at 498 nm and 604 nm, respectively.

$$A_{{498}} {\text{ }} = {\text{ }}k_{{1CR}} C_{{CR}} {\text{ }} + {\text{ }}K_{{1BB}} {\text{ }}C_{{BB}}$$
(4)
$$A_{{604}} {\text{ }} = {\text{ }}k_{{2CR}} C_{{CR}} {\text{ }} + {\text{ }}k_{{2BB}} {\text{ }}C_{{BB}}$$
(5)

where, A498 is the absorbance of mixture determined at 498 nm, A604 is the absorbance of mixture determined at 604 nm, CCR is the concentration of CR in the mixture (mg L− 1), CBB :is the concentration of BB in the mixture (mg L− 1), k1CR and k2CR are the calibration constants for the CR at λ = 498 nm and 604 nm respectively, and k1BB and k2BB are the calibration constants for the BB at λ = 498 nm and 604 nm, respectively.

Results and discussion

Characterization

Thermal analysis

The results of thermal analysis (TGA and DTA), shown in Fig. 2, indicate that bentonite undergoes both structural and chemical modifications following acid activation. The initial mass loss of 0.69% is attributed to the evaporation of physically adsorbed water molecules, likely bound through one or two silanol groups on the outer surface of the clay. This observation is supported by DTA data, which display an endothermic peak at 80.29 °C corresponding to water evaporation. A more pronounced mass loss of 4.51% was observed around 200 °C, associated with the elimination of more strongly bound water, which may include non-stoichiometric (interstitial) water or acidified hydroxyl groups25.

Additionally, thermal analysis data involving acetic acid treatment have shown dehydration events occurring around 560 to 580 °C26. A comparable dehydroxylation process was also observed in the present study, albeit under different experimental conditions. These temperature-dependent transformations reflect structural changes induced by acid treatment, confirming the significant impact of hydrochloric acid activation on the physicochemical properties of bentonite.

A final mass loss of 3.01% was recorded in the decomposition range between 600 and 800 °C. This loss is attributed to the degradation of carbonates, such as CaCO₃, and the elimination of residual organic matter through thermal treatment in this range27. These findings clearly demonstrate that acid treatments significantly alter both the composition and structure of bentonite.

Fig. 2
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TDA and TGA curves of B-8N

SEM images

Scanning electron microscopy (SEM) images of hydrochloric acid-treated bentonite, taken before and after binary adsorption of Bemacid Blue and Congo Red dyes, revealed significant morphological alterations (Fig. 3). Prior to adsorption, the bentonite surface exhibited a porous and irregular structure, characterized by particles of varying sizes and shapes. These features, commonly associated with clay materials, are beneficial for adsorption due to the presence of interparticle porosity and a high specific surface area.

Fig. 3
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SEM images of B-8 N before and after adsorption, respectively, at different magnifications.

Following binary dye adsorption, notable changes were observed in surface morphology. The numerous small pores initially present became less visible, with larger pores appearing to dominate the surface. This shift suggests that pore clogging occurred, likely due to the infiltration and binding of dye molecules within the microporous network. As the dye molecules occupy available adsorption sites, some are displaced by larger aggregates, leading to partial pore blockage. Similar phenomena have been reported in earlier studies, where the surfaces of used bentonites became less porous after successful adsorption of dyes such as Basic Violet 16 and Reactive Red 19528.

This reduction in porosity, along with evidence of densified aggregates, confirms that dye adsorption results in both pore filling and surface restructuring. A higher degree of dye accumulation was also observed, indicated by increased surface coloration and coverage. These results confirm the occurrence of direct physical or chemical interactions between the dye molecules and the modified bentonite surface29, and further support the high adsorption capacity of HCl-treated bentonite demonstrated in earlier dye adsorption studies.

EDS analysis

According to the energy dispersive spectroscopy (EDS) results presented in Fig. 4, the surface of the hydrochloric acid-treated bentonite before adsorption contained silicon (Si), aluminum (Al), iron (Fe), and oxygen (O), all derived from the mineral composition of the activated clay. These elements were present in relatively high concentrations, consistent with the mineralogical characteristics of bentonite.

Fig. 4
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Energy-dispersive X-ray (EDX) microanalysis of treated Bentonite (B-8 N) respectively before and after adsorption: (a) before adsorption and (b) after adsorption.

Following adsorption, EDS analysis revealed an increase in carbon content, confirming the presence of organic dye molecules bound to the B-8 N surface. Notably, the concentrations of the native elements in B-8 N, particularly silicon, aluminum, and iron, remained largely unchanged. This indicates that the adsorption of dyes did not significantly modify the fundamental elemental composition of the material. These findings are consistent with previous studies on Moroccan clay–chitosan composites, which demonstrated similar behavior in terms of surface chemistry and dye interaction30.

BET analysis

The specific surface area of the B-8 N material was determined to be 86.78 m² g− 1, as shown in Fig. 5. For raw bentonite the surface area is 15.85 m² g− 1, while the surface area of B-8 N was 5.48 times higher than that of unmodified bentonite. This relatively high value reflects a significant change in the textural and structural properties of the bentonite after attaching acid with HCl31. Based on adsorption and desorption experiments, the maximum adsorption capacity was found to be 101.66 mg g− 1.

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N2 adsorption-desorption isotherm of B-8 N.

An important finding is the observation of adsorption–desorption hysteresis, which is indicative of the presence of mesopores and micropores within the material’s structure32. The differing profiles of the adsorption and desorption isotherms support this conclusion. Such hysteresis behavior is commonly associated with materials that exhibit a complex porous architecture, which facilitates controlled desorption and enhances the material’s utility in repeated adsorption applications.

FTIR analysis

The infrared (IR) spectra of modified bentonite (B-8 N), the individual dyes BB and CR, and B-8 N after dye adsorption are presented in Fig. 6. The IR spectrum of the modified bentonite before adsorption exhibited characteristic absorption bands associated with the vibrational modes of functional groups specific to the clay structure33. Bands observed at approximately 3646 cm⁻¹ and 3423 cm⁻¹ correspond to the stretching vibrations of hydroxyl (OH) groups linked to the aluminosilicate lattice of the bentonite34. These signals confirm the presence of surface-bound hydroxyl groups.

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Evolution of zeta potential as a function of pH for samples B and B-8 N.

Additional peaks detected near 1648 cm⁻¹ and 1105 cm⁻¹ are attributed to the deformation and torsional vibrations of silicate (Si–O) and aluminate (Al–O) groups, respectively. These functional groups serve as active sites for interactions with dye molecules and play a critical role in the adsorption process. The IR spectra of the pure dyes also displayed distinct bands corresponding to their functional groups, allowing for the identification of interaction mechanisms when adsorbed onto B-8 N.

The spectrum of Congo red dye, prior to adsorption, has a band at 3466 cm− 1, attributed to the N-H stretching vibration. Strong bands at 1650 and 1587 cm− 1 are caused by in-plane deformation of NH2, while other bands at 1444 cm− 1, respectively, may be explained by aromatic C-C stretching. The vibrations coming from νas(S = O) are indicated by a band at 1182 cm-1, and the vibrations coming from νs(S = O) are indicated by a band at 1060 cm− 135,36. Intense bands between 900 and 650 cm− 1 arise from the overlap associated with the out-of-plane deformation of NH2 and the out-of-plane bending of the C-H bonds in the benzene core. Wisting vibrations of NH groups were observed around 593 cm− 137.

The infrared spectrum of Bemacid Blue has a broad band at 3466 cm− 1, attributed to the superposition of the stretching vibration of the = N-H group. The elongation of the N-H bond in the -NH2 group38 is responsible for the band at 1564 cm–1. The stretching of the C = C bond in the aromatic ring is responsible for the strong band located at 1664 cm− 1. Intense vibrations of the C-N bond expansion manifest as a broad band39 in the 1400–1300 cm− 1 area.

Following adsorption, the IR spectra revealed notable alterations, indicating the occurrence of chemical interactions between the dye molecules and the B-8 N bentonite surface. The characteristic hydroxyl and silicate bands of B-8 N, originally observed at 3646 cm⁻¹ and 3423 cm⁻¹, displayed changes in both intensity and position. These spectral shifts reflect interactions between the hydroxyl groups on the bentonite and the functional groups of the dyes, such as sulfonate and amino groups, most likely through hydrogen bonding40.

Additional peaks associated with the sulfonate and amino groups of the dyes were also detected in the spectra of dye-loaded B-8 N, particularly at 1428 cm⁻¹, 1362 cm⁻¹, and 1184 cm⁻¹ for the CR/BB mixture, confirming successful adsorption onto the clay surface. Further spectral modifications observed after adsorption, including changes in the regions around 1042 cm⁻¹, 798 cm⁻¹, and 523 cm⁻¹, suggest the formation of new interactions between the aromatic rings of the dyes and the siloxane groups on the bentonite surface.

Zeta potential analysis

Raw bentonite exhibits its isoelectric point (IEP) at pH 7.8 (Fig. 7), indicating a neutral surface at this pH, a positively charged surface at values below 7.8, and a negatively charged surface at pH values above this threshold41. In contrast, the B-8 N clay modified with hydrochloric acid shows an IEP at pH 6.5. This shift is attributed to the release of protons during the acid treatment process. The presence of protons on the clay surface facilitates the protonation of functional groups, thereby increasing the surface’s negative charge density42.

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FTIR spectra of B-8 N, BB, CR and BB/CR-loaded B-8 N.

As a result, B-8 N modified clay maintains a predominantly negative surface charge across a broad pH range. In the experimental section, the competitive adsorption of the two dyes was studied at pH 6.4, a value close to the IEP of the modified clay, ensuring electrostatic interaction plays a significant role in the adsorption mechanism.

Congo red and bemacid blue binary adsorption

Kinetic analysis

The influence of contact time on the adsorption of BB and CR at 25 °C and 55 °C is illustrated in Fig. 8. The results indicate that adsorption proceeded very rapidly during the initial minutes, followed by a gradual approach to equilibrium as the curves began to plateau43. In the binary system, BB adsorption at 25 °C reached a plateau within approximately 10 min, suggesting rapid saturation of available adsorption sites. In contrast, CR exhibited weaker but more stable adsorption behavior, implying strong competition for binding sites on the adsorbent surface44.

Fig. 8
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Single and binary adsorption kinetics of BB and CR dyes by B-8 N at 25 and 55 °C.

At 55 °C, BB adsorption increased steadily over time, while CR adsorption remained relatively constant throughout the experiment. These observations suggest that adsorption equilibrium was achieved after approximately two hours of contact, as variations beyond this point were not statistically significant. To analyze the adsorption kinetics, we applied pseudo-first-order, pseudo-second-order, intraparticle diffusion, and Elovich models42,45,46. The corresponding kinetic parameters obtained from these models are presented in Table 2.

Table 2 Kinetic parameters calculated for bemacid blue and congo red adsorption on B-8 N.
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The pseudo-first-order:

$$\:{\:\:\:\:\:\:Q}_{t}={{Q}_{e}\:(1-}_{\:}{e}^{-{k}_{1}t})\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:$$
(6)

The Pseudo-2nd -Order:

$$\:{\text{Q}}_{\text{t}}=\frac{{\text{k}}_{2\:}{{\text{Q}}_{\text{e}}}^{2}\:\text{t}}{1+{\text{k}}_{2\:}{\text{Q}}_{\text{e}}\text{t}}$$
(7)

Intraparticle diffusion :

$$\:Q_{t} = k_{{id}} t^{{1/2}} + C$$
(8)

Elovich.

$$Qt{\text{ }} = {\text{ }}(1/\beta \ln {\text{ }}(\alpha \beta ){\text{ }} + {\text{ }}(1/\beta )\ln {\text{ }}t$$
(9)

where, Qt is the quantity adsorbed at time t (mg g⁻¹), Qe is the quantity adsorbed at equilibrium (mg g-¹), \(\:{k}_{1}\) is the pseudo-first order rate constant (min− 1), \(\:{k}_{2}\:\)is the pseudo-second order rate constant (g mg− 1 min− 1), h is the initial adsorption rate (mg g− 1 min− 1), t is the time of contact (min), kid is the intraparticle diffusion rate constant (mg g⁻¹ min-1/2), C is the constant (mg g⁻¹), α (mgg− 1 min− 1) is the initial adsorption, and β (gmg− 1) is the desorption constant.

The adsorption kinetics of BB and CR on B-8 N were analyzed, and the results are presented in Table 2. At 25 °C, the pseudo-first-order model provided a good representation of BB adsorption, with a correlation coefficient (R²) of 0.999 and a calculated adsorption capacity that closely matched the experimental value. For CR, while the pseudo-first-order model also showed an acceptable fit, except for the sample at 55 °C, a discrepancy between the experimentally adsorbed amount and the estimated amount is noted.

In contrast, the pseudo-second-order model demonstrated an excellent fit for both dyes at all tested temperatures, providing a more accurate and consistent description of the adsorption mechanism.

CR exhibited a notably higher initial adsorption rate than BB, suggesting faster and more efficient adsorption onto B-8 N. The data also indicated enhanced particle diffusion at elevated temperatures, with CR diffusing more rapidly than BB. The values of the rate constant K₂ increased with temperature for both dyes, aligning with the observed increase in adsorption capacity. However, the initial adsorption rate (h) decreased with rising temperature for both CR and BB.

These findings are consistent with earlier studies, including one that demonstrated enhanced CR adsorption onto natural clay from Agadir region in binary mixtures with Methylene Blue and Crystal Violet, where the pseudo-second-order model also proved most suitable47. In contrast, the Elovich model yielded low R² values, indicating that it does not adequately describe the competitive adsorption of the two dyes48. This finding is further supported by the kinetic plots shown in Fig. 9.

Fig. 9
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Nonlinear kinetic modeling of Bemacid Blue and Congo Red adsorption on B-8 N at 25 °C and 55 °C using the pseudo-first-order, pseudo-second-order, and Elovich models.

Furthermore, the intraparticle diffusion model demonstrates a high R2 value, and C values differing from 0 suggest that internal diffusion is not the rate-limiting factor determining adsorption; instead, exterior diffusion is essential49.

Selectivity of CR and BB in a binary system

The relative adsorption was calculated using Eq. (10), as described in50:

$$\:{\text{a}}_{\text{i}\text{j}}=\frac{{\text{x}}_{\text{i}}{\text{y}}_{\text{j}}}{{\text{x}}_{\text{j}}{\text{y}}_{\text{i}}}$$
(10)

Where.

\(\:{\text{a}}_{\text{i}\text{j}}\) is selectivity

where, \(\:{\text{a}}_{\text{i}\text{j}}\) is the selectivity is the selectivity, \(\:{\text{x}}_{\text{i}}\) is the adsorption capacity at time t for CR in the binary mixture, \(\:{\text{x}}_{\text{j}}\) is the adsorption capacity at time t for CR in single-solute mode, \(\:{\text{y}}_{\text{i}}\) is the adsorption capacity at time t for BB in the binary mixture, and \(\:{\text{y}}_{\text{j}}\) is the adsorption capacity at time t for BB in Single-solute mode.

Figure 10 illustrates that the B-8 N material exhibited a strong selectivity for the adsorption of CR compared to BB, particularly over a contact time of up to 120 min. At 25 °C, the selectivity ratio increased from 1.85 at 10 min to a peak value of 3.47 at 120 min, followed by a slight decrease to 3.35 at 180 min. This trend indicates that B-8 N has a markedly higher affinity for CR molecules than for BB. The enhanced selectivity is likely attributed to specific interactions between the functional groups of CR and the active sites on the B-8 N surface, which facilitate more effective adsorption of CR relative to BB51.

Fig. 10
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Adsorption selectivity of B-8 N for BB and CR in a binary system at 25 °C.

Adsorption isotherm of CR and BB in binary system

The adsorption isotherms of BB and CR in single and binary dye systems at 25 °C and 55 °C are presented in Fig. 11. The results demonstrate that adsorption capacity varies as a function of temperature and the competitive presence of the other dye. At 25 °C, BB adsorption was higher in the single system than in the binary system, with a maximum adsorption capacity of 127.79 mg g⁻¹ compared to 108.8 mg g⁻¹.

Fig. 11
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Single and binary adsorption isotherms of Congo red and Bemacid blue at 25 and 55 °C.

For, CR adsorption was significantly reduced in the binary system at 25 °C, dropping from 576.8 mg g⁻¹ in the single system to 229.7 mg g⁻¹. This suggests that the presence of BB may have hindered the availability of adsorption sites for CR, or altered the interaction dynamics between CR and the B-8 N surface.

At 55 °C, the adsorption isotherms revealed different behavior. The elevated temperature appeared to activate more adsorption sites through enhanced molecular diffusion of the dyes52. Under these conditions, CR adsorption in the binary system increased to 247.7 mg g⁻¹, compared to 229.7 mg g⁻¹ at 25 °C. However, this value remained lower than the maximum capacity observed in the single-dye system, indicating that competitive effects still limited CR adsorption despite the increased temperature.

Modeling of adsorption isotherm

The adsorption of BB and CR onto B-8 N in the binary system was analyzed using Non-modified Langmuir (Eqs. 11 and 12), extended Langmuir (Eqs. 13 and 14) and extended Sips models (Eqs. 15 and 16)53.

Non-modified Langmuir model:

$$\:{\text{Q}\text{e}}_{1}=\frac{{\text{Q}}_{\text{m}1}^{}{\text{k}}_{{\text{L}}_{1}}\text{C}{\text{e}}_{1}}{1+{\text{k}}_{{\text{L}}_{1}}\text{C}{\text{e}}_{1}+{\text{k}}_{{\text{L}}_{2}}\text{C}{\text{e}}_{2}}$$
(11)
$$\:{\text{Q}\text{e}}_{2}=\frac{{\text{Q}}_{\text{m}2}^{}{\text{k}}_{L2}\text{C}{\text{e}}_{2}}{1+{\text{k}}_{{\text{L}}_{1}}\text{C}{\text{e}}_{1}+{\text{k}}_{{\text{L}}_{2}}\text{C}{\text{e}}_{2}}$$
(12)

Extended Langmuir model:

$$\:{\text{Q}\text{e}}_{1}=\frac{{\text{Q}}_{\text{m}\text{a}\text{x}1}^{}{\text{k}}_{1}\text{C}{\text{e}}_{1}}{1+{\text{k}}_{1}\text{C}{\text{e}}_{1}+{\text{k}}_{2}\text{C}{\text{e}}_{2}}$$
(13)
$$\:{\text{Q}\text{e}}_{2}=\frac{{\text{Q}}_{\text{m}\text{a}\text{x}2}^{}{\text{k}}_{L2}\text{C}{\text{e}}_{2}}{1+{\text{k}}_{1}\text{C}{\text{e}}_{1}+{\text{k}}_{2}\text{C}{\text{e}}_{2}}$$
(14)

Extended Sips model:

$$\:{\text{Q}\text{e}}_{1}=\frac{{\text{Q}}_{\text{m}\text{a}\text{x}1}^{}{\left({\text{k}}_{1}\text{C}{\text{e}}_{1\:}\right)}^{ms1}}{1+{\left({\text{k}}_{1}\text{C}{\text{e}}_{1\:}\right)}^{ms1}+{\left({\text{k}}_{2}\text{C}{\text{e}}_{2\:}\right)}^{ms2}}$$
(15)
$$\:{\text{Q}\text{e}}_{2}=\frac{{\text{Q}}_{\text{m}\text{a}\text{x}2}^{}{\left({\text{k}}_{2}\text{C}{\text{e}}_{2\:}\right)}^{ms2}}{1+{\left({\text{k}}_{1}\text{C}{\text{e}}_{1\:}\right)}^{ms1}+{\left({\text{k}}_{2}\text{C}{\text{e}}_{2\:}\right)}^{ms2}}$$
(16)

where, Qe1 is the quantity of CR adsorbed at equilibrium in the binary system (mg g⁻¹), Qe2 is the quantity of BB adsorbed at equilibrium in the binary system (mg g⁻¹), where Qm1 and Qm2 are the maximum adsorption capacity of adsorbent for CR and BB, while KL1 and KL2 are adsorption affinity constants of CR and BB, respectively. All Langmuir parameters (Qm1, Qm2, KL1 and KL2) are obtained from single adsorption isotherm data of each component and introduced to Eqs. (11) and (12).

Qmax1 is the quantity of CR adsorbed at saturation in binary mode (mg g⁻¹), Qmax2 is the amount of BB adsorbed at saturation in binary mode (mg g⁻¹), Ce1 is the equilibrium concentration of CR in binary system (mg L− 1), Ce2 is the equilibrium concentration of BB in binary system (mg L− 1), k1 is the affinity constant for CR in binary mode (L mg⁻¹), k2 is the affinity constant for BB in binary mode (L mg⁻¹), mS1 is the parameter describing material surface heterogeneity for CR, and mS2 is the parameter describing material surface heterogeneity for BB.

The experimental data for dye adsorption in the binary system could not be adequately described by the non-modified Langmuir isotherm54,55. The error values obtained were relatively high exceeding 25% (result not shown), indicating a substantial deviation between predicted and observed values. This discrepancy suggests that the non-modified Langmuir model fails to capture the competitive adsorption behavior of the dye mixture, specifically BB and CR, on acid-activated bentonite. According to the assumptions of the classical Langmuir model, all adsorbed species have equal access to homogeneous adsorption sites, the adsorption energy is uniform across the surface, and there are no interactions among adsorbed species. These conditions do not reflect the complexity of competitive binary adsorption56.

Figure 12 presents the modeling results using the extended Sips and extended Langmuir equations. The curves demonstrate good agreement between experimental data and model predictions57. Both the extended Langmuir and extended Sips models provided a better fit to the experimental data with correlation coefficients (R²) exceeding 0.94 for all samples (Table 3). These results confirm the competitive nature of binary adsorption, in which molecules of different sizes or chemical characteristics compete for active sites. Under such conditions, adsorbed species interact with each other and do not have equal access to the surface.

Fig. 12
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Isotherms data of CR and BB in binary system and according to Extended Sips and Extended Langmuir at 25 and 55 °C.

Table 3 Extended Langmuir and extended Sips parameters for BB and CR adsorption onto B-8 N in binary systems.
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The two models describing the isotherm data in the binary system is presented in Table 3. The calculated parameters and the superposition of the isotherm data and the model confirm that the extended Sips model better describes the CR isotherm data in the mixture (Fig. 12).

For BB in the mixture, the extended Langmuir model better describes the isothermal data than the extended Sips model (Table 3), and the graph shown in Fig. 12 confirms the validity of the model.

Three-dimensional isothermal surfaces

3D plots of the adsorption isotherms were generated using MATLAB version 16, based on the isotherm equations that best described the binary adsorption data. The 3D isothermal surfaces illustrating the adsorption of BB and CR onto B-8 N at 25 °C and 55 °C are shown in Fig. 13. The experimental data closely matched the modeled surfaces, validating the suitability of the extended isotherm model to describe the adsorption processes in the binary system.

Fig. 13
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3D plot of isotherm data according to Extended Sips model.

The graphical representations revealed the competitive nature of the interactions between BB and CR, as the adsorption of one dye was influenced by the concentration of the other. These findings are consistent with previous research on the simultaneous adsorption of Reactive Black 5 (RB5) and CR onto D900 resin at 25 °C and 40 °C58, where an increase in the initial concentration of one dye led to enhanced adsorption, while the presence of the competing dye reduced it. This behavior, also observed in our 3D isothermal surfaces, further confirms the competitive dynamics between CR and BB in the binary system.

Thermodynamic analyses

Investigating the thermodynamic aspects of dye adsorption is essential for assessing the feasibility and thermal nature of the process. The following equations were used for this analysis59,60:

$$Kd = Qe/Ce$$
(17)
$$\:{\Delta\:}\text{G}^\circ\:=-\text{R}\text{T}\text{ln}1000{\text{k}}_{\text{C}}$$
(18)
$$\ln K_{e} = {\text{ }}\Delta H/RT{\text{ }} + {\text{ }}\Delta S/R$$
(19)

where, Kd is the distribution coefficient (L g− 1), Ke is the equilibrium constant symbol, equal to 1000*Kd, ΔH° is the standard enthalpy change (J mol− 1), ΔS° is the standard entropy change (J mol− 1K− 1), and ΔG°is the standard Gibbs free energy (J mol− 1).

The study of thermodynamic parameters offered valuable insight into the spontaneous nature of the adsorption process61. It was observed that the removal of both dyes increased slightly with rising temperature, indicating that elevated temperatures favor the sorption process. The thermodynamic parameters were derived from the van’t Hoff plot (Fig. 14), and their values are summarized in Table 4. The negative values of ΔG° confirm that the adsorption of both dyes is spontaneous and thermodynamically feasible. The positive value of ΔH° indicates that the process is endothermic for BB and CR, while the positive ΔS° suggests an increase in randomness at the solid–solution interface during adsorption62. These observations correspond to an increase in the spontaneity of adsorption, as evidenced by the negative values of ΔG°63.

Fig. 14
Fig. 14The alternative text for this image may have been generated using AI.
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Plot of Ln (Kc) as a function of 1/T in the binary system for BB, CR.

Table 4 Thermodynamic parameters for CR and BB in binary mode through B-8 N.
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The positive value of ∆S° indicates an increase in disorder at the surface. This could be due to the redistribution of energy between the pollutant and the adsorbent. Before adsorption, the pollutants near the clay would be more organized compared to the adsorbed state that follows.

Consequently, as adsorption progresses, the distribution of rotational and translational energy among the molecules improves, leading to a positive value of ∆S°53.

Desorption and regeneration

Desorption of the dyes BB and CR was conducted following sequential adsorption under optimal conditions: pH 6.4 for BB and 5.3 for CR, an initial dye concentration of 800 mg L⁻¹, and a contact time of 120 min. After saturation, 20 mg of the adsorbent (B-8 N) was mixed with 20 mL of various desorbing agents, including NaOH, methanol, ethanol, ethanol–water mixtures, distilled water, acetone, and butanol. The mixtures were agitated in test tubes at 600 rpm for 120 min at 25 °C. The concentrations of desorbed dyes were determined by UV-visible spectrophotometry, and the desorption rate was calculated as the percentage of dye released relative to the amount initially adsorbed.

The results showed that NaOH was the most effective desorbing agent, with a maximum desorption rate of 83.20% for CR, followed by methanol at 64.43% and ethanol at 34.54%. Lower desorption efficiencies were observed for water, acetone, and butanol (Fig. 15a). A comparison between the two dyes revealed that BB consistently exhibited lower desorption rates than CR across all solvents. For instance, NaOH desorbed 83.20% of CR but only 55.23% of BB. These findings suggest that CR was more readily desorbed due to its increased surface interaction with the B-8 N material, which facilitated dye release. In contrast, BB appeared to be more strongly retained, possibly as a result of deeper or more complex interactions with the adsorbent’s active sites64.

Fig. 15
Fig. 15The alternative text for this image may have been generated using AI.
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(a) Desorption rate (%) of dyes from B-8 N; (b) adsorption quantity during successive cycle.

The reusability parameter is a critical factor for evaluating the industrial applicability of any adsorbent. In this study, five successive adsorption–desorption cycles were performed using NaOH as the desorbing agent (Fig. 15b). The B-8 N material maintained a relatively stable adsorption capacity during the first three cycles. However, a noticeable decline in adsorption performance was observed from the fourth cycle onward.

One of the challenges encountered was the gradual loss of B-8 N material during each cycle. Due to technical limitations, complete recovery of the adsorbent after desorption was not achievable. Additionally, it was found that NaOH could irreversibly occupy some of the adsorption sites during each regeneration step, thereby reducing the number of active sites available for subsequent adsorption65,66.

Comparative adsorption amounts with other materials

Table 5 presents a comparative analysis of the adsorption capacities of various materials, with a particular focus on the adsorbent used in this study. Among the materials listed, acid-treated bentonite exhibited the highest adsorption capacity. This treatment method has proven highly effective for the removal of anionic dyes such as BB and CR, due to its remarkable ability to enhance the adsorption capacity of the clay.

Table 5 The adsorption capacities shown above for different adsorbents with the congo red and bemacid Blue.
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In the binary system, the treated bentonite achieved adsorption capacities of 152 mg g⁻¹ for BB and 247.72 mg g⁻¹ for CR, demonstrating its strong performance even under competitive adsorption conditions. These results confirm that acid-activated bentonite remains highly efficient in adsorbing multiple dye species, even in complex systems involving mixed pollutants.

Mechanism adsorption of CR and BB in binary system

In general, the adsorption mechanism of organic dyes onto the surface of an adsorbent is a complex process influenced by multiple factors, including the surface characteristics of the adsorbent, the molecular structure of the dye, and the conditions of the adsorption medium. Depending on these variables, dye adsorption can be governed by various interactions such as electrostatic attraction, hydrogen bonding, Hydrophobic interaction, and n–π interactions76,77.

Isothermal, kinetic, thermodynamic, reusability, and spectroscopic analyses are essential for elucidating the adsorption mechanism. The reusability study over five consecutive cycles confirmed that the adsorption process is largely reversible. Intraparticle diffusion modeling suggested a contribution from film diffusion to the overall kinetics; however, intraparticle diffusion was not identified as the dominant mechanism.

Electrostatic attraction plays a significant role in the adsorption mechanism, as confirmed by the zeta potential analysis. Nevertheless, the ability of the modified clay to adsorb CR and BB at pH values below 6.5 also suggests the involvement of additional forces, such as n–π interactions and hydrogen bonding78. This is supported by the FTIR spectra of the clay after adsorption, which showed a notable decrease in band intensity and slight band shifts, consistent with n–π interactions79. In addition, EDS and SEM after adsorption confirm the adsorption of dyes into activated bentonite.

Based on the experimental findings and considering the molecular structures of CR and BB as well as the surface properties of the acid-activated clay, the adsorption mechanism is assumed to proceed primarily through electrostatic attraction between the negatively charged sulfonate groups (–SO₃⁻) of the dyes and the positively charged surface of the acid-activated bentonite80. Hydrogen bonding is likely to occur between nitrogen or sulfur atoms in the dye molecules and hydroxyl groups on the clay surface. n–π interactions further contribute to the overall adsorption mechanism (Fig. 16).

Fig. 16
Fig. 16The alternative text for this image may have been generated using AI.
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Mechanism of binary adsorption of CR and BB into acid-activated bentonite.

It is worth noting that CR is adsorbed more effectively than BB in the binary system, which may be attributed to its molecular structure. CR contains six nitrogen atoms and six benzene rings, offering more sites for n–π interactions, whereas BB contains only three nitrogen atoms and five benzene rings81. The siloxane moieties are considered hydrophobic, rendering them appropriate equivalents for aromatic rings82. The contact between aromatic rings and siloxane moieties would result in a hydrophobic interaction because bentonite siloxane surfaces are non-polar83.

Conclusions

This study demonstrated the effectiveness of acid-treated bentonite clay for the adsorption of Bemacid Blue (BB) and Congo Red (CR) from both single and binary dye solutions under equilibrium conditions. Characterization of the treated clay using differential thermal analysis (DTA), thermogravimetric analysis (TGA), scanning electron microscopy (SEM), and energy dispersive X-ray spectroscopy (EDS/EDX) revealed enhanced adsorptive properties following hydrochloric acid activation. Kinetic studies indicated that the pseudo-second-order model provided the best fit to the experimental data, confirming the reliability and efficiency of the activated clay for adsorbing both dyes. The equilibrium data were accurately described by the extended Sips and extended Langmuir models for CR and BB dyes, respectively. In the binary system at 55 °C, CR achieved a maximum adsorption capacity of 247.72 mg g⁻¹.

NaOH had the maximum desorption capability in the binary system, recovering 83.82% of CR and 55.23% of BB from activated bentonite, which maintained its adsorption efficacy throughout three cycles. The overall adsorption mechanism is confirmed by IR analysis involving multiple interactions, including electrostatic attraction, hydrogen bonding, n–π interaction and hydrophobic interactions between the functional groups of the dyes and the active sites of the acid-activated bentonite.

In light of these results, further investigation is recommended under real wastewater conditions. These may include complex mixtures of organic and inorganic compounds, fluctuating pH levels, and the presence of competing pollutants that can affect adsorption performance. To confirm the practical viability of this treatment method for industrial applications, future studies should also assess the long-term stability of the adsorbent, its regeneration efficiency beyond five cycles, and its scalability in continuous-flow systems.

The promising performance of the acid-activated bentonite highlights its potential as an efficient, environmentally friendly, and sustainable adsorbent for dye removal in mixed pollutant systems. With further optimization and field-scale validation, this modified clay could serve as a practical solution for wastewater treatment and other environmental remediation applications.