Use of Brazilian Kaolin as a Potential Low-cost Adsorbent for the Removal of Malachite Green from Colored Effluents

Abstract

This study investigated the potential of Brazilian kaolin as a low-cost adsorbent for the removal of Malachite Green (MG) from colored effluents. The morphology, chemical structure and surface properties of the adsorbent were investigated by characterization techniques such as X-ray diffraction, N2 adsorption-desorption isotherms, Fourier transform infrared spectroscopy, X-ray fluorescence spectrometry, scanning electron microscopy, thermogravimetric analysis and particle size distribution. A possible technological application of raw kaolin is the MG removal from aqueous media, which was investigated using batch adsorption experiments. The adsorption kinetics was studied using the pseudo-first order, pseudo-second order and Elovich models. The adsorption isotherms were studied using the Langmuir, Freundlich and Sips models. The Elovich model was the more adequate to represent the adsorption kinetic, while the equilibrium was well represented by the Langmuir model. The maximum adsorption capacity, at pH of 6.3 and temperature of 25ºC, was 128 mg g^-1, and this satisfactory result may be associated with some adsorbent properties. Therefore, the results revealed that raw kaolin can be utilized as a promising low-cost adsorbent to remove MG from colored effluents.

Keywords:
Kaolin; characterization; low-cost adsorbent; adsorption; Malachite Green

Introduction

Dyes are used as coloring agents in many industries, and if improperly discarded into the environment, it can cause adverse effects to the human life and aquatic ecosystem^1,2. Some methods used for dye removal from industrial wastewater are flotation³, filtration⁴, adsorption^5-8 and photocatalysis^9,10. Among the various available methods, the adsorption process is one of the most effective techniques, which has been successfully employed for dye removal from wastewater^11-17. Adsorption process offers significant advantages such as low-cost, efficiency and operational ease¹⁸. Low-cost materials may be used as promising dye adsorbents in order to make the adsorption process less expensive. In this sense, several low-cost materials have been used as adsorbents to treat dye-containing wastewater^19-23. Among them, clay minerals have been used as a potential adsorbents for this purpose^23,24.

Kaolin is a clay predominantly composed by kaolinite (Al₂Si₂O₅(OH)₄)²⁵, which has been widely used in a variety of technological applications^26-40. Due to the low-cost and large availability, the use of clays like kaolin becomes the adsorption process an attractive and promising technology. Although there are several works in literature reporting the removal of different classes of dyes onto kaolin^41-44, no studies were found reporting the application of a natural kaolin sample from the Rio Grande do Sul State (Brazil) for the removal of Malachite Green dye.

In this context, the aim of the present work was to investigate the potential application of a Brazilian kaolin sample as an adsorbent for the removal of Malachite Green dye from aqueous solution. Kinetic and equilibrium models were studied in order to elucidate the adsorption process.

2. Materials and Methods

2.1. Materials

The natural kaolin was obtained from a mining company located in Rio Grande do Sul State, Brazil. The sample was used as received. Malachite Green (MG) (Sigma-Aldrich, CAS number: 569-64-2, C₂₃H₂₅ClN₂, 364.91 g mol^-1) was used as target dye pollutant. The chemical structure of MG dye is shown in Figure 1.

Figure 1
Chemical structure of MG dye.

2.2. Characterization techniques

X-ray diffraction pattern (XRD) was obtained using a Rigaku Miniflex 300 diffractometer, where, the X-ray source was Cu-Kα radiation, powered at 30 kV and 10 mA. Scans were performed over 2θ angles ranging from 5 to 70º. N₂ adsorption-desorption isotherms were obtained at 77 K using an ASAP 2020 apparatus. The particle size distribution was measured using a laser particle size analyzer (Malvern Mastersizer 2000). Derivative thermogravimetric analysis (DTA) and thermogravimetric analysis (TGA) were carried out in a Netzsch STA 409 analyzer, at a heating rate of 10 ºC min^-1 and air flow rate of 35 mL min^-1. The sample morphology was examined by a scanning electron microscope (SEM, JEOL JSM-6610LV) at 15 kV. Chemical composition of the sample was determined by X-ray fluorescence spectrometry (XRF) (Bruker S8 Tiger equipment). Fourier transform infrared (FTIR) spectrum was recorded on a Shimadzu IR-Prestige-21 spectrophotometer in the range of 4000-375 cm^-1.

2.3. Adsorption experiments

In order to determine the adsorption capacity of the kaolin adsorbent, various concentrations (100 - 175 mg L^-1) of the MG dye were prepared and, 100 mL of each were added to 0.1 g of adsorbent. All the adsorption experiments were performed at natural pH of dye solution (pH = 6.3). The mixtures were agitated on a shaker for 240 min at 100 rpm and 25 ºC. After, the solutions were centrifuged (Centribio, 80-2B, Brazil) and immediately analyzed using a UV-vis spectrophotometer (Bel Photonics, SP1105) at 618 nm to verify the residual MG concentration. All experiments were carried out in triplicates and blanks were performed. The equilibrium adsorption capacity (q_e) and adsorption capacity at any time (q_t) were determined by Equations (1) and (2), respectively:

(1) ${\mathit{q}}_{\mathit{e}}=\frac{\mathit{V}({\mathit{C}}_0-{\mathit{C}}_{\mathit{e}})}{\mathit{m}}$

(2) ${\mathit{q}}_{\mathit{t}}=\frac{\mathit{V}({\mathit{C}}_0-{\mathit{C}}_{\mathit{t}})}{\mathit{m}}$

where, C₀ is the initial dye concentration in liquid phase (mg L^-1), C_e is the equilibrium dye concentration in liquid phase (mg L^-1), C_t is the dye concentration in liquid phase at any time (mg L^-1), m is the amount of adsorbent (g) and V is the volume of solution (L).

2.4. Kinetic and equilibrium modeling

Some kinetic and equilibrium models were employed to interpret the MG adsorption process on the kaolin adsorbent. Regarding to the kinetic models, pseudo first-order⁴⁵, pseudo second-order⁴⁶ and Elovich models⁴⁷ were used. These models are given by the Equations (3), (4) and (5), respectively:

(3) ${\mathit{q}}_{\mathit{t}}={\mathit{q}}_1(1-\exp (-{\mathit{k}}_1\mathit{t}\mathrm{))}$

(4) ${\mathit{q}}_{\mathit{t}}=\frac{\mathit{t}}{(1/{\mathit{k}}_2{\mathit{q}}_2^2)+(\mathit{t}/{\mathit{q}}_2)}$

(5) ${\mathit{q}}_{\mathit{t}}=\frac{1}{\mathit{b}}1n(1+\mathit{abt})$

where, k₁ and k₂ are the rate constants of pseudo first-order (min^-1) and pseudo second-order (g mg^-1 min^-1) models, respectively; q₁ and q₂ are the theoretical values for the adsorption capacity (mg g^-1), a is the initial velocity due to dq/dt with q_t = 0 (mg g^-1 min^-1), b is the desorption constant of the Elovich model (g^-1 mg^-1) and t is the time (min).

The equilibrium curves were interpreted by the Freundlich⁴⁸, Langmuir⁴⁹ and Sips⁵⁰ isotherm models. These models are given by the Equations (6), (7) and (8), respectively,

(6) ${\mathit{q}}_{\mathit{e}}={\mathit{K}}_{\mathit{F}}{\mathit{C}}_{\mathit{e}}^{1/{\mathit{n}}_{\mathit{F}}}$

(7) ${\mathit{q}}_{\mathit{e}}=\frac{{\mathit{q}}_{\mathit{m}}{\mathit{K}}_{\mathit{L}}{\mathit{C}}_{\mathit{e}}}{1+({\mathit{K}}_{\mathit{L}}{\mathit{C}}_{\mathit{e}}}$

(8) ${\mathit{q}}_{\mathit{e}}=\frac{{\mathit{q}}_{\mathit{S}}({\mathit{K}}_{\mathit{S}}{\mathit{C}}_{\mathit{e}}{)}^{\mathit{ms}}}{1+({\mathit{K}}_{\mathit{S}}{\mathit{C}}_{\mathit{e}}{)}^{\mathit{ms}}}$

where, K_F is the Freundlich constant (mg g^-1)(mg L^-1)^-1/nF, 1/n_F is the heterogeneity factor, q_m is the maximum adsorption capacity (mg g^-1), K_L is the Langmuir constant (L mg^-1), q_S is the maximum adsorption capacity from Sips model (mg g^-1), K_S is the Sips constant (L mg^-1) and ms is the Sips exponent.

2.5. Parameters estimation

The kinetic and equilibrium parameters were determined by the fit of the models with the experimental data using nonlinear regression. The parameters were estimated by the minimizing the least squares function using the Quasi-Newton estimation method. The calculations were carried out using the Statistic 9.1 software (Statsoft, USA)⁵¹. The fit quality was verified by the obtainment of determination coefficient (R²) , average relative error (ARE) and Akaike information criterion (AIC)^52,53, which are presented in the Equations (9), (10) and (11), respectively:

(9) ${\mathit{R}}^2=\left(\frac{{\sum }_{\mathit{i}}^{\mathit{n}}({\mathit{q}}_{\mathit{i},\exp }-{\stackrel{─}{\mathit{q}}}_{\mathit{i},\exp }{)}^2-{\sum }_{\mathit{i}}^{\mathit{n}}({\mathit{q}}_{\mathit{i},\exp }-{\mathit{q}}_{\mathit{i},\mathrm{mod}\mathit{el}}{)}^2}{{\sum }_{\mathit{i}}^{\mathit{n}}{\mathit{q}}_{\mathit{i},\exp }{\stackrel{─}{\mathit{q}}}_{\mathit{i},\exp }{)}^2}\right)$

(10) $\mathit{ARE}=\frac{100}{\mathit{n}}\sum _{\mathit{i}=1}^{\mathit{n}}\left|\frac{{\mathit{q}}_{\mathit{i},\mathrm{mod}\mathit{el}}-{\mathit{q}}_{\mathit{i},\exp }}{{\mathit{q}}_{\mathit{i},\exp }}\right|$

(11) $\begin{array}{c}\mathit{AIC}=\mathit{n}1n\left(\frac{\mathit{SSE}}{\mathit{n}}\right)+2\mathit{p}+\hfill \\ \frac{2\mathit{p}(\mathit{p}+1)}{\mathit{n}-\mathit{p}-1}\hfill \end{array}$

where, q_i,model corresponds to each value of q predicted by the fitted model, q_i,exp corresponds to each value of q experimentally measured, q_i,exp is the average of q experimentally measured, n is the number of experimental points, p is the number of parameters of the fitted model and, the sum of squared errors (SSE) is given by the Equation (12):

(12) $\mathit{SSE}=\sum _{\mathit{i}=1}^{\mathit{n}}({\mathit{q}}_{\mathit{i},\mathrm{mod}\mathit{el}}-{\mathit{q}}_{\mathit{i},\exp }{)}^2$

3. Results and Discussion

3.1. Characterization of kaolin

XRD pattern of raw kaolin is shown in Figure 2. The main reflections of kaolinite were at 2θ = 12.36º, 19.94º, 24.90º, 35.98º, 38.46º, 45.66º, 55.12º and 62.34º, which is matched with the JCPDS database file (PDF-01-089-6538). These findings are consistent with other previously reported works^54,55. Therefore, the sample showed a predominant phase as kaolinite, and also, quartz as minor impurity. The chemical composition (wt.%) obtained from XRF analysis of natural kaolin was: 43.50 (SiO₂), 40.03 (Al₂O₃), 0.56 (Fe₂O₃), 0.33 (K₂O), 0.27 (MgO), 0.17 (CaO), 0.08 (TiO₂), 0.02 (MnO), 0.02 (SO₃), 15.01 (Mass loss on ignition, obtained from TGA analysis). Typically, a pure kaolinite mineral is made up of 46.5 wt.% of SiO₂ and 39.5 wt.% of Al₂O₃, and exhibits 14 wt.% of mass loss on ignition⁵⁶. Therefore, the composition of the kaolin used in this work was close to a kaolinite mineral with high purity degree. The minor differences can are attributed to the presence of accessory minerals.

Figure 2
XRD pattern of raw kaolin.

FTIR spectrum of raw kaolin is shown in Figure 3. The main characteristic bands of the kaolinite are highlighted in Figure 3. The bands at 3694 and 3619 cm^-1 (OH stretching vibrations), 1114 and 694 cm^-1 (Si-O stretching), 1031 cm^-1 (Si-O-Si), 1008 and 540 cm^-1 (Si-O-Al) and, 912 cm^-1 (Al-OH) are typical of kaolinite mineral^56,57. Bands located at 789, 753 and 468 cm^-1 can be attributed to the presence of quartz^57-60. Vibration at 432 cm^-1 can be related to the deformation mode of Si-O or Al-O bonds⁶¹.

Figure 3
FTIR spectrum of raw kaolin.

Figure 4 shows the DTA/TGA curves for the natural kaolin. From these curves, it can be seen the first endothermic peak around 50 ºC, which corresponds to the adsorbed water loss (about 1.3 wt.%). The second peak centered at 500 ºC corresponds to the mass loss (about 13.7 wt.%) due to kaolinite dehydroxylation toward the formation of a non-crystalline phase (metakaolinite)^62,63.

Figure 4
DTA and TGA curves of natural kaolin.

The particle size distribution curve of kaolin is shown in Figure 5. It was found that the kaolin particles are in the range of 0.72-120 µm, resulting in an average particle size of 23.45 µm (0.2345 mm). This particle size can explain the mesoporosity of material due to a variety of pore voids among the particles caused by its agglomeration⁶⁴. Therefore, this mesoporous structure is interesting for adsorption purposes.

Figure 5
Particle size distribution curve of kaolin.

The morphology of kaolin clay observed in SEM image (Figure 6), indicates that the particles presented irregular shape, rough surface, and different particle sizes (smaller than 50 µm).

Figure 6
SEM image of raw kaolin.

The N₂ adsorption-desorption isotherms and the pore size distribution of kaolin adsorbent are exhibited in Figure 7. This figure indicates the N₂ adsorbed/desorbed from the sample in relation to the relative pressure (P/P₀) and is used to identify the pore constitution of the material. As shown in Figure 7, the N₂ adsorption-desorption isotherms of adsorbent can be classified as type IV, with type-H3 hysteresis behavior, which are indicative of predominantly mesoporous material. In addition, the material exhibited a narrow pore distribution with a maximum peak centered at 4.0 nm, indicating mesoporous characteristics, according to IUPAC. The BET specific surface area, total pore volume and average pore size of the adsorbent were 16.75 m² g^-1, 0.0628 cm³ g^-1 and 13.5 nm, respectively.

Figure 7
N₂ adsorption/desorption isotherms of kaolin and the corresponding pore size distribution (inset).

3.2. Adsorption kinetic results

The experimental kinetic curves of MG adsorption on kaolin were constructed at different initial dye concentrations (100, 125, 150 and 175 mg L^-1) and the respective data were fitted using the pseudo-first order, pseudo-second order and Elovich models. These results are presented in Figure 8 and Table 1.

Figure 8
Kinetic curves for the adsorption of MG onto natural kaolin. Experimental conditions: pH = 6.3; T = 25 ºC; Adsorbent mass = 0.1 g; V_solution = 100 mL.

Table 1
Kinetic parameters for the adsorption of MG onto natural kaolin.

Model	Initial MG concentration (mg L-1)
	100	125	150	175
Pseudo-first order
q1 (mg g-1)	91.51	97.95	111.6	119.95
k1 (min-1)	0.1835	0.2397	0.0789	0.0869
R 2	0.7505	0.7336	0.7751	0.8000
R 2 adj	0.7278	0.7094	0.7547	0.7818
ARE (%)	18.60	18.26	22.75	21.35
SSE	3021.13	3681.14	4256.23	4397.87
AIC	76.03	78.60	80.48	80.91
Pseudo-second order
q2 (mg g-1)	97.27	103.95	118.42	127.85
k2x103 (g mg-1 min-1)	2.53	2.94	1.16	1.10
R 2	0.8520	0.8369	0.8673	0.8868
R 2 adj	0.8385	0.8221	0.8552	0.8765
ARE (%)	14.31	14.30	16.83	15.45
SSE	1792.25	2253.17	2509.90	2486.60
AIC	69.24	72.21	73.62	73.49
Elovich
b (g mg-1)	0.0786	0.0756	0.0563	0.0520
a (mg g-1 min-1)	175.68	250.30	75.28	80.98
R 2	0.9655	0.9654	0.9671	0.9758
R2adj	0.9624	0.9623	0.9641	0.9736
ARE (%)	6.59	6.47	7.71	6.91
SSE	418.16	477.95	622.82	532.38
AIC	50.32	52.05	55.50	53.46

It can be noticed in Figure 8 that the curves were overlapped until the first 20 min. Until 60 min, more than 70% of saturation was attained independent of the initial dye concentration. The equilibrium was reached around 240 min. Based on the statistical parameters (R² > 0.96), (R²_adj > 0.96), (ARE < 8.0%), (SSE < 630) and (AIC < 56) (Table 1), it can be clearly observed that the Elovich model was the most suitable to represent the MG adsorption onto kaolin. At higher initial dye concentrations, the parameter “b” from the Elovich model was lower. Since that the “b” units is g mg^-1, this fact shows that the MG adsorption capacity was favored at initial concentrations of 150 and 175 mg L^-1. The Elovich model was also suitable to represent other previous studies reporting the adsorption of food dyes onto chitosan⁶⁵.

3.3. Adsorption isotherms

The adsorption isotherm of MG dye onto natural kaolin was obtained at 25 ºC and pH of 6.3 and, it is shown in Figure 9. The isotherm data were fitted using the Freundlich, Langmuir and Sips models, where the results are shown in Table 2. It can be observed in Figure 9 that the isotherm shows a strong initial inclination, followed by a plateau. The initial inclination shows a strong affinity between MG and kaolin and the plateau represents the maximum adsorption capacity. This behavior corresponds to a L2-type isotherm according to the Giles classification⁶⁶.

Figure 9
Isotherm curve for the adsorption of MG onto natural kaolin. Experimental conditions: pH = 6.3; T = 25 ºC.

Table 2
Equilibrium parameters for the adsorption of MG onto natural kaolin.

Equilibrium model
Freundlich
KF (mg g-1) (mg L-1)-1/n	112.37
1/nF	0.0469
R 2	0.9957
R 2 adj	0.9943
ARE (%)	2.03
SSE	52.77
AIC	21.78
Langmuir
qm (mg g-1)	128
KL (L mg-1)	45.33
R 2	0.9829
R 2 adj	0.9772
ARE (%)	3.51
SSE	212.10
AIC	28.74
Sips
qS (mg g-1)	259.42
KS (L mg-1)	0.0452
mS	0.083
R 2	0.9949
R 2 adj	0.9898
ARE (%)	2.19
SSE	63.01
AIC	42.67

The statistical parameters presented in Table 2 revealed that the Freundlich and Langmuir models were able to represent the experimental equilibrium data. Despite of Sips model to generate satisfactory statistical parameters, this model overestimated the maximum adsorption capacity and so, it cannot be used to predict the experimental data. The 1/n_F value was lower than 1 and consequently, n_F > 1, showing that the MG adsorption onto kaolin was a favorable process. The high K_L value confirms the high affinity between the MG dye and kaolin. The q_m parameter obtained from the Langmuir model was relatively high and, it was used to determine the quality of the kaolin adsorbent.

In order to verify the efficiency of raw kaolin for the MG dye adsorption, a comparison among the maximum adsorption capacities (q_m, mg g^-1) of several low-cost adsorbents reported in literature was performed, as shown in Table 3. The values in Table 3 were obtained under several different experimental conditions and, therefore, the maximum capacity (q_m) only from the each work was listed herein. Based on the results presented in Table 3, it can be affirmed that the natural raw kaolin used in this work can be utilized as a promising low-cost adsorbent to remove the MG organic dye from liquid effluents.

Table 3
Comparison of Brazilian natural kaolin with other low-cost adsorbents for the adsorption of MG dye.

Adsorbent	qm (mg g-1)
Raw kaolin (This work)	128
Sphagnum peat moss67	122
Walnut shell68	91
Beech sawdust69	83
Bivalve shell-treated Zea mays L. (maize)70	82
Maize cob powder71	81
Casuarina equisetifolia needle72	78
Rattan sawdust73	63
Daucus carrot leaves powder74	53
Persian kaolin75	52
Lemon peel76	52
Sea shell powder77	42
Castor bean presscake78	37
Cerastoderma lamarcki shell79	36
Annona squmosa seed80	26
Natural zeolite81	18
Bentonite clay82	8

4. Conclusions

The removal of Malachite Green dye using kaolin clay as adsorbent was systematically investigated under different experimental conditions. The raw kaolin from the Rio Grande do Sul State/Brazil presented interesting characteristics for adsorption purposes. The results indicated that the Elovich model was the more adequate to represent the adsorption kinetic data. The maximum adsorption capacity toward Malachite Green was estimated at around 128 mg g^-1, according to the Langmuir model. In summary, the findings from this study demonstrated that the use of raw kaolin as an alternative low-cost adsorbent for the removal Malachite Green from colored effluents is feasible.

5. Acknowledgments

The authors are grateful to Federal University of Santa Maria (UFSM), Brazil.

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Publication Dates

• Publication in this collection
  11 May 2017
• Date of issue
  2017

History

• Received
  15 Sept 2016
• Reviewed
  24 Jan 2017
• Accepted
  05 Apr 2017