An illite-montmorillonite clay from Naima, IMN (Algeria) was treated via physical and chemical treatment (TIMN) and investigated for the removal of methylene blue. IMN and TIMN clays were characterized by XRD, XRF, SEM-EDS, DSC-TG, FTIR and DC electrical conductivity methods. To analyze the sorption behavior of MB on the clays, a mechanistic model for interpreting the sorption data was developed. IMN clay revealed high sorption capacity (1.925 × 10−2 kg kg−1) for MB in 60 min. The pseudo-second-order model had a very good agreement to describe the MB adsorption process. The adsorption capacities, qe,exp, of 4.327 × 10−2 and 4.914 × 10−2 kg kg−1 for IMN and TIMN, respectively, were obtained. The free energy from the D–R model from adsorbing MB using IMN and TIMN ranged from 1.581 to 0.745 × 10−3J mol−1, respectively, suggesting that the process is physisorption. Besides, the sorption process was more sensible to temperatures that increase was beyond 40 °C causing a decrease in adsorption capacity, indicating that the adsorption reaction of MB onto IMN was exothermic. The adsorption mechanism of I/M clay to remove MB was likely based on hydrogen bonding, electrostatic attraction, cation exchange and nπ interaction. These results proved that TIMN was a promising adsorbent for removing MB from simulated wastewater.

  • Natural Illite-Montmorillonite clay from Naima (IMN) and its modified form (TIMN) were successfully elaborated via physical and chemical treatments.

  • IMN and TIMN clays were characterized by X-ray diffraction (XRD), X-Ray Fluorescence (XRF), Fourier Transformed Infrared (FTIR), DC electrical conductivity, Scanning Electron Microscopy Energy Dispersive X-ray Spectroscopy (SEM-EDS), and DSC-TG methods.

  • IMN and TIMN clays were explored for the removal of methylene blue (MB) dye.

  • Up to 90 % removal of MB was achieved within 60 min by IMN and TIMN clays.

  • The driving factors of the adsorption process were categorized as hydrogen bonding, electrostatic attraction, cation exchange, n-π and OH−π interactions.

Water is necessary for life on Earth. Nonetheless, different human activities, whether industrial, urban, or agricultural, make pollution worse. Dyes are used in a variety of industries, including textiles, paper, leather dyes, and the food and cosmetics industries (Batzias & Sidiras 2007). The global production of colorants is approximately 700,000 t per year (Taylor et al. 2021). Synthetic dyes, for example, utilized in the textile industry are released directly into the aquatic environment without any prior treatment. A dye is a substance with two distinct features that are unrelated to one another: color and the ability to be fixed on a support, such as a textile. Dyes with low concentrations in water (even less than 1 kgm−3 for some dyes) are noticeable, undesirable and persistent in the environment. The first medical dye was created by William Henry Perkin (quinine). This has benefited the industrial dye synthesis industry (Delgado-Vargas & Octavioparedes-Lopez 2003; Robert et al. 2004). The toxicity of various dyes has been studied in several studies on aquatic organisms (fish, algae, bacteria, etc.) and mammals (mutagenic, mortality and carcinogenic impacts). Furthermore, studies on the effect of dyes on the activity of both anaerobic and aerobic bacteria in wastewater treatment systems have been conducted. According to studies on various commercial dyes (Clarke & Anliker 1980; Thai & Ruey-Shin 2012), basic dyes are the most toxic to algae. Methylene blue (MB), one of the most common cationic dyes, is a heterocyclic aromatic chemical compound, which heavily applied in the food, rubber products, cotton and wool industries, wood and silk dyeing sectors (Vargas et al. 2011).

The aforementioned industries' effluent contains significant levels of MB (Beltrán-Heredia et al. 2011). A salt used as a color and medication is MB, also known as methylthioninium chloride (Modarai et al. 2002). As a medication, it is primarily utilized to treat methemoglobinemia (British National Form et al. 2015). It is used in particular to treat symptoms that do not go away after receiving oxygen treatment or methemoglobin levels exceeding 30%. Before this, it was recommended against using it to treat urinary tract infections and cyanide poisoning. It is usually administered via vein injection. Due to the constant structure of MB and its limited capacity to biodegrade, utilizing this dye will result in several significant environmental issues. Permanent exposure to MB will cause increasing in heart beats, cyanosis, shock, jaundice and irritation to the skin in humans (Xiao et al. 2015). Many water pollution control projects have been completed in recent years as a result of this major threat to aquatic life and the health of human populations because they are highly charged with highly toxic, harmful substances, responsible for the bad odor and abnormal coloring of the water.

Indeed, several conventional techniques, such as coagulation and flocculation, reverse osmosis, advanced oxidation filtration, electro-dialysis technology, adsorption, etc., have been employed in the removal of dyes from aqueous systems (Koulouchi 2007; Guezzen et al. 2023). However, most of these processes face various challenges and limitations, such as high cost, high energy consumption, complicated equipment, ineffective at low metal concentrations and long reaction times. Nowadays, the adsorption process is one of the effective, low investment and environmentally friendly techniques to remove recalcitrant organic and inorganic compounds from wastewater and landfill leachate (Benhadria et al. 2020; Bennama et al. 2022). Adsorption techniques for wastewater treatment have become more popular in recent years owing to their efficiency in the removal of pollutants too stable for biological methods.

Right now, various materials have been proposed to remove organic and inorganic pollutants form wastewater including activated carbon (Akar et al. 2006; Azharul et al. 2017; Cheng et al. 2018), clay minerals (Elaziouti et al. 2011a, 2011b; Gu et al. 2019; Guezzen et al. 2023; Ssouni et al. 2023), diatomite (Mohamed et al. 2019; Ebrahimi & Kumar 2021), agricultural residues (Robinson et al. 2002; Elaziouti et al. 2011a, 2011b; Bennama et al. 2022), layered double hydroxides (HDLs) (Tarmizi et al. 2019; Bouteiba et al. 2020a, 2020b) and other materials (Elaziouti et al. 2015; Dai et al. 2018; Bouhadjar et al. 2019; Benhadria et al. 2020).

An ideal potential adsorbent should have an adequate capacity with a large surface area, both thermally and chemically stable, abundantly available, selective, low cost, sustainable and easily regeneratable (Manyangadze et al. 2020; Ebrahimi & Kumar 2021).

Interstratified illite/smectitic (I/S) (montmorillonite in our case; I/M) are 2:1 dioctahdedral phyllosilicates and composed of non-expandable layers of illite and expandable layers of montmorillonite. The crystal structure of I/S or the stacking of illitic and smectitic interlayers can be described by the ‘McEwan crystallite’ or ‘fundamental particles’ models. The McEwan crystallite is considered a sequence of nonexpendable illitic and expandable smectitic interlayers separated by 2:1 layers. Fundamental particles are defined by 2:1 layers: a single 2:1 layer is considered as a smectite particle, and layers with fixed interlayer potassium are considered as illite particles. The structure model of interstratified illite-smectite described by McEwan crystallite and fundamental particles is depicted in Figure 1 (Wang & Wang 2021). In illite layers, the interlayer cations are prominently potassium ions. These are non-hydrated, due to how they are ‘fixed’ in the ditrigonal cavities on the surfaces of the tetrahedral sheet and the substitutions predominantly take place in the tetrahedral sheets. As a result of the non-hydrated nature of its interlayer cations, it is a non-swelling clay mineral. Since only cations at the external surfaces are exchangeable, illite generally presents lower CEC than smectite. Conversely, the interlayer cation in the montmorillonite layers, predominately sodium, has the capacity to become hydrated. The isomorphic substitutions take place both in the tetrahedral and octahedral sheets and these substitutions impart a permanent negative charge that is compensated by cation adsorption on the basal surfaces. The amount of these adsorbed cations corresponds to the cation exchange capacity (CEC) of the clay. Besides the cation exchange properties, 2:1 layer clays present pH-dependent sorption properties because of the edge sites, similar to those occurring on the oxide's surface, and that can be protonated or de-protonated (Van Holphen 1977). Surface complexation may take place on these edge sites.
Figure 1

Structure models of I–S described by McEwan crystallite and fundamental particles (Wang & Wang 2021).

Figure 1

Structure models of I–S described by McEwan crystallite and fundamental particles (Wang & Wang 2021).

Close modal
Figure 2

XRD pattern of TIMN sample (a). Inset : XRD pattern of IMN sample (b).

Figure 2

XRD pattern of TIMN sample (a). Inset : XRD pattern of IMN sample (b).

Close modal

To date, few studies dealing with the removal of inorganic and synthetic pollutants by the interstratified clays are reported in the literature (Hajjaji et al. 2006; Missana et al. 2008; Da Silva & Guerra 2013; Ahrouch et al. 2019a, 2019b; Taibi et al. 2020).

In this work, Interstratified illite-montmorillonite (IMN) clays abundant in the Naima area (Tiaret-Algeria) were used as an alternative adsorbent to remove MB dyes from aqueous solutions. To understand the adsorption mechanism and to know the possible interactions between different dye functions and interstratified clay, the pristine IMN and its physically and chemically treated interstratified illite-montmorillonite form (TIMN) clays were characterized by XRD, FTIR, SEM-EDS, XRF, DSC-TG and DC methods. To optimize the adsorption parameters of the MB dye by interstratified clays, the adsorption kinetics of MB were examined under the impact of three various parameters including contact time, initial dye concentration and temperature. To fully explain the adsorption mechanism, kinetic data were correlated to the pseudo-first-order, pseudo-second-order and Elovich models. The adsorption isotherms for MB dye removal by clay materials were also adjusted using Langmuir, Freundlich and Dubinin–Radushkevich (D–R) isotherm models. Besides, the thermodynamic parameters, such as enthalpy, entropy and the free energy of adsorption, were determined in detail. To analyze the sorption behavior of MB dye on the interstratified clays, a mechanistic model for interpreting the sorption data in the illite-montmorillonite system was developed. Eventually, a comparison study between the adsorption capability values of our clays to that of other clay materials in previous relevant studies for MB removal was performed.

Chemicals and materials

Chemicals used in this study, such as NaCl (CAS. 7647-14-5), KOH (CAS. 1310-58-3), NaOH (CAS. 1310-73-2) and AgNO3 (CAS. 7761-88-8) with the highest analytical purity were obtained from Aldrich chemical company ltd. MB was purchased from Biochem. All the chemicals used in this study were of analytical grade without further purification. MB dye has been used to identify the surface area of clay minerals for decades. MB is a cationic dye in water that is adsorbed by negatively charged clay surfaces. The molecular structure and chemical properties of MB dye are illustrated in Table 1. Natural illite-montmorillonite of Naima region (IMN) was obtained from the region of Naima–Tiaret–Algeria.

Table 1

3D Molecular structure and physical properties of methylene blue dye (MB) (3D molecular structure was created by CrystalMaker software)

Molecular structure in 3D presentationChemicals properties
 



Chemical name (IUPAC)
Molecular formula
λmax (m)
Molecular weight (kg mol−1)
Solubility in water at 20 °C (kg m−3)
Melting point (°C)
CAS number 
chlorure de 3,7-bis (diméthylamino) phénothiazin − 5-ium
C16H18CIN3S
0.665 × 10−6
0.319
0.040
190
61-73-4 
Molecular structure in 3D presentationChemicals properties
 



Chemical name (IUPAC)
Molecular formula
λmax (m)
Molecular weight (kg mol−1)
Solubility in water at 20 °C (kg m−3)
Melting point (°C)
CAS number 
chlorure de 3,7-bis (diméthylamino) phénothiazin − 5-ium
C16H18CIN3S
0.665 × 10−6
0.319
0.040
190
61-73-4 

Samples preparation

The IMN material was first dried in sunlight, disintegrated into small pieces and then passed through a 2 mm sieving. A fraction of 0.020–0.1 kg was treated with sodium hydroxide solution (NaOH; 0.1 M) and heated at 70 °C for 3.6 × 10+2 s under continuous stirring. The obtained solid material was filtered, rinsed repeatedly with distilled water until free Cl was not detected in the suspension (AgNO3 test) and was dried at 100 °C overnight to constant weight. It was called TIMN.

Acid–base surface properties

The properties of solid surfaces were determined using potentiometric titration. Titration was performed in a 0.01 M NaCl electrolyte solution with 0.01 M potassium hydroxide (KOH). An acid–base surface reaction produces the electrostatic charge's solid surface. The mass conservation equation, which is based on surface hydroxyl group reactions, connects them. The surface charge Q is determined for each acid–base titration point as follows (Equation (1)):
(1)
where m (kg m−3) signifies the test sample, Cb (mol m−3) is the supplied main quantity and Q (mol kg−1) indicates the surface charge. Thus, we can determine how pH affects the solid Q's average surface charge. The test portion's results (m = 10−4 kg m−3).

DC electrical conductivity

With a bridge (LCR-821, an Instek LCR meter), the DC conductivity of clay samples was assessed at frequencies (f) ranging from 104 to 106 Hz. The samples were made into a 12-mm-diameter disk using the hydraulic hot press (3.0 × 107 N m−2) and then sandwiched between two platinum parallel plate electrodes that were kept apart from one another using Teflon film. A two-probe approach is used to test the instrument's resistance, and the following equation is used to determine the resistivity and conductivity:
(2)
where, respectively, I, V, S and e stand for current, employed voltage (50 Hz), both thickness and sample areas. The instrument raises the temperature of the samples from 27 to 167 °C by connecting them to the heated chamber and temperature controller. The RS-232 terminal provides access to Windows Private Software, and each system is linked to a typical PC monitor.

Characterization

X-ray diffraction (XRD) was conducted utilizing a Siemens D 5000 automatic diffractometer with Cu-K radiation (=0.154178 × 10−9 m) and a rear monochromator to remove iron fluorescence. A 0.2 × 10−3 m rear slit was inserted, while the front and back windows were both set at 2 × 10−3 m. Low rotational speed (0.01°s−1) was chosen to produce distinct spokes over 10–80° for both the IMN and TIMN samples. A Shimatzu 8400 spectrometer with a resolution of 0.02 m−1 and a range of 4–45 × 104 m−1 was used to gather FTIR spectra. An FEI Quanta 650 Scanning Electron Microscopy (SEM) from Bruker Nano GmbH in Berlin, Germany, connected to BRUKER XFlash 6/10 energy dispersive X-ray detector (EDS) was used to assess the elemental composition and powder morphology. The elements in crude clay purification were analyzed utilizing a Bruker S1 Titan XRF X-ray fluorescence (XRF) Spectrometer. An Instek 821 LCR meter with a temperature range of 27–167 °C was employed to measure conductivity. An Agilent spectrophotometer agile model was utilized for the optical density analysis, which was controlled by an 8543 computer. The peak wavelengths are obtained via automatic scanning between 2 × 10−7 and 8 × 10−7 m. To prevent interference over time, adsorbents are developed. We monitored the pyrolysis of these clays using DSC-ATG. SETARAM-Labs evo TGA was used. The samples (m = 0.026 × 10−3 kg) were put in a boat and heated at a rate of 10 °C per minute with an airflow ranging from 25 to 1,000 °C.

Batch adsorption

The adsorption of MB dye by IMN and TIMN adsorbents was investigated using batch experiments. 8 × 10−5 m3 of dye solution was added into an Erlenmeyer flask with 10−4 kg of the absorbent. The solution was then shaken in a water bath shaker at room temperature until equilibrium was attained. The supernatant solution was separated by filtration, and the residual dye concentration was analyzed using the spectrophotometry method.

Initial concentration effect

We examine the impact of the initial dye concentration. We prepare six samples of MB solution with various MB concentrations C0 = 0.02, 0.04, 0.08, 0.12, 0.16 and 0.2 kg m−3 in a volume of 0.5 × 10−4 m3 as well as a test sample of 10−4 kg of clay, with magnetic stirring at 300 rpm and room temperature. We measure the absorbance of the solution for the various concentrations at the end of the reaction (Equation (3))
(3)
where qe is the pollutant concentration per unit mass of clay (kg kg−1), C0 is the starting concentration (kg m−3), Ce is the equilibrium concentration (kg m−3), V is the adsorbate volume (m3) and m is the adsorbent mass (kg).

Kinetic modeling

The model of pseudo-first order is used to investigate the experimental kinetic data utilizing Lagergren's equation (Hosseini-Bandegharaei et al. 2010) and expression (Equation (4)).
(4)
where qt stands for the adsorption capacity at time t (kg kg−1) and k1 refers to the pseudo-first-order kinetic rate constant (s−1). Calculating k1 and Qe involves finding the slope (k1) and analyzing (ln) of the linear plots of ln(qeqt) vs t (Equation (5)) shows how the data kinetic was further examined utilizing a model of pseudo-second-order (Ho & McKay 1999):
(5)
where k2 is the pseudo-second-order (kg kg−1 s−1) rate constant. Therefore, a straight line with slope and explanation equal to 1/qe and 1/qe2k2 is obtained from plotting t/qt versus t.
The basic assumptions of the Elovich model were (1) the activation energy increased with adsorption time and (2) the surface of the adsorbent was heterogeneous. The Elovich model is an empirical model without definite physical meanings. It is commonly used to model the chemisorption of gas onto a solid. The Elovich model has been described by the following equation (Elovich & Larinov 1962):
(6)
where the preliminary adsorption rate, mol kg−1 min−1, β is proportional to the surface area covered and the energy activation involved in chemisorption.

Isotherm adsorption modeling

The Langmuir adsorption isotherm has relied on the hypotheses that there are comparable sites, only one monolayer forms during the reaction, the adsorbate is immobile and there is no adsorbate–adsorbent interaction. The Langmuir equation, also known as Equation (7) has the following linear form (Langmuir 1916).
(7)
where qe is the quantity of metal adsorbed per gram of adsorbent (kg kg−1) and Ce is the concentration of equilibrium of the examined metal (kg m−3). The Langmuir constants qe and KL link adsorption energy (m3 kg−1) and capacity (kg kg−1). The slope and explanation of the linear plots of Ce/qe vs Ce are usable to measure these constants. The Freundlich isotherm, which expresses adsorption on heterogeneous solid surfaces with an infinity site, was applied to the adsorption data. The Freundlich equation (Freundlich & Umber 1906) is expressed in logarithmic form (Equation (8)):
(8)

KF (m3 kg−1) and 1/n are Freundlich constants. According to predictions, the adsorption process will either be linear (n = 1), chemical (n < 1) or a beneficial physical procedure (n > 1). The intercept and slop of the linear plot of ln qe vs ln Ce were used to determine KF and 1/n.

The Dubinin–Radushkevich adsorption isotherm (Dubinin et al. 1947) is used to describe the adsorption mechanism with a Gaussian energy distribution on a heterogeneous surface. The Dubinin–Radushkevich adsorption isotherm does not assume homogeneous surface or constant sorption potential and helps to determine the apparent energy of adsorption. The model's linear form is given by the following equation.
(9)
where ε is the Polanyi potential equation (Equation (10))
(10)
where R represents the universal gas constant (8.314 J K−1mol−1), T (°C) demonstrates the absolute temperature and β ± (kg2 J−1) is a constant related to adsorption energy. The intercept and slope of the plot ln qe against ε2 are used to calculate qm and β. The mean adsorption energy E (J mol−1) is calculated utilizing the following equation.
(11)

The mechanism of withdrawal is mainly physical connection when E < 8 kJ/mol and ion exchange if E 8 × 10−3 J mol−1E ≤ 16 × 10−3 J mol−1 (Felhi et al. 2008).

Cation exchange capacity

The relative ability of soils to store one particular group of nutrients, the cations, is referred to as cation exchange capacity or CEC. It has two origins. One origin is isomorphic substitution in the tetrahedral- and/or octahedral sheet of the clay mineral layer. Substitution of aluminum by magnesium or silicon by aluminum leads to a negative net charge. This part of the CEC is considered to be constant since it is almost not sensitive to the pH of the system. The second origin is the dissociation of aluminol groups on the edges. Since the acidity of these groups is weak, the edge charges are pH dependent and the CEC depends on the pH. Table 2 presents the estimated CEC values for IMN and TIMN samples along with these reported for different materials in the literature (Eloussaief et al. 2009). The CEC of the IMN and TIMN, estimated by the MB method (Pal & Ghoshal 1977) are 35–50 cmol (+) kg−1 and 51 cmol (+) kg−1 of IMN, respectively.

Table 2

Cation exchange capacity (CEC) values of IMN, TIMN and clay minerals and reported materials in the literature

I.SIMNaTIMNaKIKOMSLS to SLLC
 (Eloussaief et al. 2009
CEC (cmol (+) kg−135–50 51 3–15 15–40 80–100 200–400 1–5 5–10 5–15 >30 
I.SIMNaTIMNaKIKOMSLS to SLLC
 (Eloussaief et al. 2009
CEC (cmol (+) kg−135–50 51 3–15 15–40 80–100 200–400 1–5 5–10 5–15 >30 

aExperimental results; IMN, illite-montmorillonite of Naima; TIMN, treated illite-montmorillonite of Naima; K, kaolinite; I, illite; M, montmorillonite; OM, organic matter; S, sand; LS to SL, loamy sand to sandy loam; L, loam and C, clay.

Surface acidity

Commonly, the surface active sites of aluminosilicates are characterized in terms of Broensted and Lewis acidity/basicity comprising exchangeable cations, coordinatively unsaturated ions Al3+, Mg2+, Fe3+, acid/basic hydroxyl groups and oxygen anions of aluminosilicates (Novikova et al. 2014). Surface Broensted acid sites (donate protons) and Lewis acid sites (accept electrons) are represented by different surface groups and exchangeable ions (Alda et al. 2017). In the aspect of mineralogy, lattice defects such as isomorphous substitution present in the clay or nanosheet surface are known to significantly affect clay properties. The resulting structure surfaces can be either electrically neutral or negatively charged (Zhang et al. 2017). The nature of the surface sites of the IMN sample is determined by using the potentiometric titration method. As reported in Table 3, the surface of IMN clay is positively charged in the whole range of pH acid. The weak isomorphic substitution of low valence cations for higher valence cations and the influence of the contaminant minerals such as kaolinite and illite are expected to be the primary reasons for the elevated yield of acidic products (Šucha et al. 2009). It is wealthy to know that kaolinite and illite, which are alumino-silicate clays, have higher Lewis acid components. Besides, Brönsted acid sites are characterized by MVI–OH (M = Si, Al, Mg, Fe), in agreement with FTIR results which revealed an intense band at 16–14 × 104 m−1 region.

Table 3

The surface acidity of IMN clay sample

pH 5.45 5.55 5.59 5.62 5.83 5.90 6.2 7.5 
Surface acidity Q > 0 Q > 0 Q > 0 Q > 0 Q > 0 Q > 0 Q > 0 nd 
pH 5.45 5.55 5.59 5.62 5.83 5.90 6.2 7.5 
Surface acidity Q > 0 Q > 0 Q > 0 Q > 0 Q > 0 Q > 0 Q > 0 nd 

nd, not detected.

XRD analysis

XRD is the primary tool for identifying and quantifying crystalline compounds. Powder XRD diffractograms characterize minerals and elements present in solids. Clay powders have been distinguished into smectites and kaolinites based on XRD patterns. The XRD patterns of IMN and TIMN samples, as presented in Figure 2, exhibited mainly basal reflections of montmorillonite, and illite with interstratified illite-montmorillonite, quartz and kaolinite as the major phase, besides minor amounts of muscovite and chlorite minerals. In the XRD patterns of IMN, the peaks (001) located at 26.49 ° and (003) at 217.17° obviously corresponded to the montmorillonite fraction while the illite phase was evidenced by the main peak (002) at 28.87°. The basal spacing at 7.20 and 3.58 × 10−10 m matching to the (001) and (002) reflections, approving the presence of kaolinite. The interstratified illite-montmorillonite (I/M) was evidenced by the main peak located at 2θ = 3.42° with a calculated basal spacing of 25.83 × 10−10 m. Additionally, quartz was presented by the prominent peak (011) at 3.33 × 10−10 m. In the TIMN sample, no significant change in the XRD profile was observed during the purification process. However, the decrease in intensity of the quartz reflections at 2θ = 27.8° (3.2 × 10−10 m), indicates the effectiveness of the purification process (Bhattacharyya & Gupta 2008).

XRF analysis

Clay mineralogy is useful in characterizing the nature of clay minerals and is critical to many geoscience projects and understanding of palaeoclimate. As briefly mentioned in Table 4, chemical analysis showed three primary ingredients of IMN and TIMN samples: silica (SiO2), alumina (Al2O3) and ferric oxide (Fe2O3). Besides, the IMN clay contained Ca, K, and Mg Ti oxides, as minor amounts, with other metal cations, and trace fractions. The mass fraction of SiO2 and Al2O3 increased from 42.2 to 46.45% and from 11.97 to 12.98%, respectively. Conversely, the CaO and MgO mass fractions decreased from 1.52 to 1.23% and from 2.05 to 1.97%, respectively. The SiO2/Al2O3 molar ratio of 3.52 and 3.57 for IMN and TIMN, respectively. The prominent K2O content may indicate the possible presence of large amounts of illite in both samples (Hamdaoui et al. 2008).

Table 4

Physico-chemical properties of the IMN and TIMN clay samples

ElementsIMN (wt.%)TIMN (wt.%)
SiO2 42.21 46.45 
Al2O3 11.97 12.98 
Fe2O3 5.8 5.48 
K23.32 3.45 
MgO 2.05 1.97 
CaO 1.52 1.23 
TiO2 0.84 0.89 
Ba 0.05 0.04 
P2O5 0.04 nd 
Rb 0.03 0.02 
MnO 0.02 0.03 
Sr 0.02 0.01 
0.01 0.01 
Zr 0.01 0.01 
Cl 0.01 nd 
Ta 0.009 nd 
0.006 0.006 
Ag 0.005 nd 
Cu 0.004 0.007 
Ni 0.003 nd 
ElementsIMN (wt.%)TIMN (wt.%)
SiO2 42.21 46.45 
Al2O3 11.97 12.98 
Fe2O3 5.8 5.48 
K23.32 3.45 
MgO 2.05 1.97 
CaO 1.52 1.23 
TiO2 0.84 0.89 
Ba 0.05 0.04 
P2O5 0.04 nd 
Rb 0.03 0.02 
MnO 0.02 0.03 
Sr 0.02 0.01 
0.01 0.01 
Zr 0.01 0.01 
Cl 0.01 nd 
Ta 0.009 nd 
0.006 0.006 
Ag 0.005 nd 
Cu 0.004 0.007 
Ni 0.003 nd 

nd, not detected.

FTIR analysis

Infrared spectroscopy (IR) is extensively used to determine and investigate the structure of the various mineral phases. It provides information ranging from the detection and identification of specific or minor mineral constituents, hardly accessible from XRD techniques, to the determination of the stacking order and ordering pattern of substituting cations in clay minerals (Keren 1988). Figure 3 illustrates the FTIR spectrum of IMN clay. From the FTIR spectrum obtained, the following minerals were classified: OH group indicated by two adsorption bands ranging between 32 and 38 × 104 m−1 and between 16 and 17 × 104 m−1. The band near 16 × 104 − 17 × 104 m−1 is attributed to the bending vibration of adsorbed hydroxyl groups of water. Bands in the range 32 × 104–38 × 104 m−1 with an intense band and landslide in 36.25 and 34 × 104 m−1 characteristic of montmorillonite related to stretching vibrations of OH groups of the octahedral coordinated either 1AL + 1Mg (36.40 × 104 m−1) or 2Al (36.20 × 104 m−1). Water: The bending vibrations of water molecules are characterized by the band at 34 × 104 m−1. The band located around 16.30 × 104 m−1 is ascribed to deformation vibrations of adsorbed water molecules between the sheets. Si–O group: the Si–O are characterized by the intense band between 9 and 12 × 104 m−1 and centered around 10.40 × 104 m−1 are attributed to the stretching vibrations of the Si–O. The lower wavenumbers at 5.25, 4.68 and 4.25 × 104 m−1 are indicative of a greater proportion of Si–O–AlVI, Si–O–MgVI and Si–O–Fe in the clays. MVI-OH (M=Al, Mg, Fe) bonds or illite-montmorillonite. The sharing of the OH group between the atoms Fe and Al in the octahedral position may move Al–OH vibrations at low frequencies around 8.15 and 9.15 × 104 m−1. Thus the vibration Mg–O and Mg–OH (combined with that of Si–O) located at 5.30 and 5.60 × 104 m−1, respectively, highlighted the presence of illite-montmorillonite mixtures. Kaolinite: the intense band at 36.94 × 104 m−1 corroborated the presence of kaolinite. Quartz: quartz is usually detected by two characteristic bands near 7.90–7.95 × 104 m−1 and 7.50–7.55 × 104 m−1. Calcite: the stretching band at 14.35 × 104 m−1, corresponding to the CO stretching of carbonate, is attributed to calcite (Ulmanu et al. 2003).
Figure 3

FTIR spectrum of IMN clay samples.

Figure 3

FTIR spectrum of IMN clay samples.

Close modal

DC electrical conductivity

The phenomena of electrical conductivity in soils are subject to different parameters, internal and external, at both micro and macroscale. The electrical conductivity is frequency and temperature-dependent. The electrical conductivity in soil and/or soil–water mixture is the combination of surface conduction, particle conduction and pore fluid conduction. The impact of the temperature on the electrical conductivity of the clays used in this study is reported in Figure 4. The electrical conductivity of both clays showed different sensitivities to temperature. For the TIMN sample, the electrical conductivity sharply increased from 8.9 × 10−7 Ω−1 m−1 at 8 °C to 1.45 × 10−6 Ω−1 m−1 at 32 °C and decreased linearly with rising temperature, almost reaching 2.23 × 10−7 Ω−1 m−1 at 140 °C. For IMN clay, the electrical conductivity slightly increased from 2.12 × 10−7 to 1.69 × 10−6 Ω−1 m−1 as the temperature was increased from 8 to 100 °C and then declined severely to 9.13 × 10−8Ω−1 m−1 at 140 °C. For low temperature (8 °C ≤ T ≤ 72 °C), significant electrical conductivity (σ = 1.45 × 10−6 Ω−1 m−1) for TIMN clay was observed, whereas a significant conductivity response (σ = 1.69 × 10−6Ω−1 m−1) for IMN clay sample as found for high temperature (72 °C ≤ T ≤ 140 °C). Higher electrical conductivity is associated with moisture content and saturation of clay (Dafalla et al. 2018). However, there are many parameters that can affect the measurement of the electric conductivity such as clay texture, porosity, particle-size distribution, mineralogical composition, form and distribution of water in clay, salt content, charge carriers and temperature. An increase in temperature can result in a rise in clay electrical conductivity. The mobility of Na+ counter-ions and the charge carriers are the main driving force for increasing the electrical conductivity of TIMN clay. However, the reduction in conductivity with temperature is due to a smaller proportion of these ions in the Gouy layer and/or a decrease in their mobilities. For the pristine IMN clay, in contrast, the optimum moisture content (saturation) is found to be the primary cause for rising the electrical conductivity, while, the decline in electrical conductivity with temperature is ascribed to the decrease in the mobility of the charge carriers and the moisture exclusion effect (via drainage and evaporation process).
Figure 4

Conductivity measurement of IMN and TIMN clay samples.

Figure 4

Conductivity measurement of IMN and TIMN clay samples.

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SEM analysis

Scanning electron microscopy (SEM) or SEM analysis is a powerful analytical technique to perform analysis on a wide range of materials, at high magnifications, and to produce high-resolution images. SEM is a test process that scans a sample with an electron beam to produce a magnified image for analysis and is used very effectively in microanalysis and failure analysis of solid inorganic materials. Figure 5 shows SEM images of clay samples with varying resolutions. The SEM image of the bare IMN (Figures 5(a)–5(d)) indicated a uniform paste with a few dolomite rhombohedra. The sample had lamellar flakes and a spongy structure, that might be a typical SEM micrograph of sodium montmorillonite. SEM images of clay samples at various resolutions are indicated in Figure 5. The SEM image of the bare IMN (Figures 5(a)–5(d)) showed a uniform paste with a few dolomite rhombohedra. The sample resembled a typical sodium montmorillonite SEM micrograph, with lamellar flakes and a spongy structure. On the other hand, in the RM sample, the TIMN clay particles take the form of clusters of fine aggregates and platelets in the shape of sticks with irregular contours, as illustrated in Figures 5(d) and 5(g). Both poorly crystallized kaolinites and illite demonstrate this morphology (Ho & Mckay 1999; Hu et al. 2015).
Figure 5

SEM images of IMN (a–d) and TIMN (e–h) clay samples.

Figure 5

SEM images of IMN (a–d) and TIMN (e–h) clay samples.

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EDS analysis

Energy-dispersive x-ray spectroscopy (EDXS), also known as EDX analysis and EDS analysis, is a qualitative and semi-quantitative X-ray microanalytical technique that can provide information about the elemental composition of a sample. It is useful in identifying metals and certain types of polymeric materials with unique elemental signatures. The energy-dispersive X-ray mapping was carried out to determine the chemical composition of the clay samples. The EDX spectrum shown in Figure 6, obviously reveals the presence of various metal elements within the IMN clay sample (Table 5). There is a significantly high concentration of silicon mainly due to the majority presence of quartz in the sample studied. Meanwhile, the appearance of a new peak corresponding to the carbon element, probably comes from the support grid of the sample. The EDX result largely confirms the presence of the clay phases in relation to the percentage of silicon, aluminum and oxygen. Carbon ions are absent in the spectrum of TIMN clay (Figure 7) and the results basically confirm the removal of carbonate and organic matter during the treatment process. The low potassium fraction and the absence of calcium in the treated clay indicate the efficient exchange of these ions by the sodium species which makes the clay surface more homogeneous, so in this case, we are talking about sodium monotonic clay. As displayed in Table 4, the total net composition for IMN and TIMN are 102.42 and 101.02 wt (%), respectively.
Table 5

Energy-dispersive X-ray test results of the IMN and TIMN clay samples

ElementsComposition
IMN
TIMN
Net wt (%)Normal wt (%)Net wt (%)Normal wt (%)
Silicium (Si) 19.75 19.29 19.74 19.54 
Oxygen (O) 47.95 46.81 47.41 46.93 
Aluminum (Al) 7.56 7.39 7.56 7.48 
Potassium (K) 3.68 3.59 3.65 3.61 
Iron (Fe) 3.48 3.39 3.57 3.54 
Carbon (C) 14.76 14.42 14.33 14.18 
Magnesium (Mg) 1.29 1.26 1.29 1.27 
Titanium (Ti) 0.39 0.39 nd nd 
Sodium (Na) nd nd nd Nd 
Calcium (Ca) 3.56 3.47 3.48 3.44 
Total Wt (%) 102.42 100 101.02 100 
ElementsComposition
IMN
TIMN
Net wt (%)Normal wt (%)Net wt (%)Normal wt (%)
Silicium (Si) 19.75 19.29 19.74 19.54 
Oxygen (O) 47.95 46.81 47.41 46.93 
Aluminum (Al) 7.56 7.39 7.56 7.48 
Potassium (K) 3.68 3.59 3.65 3.61 
Iron (Fe) 3.48 3.39 3.57 3.54 
Carbon (C) 14.76 14.42 14.33 14.18 
Magnesium (Mg) 1.29 1.26 1.29 1.27 
Titanium (Ti) 0.39 0.39 nd nd 
Sodium (Na) nd nd nd Nd 
Calcium (Ca) 3.56 3.47 3.48 3.44 
Total Wt (%) 102.42 100 101.02 100 

nd, not detected.

Figure 6

EDS spectrum of IMN clay samples.

Figure 6

EDS spectrum of IMN clay samples.

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Figure 7

EDX spectrum of TIMN clay samples.

Figure 7

EDX spectrum of TIMN clay samples.

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Thermal behavior (DSC-TG)

Differential scanning calorimetry (DSC) measures the heat flow associated with phase transitions or reactions. Ideally, this technique is used to determine melting point, crystallinity or degree of hardening. While thermogravimetric analysis (TGA) consists in measuring the variation of mass of a material as a function of time and temperature. This technique is used to determine material characteristics such as thermal stability, kinetics of chemical reactions, degradation temperatures and volatility. The thermal decomposition and the heat flow curves of the IMN support were investigated using DSC-TG. Based on the TGA curve in Figure 8, IMN powder displays two well-defined events of weight loss. The first stage of dehydration occurs between 40 and 200 °C due to the departure of surface water and water contained between the layers of the montmorillonite-illite laminate. A mass loss of around 1% associated with a larger first endothermic TGA peak at 100 °C is most likely due to the presence of the smectite/illite layer (Jang et al. 2013). Water adsorbed swelling clays like montmorillonite and beidellite near 140 °C, following these researchers. Dehydration of weakly bound water to the solid continues from 250 °C, with the appearance of a second-weak endothermic TGA peak at 270 °C. This peak is most likely caused by poorly crystallized iron and/or aluminum oxyhydroxides.
Figure 8

The mass loss (DSC-TG) and heat flow curves of the IMN clay sample.

Figure 8

The mass loss (DSC-TG) and heat flow curves of the IMN clay sample.

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Adsorption experiment

Qualitative study

The evolution of maximum absorption bands of dye in aqueous solution at various pH. The location of the absorption bans maxima of dye are collected in Table 6.

Table 6

The position of the absorption bands of MB in aqueous solution as a function of pH ([MB] = 0.05 kg m−3 and T = 25 °C)

Initial pH λ (MB+) (×106 m)λ(MB+)2 (×106 m)R
0.648 – ∞ 
0.668 0.624 1.028 
0.647 – ∞ 
0.668 – ∞ 
11 0.668 0.621 1.029 
13 0.653 0.610 1.053 
Initial pH λ (MB+) (×106 m)λ(MB+)2 (×106 m)R
0.648 – ∞ 
0.668 0.624 1.028 
0.647 – ∞ 
0.668 – ∞ 
11 0.668 0.621 1.029 
13 0.653 0.610 1.053 

The visible spectra of MB in aqueous solution show that MB exhibits a main band at 0.668 × 10−6 m assigned to the absorption of monomers and associated with a shoulder attributed to the 0–1 vibronic transition of monomers MB+ at about 0.605 × 10−6 m nm. The MB monomers have nearly constant absorption bands and absorbance intensities over the pH values in the range of pH between 3 and 13, while the shoulder is most sensitive to the pH solution. The absorbance of the vibronic shoulder at about 0.605 × 10−6 m increases and shifts slightly to 0.624 × 10−6, 0.621 × 10−6 and 0.610 × 10−6 m at pH 7, 11 and 13, respectively, whereas no change is observed in 0.605 × 10−6 m-shoulder at pH 3, 5 and 9, respectively. The increase and the bathochromic shift in 0.605 × 10−6m-shoulder are attributed to the partial self-association of MB monomers as cationic dimmers in face-to-face arrangement to minimize their hydrophobic interaction with water. This metachromatic effect (the replacement of the main absorption band for other absorption bands placed at lower wavelengths) was analyzed by the following formula (Equation (12)).
(12)
where A(MB+) is the absorbance maximum of the MB monomer, A(MB+) n is the absorbance in the shoulder or agglomerate and n is the number of monomers in the agglomerate species. As elucidated in Table 6, the ratio of absorbance intensities R in aqueous solution at pH 3, 7 and 9, respectively, was maximum (R = ∞), while those at pH 5, 11 and 13 were equal to 1.028, 1.029 and 1.053, respectively. The drastic decrease in the R parameter with pH is ascribed to the hydrophobic properties (the hydrophobicity of the aromatic rings and dimethylamine groups) of the dye, resulting in higher agglomerates. Thus, the MB molecules self-associate in order to minimize their contact with water molecules (Elaziouti & Laouedj 2010).

Contact time effect

The effect of time on the adsorption of MB onto IMN is illustrated in Figure 9. The removal of this dye was fast in the first 5 min, and then gradually slowed between 0.3 × 10+3 and 0.6 × 10+3 s until the equilibrium was reached. The adsorption equilibrium time was obtained at 3.6 × 10+2 s. As displayed in Table 3, the sorption efficiency of MB onto IMN was 1.925 × 10−2 kg kg−1.
Figure 9

The adsorption kinetic of MB onto IMN sample (m = 10−4 kg; C0 = 0.04 kg m−3, T = 16 °C and pH = 7).

Figure 9

The adsorption kinetic of MB onto IMN sample (m = 10−4 kg; C0 = 0.04 kg m−3, T = 16 °C and pH = 7).

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Initial concentration effect

The effect of initial dye concentration on the adsorption process of MB using IMN and TIMN as adsorbent materials was conducted in the range of 0–3.6 × 10+2 s. The results, as represented in Figure 10, indicated that the adsorption capacity of both IMN and TIMN increased linearly from 0 to 3.97 × 10−2 kg kg−1 when the initial concentration of dye was increased from 0 to 0.080 × 10+2 kg m−3, and then gradually slows, almost reaching 4.49 × 10−2 kg kg−1 and 5.09 × 10−2 kg kg−1 at 0.160 kg m−3, for IMN and TIMN, respectively. Further increase in the dye concentration beyond 0.160 kg/m3 the adsorption capacity steadily decreased, almost reaching 4.31 × 10−2 kg kg−1 for IMN and 4.51 × 10−2 kg kg−1 for TIMN, due to the reduction of the thermal mobility of the adsorbed aggregates.
Figure 10

Effect of the initial concentration of MB onto IMN and TIMN clay samples.

Figure 10

Effect of the initial concentration of MB onto IMN and TIMN clay samples.

Close modal
The adsorption kinetics of MB dye onto IMN material at different initial dye concentrations, as illustrated in Figure 11, were treated with pseudo-first-order, pseudo-second-order and Elovich models. The adsorption rate constants (K1 ans K2), the theoretical equilibrium adsorption capacity (qe,th), the initial sorption rate (α) is the desorption constant (β), calculated experimentally from the linear plots of Ln (qeqt) versus t (Figure 11(a)), t/qt versus t (Figure 11(b)) and qt versus Ln t (Figure 11(c)) at various dye concentrations are summarized in Table 7. The pseudo-second-order model showed the highest value of correlation coefficient (R2 = 0.99) compared with the other models. Besides, the equilibrium values of the MB adsorption capacity (qe,th) calculated from the pseudo-second-order kinetic model were almost similar to the experimental data (qe,exp) for both IMN and TIMN. This finding indicated that the pseudo-second-order model had a very good agreement to describe the MB dye adsorption by IMN surface. As a result, the pseudo-second-order model accurately depicts valence forces by having MB and the treated IMN clay share or exchange electrons and also highlights that the process was mainly controlled by chemical sorption. This result is similar to other recently published studies (Hoang et al. 2022; Soleimani et al. 2023).
Table 7

Kinetic model constants and correlation coefficients for the adsorption of MB onto IMN at various dye concentrations

Experimental resultsPseudo-first-order kinetic model
Pseudo-second-order kinetic model
Elovitch model
qe, exp (kg kg−1)qe,th (kg kg−1)K1 (s−1)R2qe,th (kg kg−1)K2 (kg kg−1s−1)R2αΒR2
1.925 × 10−2 2.55 × 10−2 −0.0024 0.54 1.934 × 10−2 3.484  0.99  966.673  1.11 0.49 
Experimental resultsPseudo-first-order kinetic model
Pseudo-second-order kinetic model
Elovitch model
qe, exp (kg kg−1)qe,th (kg kg−1)K1 (s−1)R2qe,th (kg kg−1)K2 (kg kg−1s−1)R2αΒR2
1.925 × 10−2 2.55 × 10−2 −0.0024 0.54 1.934 × 10−2 3.484  0.99  966.673  1.11 0.49 
Figure 11

(a) Plot of Ln (qeqt) vs time for the kinetic of MB adsorption onto IMN sample at different initial dye concentrations, (b) plot of t/qt vs time for the kinetic of MB adsorption onto IMN sample at different initial dye concentrations, and (c) plot of qt vs Ln t for the kinetic of MB adsorption onto IMN sample at different initial dye concentrations.

Figure 11

(a) Plot of Ln (qeqt) vs time for the kinetic of MB adsorption onto IMN sample at different initial dye concentrations, (b) plot of t/qt vs time for the kinetic of MB adsorption onto IMN sample at different initial dye concentrations, and (c) plot of qt vs Ln t for the kinetic of MB adsorption onto IMN sample at different initial dye concentrations.

Close modal

Adsorption isotherm

The adsorption isotherm is a crucial fundamental for describing the mechanism of dye removal onto the adsorbent surface. As represented in Figure 12, the adsorption isotherms of MB onto IMN and TIMN materials are L type according to Gilles et al. classification (Giles et al. 1960). The maximum adsorption capacities, qm,exp, were 4.327 × 10−2 and 4.914 × 10−2 kg kg−1 for IMN and TIMN, respectively.

Most of the study of adsorption characteristics is confined to the analysis of mono- and bi-parametric isotherm models (and rarely, linearized multi-parametric isotherm models), due to the difficulties in solving higher parametric models, as well as fairly satisfying results by lower-parametric models. To fit adsorption equilibrium data, three isothermal models, Langmuir, Freundlich and Dubinin–Radushkevich (D–R) were used in the present study. The linearized Freundlich, Langmuir and D–R isotherms for MB onto IMN and TIMN materials are shown in Figures 13(a)–13(c), and their model parameters are summarized in Table 8.
Table 8

Langmuir, Freundlich and (D–R) models

Langmuir model
Freundlich model
D–R model
I.S.qe,th (kg kg−1)KL (m3kg−1)RLR2qe,th (kg kg−1)KFnR2qe,th (kg kg−1)B103E (J/mol)R2
IMN 4.673 × 10−2 0.82 × 10−3 0.006 0.485 4.782 × 10−2 20.09 5.46 0.58 4.295 × 10−2 2 × 10−7 0.58 0.63 
TIMN 2.739 × 10−2 4.62 × 10−3 0.001 0. 03 5.088 × 10−2 21.11 5.34 0.36 4.339 × 10−2 9 × 10−7 0.75 0.91 
Langmuir model
Freundlich model
D–R model
I.S.qe,th (kg kg−1)KL (m3kg−1)RLR2qe,th (kg kg−1)KFnR2qe,th (kg kg−1)B103E (J/mol)R2
IMN 4.673 × 10−2 0.82 × 10−3 0.006 0.485 4.782 × 10−2 20.09 5.46 0.58 4.295 × 10−2 2 × 10−7 0.58 0.63 
TIMN 2.739 × 10−2 4.62 × 10−3 0.001 0. 03 5.088 × 10−2 21.11 5.34 0.36 4.339 × 10−2 9 × 10−7 0.75 0.91 

Correlation coefficients and parameters for adsorption of BM IMN and TIMN caly samples.

I.S., identification sample.

Figure 12

Adsorption isotherms for MB dye onto IMN and TIMN clay samples.

Figure 12

Adsorption isotherms for MB dye onto IMN and TIMN clay samples.

Close modal
Figure 13

(a) Plot of 1/qe vs 1/Ce for the kinetic of MB adsorption onto IMN and TIMN caly samples, (b) plot of Ln qe vs Ln Ce for the kinetic of MB adsorption onto IMN and TIMN caly samples, (c) plot of Ln qe vs ε2 for the kinetic of MB adsorption onto IMN and TIMN clay samples.

Figure 13

(a) Plot of 1/qe vs 1/Ce for the kinetic of MB adsorption onto IMN and TIMN caly samples, (b) plot of Ln qe vs Ln Ce for the kinetic of MB adsorption onto IMN and TIMN caly samples, (c) plot of Ln qe vs ε2 for the kinetic of MB adsorption onto IMN and TIMN clay samples.

Close modal

The usual way to validate a model is to consider the goodness-of-fit using the linear regression coefficients, R2. Results from using the Langmuir, Freundlich and D–R isotherm models have low regression coefficient values (R2 ≤ 0.91), suggesting that it is not appropriate to use these types of linearization for this study. Additionally, the theoretical equilibrium adsorption capacities, qe,th, for the whole applied models were significantly similar to that of the experimental data, excluding that deduced from the linear regression of the Langmuir for the TIMN sample. Besides, the obtained free energy (E) values for adsorbing MB using IMN and TIMN ranged from 0.58 to 0.75 × 10+3 J mol−1, respectively, which are less than 8 × 10+3 J mol−1, signifying that the process is physisorption (Elaziouti et al. 2015).

However, using only the linear regression method may not be appropriate for comparing the goodness of fit of isotherm models. This is because an occurrence of the inherent bias resulting from linearization may affect the deduction. Therefore, in addition to the linear regression analysis, the experimental data were tested with Chi-square χ2 (Equation (13)): and average percentage errors (APE) (Equation (14)) to determine the best fitting isotherm model (Subramanyam & Das 2009; Zare et al. 2022).
(13)
(14)
where N value is the observation data number of the experiment points, while the subscripts ‘exp’ and ‘the’ represent the experimental and theoretical values of qe.

The smallest Chi-square χ2 and APE values designate the similarity between the experimental and the theoretical data and reflect the best-fit isotherm model for the adsorption process (Auta & Hameed 2012). Table 9 presents two error functions (Chi-square χ2 and APE) extracted from the linear regression of the Langmuir, Freundlich and D–R isotherm models.

Table 9

Comparison of linearized isotherm models (Chi-square χ2 and average percentage errors (APE)) for MB adsorption onto IMN and TIMN caly samples

Langmuir model
Freundlich model
D–R model
I.S.χ2APEχ2APEχ2APE
IMN 0.0002554 7.9838 0.0004310 10.4910 0.00000245 0.0075101 
TIMN 0.0172793 44.266 0.0000591 3.5303 0.00076331 11.710245 
Langmuir model
Freundlich model
D–R model
I.S.χ2APEχ2APEχ2APE
IMN 0.0002554 7.9838 0.0004310 10.4910 0.00000245 0.0075101 
TIMN 0.0172793 44.266 0.0000591 3.5303 0.00076331 11.710245 

I.S., identification sample.

The lower values of Chi-square χ2 of the applied linearized models (Table 9) approve the better correlation between the experimental and calculated data. However, the higher APE values (APE was more than 10%) established that the Langmuir (APE = 44.2669) and D–R (APE = 11.7102) isotherm models did not present a suitable fit to the experimental results of MB by TIMN sample compared to the Freundlich model (APE = 3.5307). In contrast, the lower values of APE values obtained from the linear form of Langmuir (APE = 7.9838) and D–R (APE = 0.7510) isotherm models, in comparison to that of the Freundlich model (APE = 10.4910), confirm the better correlation between the experimental and calculated data of the adsorption of MB by IMN sample. In spite of lower standard error values like Chi-square χ2 with all linearized models, they do not describe the equilibrium data adequately, because of the poor linear regression and high error function APE.

Effect of temperature
The influence of temperature on the dye adsorption was investigated over the range of temperatures between 20 and 100 °C. As shown in Figure 14, increasing the temperature parameter beyond 40 °C causes a decrease in adsorption capacity. This result indicates that the adsorption reaction of MB onto TIMN is exothermic. Thermodynamic parameters were determined using the following equations:
(15)
(16)
where Kd is the distribution coefficient (m3kg−1), Ce is the dye concentration (kg m−3) and qe is the adsorption capacity at equilibrium, respectively (kg kg−1). ΔH° and ΔS° are the change in enthalpy (J mol−1) and the change in entropy (J K−1mol−1), respectively. T is the temperature (K), respectively, R is the universal gas constant (8.314 J K−1mol−1). The ΔH° and ΔS° values obtained from the slope and intercept of Van't Hoff plots of Ln Kd versus 1/T for the optimum initial concentration of 0.08 kg m−3 was presented in Figure 15. At constant temperature and pressure, the change in Gibbs free energy is (Equation (17)):
(17)
Figure 14

Effect of the temperature on the adsorption of MB onto TIMN clay samples.

Figure 14

Effect of the temperature on the adsorption of MB onto TIMN clay samples.

Close modal
Figure 15

Plot of Ln Kd vs 1/T for the kinetic of MB adsorption onto TIMN caly samples.

Figure 15

Plot of Ln Kd vs 1/T for the kinetic of MB adsorption onto TIMN caly samples.

Close modal

The values of the thermodynamic parameters for the sorption of dyes onto the TIMN clay sample are given in Table 10. The negative value of ΔH° (−381.281 J mol−1) indicated the exothermic nature of the adsorption of MB onto TIMN for all tested temperatures. The positive value of ΔS° (18.518 J mol−1 K−1) showed that the sorption process was irreversible and random at the solid–liquid interface during the sorption of MB onto TIMN clay adsorbent.

Table 10

Thermodynamic parameters of adsorbing MB adsorption onto TIMN clay sample

T (°C)
20406080100
ΔH° (J mol−1ΔS° (J mol−1 K−1R2   ΔG° (J mol−1  
−381.281 18.518 0.9297 −5,807.003 −6,177.359 −6,547.716 −6,918.073 −7,288.429 
T (°C)
20406080100
ΔH° (J mol−1ΔS° (J mol−1 K−1R2   ΔG° (J mol−1  
−381.281 18.518 0.9297 −5,807.003 −6,177.359 −6,547.716 −6,918.073 −7,288.429 

The negative values of free energy ΔG°, as mentioned in Table 10, revealed that the adsorption is highly favorable and spontaneous (Benguella & Yacouta-Nour 2009). The ΔG° values obtained in this investigation are < −12,000 J mol−1, indicating that physical adsorption is the predominant mechanism in the sorption process.

Comparison study

As indicated in Table 11, RM (raw material of clay) samples considerably reduced pollution compared to the other samples. This finding demonstrates that the physico-chemical features of the clay and the pollutant affect the removal efficiency. The estimated monolayer coverage capacities, qe,th, were 4.673 × 10−2 and 2.739 × 10−2 kg kg−1 for the adsorption of MB onto IMN and TIMN, respectively. The removal efficiency of IMN and TIMN samples was found to be great (Kannan & Sundaram 2001; Gücek et al. 2005; Rafatullah et al. 2010; Pimolpun & Pitt 2014; Allam et al. 2016), as a result of their affinity for MB removal.

Table 11

Adsorption capacity in comparison to that of earlier research on the removal of MB

I.SLangmuir model
Freundlich model
(D – R) model
Ref.
qe,th (10−2 kg kg−1)R2KFR2qm (10−2 kg kg−1)E (103 Jmol−1)R2
IMN 4.673 0.485 20.09 0.584 4.295 0.581 0.628 Present study 
TIMN 2.739 0.028 21.11 0.358 4.339 0 .745 0.91 Present study 
RM 25.0 0.951 74.89 0.873 15.7 1.581 0.85 Rafatullah et al. (2010)  
RM 1.47 0.98 Pimolpun & Pittx (2014)  
RM 24.4 0.99 2.21 0.99 Allam et al. (2016)  
RM 6.51 0.98 18 0.98 Gücek et al. (2005)  
RM 5.0 36.64 0.77 Kannan & Sundaram (2001)  
I.SLangmuir model
Freundlich model
(D – R) model
Ref.
qe,th (10−2 kg kg−1)R2KFR2qm (10−2 kg kg−1)E (103 Jmol−1)R2
IMN 4.673 0.485 20.09 0.584 4.295 0.581 0.628 Present study 
TIMN 2.739 0.028 21.11 0.358 4.339 0 .745 0.91 Present study 
RM 25.0 0.951 74.89 0.873 15.7 1.581 0.85 Rafatullah et al. (2010)  
RM 1.47 0.98 Pimolpun & Pittx (2014)  
RM 24.4 0.99 2.21 0.99 Allam et al. (2016)  
RM 6.51 0.98 18 0.98 Gücek et al. (2005)  
RM 5.0 36.64 0.77 Kannan & Sundaram (2001)  

I.S., Identification sample.

Probable interaction mechanism
The surface chemistry of the adsorbents plays a major role in the adsorption. To analyze the sorption behavior of MB dye on the interstratified clays, a mechanistic model for interpreting the sorption data in the treated TIMN system was developed. Based on the above-mentioned parameters optimizations, it was proposed a probable mechanism for the interactions between MB and TIMN at pH 7.0 and 40 °C. The overall mechanism of TIMN- -adsorption with MB is shown in Figure 16. In TIMN, therefore, the driving factors of the interaction with MB dye from aqueous solution have been categorized as hydrogen bonding, electrostatic attraction, cation exchange, n–π and OH − π interactions.
Figure 16

Schematic of the possible interactions between methylene blue (MB) and TIMN clay samples.

Figure 16

Schematic of the possible interactions between methylene blue (MB) and TIMN clay samples.

Close modal

According to the available functional groups (coordinatively unsaturated ions Al3+, Mg2+, Fe3+, exchangeable cations, acid hydroxyl groups and oxygen anions of aluminosilicates) on the surface of the TIMN, as buttressed by the XRD, FTIR and surface acidity results, there are possible:

  • (1)

    Hydrogen bonding. The highly electronegative nitrogen atoms on the adsorbate MB molecule could generate hydrogen bonding with the hydrogen atoms covalently bonded to the surface of the TIMN clay (Liu et al. 2021)

  • (2)

    Electrostatic attractions (ionic bonding). The edges of the TIMN clay surface contain hydroxyl surfaces (Si–OH, Al–OH, and Mg–OH groups), which could engender hydrophilic adsorption and can be attributed as a result of electrostatic attractions between the positively charged species of the MB (the positive charge is located on the N or S hetero–atoms of the MB molecule) and the negatively charged functional groups (variable charge at broken edges Si–O, Mg–O or hydroxyl surfaces (Si–OH, Al–OH and Mg–OH groups). In acidic environments, the release of H+ ions from the edge (more active) of the TIMN structure causes dye adsorption, from aqueous matrices, onto the edges of TIMN sample for cations like MB+ (Haounati et al. 2021).

  • (3)

    Additionally, cationic exchange can take place due to the interlayer nature of the smectite (montmorillonite) fundamental particle in TIMN adsorbent with acceptable host interlayer space, thus cationic exchange is considered a potential mechanism. Based on the XRD results and assuming dimensions of 17 × 10−10 m × 7.6 × 10−10 m × 3.25 × 10−10 m for the MB molecule, we can assume that the exchangeable interlayer sodium cations could easily exchange with the MB+ cations through cation exchange mechanism and the intercalation of MB molecules in the interlayer space of TIMN has occurred. In the present study, the basal spacing for TIMN sample was 25.83 × 10−10 m, and by subtracting 10 × 10−10 m (d001-spacing of dehydrated illite) and 10.1 × 10−10 m (basal space of hydrated montmorillonite), resulted in an interlayer space of 5.73 × 10−10 m, which is much larger than the thickness of one layer of MB orientated in the interlayer space in a nearly horizontal configuration (Li et al. 2010).

  • (4)

    Methachromasy effect. The substitution of the main absorption band, which corresponds to the absorption of monomer, MB+ (MB is a metachromatic dye), by a new absorption band placed at shorter wavelengths. This metachromatic effect is observed in several clay/dye systems attributed to different processes.

    • (i) Self-association of dye molecules (dimers and H-aggregates) when they are adsorbed on the clay surface.

Surface charge density plays an important role in metachromatism. Thus, MB cations form predominantly larger H-aggregates (composed of three or more MB molecules) on the surface of smectites with a high charge density (high negative charge) (Bujdák et al. 2001; Cenens & Schoonheydt 1998; Elaziouti & Laouedj 2010; Li et al. 2010).

  • (ii) n–π interactions. Intermolecular interaction between the electronic π-system of the dye with the electron lone- pairs of the oxygen atoms or at the clay surface. OH − π interactions between the OH groups on the surfaces of the clay and aromatic rings of MB dye may be one of the important interactions for the adhesion of MB dye including aromatic rings contributing to the adsorption of dye molecules (Nakamura et al. 2020).

The surface functional groups pre-demonstrated by FTIR analysis allow for interaction with the dye molecule through nπ interactions. The nπ interaction is proposed for clays with partial tetrahedral substitution of Si+4 by Al+3. Since TIMN Clay has this unique property, methachromatic effect has to be related to the n-π interactions between the organic functions of the MB dye molecule with the electron lone-pairs of the oxygen atoms in Si–O–Al, Si–O–Mg and Si–O–Fe groups of the TIMN clay surface through their different C = C double bonds of the aromatic rings (Wang et al. 2014; Jawad & Abdulhameed 2020; Ssouni et al. 2023).

A novel modified illite-montmorillonite clay was successfully elaborated via a chemical treatment process and characterized using XRD, FTIR, SEM-EDS, XRF, DSC-TG and DC methods. The adsorption capacity of the bare and treated IMN clays for MB dye was tested under conditions including contact period, initial dye concentration and temperature. It increased with the rise in the initial dye concentration, whereas it decreased significantly with increasing temperature. The adsorption process is well-fitted to the pseudo-second-order kinetic model. The maximum adsorption capacities, qe exp, were 4.327 × 10−2 and 4.914 × 10−2 kg kg−1 for IMN and TIMN, respectively. Results from using the Langmuir, Freundlich and Dubinin–Radushkevich (D–R) isotherm models have low regression coefficient values (R2 ≤ 0.91), suggesting that it is not appropriate to use these types of linearization for this study. In spite of lower standard error values like Chi-square χ2 with all linearized models, they do not describe the equilibrium data adequately, because of the poor linear regression and high error function APE. The obtained free energy (E) from D–R model values for adsorbing MB using IMN and TIMN ranged from 0.581 to 0.745 × 10−3J mol−1, respectively, suggesting that the process is physisorption. According to the thermodynamic aspect, the negative value of ΔH° (−318.281 Jmol−1) suggested that the sorption was exothermic in nature. The positive value of ΔS° (18.518 J mol−1K−1) showed that the sorption process was irreversible and random at the interface between adsorbent (IMN) and adsorbate solution (MB). The negative values of free energy ΔG° for all tested temperatures suggest that the adsorption was a highly favorable and spontaneous process. The main adsorption mechanisms of MB were hydrogen bonding, electrostatic attraction, cation exchange, n-π and OH − π interactions. These findings demonstrated the viability of an efficient TIMN adsorbent for MB dye removal in wastewater treatment systems.

The author gratefully acknowledges the material support from the Directorate-General for Scientific Research and Technological Development (DGSRTD) and the Ministry of Higher Education and Scientific Research (Algeria). We are also greatly indebted to the Laboratory of Agro-biotechnology and Nutrition in Semi-arid Zones, Ibn Khaldoun University, Tiaret, Algeria for their material support and the University of Science and Technology of Oran - Mohamed Boudiaf (USTO M.B.), Oran, Algeria.

All relevant data are included in the paper or its Supplementary Information.

The authors declare there is no conflict.

Ahrouch
M.
,
Gatica
J. M.
,
Draoui
K.
,
Bellido
D.
&
Vidal
H.
2019a
Lead removal from aqueous solution by means of integral natural clays honeycomb monoliths
.
J. Hazard Mater.
365
,
519
530
.
https://doi.org/10.1016/j.jhazmat.2018.11.037
.
Ahrouch
M.
,
Gatica
J. M.
,
Draoui
D.
&
Vidal
H.
2019b
Adding value to natural clays as low-cost adsorbents of methylene blue in polluted water through honeycomb monoliths manufacture
.
SN Appl. Sci.
1
,
1595
.
https://doi.org/10.1007/s42452-019-1636-4
.
Akar
T.
,
Demir
T. A.
,
Kiran
I.
,
Özcan
A.
,
Özcan
A. S.
&
Tunali
S.
2006
Biosorption potential of Neurospora crassa cells for decolorization of Acid Red 57 (AR57) dye
.
J. Chem. Technol. Biotechnol.
81
,
1100
1106
.
https://doi.org/10.1002/jctb.1462
.
Alda
M.
,
McKinnon
M.
,
Blagdon
R.
,
Garnham
J.
,
Mac Lellan
S.
&
O'Donovan
C.
2017
Methylene blue treatment for residual symptoms of bipolar disorder: Randomised crossover study
.
British J. Psychiatry
210
(
1
),
54
60
.
doi:10.1192/bjp.bp.115.173930. PMID 27284082
.
Allam
K.
,
El Bouari1
A.
,
Belhorma
B.
&
Biha
L.
2016
Removal of methylene blue from water using hydroxyapatite submitted to microwave irradiation
.
J. Water Resour. Prot.
8
(
3
).
doi:10.4236/jwarp.2016.83030
.
Auta
M.
&
Hameed
B. H.
2012
Modified mesoporous clay adsorbent for adsorption isotherm and kinetics of methylene blue
.
Chem. Eng. J.
17
,
219
227
.
https://doi.org/10.1016/j.cej.2012.05.075
.
Azharul
I. M.
,
Sabar
S.
,
Benhouria
A.
,
Khanday
W. A.
,
Asif
M.
&
Hameed
B. H.
2017
Nanoporous activated carbon prepared from karanj (Pongamia pinnata) fruit hulls for methylene blue adsorption
.
J. Taiwan Inst. Chem. Eng.
74
,
96
104
.
https://doi.org/10.1016/j.jtice 0.2017.01.016
.
Batzias
F. A.
&
Sidiras
D. K.
2007
Dye adsorption by prehydrolysed beech sawdust in batch and fixed-bed systems
.
Bioresour. Technol.
98
,
1208
1217
.
doi:10.1016/j.biortech.2006.05.020
.
Beltrán-Heredia
J.
,
Sánchez-Martín
J.
&
Dávila-Acedo
A.
2011
Optimization of the synthesis of a new coagulant from a tannin extract
.
J. Hazard. Mater.
186
(
2011
),
1704
1712
.
doi: 10.1016/j.jhazmat.2010.12.075
.
Benguella
B.
&
Yacouta-Nour
A.
2009
Elimination des colorants acides en solution aqueuse par la bentonite et le kaolin
.
C.R. Chim.
12
,
762
771
.
http://dx.doi.org/ 10.1016/j.crci.2008.11.008
.
Benhadria
N.
,
Elaziouti
A.
,
Laouedj
N.
&
Sari
E.
2020
NZF nanoscale particles: Synthesis, characterization and its effective adsorption of bromophenol blue
.
Bull. Chem. React. Eng. Catal.
15
(
3
),
726
742
.
https://doi.org/10.9767/bcrec.15.3.8558.726-742
.
Bennama
T.
,
Elaziouti
A.
&
Debab
A.
2022
Effective removal of chemical oxygen demand from sanitary landfill leachate using raw and chemically treated olive stones
.
Int. J. Environ. Anal. Chem.
1
20
.
https://doi.org/10.1080/03067319.2022.2100255
.
Bhattacharyya
K. G.
&
Gupta
S. S.
2008
Adsorption of a few heavy metals on natural and modified kaolinite and montmorillonite: A review
.
Adv. Colloid Interface Sci.
140
,
2008114
131
.
doi:10.1016/j.cis.2007.12.008
.
Bouhadjar
L.
,
Boukoussa
B.
,
Kherroub
D. E.
,
Hakiki
A.
,
Elaziouti
A.
,
Laouedj
N.
,
Benhadria
N.
&
Chikh
K.
2019
Adsorption behavior of carbon dioxide on new nanocomposite CuO/PPB: Effect of CuO content
.
J. Inorg. Organomet. Polym. Mater
.
https://doi.org/10.1007/s10904-018-1002-9
.
Bouteiba
A.
,
Benhadria
N.
,
Elaziouti
A.
,
Ezzianea
K.
&
Bettahar
N.
2020a
Competitive adsorption removal of indigo carmine and Congo red dyes from residual effluents by Zn2Al-LDH prepared by co-precipitation
.
Desalin. Water Treat.
201
,
404
419
.
doi: 10.5004/dwt.2020.26016
.
Bouteiba
A.
,
Benhadria
N.
,
Elaziouti
A.
,
Karima
E.
&
Bettahar
N.
2020b
Competitive adsorption of binary dye from aqueous solutions using calcined layered double hydroxides
.
Int. J. Environ. Anal. Chem.
2020
,
1
20
.
https://doi.org/10.1080/03067319.2020.1766035
.
British National Form: BNF 69 (69 ed.). British Medical Association. 2015. p. 34. ISBN 9780857111562
.
Bujdak
J.
,
Janek
J. M.
,
Madejova
J.
&
Komadel
P.
2001
Methylene blue interactions with reduced-charge smectites
.
Clays Clay Miner.
49
,
244
254
.
Cheng
S.
,
Zhang
L.
,
Ma
A.
,
Xia
H.
,
Peng
J.
,
Li
C.
&
Shu
J.
2018
Comparison of activated carbon and iron/cerium modified activated carbon to remove methylene blue from wastewater
.
J. Environ. Sci.
65
,
92
102
.
https ://doi.org/10.1016/j.jes.2016.12.027
.
Clarke
A. E.
&
Anliker
R.
1980
Organic dyes and pigments, in the handbook of environmental chemistry, Hutzinger, Editor. 1980, Springer-Verlag: Berlin
.
Dafalla
M.
,
Al-Mahbashi
A.
&
Al-Shamrani
M.
2018
Trends of moisture and electrical conductivity in clay liners
.
Hindawi Geofluids
2018
,
7
.
Article ID 8391830. https://doi.org/10.1155/2018/8391830
.
Da Silva
R. A. R.
&
Guerra
D. J. L.
2013
Use of natural and modified kaolinite/illite as adsorbent for removal methylene blue dye from aqueous solution
.
J. Chil. Chem. Soc.
58
(
1
),
1517
1519
.
http://dx.doi.org/10.4067/S0717-97072013000100003
.
Delgado-Vargas
F.
&
Octavioparedes-Lopez
,
2003
Natural Colorants for Food and Nutraceutical Uses. ISBN 9780429133534. doi.org/10.1201/9781420031713
.
Dubinin
M. M.
,
Zaverina
E. D.
&
Radush-kevich
L. V.
1947
Sorption and structure of active carbons. I. Adsorption of organic vapors
.
J. Phys. Chem.
21
,
1351
1362
.
doi: 10.4236/oalib.1103363
.
Ebrahimi
P.
&
Kumar
A.
2021
Diatomite chemical activation for effective adsorption of methylene blue dye from model textile wastewater
.
Int. J. Environ. Sci. Dev.
12
(
1
).
doi: 10.18178/ijesd.2021.12.1.1313
.
Elaziouti
A.
&
Laouedj
N.
2010
Influence of pH solution on the optical properties of methylene blue in aqueous suspension of Maghnia Montmorillonite
.
Korean J. Vis. Sci.
12
(
2
).
UCI I410-ECN-0102-2012-510-001666386
.
Elaziouti
A.
,
Laouedj
N.
&
Bekka
A.
2011a
Degradation study of phenazin neutral red from aqueous suspension by paper sludge
.
J. Chem. Eng. Processes Technol.
2
(
3
),
1000109
.
doi:10.4172/2157-7048.1000109
.
Elaziouti
A.
,
Laouedj
N.
&
Bekka
A.
2011b
Effect of pH solution on the optical properties of cationic dyes in dye/maghnia montmorillonite suspensions
.
Chem. Eng. Processes Technol.
2
(
4
),
1
5
.
http://dx.doi.org/4172/2157-7048.1000113
.
Elaziouti
A.
,
Laouedj
N.
&
Vannier
R. N.
2015
Adsorption of Congo red azo dye on nanosized sno2 derived from sol-gel method
.
Int. J. Ind. Chem.
7
,
53
70
.
doi:10.1007/s40090-015-0061-9
.
Eloussaief
M.
,
Jarraya
J.
&
Benzina
M.
2009
Adsorption of copper ions on two clays from Tunisia: pH and temperature effects
.
Appl. Clay Sci.
46
,
409
413
.
doi:10.1016/j.clay.2009.10.008
.
Elovich
S. Y.
&
Larinov
O. G.
1962
Theory of adsorption from solutions of non-electrolytes on solid (I) equation adsorption from solutions and the analysis of its simplest form, (II) verification of the equation of adsorption isotherm from solutions. Izv. Akad. Nauk. SSSR, Otd. Khim. Nauk. 2, 209–216
.
Felhi
M.
,
Tlili
A.
,
Gaied
M. E.
&
Montacer
M.
2008
Mineralogical study of kaolinitic clays from Sidi El Bader in the far north of Tunisia
.
Appl. Clay Sci.
39
,
208
217
.
doi: 10.1016/j.clay.2007.06.004
.
Freundlich
H.
&
Umber
M. F.
1906
Die adsorption in lasugen
.
J. Phys. Chem.
57
,
385
470
.
doi: 10.12691/ijebb-5-2-1
.
Gu
S.
,
Kang
X.
,
Wang
L.
,
Lichtfouse
E.
&
Wang
C.
2019
Clay mineral adsorbents for heavy metal removal from wastewater: a re-view
.
Environ. Chem. Lett.
17
,
629
654
.
doi: 10.1007/s10311-018-0813-9
.
Gücek
A.
,
Sener
S.
,
Bilgen
S.
&
Mazmanc
M. A.
2005
Adsorption and kinetic studies of cationic and anionic dyes on pyrophyllite from aqueous solutions
.
Colloid Interface Sci.
286
,
53
60
.
doi:10.1016/j.jcis.2005.01.012
.
Guezzen
B.
,
Nebatti Ech-Chergui
A.
,
Elaziouti
A.
,
Demey
H.
,
Abdelhalim Zoukel
A.
,
Didi
M. A.
,
Abdelkrim Boudia
R. A.
&
Adjdir
M.
2023
Adsorption isotherm and kinetic modeling of the Congo Red (CR) and Indigo Carmine (IC) dyes removal onto novel bentonite hybrid material
.
ChemistrySelect
8
(
e202300592
),
1
14
.
https://doi.org/10.1002/slct.202300592
.
Hajjaji
M.
,
Alami
A.
&
El Bouadili
A.
2006
Removal of methylene blue from aqueous solution by fibrous clay minerals
.
J. Hazard. Mater.
B135
,
188
192
.
doi:10.1016/j.jhazmat.2005.11.048
.
Hamdaoui
O.
,
Saoudi
F.
,
Chiha
M.
&
Naffrechoux
E.
2008
Sorption of malachite green by a novel sorbent, dead leaves of plane tree: Equilibrium and kinetic modeling
.
Chem. Eng.
143
,
73
84
.
http://dx.doi.org/10.1016/j.cej.2007.12.018
.
Haounati
R.
,
Ouachtak
H.
,
El Haouti
R.
,
Akhouairi
S.
,
Largo
F.
,
Akbal
F.
,
Benlhachemi
A.
,
Jada
A.
&
Ait Addi
A.
2021
Elaboration and properties of a new SDS/CTAB@ Montmorillonite organoclay composite as a superb adsorbent for the removal of malachite green from aqueous solutions
.
Sep. Purif. Technol.
255
,
117335
.
https://doi.org/10.1016/j.seppur.2020.117335
.
Ho
Y. S.
&
McKay
G.
1999
Pseudo-second order model for sorption processes
.
Process Biochem.
34
,
451
465
.
doi: 10.1016/S0032-9592(98)00112-5
.
Hoang
L. P.
,
Nguyen
T. M. P.
,
Van
H. T.
,
Yılmaz
M.
,
Hoang
T. K.
,
Nguyen
Q. T.
,
Huong Vi
T. M.
&
Nga
L. T. Q.
2022
Removal of tetracycline from aqueous solution using composite adsorbent of ZnAl layered double hydroxide and bagasse biochar
.
Environ. Technol. Innovation
28
,
102914
.
https://doi.org/10.1016/j.eti.2022.102914
.
Hosseini-Bandegharaei
A.
,
Hosseini
M. S.
,
Sarw-Ghadi
M.
,
Zowghi
S.
,
Hosseini
E.
&
Hosseini-Bandegharaei
H. J.
2010
Chem. Eng., 160, 190–198
.
Hu
X.
,
Laguerre
V.
,
Packert
D.
,
Nakasone
A.
&
Moscinski
L.
2015
A simple and efficient method for preparing cell slides and staining without using cytocentrifuge and cytoclip
.
Int. J. Cell Biol.
2015
,
813216
.
doi:10.1155/2015/813216. PMC 4664808. PMID 26664363
.
Jang
D. H.
,
Nelson
L. S.
&
Hoffman
R. S.
2013
Methylene blue for distributive shock: A potential new use of an old antidote
.
J. Med. Toxicol.
9
(
3
),
242
249
.
doi:10.1007/s13181-013-0298-7. PMC 3770994. PMID 23580172
.
Jawad
A. H.
&
Abdulhameed
A. S.
2020
Mesoporous Iraqi red kaolin clay as an efficient adsorbent for methylene blue dye: Adsorption kinetic, isotherm and mechanism study
.
Surf. Interface
18
,
100422
.
https://doi.org/10.1016/j.surfin.2019.100422
.
Kannan
N.
&
Sundaram
M. M.
2001
Kinetics and mechanism of removal of methylene blue by adsorption on various carbons – a comparative study
.
Dyes Pigm.
51
,
25
40
.
doi:10.1016/S0143-7208(01)00056-0
.
Koulouchi
S.
2007
Etude expérimentale des mélanges sable-bentonite, leur performance comme barrières de confinement dans CET . Thèse de doctorat de l'université Mentouri de Constantine-Algérie
.
Langmuir
I.
1916
The constitution and fun-damental properties of solids and liquids
.
J. Chem. Soc.
38
,
2221
2295
.
doi:10.1021/ja02268a002
.
Liu
Y.
,
Chen
Y.
,
Shi
Y.
,
Wan
D.
,
Chen
J.
&
Xiao
S.
2021
Adsorption of toxic dye Eosin Y from aqueous solution byclay/carbon composite derived from spent bleaching earth
.
Water Environ. Res.
93
(
1
),
159
169
.
https://doi.org/10.1002/wer.1376
.
Manyangadze
M.
,
Chikuruwo
N. H. M.
,
Narsaiah
T. B.
,
Chakra
C. S.
,
Radhakumari
M.
&
Danha
D.
2020
Enhancing adsorption capacity of nano-adsorbents via surface Q23 modification: A review
.
South African J. Chem. Eng.
31
,
25
32
.
https://doi.org/10.1016/j.sajce.2019.11.003
.
Missana
T.
,
Garcia-Gutierrez
M.
&
Alonso
U.
2008
Sorption of strontium onto illite/smectite mixed clays
.
Phys. Chem. Earth.
33
,
S156
S162
.
doi:10.1016/j.pce.2008.10.020
.
Modarai
B.
,
Kapadia
Y. K.
,
Kerins
M.
&
Terris
J.
2002
Methylene blue: A treatment for severe methaemoglobinaemia secondary to misuse of amyl nitrite
.
Emerg. Med. J.
19
(
3
),
270
271
.
doi:10.1136/emj.19.3.270. PMC 1725875. PMID 11971852
.
Mohamed
E. A.
,
Selim
A. Q.
,
Zayed
A. M.
,
Komarneni
S.
,
Mobarak
M.
&
Seliem
M. K.
2019
Enhancing adsorption capacity of Egyptian diatomaceous earth by thermo-chemical purification: Methylene blue uptake
.
J. Colloid Interface Sci.
534
,
408
419
.
https://doi.org/10.1016/j.jcis.2018.09.024
.
Nakamura
S.
,
Tsuji
Y.
&
Yoshizawa
K.
2020
Role of hydrogen-bonding and OH − π interactions in the adhesion of epoxy resin on hydrophilic surfaces
.
ACS Omega
5
,
26211
26219
.
https://dx.doi.org/10.1021/acsomega.0c03798
.
Novikova
L.
,
Roessner
F.
,
Belchinskaya
L.
,
AlSawalha
M.
&
Krupskaya
V.
2014
Study of surface acid–base properties of natural clays and zeolites by the conversion of 2-methylbut-3-yn-2-ol
.
Appl. Clay Sci.
101
,
229
236
.
https://doi.org/10.1016/j.clay.2014.08.005
.
Pal
B. K.
&
Ghoshal
D. N.
1977
Adsorption of cetylpyridinium chloride & cetyltrimethylammonium bromide on bentonite
.
Indian J. Chem.
15A
,
680
683
.
Rafatullah
M.
,
Sulaiman
O.
,
Hashim
R.
&
Ahmad
A.
2010
Adsorption of methylene blue on low-cost adsorbents: A review
.
Hazard. Mater.
177
,
70
80
.
doi:10.1016/j.jhazmat.2009.12.047
.
Robert
A.
&
Charvat
C.
&
Associates
2004
Inc Cleveland, Ohio: Coloring of plastics, 52. ISBN: 978-0-471-13906-5
.
Robinson
T.
,
Chandran
B.
&
Nigam
P.
2002
Effect of pretreatments of three waste residues, wheat straw, corncobs andbariey husks on dye adsorption
.
Bioresour. Technol.
85
(
2
),
119
124
.
https ://doi. org/10.1021/je700 008g
.
Soleimani
H.
,
Sharafi
K.
,
Parian
J. A.
,
Jaafari
J.
&
Ebrahimzadeh
G.
2023
Acidic modification of natural stone for Remazol Black B dye adsorption from aqueous solution-central composite design (CCD) and response surface methodology (RSM)
.
Heliyon
9
,
e14743
.
https://doi.org/10.1016/j.heliyon.2023.e14743
.
Ssouni
S.
,
Miyah
Y.
,
Benjelloun
M.
,
Mejbar
F.
,
El-Habacha
M.
,
Iaich
S.
,
Ait Addi
A.
&
Lahrichi
A.
2023
High- performance of muscovite clay for toxic dyes’ removal: Adsorption mechanism, response surface approach, regeneration, and phytotoxicity assessment
.
Case Stud. Chem. Environ. Eng.
8
,
100456
.
https://doi.org/10.1016/j.cscee.2023.100456
.
Subramanyam
B.
&
Das
A.
2009
Linearized and non-linearized isotherm models comparative study on adsorption of aqueous phenol solution in soil
.
Int. J. Environ. Sci. Technol.
6
(
4
),
633
640
.
doi:10.1007/BF03326104
.
Šucha
V.
,
Czímerová
A.
&
Bujdák
J.
2009
Surface properties of illite-smectite minerals as detected by interactions with rhodamine 6G dye
.
Clays Clay Miner.
57
(
3
),
361
370
.
doi:10.1346/CCMN.2009.0570308
.
Taibi
M.
,
Elaziouti
A.
,
Laouedj
N.
&
Dellal
A.
2020
Study of the interaction of heavy metals (Cu(II), Zn(II)) ions with a clay soil of the region of Naima-Tiaret-Algeria
.
Bull. Chem. React. Eng. Catal.
15
(
3
),
765
785
.
https://doi.org/10.9767/bcrec.15.3.8773.765-785
.
Tarmizi
T.
,
Mikha
M. C.
,
Muhammad
S.
,
Nurlisa
H.
,
Ferlinahayati
F.
&
Aldes
L.
2019
Removal of iron(II) using intercalated Ca/Al layered double hydroxides with [α-SiW12O40]4−
.
Bull. Chem. React. Eng. Catal.
14
,
260
267
.
doi:10.9767/bcrec.14.2.2880.260-267
.
Taylor
G. M.
,
Avera
R. S.
,
Strachan
C. C.
,
Briggs
C. M.
,
Medler
J. P.
,
Pafford
C. M.
&
Gant
T. B.
2021
Severe methemoglobinemia secondary to isobutyl nitrite toxicity: The case of the ‘Gold Rush’
.
Oxford Medical Case Reports.
2021
(
2
),
omaa136
.
doi:10.1093/omcr/omaa136. PMC 7885148. PMID 33614047
.
Thai
A. N.
&
Ruey-Shin
J.
2012
Treatment of waters and wastewaters containing sulfur dyes: A review. Volume 219, 1 March 2013, 109–117. doi.org/10.1016/j.cej.2012.12.102
.
Ulmanu
M.
,
Marañón
E.
,
Fernández
Y.
,
Castrillón
L.
,
Anger
I.
&
Dumitriu
D.
2003
Removal of copper and cadmium ions from diluted aqueous solutions by low cost and waste material adsorbents
.
Water. Air. Soil Pollut.
142
,
357
373
.
doi:10.1023/A:1022084721990
.
Van Holphen
H.
1977
An Introduction to Clay Colloids Chemistry
.
Wiley Interscience, New York
, p.
318
.
Vargas
A. M.
,
Cazetta
A. L.
,
Kunita
M. H.
,
Silva
T. L.
&
Almeida
V. C.
2011
Adsorption of methylene blue on activated carbon produced from flamboyant pods (Delonix regia): Study of adsorption isotherms and kinetic models
.
Chem. Eng. J.
168
,
722
730
.
doi:10.1016/j.cej.2011.01.067
.
Wang
X.
&
Wang
H.
2021
Structural analysis of interstratified illite-smectite by the Rietveld method
.
Crystals
11
(
224
),
1
15
.
Https://doi.org/10.3390/cryst11030244
.
Wang
P.
,
Cheng
M.
&
Zhang
Z.
2014
On different photodecomposition behaviors of rhodamine B on laponite and montmorillonite clay under visible light irradiation
.
J. Saudi Chem. Soc.
18
,
308
316
.
Http://dx.doi.org/10.1016/j.jscs.2013.11.006
.
Zare
N.
,
Kojoori
R.
,
Abdolmohammadi
S.
&
Sadegh-Samiei
S.
2022
Ultrasonic-assisted synthesis of highly effective visible light Fe3O4/ZnO/PANI nanocomposite: Thoroughly kinetics and thermodynamic investigations on the Congo red dye decomposition
.
J. Mol. Struct.
1250
,
131903
.
https://doi.org/10.1016/j.molstruc.2021.131903
.
Zhang
X.
,
Yi
H.
,
Zhao
Y.
&
Song
S.
2017
Quantitative determination of isomorphous substitutions on clay mineral surfaces through AFM imaging: A case of mica
.
Colloids Surf., A
533
,
55
60
.
https://doi.org/10.1016/j.colsurfa.2017.08.024
.
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