Magnetite-diatomite nanocomposite was synthesized through co-precipitation methods as an effective Cr(VI) removal adsorbent. The properties of diatomite, thermochemically modified diatomite (TMD), and magnetic–diatomite nanocomposite (MDN) were investigated using Fourier-transform infrared spectroscopy, X-ray diffraction analysis, Brunauer–Emmett–Teller, and complete silicate chemical analysis. The MDN shows 98.89% adsorption removal at optimized conditions using the response surface methodology of Box–Behnken Design. The kinetic data for Cr(VI) sorption on MDN were well described by pseudo-second order, which indicates the Cr(VI) adsorption was mainly due to chemisorption. The isotherm data show that the Langmuir and Freundlich models better described Cr(VI) ion sorption data. The thermodynamic parameters ΔG°, ΔH°, and ΔS° were estimated, and the results indicate Cr(VI) sorption on MDN was a spontaneous (ΔG° < 0) and exothermic process (ΔH° < 0). The proper Fe3O4 loading into TMD improves the gram susceptibility (Xg) of MDN for magnet separation. The regeneration of nanocomposite material revealed over 80% Cr(VI) removal efficiency after five consecutive adsorption–desorption cycles. The produced MDN was tested for the removal of Cr(VI) from real tannery wastewater. The obtained results suggest the possibility of using this nanocomposite as an effective, efficient adsorbent to remove Cr(VI) laden wastewater.

  • Easy magnetic recyclable adsorbent.

  • Efficient Cr(VI) removal adsorbent from Cr(VI) laden tannery effluent.

  • Easy synthesis and low-cost material.

  • Highly stable with magnetic reusable potential.

  • Composite with high electron density and porous material.

Uncontrolled waste discharge of heavy metals from different industrial sectors causes bioaccumulation in the food chain, leading to serious human and animal health issues (Gaur et al. 2021). Chromium and its compounds are used in electroplating, metal processing, leather tanning, pigments, and metallurgy (Matei et al. 2011; Wang et al. 2016), and their waste discharge is a serious concern due to potential health effects and mobility in aquatic environments (Gorzin & Bahri Rasht Abadi 2018). Chromium exists in two stable oxidation states, Cr(III) and Cr(VI) (Zhang et al. 2019) and occurs most frequently in the form of the oxyanions , , and (Huang et al. 2015). In addition, under certain conditions, oxidation by bacteria or manganese oxides can convert Cr(III) to Cr(VI), which is approximately 100 times more toxic than Cr(III) forms (Shahadat et al. 2015). Cr(VI) is exceptionally mobile in aquatic systems at a wider pH range and has been identified as a causative agent of lung cancer, kidney, liver, and gastric damage (Duranoĝlu et al. 2012; Balali-Mood et al. 2021).

Several Cr(VI) removal techniques – physical, chemical, and biological – have been reported. These include chemical precipitation (Ramakrishnaiah & Prathima 2012; Minas et al. 2017), photo-reduction (Du et al. 2018), membrane filtration (Abbasi-Garravand & Mulligan 2013), electrocoagulation (Azis et al. 2021; Villabona-Ortíz et al. 2021), phytoremediation (Kiran Marella et al. 2020), and adsorption (Baehaki et al. 2020). However, these removal techniques lead to incomplete removal, thus involving excess monitoring; they are energy-intensive and require high initial capital costs. Among the aforementioned methods, adsorption is a promising technology and has received increasing attention owing to its high efficiency at trace amounts, easy operation, low cost, and excellent adsorbent recycling performance (Yan et al. 2018; Song et al. 2019). Besides high efficiency and simple operating design, the wide accessibility of natural materials is crucial for adsorption technology (Ahmed et al. 2022).

Nowadays, low-cost adsorbents, including clay, agricultural wastes, and their composite, are among the widely reported adsorbents used for sustainable wastewater management. In this regard, Ethiopia is rich in natural inorganic minerals such as the diatomite (DM) clay of lacustrine origin present in deposits of more than 40 million tons, mainly along the Rift Valleys of Adami Tulu, Gade-Mota, Chefe Jilla, and Abiyata (Weldemariam et al. 2019), the Afar depression, and in some basin catchments (Kurkura et al. 2012). Diatomites are eco-environmental functional materials with very promising and effective adsorption capacities due to their porous structure (Wu et al. 2016; Touina et al. 2021), high specific surface area (Zhao et al. 2019), increased stability (Touina et al. 2021), low water solubility (Le et al. 2020), chemical inertness (Khaldi et al. 2018), potential for reuse (Gao et al. 2021; Zhang et al. 2021), and surface silanol groups(Si-OH) (Chu et al. 2012) that account for their good adsorption characteristics.

The DM, or amorphous hydrated silica (SiO2·nH2O), also contains some impurities including silica sand (Flores-Cano et al. 2013), clay mineral (Galal Mors 2010; Touina et al. 2021), carbonates, metal oxides ((Tsai et al. 2006; Cabrera et al. 2017), and organic matter (Ahmed et al. 2022). However, impurities that block some of its pores and other surface properties limit the commercial application of natural DM as an adsorbent.

Even though different techniques for removal of impurities in DM, such as calcination, acid/alkali leaching, and thermochemical treatment, have been reported (Weldemariam et al. 2019; Reka et al. 2020), its adsorption capacity is still less competitive as compared to seolite, kaolinite, and montmorillonite (Yuan et al. 2013; Zhao et al. 2019; Le et al. 2020). Besides, different clay-based composite adsorbents have been reported to be effective for adsorptive removal of Cr(VI) ions from wastewater; for example, montmorillonite nanocomposite (Wang et al. 2016), glutaraldehyde cross-linked chitosan–bentonite composites (Altun 2020) and clay–biochar composites (Wang et al. 2019) have reasonable adsorption capacity from wastewater. However, the production of these composite adsorbents involves high costs of surfactants for clay–composite synthesis. The problems associated with used adsorbents’ separation/regeneration from aqueous solution hinder their large-scale application.

In the current study, magnetite (Fe3O4) nanoparticle modification of purified DM to enhance its adsorption capacity and ease of separation/regeneration of used adsorbent was investigated. Fe3O4 nanoparticles have excellent properties (higher magnetic properties than other iron oxides) and can be easily recycled through magnetic separation (Chen et al. 2016). Even though Fe3O4 has a strong tendency to agglomerate due to Van der Waals forces or magnetic attraction forces, its composite form shows high stability with polymers, chitosan, carbon nanotubes, and clay minerals (Pandit et al. 2022).

The main objective of this research was to study the synergistic effects of Fe3O4 loaded into thermochemically modified DM (TMD) through co-precipitation methods for Cr(VI) adsorption removal from synthetic and tannery wastewater. The novel aspect of this study is to synthesize nanocomposite materials with magnetic susceptibility for easy separation/regeneration of used adsorbent by means of an external magnetic field and superior Cr(VI) adsorption properties of composite materials. The response surface methodology (RSM) of multiple factors at the optimal time using a three-level Box–Behnken design (BBD) was used for operating variables like adsorbent dose, initial Cr(VI) load, pH, and contact times for Cr(VI) removal in a batch adsorption process to reduce the number of experimental runs at wider ranges of stated parameters.

Chemicals and instruments

Chemicals used were ferric chloride hexahydrate (FeCl3. 6H2O, 97%, AR/ACS, Loba Chemie, PVT.LTD) and ferrous chloride tetra-hydrate (FeCl2. 4H2O, ATICO, India), potassium dichromate (K2Cr2O7, 99 + %, Sigma-Aldrich), ammonium hydroxide (NH4OH, ATICO), and hydrochloric acid, 37%, Sigma-Aldrich). All analytical grade chemicals were used without any purification, and all solutions were prepared using ultrapure water. The DM used for this experiment was obtained from the Great Rift Valley of Oromia Regional State, Ethiopia.

Adsorbent preparation methods

The DM was ground to powder and sieved with 825 mesh size to obtain uniform particle size. Acid purification of DM was performed using the methods of Turkten (2022) with some modifications. Fifty grams of sieved DM was added to the flask and mixed with 500 mL of 10% HCl. The sample DM was shaken at 200 rpm in a water batch for 2 h at 60 °C. The solution was filtered using filter paper, and repeatedly washed with ultrapure water and oven-dried at 60 °C overnight. The oven-dried DM was calcined at 900 °C for 1 h. The magnetite–DM nanocomposites were synthesized according to Li et al. (2020) with some modifications. Six grams of thermochemically modified DM was dissolved in 50 mL of deionized water and slowly poured into a 250 mL flask containing 10 g of FeCl3. 6H2O and 3.5 g of FeCl2. 4H2O. The mixture was adjusted to a pH of 8–9 using 0.5 M HCl and 30% NH4OH. The solution was ultrasonicated at 85 °C for 2 h using a shaker at 200 rpm. It was centrifuged at 2,500 rpm for 5 min to separate the sediment, and the residue was washed with ultrapure water until neutral pH and dried in an oven at 60 °C overnight. The dried material was calcined at 500 °C for 1 h.

Characterization of adsorbents

The X-ray diffraction analysis (XRD) patterns of natural and modified DM were investigated using a Rigaku Ultima IV diffractometer, with Cu K radiation operated at 40 kV and 40 mA in the scan range 3–80° 2 and a scan speed of 10° min. The Fourier-transform infrared spectroscopy (FTIR) spectroscopy analysis was used to detect the functional groups present in the adsorbent materials using a Spectrum 65 Perkin Elmer spectrometer in the range 4,000–400 cm−1 and spectral resolution of 4.0 cm−1. The chemical composition of adsorbents was determined using complete silicate chemical analysis, LiBO2 fusion, hydrogen fluoride (HF) attack, gravimetric methods, and colorimetric and atomic adsorption spectroscopic techniques. The surface area, pore volume, and average pore diameter were determined using Quanta Chrome version 11.0 of N2 – Brunauer–Emmett–Teller (BET) analysis at 77.3°K using a SA-9600 Series Surface Area Analyzer (Horiba Instruments, Inc.). The samples were degassed at 100 °C for 2 h and the specific surface area was determined by the multipoint BET method in an N2 gas relative pressure (P/P0) range of 0.05–0.30. To understand the magnetic properties of the magnetite–diatomite nanocomposite (MDM), the magnetic susceptibility study of the material was determined using Sherwood's scientific magnetic susceptibility balance.

Determination of point of zero charges (pzc)

The pzc of the MDM nanocomposite was determined by using salt addition methods (Mahmood et al. 2011). A sample of adsorbent (0.2 g) was added to 40 mL of 0.1 M NaNO3 solutions and the pH of sample solutions was adjusted with 0.1 M HCl and 0.1 M NaOH to obtain the appropriate pH ranges of 2–9 (± 0.02). The pH of the adjusted solution was denoted as pHi and the experiment was repeated with 0.05 M NaNO3 solutions and each set of experiments was performed in triplicate. The sample was shaken for 24 h at 170 rpm in a shaker. After settling, the pH values of each sample solution were measured as pHfinal. Thus, pHpzc of MDM was obtained from the plot of ΔpH (ΔpH = pHinitial − pHfinal) against pHinitial.

Adsorption experiment

The preliminary Cr(VI) adsorption removal and adsorption capacity of MDM were measured in a batch adsorption process. The preliminary investigation results confirmed that MDM showed a remarkable adsorption capacity for Cr(VI) ions without competing ions and was chosen for further adsorption studies. The batch adsorption was conducted at room temperature and using a water bath shaker (WS17-2 SHEL LAB) at a speed of 200 rpm. A stock solution of 100 mg L−1 of Cr(VI) was prepared using 0.28286 g of potassium dichromate (K2Cr2O7) in 1 L of ultrapure water, and different standard solutions of Cr(VI) were prepared by serial dilution from the stock solution.

A range of operating conditions was studied: pH (2–5), adsorbent dose (0.2–1 g·L−1), initial Cr(VI) ion concentration (2–30 mg·L−1), and contact times (15–105 min). During adsorption studies, the sample solution pH was adjusted using 0.1 M HCl and 0.1 M NaOH. For every adsorption experiment, the sample solution was added to a 250 mL conical flask, and after each adsorption process the sample solution was filtered using a microfiltration syringe to determine the Cr(VI) concentration using inductively coupled plasma optical emission spectroscopy (Agilent; 5800). The kinetic experiments for Cr(VI) adsorption removal using MDM were studied at 15, 30, 45, 60, 75, 90, 105, and 120 min. The temperature-dependent thermodynamic adsorption process was investigated at 30, 50, and 70 °C. The kinetic, isotherm, and thermodynamics of Cr(VI) adsorption on MDM were studied at optimized operation parameters (pH = 3, adsorbent dose = 0.6 g·L−1, Cr(VI) initial concentration = 16 mg·L−1, and contact time = 60 min) and each experiment was conducted in triplicate. The Cr(VI)ions removal efficiency (R%) and adsorption capacity (qe) in mg·g−1 of adsorbent were calculated using the following equations.
formula
(1)
formula
(2)
where Co and Ct are initial and final Cr (VI) concentrations in the solutions, m is the mass of adsorbent in g·L−1, and V is the volume of the solution.

Chi-square test (X2)

The fitness of the adsorption models was used to describe the adsorption process at equilibrium. While the correlation coefficient (R2) only represents the fitness between linear forms of model equations and experimental data, it is not sufficient to validate an adsorption model. Thus, an error analysis method (chi-square (X2)) was investigated to validate the adsorption model in addition to R2 analysis. Chi-square (X2) is the variance between the attained experimental adsorption capacity (qe,exp), and the theoretically calculated adsorption capacities (qe, cal) that can be obtained from the linear plots of kinetic adsorption data were measured using chi-square (X2) in the following equation
formula
(3)

Desorption and recycling study

To investigate the experimental reusability, 0.6 g of MDM was used for the uptake of Cr(VI) at BBD-optimized parameters. To explore the desorption capacity, 50 mL of 0.1 M NaOH was added to a flask containing 2.0 g of MDM adsorbent (at pH ∼ 12) and ultrasonicated in a water bath shaker of 25 °C for 1 h. The regeneration capacities of MDM were investigated for five consecutive adsorption–desorption cycles and the concentration of Cr(VI) was measured at each adsorption–desorption cycle. The percent of Cr(VI) desorption capacity of NaOH and reusability of MDM were calculated (Liu et al. 2022) using Equations (4) and (1) as;
formula
(4)
where md and mo represent the mass of Cr (VI) desorbed from MDM and the mass of Cr(VI) remaining on the MDM surface before desorption in grams, respectively.

Modeling of experiment

RSM coupled with BBD was applied to design Cr(VI) adsorption on MDM experiments. The design expert software (version 13.0) was used to perform statistical analysis and the three-level BBD was applied to investigate the independent variables pH, adsorbent dose, initial Cr(VI) concentration, and contact time with their coded levels −1 (minimum), 0 (medium point), and +1 (maximum) as listed in Table 1.

Table 1

The operating factors and their three-level scale for optimized Cr(VI) removal

VariableUnitLevel
Minimum (−1)Medium (0)Maximum (+1)
pH 
Adsorbent dose g·L−1 0.2 0.60 
Pollutant load mg·L−1 16 30 
Contact time minutes 15 60 105 
VariableUnitLevel
Minimum (−1)Medium (0)Maximum (+1)
pH 
Adsorbent dose g·L−1 0.2 0.60 
Pollutant load mg·L−1 16 30 
Contact time minutes 15 60 105 

Characterization of adsorbent

Chemical composition analysis

The purely whitish colour of the DM sample (Supplementary material, Figure S1) was collected from Adami Tulu, Oromia Regional State, in the Great Rift Valley, Ethiopia. Using LiBO2 fusion, HF attack, and gravimetric, colorimetric and atomic adsorption spectroscopic methods, the chemical composition of the material was analyzed. As shown in Table 2, raw DM is primarily composed of SiO2, Al2O3, Fe2O3, and CaO, with other oxides, such as MgO, Na2O, K2O,P2O5, TiO2, found at low concentrations (Weldemariam et al. 2019). Upon acid treatment and calcination of DM, slight decomposition and leaching of soluble oxides from the surface of DM were observed. Consequently, the fractional composition of silica content increased from 76% for DM to 83.68% for TMD. Whereas, for magnetite (Fe3O4) intercalated into TMD to form a composite material, both composite fractions SiO2, and Fe2O3 increase from 76.00 to 79.22% and 0.46 to 4.68%, respectively. The slight leaching of inorganic impurities from the DM surface may account for the increase in SiO2 in the TMD. The enhancement of iron oxide composition in TMD to form nanocomposites may develop composite materials with magnetic properties due to ferromagnetic intercalation into TMD layers. Furthermore, in the thermochemical purification of DM, significant loss on ignition was observed at 900 °C as previously reported (Bello et al. 2014), and this may account for increasing the purity of DM, for which the percentage composition of SiO2 is one of the main factors in determining the degree of purity, as previously reported (Mohamed et al. 2018).

Table 2

Chemical composition of Ethiopian diatomite (DM), thermochemical modified, and magnetite–diatomite (MDM) nanocomposites

AdsorbentOxide weight percentage (wt%)
Total
SiO2Al2O3Fe2O3CaOMgONa2OK2OP2O5TiO2H2OLIO
DM 76.0 14.11 0.46 0.60 <0.01 <0.01 0.20 0.23 0.13 0.57 7.68 100 
TMD 83.68 13.83 0.43 0.46 <0.01 <0.01 0.45 0.16 0.13 0.27 0.57 100 
MDM 79.22 13.48 4.68 <0.01 0.54 0.08 0.94 0.15 0.13 0.47 0.30 100 
AdsorbentOxide weight percentage (wt%)
Total
SiO2Al2O3Fe2O3CaOMgONa2OK2OP2O5TiO2H2OLIO
DM 76.0 14.11 0.46 0.60 <0.01 <0.01 0.20 0.23 0.13 0.57 7.68 100 
TMD 83.68 13.83 0.43 0.46 <0.01 <0.01 0.45 0.16 0.13 0.27 0.57 100 
MDM 79.22 13.48 4.68 <0.01 0.54 0.08 0.94 0.15 0.13 0.47 0.30 100 

XRD result analysis

XRD patterns of DM and TMD (Figure 1) mainly depict crystalline behavior with the presence of a small number of impurities such as the kaolinite peak observed at 2, 13.25° and amorphous matter. The DM, TMD, and MDM materials show sharp crystalline phases at 2, 26.657°, 26.762°, and 26.85°, respectively that mainly represent silica (quartz) as reported elsewhere (Touina et al. 2021). Upon calcination at 900 °C, the solid phase transition of quartz to crystobalite did not occur significantly as previously reported (Reka et al. 2020), and a more dominant quartz phase was observed in the diffractogram. Fe3O4 magnetite surface modification of TMD shows the destruction of kaolinite, and the main magnetite peaks were observed at 2, 35.86°, 62.78°.
Figure 1

XRD diffractogram spectra of DM, TMD, and MDM samples.

Figure 1

XRD diffractogram spectra of DM, TMD, and MDM samples.

Close modal
The average crystal size of the adsorbent was calculated using the Scherrer equation as follows,
formula
(5)
where D is average crystal size, λ is the wavelength of the X-ray = 0.1541 nm, β is full width at half-maximum of an XRD peak, and θ is Bragg's angle.

The XRD result of the calculated crystal size for MD, TMD, and MDM is shown in Supplementary material, Table S1. Thermochemical purification shows a decrease in crystal sizes from 124 nm DM to 71.205 nm: this accounts for the increase in its specific surface area for Cr(VI) adsorption uptake. This result is in agreement with previous reports (Yusan et al. 2014). Whereas, Fe3O4 nanoparticle incorporation into the DM surface shows more decrease in composite crystal size from 71.205 nm for TMD to 53.24 nm. This may be due to inter-grain porosities of magnetite over TMD surface, and the positive charge of magnetite was adsorbed by the negatively charged DM surface. Similar results were reported for DM modified with Fe(SO4)2·7H2O (Knoerr et al. 2013) and 3-aminopropyl tri-ethoxy silane and EDTA with magnetic DM (Wu et al. 2021). Chemical composition analysis shows that Ethiopian-origin DM contains more quartz, kaolinite (Al2Si2O5(OH)4, and alunite KAl3(SO4)2(OH)6 in polymorphs of quartz, as shown in Table S2 (Supplementary material).

FTIR result analysis

As shown in Figure 2, the FTIR spectrum of DM shows broader peaks at 3,694 and 3,619 cm−1 attributed to stretching vibration of physically adsorbed water on the surface of DM. The weak stretching vibration of 3,619 cm−1 for TMD showed low water contents after calcination. This may be due to gradual loss of physically adsorbed water from the DM surface (Ibrahim & Selim 2012; Erol et al. 2019). The DM and TMD peaks at 3,477 and 3,441 cm−1 are assigned to O–H stretching of free silanol (Yusan et al. 2014) and the adsorption peak at 2,849 cm−1 is due to C–H stretching (Mohamed et al. 2018). The main adsorption peaks at 1,020, 1,059, 1,052, and 784 cm−1 represent asymmetric stretching of layered silicates of quartz (Weldemariam et al. 2019; Reka et al. 2020). The symmetric stretching of –Si–O–Si– that was not affected by thermochemical or magnetite surface functionalization is observed at 784 cm−1 (Mohamedbakr & Burkitbaev 2009). The adsorption peaks at 915 cm−1 for natural DM were due to Al–O–Si stretching, which corresponds to those at 900 and 850 cm−1 as previously reported (Khodabakhshloo & Biswas 2023). The new peaks of metal–oxygen bonds around 637 cm−1 for MDM may be attributed to bending and stretching, frequency corresponding to Fe–O–Si– as nearly similar reports for DM/CoFe2O4@APTES-EDTA (Wu et al. 2021) and amine-modified magnetic DM (Alacabey 2022). Also, three peaks seen at 463, 468, and 458 cm−1 are due to intrinsic bending and stretching vibration of Si–O– (Tironi et al. 2012).
Figure 2

FTIR spectra of DM, TMD, and MDM in the range 4,000–400 cm−1.

Figure 2

FTIR spectra of DM, TMD, and MDM in the range 4,000–400 cm−1.

Close modal

BET surface area analysis

The moderately pure DM from Ethiopia shows remarkable surface areas: this may be due to the low fractional composition of CaO and high concentration of Al2O3 as shown in the chemical silicate analysis (Table 2). Thermochemical modification (acid washing and calcination) of DM enhances the BET-specific surface area from 357.835 m2·g−1 for DM to 364.627 m2·g−1 for TMD: this is due to removal of impurities (loss on ignition) that mask natural pore volume and removes alkali oxides to make available new micro and nanopores on the surface of modified DM, as reported by other authors (Goren et al. 2002; Yuan et al. 2013; Zelentsov 2017; Dim et al. 2021). As shown in Table 3, magnetite surface modification of DM (forming MDM) synergistically increases the surface area of TMD from 364.627 to 387.707 m2·g−1 and the pore volume from 0.0571 to 0.0673 cm3/g, respectively. This is due to the blocking of large mesoporous DM through the formation of a uniform thin layer of Fe3O4 through in situ reaction, which was also reported for DM modified with aluminum silicate (Zelentsov 2017) and DM modified with MnO2 (Li et al. 2014). However, high concentration ratios of the magnetite precursor to DM show a significant decrease in the surface area and this may be due to the physical alteration of pore structure and the development of a thicker layer on the surface of DM that may block the fine pores formed by thermochemical modification of DM and blocked (re-occupied) with Fe3O4 nanoparticles, as reported by Li et al. (2020).

Table 3

BET surface area, pore volumes and pore sizes of DM, TMD and MDM

AdsorbentSurface area (m2·g−1)Pore volume (m3·g−1)Pore sizes (nm)
DM 357.838 0.0552 8.587 
TMD 364.627 0.0587 8.837 
MDM 387.707 0.0673 8.912 
AdsorbentSurface area (m2·g−1)Pore volume (m3·g−1)Pore sizes (nm)
DM 357.838 0.0552 8.587 
TMD 364.627 0.0587 8.837 
MDM 387.707 0.0673 8.912 

Magnetic susceptibility studies

Magnetic susceptibility indicates the degree of magnetization of materials when an external magnetic field is applied (Yamato & Kimura 2020). According to their magnetic properties, all substances are divided into three groups that differ in magnetic susceptibility range: diamagnetic, paramagnetic, and ferromagnetic (Bangari et al. 2020). The paramagnetic substance has gram susceptibility in the range 10−5–10−3 and is attracted by magnetic fields (Gaeta et al. 2021). In this study, the magnetic susceptibility of MDM was studied by using a Sherwood scientific magnetic susceptibility balance, and the composite materials result shows from the minimum of 2.617 × 10−5 g susceptibility to above the range of the instrument. The gram susceptibility analysis confirms the magnetization of composite materials with a high potential to be attracted by external magnetic fields. This is due to the ferromagnetic coupling of Fe3O4 with TMD that may create spin-polarized carriers with a high molecular field for magnetization of MDM composite materials, as previously reported for magnetic montmorillonite (Cabrera et al. 2014) and MDM composites (Li et al. 2020). In addition, complete chemical silicate analysis results show an enhancement of Fe oxides composition in the MDM materials.

Point of zero charge

The point of zero charge (pzc) is the pH value for which the net charge on the surface of adsorbents is equal to zero; that is, there is an equal number of positive and negative charges on the surface, other than H+ and OH (Fito et al. 2023). The point of zero charges of MDM adsorbent was studied in the range pH 2–9 at two concentrations of NaNO3 (0.1 and 0.05 M) solution. As illustrated in Figure 3, the plot of ΔpH vs initial pH shows that pzc of MDM was obtained at pH = 6, similar to that reported for iron oxide modified DM by Jemutai-Kimosop et al. (2020). The surface charge of MDM bears net positive charges at pH < 6 and is negatively charged at pH > 6. pzc plays an important role in determining how easily the MDM adsorbent can adsorb Cr(VI) ions based on the surface nature of adsorbent at different pH ranges.
Figure 3

The pH of point of zero charges of MDM adsorbent.

Figure 3

The pH of point of zero charges of MDM adsorbent.

Close modal

ANOVA for the quadratic model

For the statistical evaluation of input effective variables (A, B, C, D) and in order to validate the empirical models, several parameters were considered. Analysis of variance (ANOVA) is an analytical technique that is used to identify the validity and adequacy of the models using Fisher's, F-test, and Student's t-test. In this case, F-values and P-values suggest the design factors, pH, adsorbent dose, initial Cr(VI) concentration, and contact time are highly significant for the quadratic model, as shown in Table 4. The Cr(VI) adsorption removal responses of the experimental design show optimal conditions at pH = 3, MDM = 0.6 g, initial Cr(VI) concentration = 16 mg·L−1 and contact times of 60 min with 98.89% removal efficiency and 26.36 mg·g−1 adsorption capacity (see Supplementary material, Table S3).

Table 4

Analysis of variance (ANOVA) for quadratic model of Cr(VI) adsorption removal

SourceSum of squaresDegree of freedomMean squareF-valuep-valueSignificance
Model 14,838.52 14 1,059.89 203.97 <0.0001 
A – pH 65.33 65.33 12.57 0.0002 
B – Adsorbent dose (g/L) 189.93 189.93 36.55 <0.0001 
C – Pollutant load (mg/L) 164.28 164.28 31.61 <0.0001 
D – Contact time 8,914.02 8,914.02 1,715.44 <0.0001 
A2 1,468.15 1,468.15 282.53 <0.0001 
B2 546.28 546.28 105.13 <0.0001 
C2 337.16 337.16 64.88 <0.0001 
D2 4,700.52 4,700.52 904.58 <0.0001 
Residual 72.75 14 5.20    
Lack of fit 72.75 10 7.27 1.63 0.2813 NS 
Cor total 14,911.27 28     
SourceSum of squaresDegree of freedomMean squareF-valuep-valueSignificance
Model 14,838.52 14 1,059.89 203.97 <0.0001 
A – pH 65.33 65.33 12.57 0.0002 
B – Adsorbent dose (g/L) 189.93 189.93 36.55 <0.0001 
C – Pollutant load (mg/L) 164.28 164.28 31.61 <0.0001 
D – Contact time 8,914.02 8,914.02 1,715.44 <0.0001 
A2 1,468.15 1,468.15 282.53 <0.0001 
B2 546.28 546.28 105.13 <0.0001 
C2 337.16 337.16 64.88 <0.0001 
D2 4,700.52 4,700.52 904.58 <0.0001 
Residual 72.75 14 5.20    
Lack of fit 72.75 10 7.27 1.63 0.2813 NS 
Cor total 14,911.27 28     

S, significant; NS, not significant.

In Table 4, the P-value of the quadratic model is <0.005, which shows that the quadratic model fits the Cr(VI) adsorption data on MDM adsorbent. The F-value of lack of fit of 1.63 indicates that the lack of fit is relatively low in comparison to the absolute errors. The model test shows that the design model accurately illustrates the data behavior for the experiments and the factors investigated have very significant effects on removal efficiency (Qiu et al. 2014). In the plots of actual vs predicted values for Cr(VI) adsorption data on MDM (Supplementary material, Figure S2), the predicted values are represented by straight lines inclined from the origin, while the actual points are also aligned with predicted values.

The BBD for Cr(VI) removal optimized model suggested a quadratic model, with adjusted and predicted regression (R2) values of 0.9902 and 0.9719, respectively, as shown in Table 5. The model is more acceptable when R2 approaches unity (Mondal et al. 2017). These factors have very large effects on removal efficiency (Qiu et al. 2014). In general, to validate this empirical model, several parameters were considered, such as probability < 0.05 would show the significance of the model and lack of fit should be not significant (>0.05), and adequate precision (signal-to-noise ratio) is ≥4, as shown in Table 4.

Table 5

Fit summary and statistics

Sourcep-valueAdjusted R2Predicted R2
Linear <0.0001 0.5636 0.5105 Not adequate 
2FI 0.9993 0.4280 0.2186 Not adequate 
Quadratic <0.0001 0.9902 0.9719 Suggested 
Cubic 0.8884 0.9851 0.5395 Aliased 
Sourcep-valueAdjusted R2Predicted R2
Linear <0.0001 0.5636 0.5105 Not adequate 
2FI 0.9993 0.4280 0.2186 Not adequate 
Quadratic <0.0001 0.9902 0.9719 Suggested 
Cubic 0.8884 0.9851 0.5395 Aliased 

Optimization of factors for Cr(VI) adsorption removal using Box–Behnken design

Graphical interpretation of interactions by using three-dimensional (3-D) plots of the regression model is highly recommended and is used to assess the interactive effects between the process variables and treatment efficiencies of dependent variables (Asghar et al. 2014). The interaction effects of four designed variables, namely, pH, adsorbent dose, initial Cr(VI) concentration, and contact time, are shown in Figure 4(a)–4(d). The Cr(VI) adsorption removal varies from a minimum of 29.94% to a maximum of 98.89% at optimal independent variables of adsorbent doses = 0.60 g·L−1, initial Cr(VI) = 16 mg·L−1, pH = 3, and contact time = 60 min. Similarly, the MDM Cr(VI) removal efficiency was evaluated for Ziang Xuang tannery effluents. The Ziang Xuang tannery is one of the highly environmentally polluting tanning factories in Addis Ababa, Ethiopia, and its wastewater effluent contains about 53.598 mg·L−1 of total chromium. The permissible concentration limits of Cr(VI) in most industrial waste effluents are 0.05–0.1 mg·L−1 (Sun et al. 2017a). Thus, the MDM adsorbent showed 76.04% remediation of Cr(VI) from Ziang Xuang tannery effluents at optimized parameters.
Figure 4

The 3-D structures of interaction effects of (a) pH vs adsorbent dose, (b) pH vs initial Cr(VI) concentration, (c) pollutant load vs adsorbent dose, and (d) contact time vs adsorbent dose.

Figure 4

The 3-D structures of interaction effects of (a) pH vs adsorbent dose, (b) pH vs initial Cr(VI) concentration, (c) pollutant load vs adsorbent dose, and (d) contact time vs adsorbent dose.

Close modal

Effect of pH on Cr(VI) adsorption

The pH of a solution changes the chemical states of active groups and the charge distribution on the adsorbent surface and the dissolution of pollutants in the solution, whereby all of them affect the adsorbent's adsorption affinity (Bilgiç & Karapınar 2022). As depicted in Figure 4(a), at low pH, MDM adsorbs protons (H+) and its surface is positively charged due to the presence of Si-OH functional groups (Yang et al. 2017). Cr(VI) ions exist mostly in three forms, i.e. oxyanions in aqueous solution such as , , and , depending on the solution pH. In an extremely acidic environment (pH < 1), Cr(VI) ions exist as H2Cr2O7 and where the pH is in the range 2–6, Cr(VI) exists predominantly as oxyanions (Belibağli et al. 2020). Among Cr(VI) oxyanions, is the most prominent species to be adsorbed on the positive surface (Sun et al. 2017a). This may account for maximum Cr(VI) adsorption values on DM and TMD that were obtained at pH 3. This result is in agreement with previous reports (Memedi et al. 2021). Also, Fe3O4 functionalization of TMD does not significantly change the pH of MDM for maximum Cr(VI) adsorption, allowing maximum adsorption performance at a pH of 3. Similar results were reported for Cr(VI) removal using activated carbon–attapulgite clay composite (Hlungwane et al. 2018), clay–biochar composite (Wang et al. 2019) and DM supported by zero-valent iron nanoparticle (Zhang et al. 2019). While the pzc of MDM was obtained at pH 6, as the solution pH increases from 3 to 5, the adsorption capacity decreases. This is explained by the fact that, as the solution pH approaches the pzc, there is a decrease in the positive charge density on the MDM surface and therefore less electrostatic interaction with ions. In contrast, increasing solution pH above pzc, the MDM surface is negatively charged and adsorption of Cr(VI) ions on the negative adsorbent surface leads to electrostatic repulsion interaction between the negatively charged surface of MDM and Cr(VI) ions. In addition, the Cr(VI) ion is competing with OH ions above pzc (pH > 6) (Bilgin & Tulun 2015).

Effects of initial Cr(VI) concentration

Figure 4(b) illustrates that removal efficiency increases as the initial Cr(VI) ion concentration increases and reaches its maximum at 16 mg·L−1 with 98.89% removal. However, further increase in Cr(VI) initial concentration up to 30 mg·L−1 shows a decline in removal efficiency and this may be due to the ratio of active adsorption surface sites on MDM surfaces that are occupied with Cr(VI) ions in the solution. An increase in the initial concentration above the maximum level cannot favor the adsorption process (Jayasree et al. 2021).

Effect of adsorbent dose for Cr(VI) adsorption

As shown in Figure 4(c), increasing the adsorbent doses from 0.30 to 0.60 g L−1 enhances the Cr(VI) adsorption removal and this may be due to an increase in the number of binding sites on the adsorbent surfaces. MDM shows rapid uptake of Cr(VI) with increasing adsorbent doses and attained equilibrium at 0.60 g·L−1 with more than 98.89% of adsorption removal. Also, increased concentration of MDM to 1 g·L−1 decreases the Cr(VI) adsorption and this may be due to more adsorbent–adsorbent (hole–hole) interaction than with Cr(VI) ions (Acharya et al. 2017).

Effects of contact time on Cr(VI) adsorption removal

As shown in Figure 4(d), rapid initial adsorption of MDM is observed in the time-dependent kinetic adsorption data. This is likely to be due to initial excess active adsorption sites, and Cr(VI) ions easily interacting with active sites (Yang et al. 2017). As contact time increases from 45 to 60 min, MDM adsorption rates reach the maximum of 89.98% at 60 min. However, with a further increase in contact time of Cr(VI) ions with MDM to above 60 min, the results show a slowdown of adsorption rates and reach a stagnant state. This occurs because all available active adsorption sites are occupied with Cr(VI) and a further increase in contact time does not facilitate the adsorption process.

Adsorption kinetic studies

Time-dependent adsorption studies can be used to estimate the adsorption rate and adsorption mechanism from experimental adsorption data (Liu et al. 2022). A better understanding of kinetic data is crucial to gain a clearer explanation of the adsorption mechanism. Thus, to explore the reaction mechanism and pathways between the Cr(VI) and MDM, the adsorption data were analyzed using pseudo-first-order, pseudo-second-order, and intra-particle diffusion models and the linear plot equation of each model was expressed using the following equations (Giraldo et al. 2013; Zhang et al. 2023):
formula
(6)
formula
(7)
formula
(8)
where qt is the adsorption capacity by the adsorbent (mg·g−1) at time t (min); qe is the maximum adsorption capacity (mg·g−1); k1 and k2 are the rate coefficients of the pseudo-first-order kinetic (min−1) and the pseudo-second-order kinetic (g·mg−1·min−1); Kid is the intra-particle diffusion constant (mg·g−1·h1/2) and is square root of time.
The kinetic experimental data were plotted for each kinetic model: ln(qeqt) vs t for PFO; vs t for PSO and qt vs for IPD. The adsorption kinetic parameters were estimated from the slope (m) and intercepts (b) of corresponding linear plots. The adsorption kinetic model matched well with the pseudo-first-order model (Figure 5) and other kinetic properties are exhibited in Table 6. It should be noted that the pseudo-second-order model best suits the Cr(VI)adsorption data on DM, TMD, and MDM adsorbents along with correlation coefficient (R2) of 0.9853, 0.9996, and 0.9998, respectively. Thus, the Cr(VI) adsorption follows the PSO mechanism, and is likely controlled by chemisorption (Giraldo et al. 2013). Similarly, experimental adsorption shows smaller Chi-square (X2) statistics for PSO, i.e. the calculated adsorption capacity (qe.cal) is closer to the experimental adsorption capacities (qe.exp). Furthermore, the removal of Cr(VI) using tested adsorbent materials obeys PSO rate kinetics, where chemisorption is considered to be the rate-controlling step as previously reported for different clay-based composite adsorbents (Hlungwane et al. 2018; Adisu et al. 2022).
Table 6

Parameters derived from pseudo-first, pseudo-second-order and intra-particle diffusion kinetic models

AdsorbentPseudo-first-order
Pseudo-second-order
Intra-particle diffusion
qe,Cal (mg·g−1)k1 (min−1)R2k2 (g·mg−1 min−1)qe.Calc. (mg·g−1)R2Ki (mg·g−1min1/2)CR2
DM 14.266 −3.224 × 10−3 0.834 −1.546 15.601 0.9853 −0.869 22.879 0.5163 
TMD 14.391 6.909 × 10−4 0.780 2.457 × 101 24.272 0.9996 0.1040 23.013 0.6346 
MDM 14.581 3.224 × 10−3 0.801 −2.5 × 103 25.839 0.9998 0.0553 24.609 0.7345 
AdsorbentPseudo-first-order
Pseudo-second-order
Intra-particle diffusion
qe,Cal (mg·g−1)k1 (min−1)R2k2 (g·mg−1 min−1)qe.Calc. (mg·g−1)R2Ki (mg·g−1min1/2)CR2
DM 14.266 −3.224 × 10−3 0.834 −1.546 15.601 0.9853 −0.869 22.879 0.5163 
TMD 14.391 6.909 × 10−4 0.780 2.457 × 101 24.272 0.9996 0.1040 23.013 0.6346 
MDM 14.581 3.224 × 10−3 0.801 −2.5 × 103 25.839 0.9998 0.0553 24.609 0.7345 
Figure 5

Linear plot of (a) pseudo-first-order, (b) pseudo-second-order, and (c) intra-particle diffusion models for time-dependent Cr(VI) adsorption data.

Figure 5

Linear plot of (a) pseudo-first-order, (b) pseudo-second-order, and (c) intra-particle diffusion models for time-dependent Cr(VI) adsorption data.

Close modal

Adsorption isotherm studies

Various isotherm models have been reported to describe the distribution of adsorbate in the bulk solution and at the solid–liquid interface. The isotherm study adsorption process is essential for the investigation of the interaction between adsorbent and adsorbate molecules. The isotherm study also gives information about the surface nature coverage (monolayer or multilayer formation). In this study, Langmuir and Freundlich isotherm models were investigated to describe the Cr(VI) adsorption isotherm process on MDM adsorbent. The Langmuir adsorption isotherm model assumes the sorption process takes place at specific homogeneous sites on the adsorbent leading to monolayer surfaces with no interaction between the adsorbed molecules (Armbruster & Austin 1938) and is used to predict the theoretical maximum adsorption capacity of adsorbent (qmax) in mg·g−1. The linear form of the Langmuir model can be expressed as:
formula
(9)
The Langmuir adsorption constants qmax and KL can be calculated from the linear plot of vs Ce, which gives a straight line with slope and intercepts of . The Langmuir dimensionless separation factor (RL) was used to determine the possibility of adsorption process and indicates the shape of adsorption isotherm.
formula
where Co is highest initial concentration of adsorbate (mgL−1); KL is Langmuir adsorption constant (L·mg−1), which relates to the free energy of adsorption; and RL is dimensionless Langmuir separation factor that provides information about whether the adsorption process is reversible (RL = 0), favorable (0 < RL <1), linear (RL = 1), or unfavorable (RL > 1).

In contrast, the Freundlich isotherm model assumption was based on heterogeneity of adsorption surface and the active sites difference gives different adsorbate and adsorbent interfaces based on multilayer adsorption properties (Foo & Hameed 2010). The Freundlich isotherm model defines the behavior of adsorption as non-ideal, reversible, and non-restricted to monolayer formation, and assumes non-uniform distribution of adsorption heat and affinities over the adsorbent surface (Alam et al. 2021).

The linearized form of the Freundlich model can be given as follows:
formula
(10)
where KF is the Freundlich adsorption isotherm constant and n is the Freundlich empirical constant that measures adsorption intensity and provides information about adsorption nature as irreversible (1/n = 0), favorable (0 < 1/n < 1), or unfavorable adsorption (1/n > 1). The Freundlich isotherm parameters KF and n can be calculated from linear plots of ln qe vs lnCe, which gives a straight line with slope and y-intercepts of KF.
As shown in Figure 6 and Table 7, the Langmuir isotherm model best fits the adsorption mechanism with a corresponding coefficient of regression (R2) of 9,753 and 9,941 for MD and TMD, respectively. Also, the calculated RL values of DM and TMD were 0.0165 and 0.0164 and found in the ranges of 0–1: this confirms that the Cr(VI) adsorption result best fits the Langmuir adsorption isotherm model. The surface properties of DM and MDM show uniform adsorption active sites of protonated silanols (), as previously reported (Mohamed et al. 2018). As shown in Table 7, the R2 values of the Freundlich model for Cr(VI) on MD and TMD are 0.947 and 0.919, respectively. This indicates that the Langmuir models are more representative of Cr(VI) adsorption on MD and TMD adsorbents. The correlation coefficients (R2) for the Langmuir and Freundlich isotherm for Cr(VI) adsorption using MDM are 0.964 and 0.989, respectively. This shows that both the Langmuir and Freundlich models successfully describe the Cr(VI) adsorption on MDM surfaces. From the Langmuir model parameters, RL value is 0.271, confirming the favorable adsorption process. The calculated relative Freundlich adsorption isotherm parameters value is 0.7129, which is in the range 0 < < 1, showing the Freundlich adsorption isotherm possibilities. This can be attributed to thin layers of magnetite developed on DM surface sites, consistent with previous reports (Yuan et al. 2013).
Table 7

Data calculated from adsorption isotherm models graphs

AdsorbentLangmuir constant parameters
Freundlich parameters
qmaxKLRLR2KFR2
DM 26.316 3.732 0.0164 0.9753 1.0876 0.7023 0.9471 
TMD 29.762 3.730 0.0165 0.9944 0.0959 0.7298 0.9194 
MDM 88.495 0.168 0.271 0.9648 1.0914 0.7129 0.9899 
AdsorbentLangmuir constant parameters
Freundlich parameters
qmaxKLRLR2KFR2
DM 26.316 3.732 0.0164 0.9753 1.0876 0.7023 0.9471 
TMD 29.762 3.730 0.0165 0.9944 0.0959 0.7298 0.9194 
MDM 88.495 0.168 0.271 0.9648 1.0914 0.7129 0.9899 
Figure 6

Plots of Langmuir and Freundlich isotherms of MD (a,b), TMD (c,d), and MDM (e,f), respectively.

Figure 6

Plots of Langmuir and Freundlich isotherms of MD (a,b), TMD (c,d), and MDM (e,f), respectively.

Close modal

Thermodynamics of Cr(VI) adsorption process

The thermodynamic parameters, namely the standard in Gibbs free energy (ΔG°), the standard entropy (ΔS°), and the standard enthalpy changes (ΔH°), were calculated using Van't Hoff equations to understand the nature of Cr(VI) adsorption on MDM. The enthalpy (ΔH°) in kJ·mol−1, entropy (ΔS°) in kJ·mol−1K−1and Gibbs free energy (ΔG°) in kJ·mol−1 for adsorption of Cr(VI) was determined at thermodynamic equilibrium constants (Kc). The Gibbs free energy of the adsorption is given as follows:
formula
(11)
where is given by Van't Hoff equations and applying the equation of Sheng et al. (2009) as follows;
formula
(12)
formula
(13)
formula
(14)
where Kc is the equilibrium constant, Co and Ce are the initial and equilibrium concentration in mg·L−1, V is the volume of solution in liters, and M is the weight of adsorbent in g·L−1. From the Van't Hoff linear plots of lnKc vs 1/T, the thermodynamic parameters, enthalpy (ΔH°), and standard adsorption entropy change (ΔS°) were determined from slopes and y-intercepts, respectively.
The influence of temperature (303–343 K) on Cr(VI) adsorption using DM, TMD, and MDM was studied with the obtained results shown in Figure 7 and Table 8. Thus, immobilization of Cr(VI) on DM and TMD and its enthalpy value (ΔHo) were determined at 19.778 and 32.895 kJ·mol−1·K−1, respectively. The positive ΔHo value of adsorption indicates that the process is endothermic and that increasing temperature favors further adsorption of Cr(VI)ions on the surface of DM and TMD adsorbents. However, the ΔHo value of Cr(VI) adsorption on MDM was −2.19 kJ · mol−l·K−1, and negative ΔHo of reaction indicates an exothermic adsorption process. This implies that increasing temperature cannot favor the adsorption of Cr(VI) ions. This is due to decreased residual attraction forces (surface energy) on the adsorbent surface, which may evolve heat. The entropy (ΔS°) values of DM, TMD, and MDM have positive values, confirming that some structural change has occurred during the Cr(VI) adsorption process, and MDM shows more stability as seen from the entropy values of Table 8.
Table 8

Thermodynamic parameters studies of Cr(VI) adsorption removal using DM, TMD, and MDM adsorbents

AdsorbentΔHo (kJ·mol−1k−1)ΔS° (kJ·mol−1k−1)ΔG° (kJ·mol−1)
303.15 K323.15 K343.15 K
DM 19.778 2.6481 −782.993 −835.955 −888.917 
TMD 32.895 1.8073 −514.987 −551.134 −587.297 
MDM −2.190 1.0617 −324.044 −345.278 −366.512 
AdsorbentΔHo (kJ·mol−1k−1)ΔS° (kJ·mol−1k−1)ΔG° (kJ·mol−1)
303.15 K323.15 K343.15 K
DM 19.778 2.6481 −782.993 −835.955 −888.917 
TMD 32.895 1.8073 −514.987 −551.134 −587.297 
MDM −2.190 1.0617 −324.044 −345.278 −366.512 
Figure 7

The plots of thermodynamic adsorption removal of Cr(VI) on DM, TMD, and MDM.

Figure 7

The plots of thermodynamic adsorption removal of Cr(VI) on DM, TMD, and MDM.

Close modal

Desorption and reusability of regenerated MDM adsorbent

The ability of an effective sorbent to be regenerated and safe disposal of wastewater is a key aspect in determining its economic viability (Momina et al. 2018). As shown in Figure 8, the adsorption capacity of MDM decreased only slightly after each adsorption–regeneration cycle and after five consecutive adsorption–desorption tests, MDM shows a 12% loss of its Cr(VI) removal efficiency with NaOH as desorbent (Supplementary material, Table S4). The Fe3O4 nanoparticles provide excellent magnetic separation capacity and are frequently employed to improve separation efficiency (Bilgiç & Karapınar 2022). Similarly, Fe3O4-modified materials show high alkali solution stability (Zhao et al. 2019). Also, as shown in Figure 9, the FTIR spectra peaks of MDM decreased after Cr(VI) adsorption, consistent with a previous report (Mohamed et al. 2018), and confirms the electrostatic types of the adsorption process. This is due to the electrostatic interaction of protonated silanols () on the surface of MDM with Cr(VI) () ions. However, after Cr(VI) desorption from the MDM surface with NaOH de-sorbents, it regains its original FTIR spectrum. This shows that the MDM adsorbent is highly stable with reuse potential for five consecutive Cr(VI) adsorption–desorption cycles.
Figure 8

The Cr(VI) desorption capacity of NaOH from MDM surface and its Cr(VI) adsorptive removal efficiency of regenerated adsorbent.

Figure 8

The Cr(VI) desorption capacity of NaOH from MDM surface and its Cr(VI) adsorptive removal efficiency of regenerated adsorbent.

Close modal
Figure 9

FTIR spectra of MDM, Cr(VI) adsorbed MDM (Cr + MDM), and after desorption of adsorbed Cr(VI) from MDM surface (Cr-MDM).

Figure 9

FTIR spectra of MDM, Cr(VI) adsorbed MDM (Cr + MDM), and after desorption of adsorbed Cr(VI) from MDM surface (Cr-MDM).

Close modal

Comparison of MDM with other clay composite adsorbents for adsorptive removal of Cr(VI)

Clay-based composites have received much attention for the adsorption removal of different pollutants due to their high stability, low cost, and high adsorption capacities. The maximum adsorption capacity of MDM adsorbent obtained was 88.49 mg/g−1 of Cr(VI). This makes MDM a very promising adsorbent with 76.04% of Cr(VI) removal from a real industrial tannery effluent containing Cr(VI). The high adsorption capacity of MDM can be ascribed to the electrostatic attraction between negatively charged Cr(VI) oxyanions and positive charges of MDM surface at optimized values. Table 9 summarizes the Cr(VI) adsorption capacity reported for various clay-based composite adsorbents. In this study, MDM was found to be effective for the removal of heavy metal contaminants and compared to other adsorbents, it has high adsorption efficiency at low adsorbent dose and room temperature. MDM can be synthesized from cheap and easily available clay minerals, so its use may contribute to sustainable waste treatments. Moreover, MDM can be easily separated from the solution using an external magnetic field with reuse capacity.

Table 9

Comparison of MDM adsorbent for Cr(VI) removal capacity with other clay-based composite adsorbents

Clay-based composite adsorbentsAdsorbent dose (mg/g)Temp (°C)Percent removal (%) or maximum adsorption capacity (mg/g)Isotherm modelKinetic modelReferences
Carbon–diatomite 6.35 45 19.91 mg/g Langmuir Pseudo-second-order Sun et al. (2017b)  
Magnetic bentonite 2.5 35 96.84% Tempkin Pseudo-second-order Belibağli et al. (2020)  
Kaolinite–Fe/Al oxide (hydroxide) 25 70.71 mg/g Langmuir – Bezza & Chirwa (2022)  
Chitosan-coated bentonite clay 0.04 25 106.444 mg/g Dubinin Radushkevich – Altun (2020)  
Magnetic zeolite 25 43.93 mg/g Langmuir Pseudo-first-order Asanu et al. (2022)  
Magnetite diatomite 0.6 25 88.49 mg/g Langmuir and Freundlich Pseudo-second-order This study 
Clay-based composite adsorbentsAdsorbent dose (mg/g)Temp (°C)Percent removal (%) or maximum adsorption capacity (mg/g)Isotherm modelKinetic modelReferences
Carbon–diatomite 6.35 45 19.91 mg/g Langmuir Pseudo-second-order Sun et al. (2017b)  
Magnetic bentonite 2.5 35 96.84% Tempkin Pseudo-second-order Belibağli et al. (2020)  
Kaolinite–Fe/Al oxide (hydroxide) 25 70.71 mg/g Langmuir – Bezza & Chirwa (2022)  
Chitosan-coated bentonite clay 0.04 25 106.444 mg/g Dubinin Radushkevich – Altun (2020)  
Magnetic zeolite 25 43.93 mg/g Langmuir Pseudo-first-order Asanu et al. (2022)  
Magnetite diatomite 0.6 25 88.49 mg/g Langmuir and Freundlich Pseudo-second-order This study 

Adsorption mechanism

Silanol (Si-OH), the main functional group in DM, provides a suitable shell structure and ideal coating layer for Fe3O4 with its chemical stability and easy surface modification (Bilgiç & Karapınar 2022). Cr(VI) adsorption capacity is pH dependent and the point of zero charges (zero surface charge) of MDM was obtained at pH = 6. At pH < pzc the adsorbent surface was protonated with positive surfaces () as shown in Figure 10 and protonated surface may create electrostatic interaction with negatively charged ions. However, at pH > 6, the surface charge of MDM is negative, and there is electrostatic repulsion of Cr(VI) ion from the negative surface, and this is reasonable for low adsorption capacity.
Figure 10

Sketch of Cr(VI) adsorption–desorption mechanism on MDM nanocomposite.

Figure 10

Sketch of Cr(VI) adsorption–desorption mechanism on MDM nanocomposite.

Close modal

In this case, Cr(VI) adsorption occurs: first, the MDM adsorbs protons in acid conditions (pH = 3) and is positively charged. Then, the electrostatic interaction between the positively charged surface and the predominant Cr(VI) species in acidic environments (pH = 2–5) is , which accounts for high Cr(VI) adsorption capacity (Zhang et al. 2019). Fe3O4 immobilization on DM increases the functional group density on the MDM surface and accounts for the effective chemical entrapment of Cr(VI) ions (Li et al. 2014; Sun et al. 2017b). At high pH of alkaline solution, the Cr(VI) ions can be desorbed from the MDM surface and the adsorbent materials regenerated for reuse as shown in the proposed mechanism in Figure 10.

MDM nanocomposite was fabricated as a low-cost adsorbent for effective Cr(VI) removal from wastewater. Batch experiments were performed to investigate kinetics, equilibrium isotherm, and thermodynamics of the Cr(VI) sorption process on MDM adsorbent. The synergetic effects between Fe3O4 and TMD composite show 98.89% removal efficiency and 26.36 mg·g−1 adsorption capacity of Cr(VI) at BBD-RSM designed optimal parameters. The optimal Cr(VI) adsorption on MDM adsorbent was obtained at adsorbent dose = 0.6 g·L−1, pH = 3, initial Cr(VI) concentration = 16 mg·L−1, and contact time of 60 min. The adsorption process is best described by pseudo-second-order kinetic models, while both the Langmuir and Freundlich adsorption isotherm best describe the adsorption process of MDM with a maximum adsorption capacity of 88.49 mg·g−1. Thermodynamic experimental data revealed the adsorption process is exothermic and spontaneous for Cr(VI) uptake by composite adsorbents. MDM is highly stable for Cr(VI) removal over five reuse cycles; only a 12% decrease in its removal efficiency was observed after five adsorption–desorption cycles. When the ferromagnetic Fe3O4 is intercalated into the TMD layer, it enhances adsorption capacity and improves adsorbent recovery by an external magnetic field. In addition, the MDM is a suitable adsorbent for removing Cr(VI) from real tannery wastewater. On this basis, MDM composite could be an efficient, sustainable and affordable adsorbent with a promising potential for eliminating Cr(VI) from tannery effluents.

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

The authors declare there is no conflict.

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