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Abstract

Red mud was activated by a digestion–precipitation method, resulting in a mesostructure with high surface area, and the activated red mud was further used as the adsorbent for methylene blue removal. The physicochemical properties of the resultant samples were characterized by X-ray diffraction, Fourier transform infrared spectroscopy, thermogravimetry analysis, and nitrogen sorption techniques. Batch studies were measured to investigate the influence factors including adsorbent dosage, contact time, pH, and initial concentration. It was revealed that the activated red mud was highly efficient for removal of methylene blue. Adsorption experiments were found to be better achieved in faintly acidic and alkaline conditions, where the adsorption capacity of activated red mud and activated red mud-200 reached 232 and 274 mg/g at pH 7.0, respectively. Langmuir, Freundlich, Temkin isotherms, and pseudo-second-order kinetic model fitted the experimental data well, demonstrating an electrostatic interaction mechanism.

Keywords

Methylene blue red mud adsorbents mesopores isotherms kinetics

Introduction

Synthetic dyes are common pollutants discharged from many industries such as paint, plastics, food, textile, rubber, etc. (Hajjaji et al., 2016; Rafatullah et al., 2010). Up to now, more than 100,000 kinds of commercial dyes exist, and over 700,000 tons of synthetic dyes are produced every year (Asfaram et al., 2016; Hou et al., 2013). Due to its good solubility, high toxicity, and broad application, many diseases such as vomiting, dermatitis, cancer, gene mutations, and mental confusion in people are connected with colored dye effluents (Bhatnagar et al., 2011). Methylene blue (MB), one kind of common industrial dyes, is usually used for dying wood, silk, and cotton. It is harmful to human beings, animals, and plants. So, the treatment of wastewater containing such dye is very important. Now, there are four main categories for treating dye wastewater: (i) biological, (ii) physical, (iii) chemical, and (iv) acoustical, radiation, and electrical processes (Gupta, 2009). Among these methods, currently adsorption has been considered to be the most promising way for overall treatment because it is quick, easy, and economical. Carbon-based materials such as activated carbon, carbon nanotubes, mesoporous carbon and so on, have been proved to be the most promising adsorbents for dye removal, but their use is sometimes restricted in view of their high cost (Kannan and Sundaram, 2001; Norzilah et al., 2011; Yuan et al., 2007). So, the exploitation of new effective and low-cost adsorbents for the effluent treatment is very necessary.

Red mud, a large scale waste residue from alumina industry, is harmful to the environment due to its highly alkaline and saline properties (Hu et al., 2016a, 2016b). And its safe treatment, disposal, or re-use is a complex problem that long-term plagues the researchers. Development of adsorbent based on red mud for wastewater treatment can provide many advantages for pollution control, since it is an environmental-friendly process that can not only reduce costs but also save raw materials. Red mud is a high alkaline material, and thus can't be directly added into the water. So, before using red mud, it needs to be neutralized (Zhou and Haynes, 2010). Genç-Fuhrman et al. (2004) investigated the arsenic adsorption characteristics of neutralized red mud, and its adsorption capacity was comparable with commonly used adsorbents. Also, Gupta et al. (2004) and Tor et al. (2009) used activated red mud (ARM) for phenol and chlorophenols removal, and batch studies showed that the red mud was an efficient, rapid, and economic adsorbent. Recently, several researchers found that red mud could be successfully used as the adsorbents for dye removal (de Souza et al., 2013; Gupta et al., 2004; Ratnamala et al., 2012; Tor and Cengeloglu, 2006). However, the research about dye and red mud are really rare, and the adsorption mechanism is also unclear. So, it is very necessary to continue more studies on red mud for efficient removal of various dyes. In addition, further research are also needed to make clear about the adsorption mechanism between red mud and dyes.

In this work, the ARM was taken as the adsorbent for MB removal. The aim of this study was to find out a low-cost adsorbent for wastewater treatment, as well as search a new way for using red mud. The affecting factors including adsorbent dosage, contact time, initial pH, and concentration, were studied in detail. Additionally, to better understand the adsorption processes, thermodynamics (Langmuir, Freundlich and Temkin models) and kinetics were also selected to fit the experiment data.

Experimental section

Materials and synthesis

The red mud (RM) sample was obtained from Henan Zhongmei Aluminum Corporation (China). HCl, NH₄OH, and MB were supplied by Tianjin Guangfu Fine Chemical Co.

The RM was smashed and the particles below 60 meshes were used for experiments. In the activation procedure, 10 g of RM powder was mixed with 100 mL of 6 M hydrochloric acid solution, and the mixture was digested at 90℃ in an oil-bath heater for 2 h. Then, ammonium hydroxide was added to the mixture to adjust the pH around 8. The sample was washed with excessive water until the pH ≈ 7, dried at 110℃ overnight, and referred to ARM. The ARM was then annealed in muffle furnace at 200℃ for 12 h, which was denoted as ARM-200. These two samples were smashed and the particles below 60 meshes were used for the adsorption experiments.

Characterization

X-ray diffraction (XRD) patterns were collected on a Bruker D8 Focus Diffractometer with Cu-Kα radiation (λ = 0.15418 nm) operated at 40 kV and 40 mA, with a scanning range from 10° to 80° (2θ). Fourier transform infrared spectroscopy (FT-IR) spectra were measured on a Bruker Tensor 27 spectrometer with KBr pellet technique, and the ranges of spectrograms were from 4000 to 400 cm⁻¹. Nitrogen adsorption–desorption isotherms were determined on a Quantachrome NOVA 2000e analyzer at liquid nitrogen temperature (−196℃). Before the measurements, each sample was degassed at 110℃ overnight. The surface area (S_BET) of the sample was obtained by the Brunauer–Emmett–Teller (BET) method, the total pore volume (V_total) was estimated from the volume adsorbed at a relative pressure (P/P₀) of 0.99, and the pore size distribution was calculated from the adsorption isotherm by the nonlocal density functional theory (NLDFT). Thermogravimetric analysis was conducted on a TA SDT Q600 analyzer in N₂ atmosphere with a heating rate of 10℃ min⁻¹ using α-Al₂O₃ as the reference.

Adsorption experiments

In this work, all the tests were measured at room temperature (25 ± 2℃), and the initial pH of the solution was adjusted by NH₄OH (0.1 mol/L) and HCl (0.1 mol/L) solution. To investigate the influence of contact time and initial concentration, 50 mg of ARM and ARM-200 were added into 50 mL of MB solution with three different initial concentrations (100, 200 and 300 mg/L) at pH = 7. The optimum pH and adsorbent dosage were also investigated by batch tests at different pH (3 to 11) and dosage (0 to 2.0 g/L). In order to obtain the adsorption equilibrium, the mixture was vigorously stirred for 2 h, then centrifuged at 6,000 r/min, and the final supernatants were analyzed by a UV spectrometer (SP-722) at λ_max = 660 nm.

Results and discussion

Materials and characterization

RM is a byproduct from aluminum industry. Its main compositions are Al₂O₃, SiO₂, CaO, Fe₂O₃, TiO₂, Na₂O, and K₂O, which have been previously described by Cao et al. (2014a, 2014b). The powder XRD patterns of RM, ARM, and ARM-200 are shown in Figure 1. The as-received RM is a complex mixture that contains katoite, tilleyite, bayerite, hematite, lepidocrocite, and rutile (compared with the JCPDS Data File). After activation, the main complex compounds, such as katoite and tilleyite, are decomposed, and most of sodium and calcium are removed. Furthermore, it causes dispersion of dissolved metal oxides as hydroxides which leads to formation of pores thereby increasing the surface area (Hu et al., 2016a, 2016b). Meanwhile, the intensities of Fe- and Al-containing species are decreased obviously. Specifically, the main phases in ARM are bayerite, rutile, and hematite. After being annealed at 200℃, the intensities of the bayerite, rutile, and hematite peaks become stronger. This indicates that the activation process makes great changes in the RM.

Figure 1.

(a) XRD pattern of the RM, ARM, and ARM-200; (b) XRD patterns of the raw RM and the corresponding JCPDS files ((1) katoite (Ca_2.93Al_1.97(Si_0.64O_2.56)(OH)_9.44) JCPDS 77-1713; (2) tilleyite (Ca₅Si₂O₇(CO₃)₂), JCPDS71-2079; (3) bayerite (Al(OH)₃), JCPDS83-2256; (4) hematite (Fe₂O₃), JCPDS85-0987; (5) lepidocrocite (FeO(OH)), JCPDS74-1877; (6) rutile (TiO₂), JCPDS76-0326).

The morphologies of the RM and the ARM-200 are shown in Figure 2. It is seen that the raw RM is composed of a large quantity of random huge agglomerates. After activation, the larger particles are decomposed, formatting a number of small nanoparticles. And these particles are tend to agglomerate, resulting in a looser structure with many pores (Figure 2(c) and (d)), which should be beneficial for the adsorption performance of the samples. The energy dispersive x-ray spectroscopy images of the RM and ARM-200 are shown in Figure 2(c) and (f), respectively. It is observed that the raw RM contains many elements such as Al, Si, Fe, Ti, Na, K, and Ca. After activation, most of Na and Ca are removed. This is in accordance with XRD results in Figure 1.

Figure 2.

SEM images of the raw RM (a, b) and the ARM-200 (e, f), and the energy dispersive x-ray spectroscopy data of RM (c) and ARM-200 (f).

Figure 3 shows the FT-IR spectra of RM, ARM, and ARM-200. All the samples show two peaks at around 3450 and 1643 cm⁻¹, corresponding to the stretching vibration of –OH (Sushil and Batra, 2012). This is likely caused by the presence of H₂O or hydroxyl compounds in the samples. In the RM and ARM samples, bands at 1498, 387 and 1400 cm⁻¹ corresponding to the ${CO}_{3}^{2 -}$ are visible, indicating the presence of a large amount of carbonate compounds (Cao et al., 2014a, 2014b). However, these two bands are not presented in ARM-200, owing to the fact that the carbonates are reacted with HCl and decomposed after thermal treatments. The peaks at 534 and 469 cm⁻¹ in RM and 538, 542 and 478 cm⁻¹ in ARM and ARM-200 are attributed to the stretching vibration of Fe–O, indicating the existence of Fe compounds in these three samples (Sushil and Batra, 2012). The Si–O stretching vibrations can be seen at 1002 cm⁻¹ in RM, and exhibit lower intensity at 1030 cm⁻¹ in ARM and ARM-200 (Castaldi et al., 2010), suggesting that the silicate groups are decreased after activation. Noticeably, bands at 687 and 623 cm⁻¹ correspond to Al–O band, which are disappeared in ARM and ARM-200. This may be due to the phase changes during the activation process. These results are supported by the XRD analysis in Figure 1.

Figure 3.

FT-IR spectra of RM, ARM, and ARM-200.

The textural properties of RM, ARM, and ARM-200 are measured by N₂ sorption techniques, and the results are shown in Figure 4 and Table 1. From Figure 4, the isotherms of as-received red mud are of type III, indicating a non-porous structure. While, the isotherms of ARM and ARM-200 are of classical type IV nitrogen sorption isotherms with a type H3 hysteresis loops, typical for mesoporous materials (Cao et al., 2014a; Deng et al., 2013). Noticeably, for ARM-200 sample, when the relative pressure (P/P₀) is above 0.85, the nitrogen-adsorbed volume rises sharply, revealing the presence of abundant large mesopores or macropores. The S_BET and V_total of the RM are 56 m²/g and 0.08 cm³/g, respectively, which increase to 207 m²/g and 0.31 cm³/g (ARM) and 381 m²/g and 0.90 cm³/g (ARM-200) after activation. This maybe because the sodium and calcium ions are removed during the acid–alkali treatment whereas some hydroxides are formed simultaneously. Then, the main compositions of RM can be redistributed during drying in 110℃, resulting in a loose structure of ARM. In addition, a certain temperature (200℃) can also eliminate some volatile matter, further increasing the surface area and pore volume. The pore size distribution curves of ARM and ARM-200, calculated from the NLDFT model, exhibiting three broad peaks centered at around 3.8, 5.4, and 8.1 nm, respectively, revealing a relative uniform mesostructure of both ARM and ARM-200 samples.

Figure 4.

(a) Nitrogen adsorption–desorption isotherms and (b) the corresponding pore size distribution curves of RM, ARM, and ARM-200.

Table 1.

The parameters of Langmuir, Freundlich, and Temkin isothermal for adsorption of MB.

Samples	S_BET (m²/g)	V_total (cm³/g)	Langmuir isotherm				Freundlich isotherm			Temkin isotherm
Samples	S_BET (m²/g)	V_total (cm³/g)	q_m (mg/g)	K_L (L/mg)	R _L	R ²	1/n	K_F (L/mg)	R ²	k₁(L/g)	k ₂	R ²
ARM	207	0.31	232.2	0.056	0.06	0.99	0.447	38.70	0.96	86.11	0.08	0.97
ARM-200	381	0.90	274	0.032	0.09	0.86	0.723	28.68	0.98	117.96	0.12	0.95

The TG-derivative thermogravimetric (TG-DTG) results of RM and ARM-200 are shown in Figure 5, and all the samples are dried at 110℃ overnight before the tests. The TG curves show a weight loss of 12% and 15% from 30℃ to 800℃ for RM and ARM-200, respectively. For RM (Figure 5(a)), the weight loss of 1.3% from 30℃ to 232℃ can be attributed to the physical adsorption water evaporation (Zhu et al., 2014a). From 232℃ to 450℃, the TG curve exhibits a weight loss of 6.6%, accompanied by a weight loss peak at 255℃ in the DTG curve, which can be attributed to the decomposition of goethite, gibbsite, and boehmite to hematite, boehmite, and alumina, respectively (Cao et al., 2014a, 2014b). Noticeably, a strong peak at the temperature from 600℃ to 700℃ in DTG curve with the mass loss of 3.3% can be observed in the sample of RM, corresponding to the decomposition of calcite and tilleyite. After 700℃, the weight loss can be attributed to the decomposition of silicon aluminate compounds (such as katoite). Figure 5(b) shows the thermal property of ARM-200 sample. It is shown that ARM-200 (6.7%) has more weight loss than RM (1.1%) before 200℃, probably because the loose structure of ARM-200 is conductive for adsorption water. From 220℃ to 669℃, the weight loss of 4.9% can be due to the decomposition of goethite, diaspore, and boehmite. And this makes great contribution to the formation of pores (Hu et al., 2016). Compared with RM and ARM-200, no obvious weight loss can be seen at around 600℃ in ARM-200, indicating that the calcite almost completely wiped out after acid–alkali treatment.

Figure 5.

TG-DTG curves of (a) RM and (b) ARM-200.

Effect factors (adsorbent dosage, contact time, dye concentration, and initial pH)

To obtain the optimal dosage of the adsorbent, batch adsorption experiments were conducted with 0.25 to 2 g/L of adsorbent. The concentration of MB is 200 mg/L, and the results are presented in Figure 6. The percentage adsorption of MB increases with the increase of the adsorbent dosage. At the adsorbent dosage below 1 g/L, the removal efficiency increases sharply. However, further increase in the quantity of adsorbent from 1 to 2 g/L, only a slight increase of MB adsorption can be observed by 2% and 5% for ARM-200 and ARM, respectively. Similar results were reported earlier in adsorption of Congo Red (Tor and Cengeloglu, 2006) and Remazol Brilliant Blue dye (Ratnamala et al., 2012) by red mud, that the removal of dyes increased with increase in dosage, however, beyond a critical quantity, any additional red mud dosage had little contribution to the adsorption process. From Figure 6, we can see that the removal efficiency of MB is high enough when the dosage is 1 g/L. Therefore, 1 g/L of adsorbent is chosen in the subsequent experiments.

Figure 6.

The adsorption efficiency of MB with different adsorbent dosages (pH = 7.0, T = 25 ± 2℃).

Figure 7 shows the plots of the adsorption capacity of ARM (Figure 7(a)) and ARM-200 (Figure 7(b)) with time at three different MB concentrations. The equilibrium can be achieved within 40 minutes for both ARM-200 and ARM. Furthermore, the removal of MB is rapid at the first 10 min, and a slower second stage of gradual adsorption from 10 to 40 min. Finally, the MB adsorption can reach equilibrium after 40 minutes, which is a little faster in comparison to many synthesized adsorbents (Liu et al., 2014; Yue et al., 2011). As at the initial time, due to the higher concentration of the solution, the driving forces are very strong, leading to a fast adsorption rate. But when the adsorption proceeds, the concentration of solution reduces while approaching equilibrium and the adsorption rate decreases. Noticeably, the adsorption capacity of ARM-200 is much higher than that of ARM, especially at high initial concentration of MB, which can be attributed to the high porosity of ARM-200 resulting in more surface adsorption sites. When the MB concentration enlarges from 100 to 300 mg/L, the equilibrium adsorption capacities increase from 90.8 to 232.2 mg/g and 93 to 274 mg/g for ARM and ARM-200, respectively, which are much higher than other early reported adsorbents (Table 2).

Figure 7.

The adsorption efficiency for MB with different contact time: (a) ARM; (b) ARM-200 (pH = 7.0, T = 25 ± 2℃).

Table 2.

Comparison of the MB adsorption capacities of various adsorbents.

Adsorbent	q_m (mg/g)	References
Coal fly ash	12.7	Wang et al. (2008)
Magnetite-loaded MWCNTs	40.1	Ai et al. (2011)
Palygorskite	50.8	Al-Futaisi et al. (2007)
Crushed brick	96.6	Hamdaoui (2006)
Fe₃O₄ magnetic particles	99.4	Zhu et al. (2015)
Sulfuric acid treated kaolinite	101.5	Gao et al. (2016)
PPy/Al₂O₃	134.77	Chen et al. (2016)
Cedar sawdust	142.4	Hamdaoui (2006)
Polysaccharide-derived mesoporous carbon	186	Parker et al. (2012)
Mn–Fe₃O₄–NPs–AC	229.4	Asfaram et al. (2015)
ZnS–NPs–AC	243.9	Asfaram et al. (2016)
Watermelon rind	231.48	Üner et al. (2016)
CNT/AC	500	Karaer and Kaya (2016)
Fe₃O₄-xGO	526.32	Cui et al. (2015)
Chemically activated carbon microspheres	602.4	Jia et al. (2016)
ARM	232	This work
ARM-200	274	This work

The adsorption results of ARM and ARM-200 at different MB concentrations are studied in detail (Figure 8). The equilibrium adsorption capacity of the two samples decreases with the increase of the initial dye concentration. This can be attributed to the existence of more dye molecules or ions in solution at higher concentration, thus more intense completion occurs between the adsorbate and available binding sites of the adsorbent, leading to higher adsorption (Ahmad and Alrozi, 2010; Hou et al., 2013). Noticeably, the MB adsorption capacity of ARM-200 (S_BET, 381 m²/g, V_total, 0.90 cm³/g) is higher than that of ARM (S_BET 207 m²/g, V_total 0.31 cm³/g) in various dye concentration, probably due to the different surface area and pore volume of the adsorbents. The high surface area and large pore volume of the adsorbent can provide more adsorption sites, so as to increase the MB removal percentage. What's more, the removal efficiencies of ARM are decreased more obviously than that of ARM-200 sample from 100 to 300 mg/L, suggesting a better adsorption ability of ARM-200.

Figure 8.

The adsorption efficiency for MB with different initial concentrations (pH = 7.0, T = 25 ± 2℃).

The pH of the solution is a very important factor affecting the ionization degree of dye molecules and the surface charge of the adsorbent (Cengeloglu et al., 2006; Ren et al., 2013). In this study, batch experiments are performed over a pH range of 3–11. The dye concentration and adsorbent dosage are 200 mg/L and 1 g/L, respectively, and the experimental results are shown in Figure 9. The adsorptions of MB on both RM and ARM-200 are favorable at higher pH. Indeed, the MB removal efficiency increases sharply in the pH range 3–5. When the initial pH is above 5.0, only a slight increase of absorption amount of MB can be observed in both ARM and ARM-200, where the maximum adsorption of MB is achieved at pH 9.0. Red mud is a mixture of oxides containing abundant surface hydroxyl groups, while MB is a cationic dye molecule. The adsorption mechanism between the dyes and the adsorbent surface can be attributed to the ionic interactions. In aqueous solution, the adsorbent surface will be positively charged (Cengeloglu et al., 2007; Ozcan et al., 2011). At lower pH condition, the MB molecules are apt to dissociate into ions which is unfavorable for adsorption (electrostatic repulsion). With the increase of solution's pH, the MB species are transformed into molecular form. Also, the adsorbent surface will be negatively charged, and the MB molecules are easily adsorbed on the negative surface of the adsorbent. Therefore, we can deduce that the adsorption mechanism between the MB and the adsorbent is derived from electrostatic interaction. Similar trends are also reported earlier in adsorption reactive blue (KNR), acid red, and direct blue (B₂R_L) (Wang et al., 2009). The chemical interaction between MB and hydroxylated surface of red mud can be represented schematically in Figure 10.

Figure 9.

The effect of pH of the initial solution on the MB adsorption efficiency (T = 25 ± 2℃).

Figure 10.

The schematic mechanism for the removal of MB by ARM samples.

Adsorption isotherm

Adsorption isotherms are usually used to investigate the adsorption process and estimate the adsorption ability of an adsorbent. In this work, the MB species adsorption on the ARM and ARM-200 are analyzed by three different adsorption models (Langmuir, Freundlich, and Temkin). In general, the Langmuir isotherms are commonly used to describe the monolayer adsorption process over a homogenous surface, where no interaction between adsorbed molecules existed (Amin, 2009; Malik, 2003). The isotherms are calculated as follows

c_{e} / q_{e} = 1 / (q_{max} K_{L}) + c_{e} / q_{max}

(1) where c_e (mg/L) and q_e (mg/g) are the equilibrium concentration and adsorption capacity of the adsorbate, respectively. q_max (mg/g) represents the maximum adsorption capacity. K_L (L/mg) is the Langmuir constant related to the adsorption energy.

Additionally, to confirm whether the MB adsorption process is favorable for monolayer adsorption, the experimental data are evaluated by dimensionless constant separation factor (R_L). The R_L is calculated as follows (Singh et al., 2006; Yu et al., 2013)

R_{L} = 1 / (1 + K_{L} C_{0})

(2) where C₀ (mg/L) is the initial concentration. The value of R_L is critical parameter determining the adsorption: irreversible (R_L = 0), favorable (0 < R_L < 1), linear (R_L = 1), or unfavorable (R_L > 1). And the R_L values are supported in Table 1.

The Freundlich isotherms are usually used for fitting the multilayer sorption on heterogeneous surface (Akin et al., 2012; Tor et al., 2006). The equation is calculated as follows

q_{e} = {K_{F^{C} e}}^{1 / n}

(3)

The above equation can be converted into a linear equation

\log q_{e} = 1 / n \log c_{e} + \log K_{F}

(4) where n and K_F are the Freundlich parameters, and their values can be calculated by the slope and intercept of the fitting lines.

The derivation of the Temkin model takes into account the interactions between the adsorbates, assuming that the decline of the adsorption heat is linear (Yu et al., 2013). And the equation is described as follows

q_{e} = RT / b \ln (k_{2} c_{e})

(5)

The equation can be transformed into a linear form

q_{e} = k_{1} \ln k_{2} + k_{1} \ln c_{e}

(6) where

k_{1} = RT / b

(7)

In the Temkin model, k₁ is the Temkin isotherm energy constant, and k₂ is the Temkin isotherm constant corresponding to the maximum binding energy.

The fitting results of the three adsorption models of MB adsorption by ARM and ARM-200 are shown in Figure 11, and the detailed results are given in Table 1. In this study, the q_m of ARM and ARM-200 are 232.2 and 274 mg/L, respectively, suggesting a superior adsorbent system. The correlation coefficient (R²) obtained from Langmuir model are 0.99 and 0.86 for ARM and ARM-200, respectively. Moreover, the dimensionless constants (R_L) of the two samples are in the range of 0–1, indicating that they are all suitable for MB adsorption. In Figure 11(b), the R² values of ARM and ARM-200 calculated from Freundlich isothermal model are 0.96 and 0.98, respectively, revealing a good applicability of the Freundlich isotherm for the two samples. In addition, the values of 1/n are 0.447 and 0.723 for ARM and ARM-200, respectively, indicating that the samples are favorable for MB adsorption (Rauf et al., 2008). Noticeably, for ARM sample, Langmuir and Temkin models fit the experimental data better than Freundlich model. While, the experimental data of ARM-200 sample fit better with the Freundlich and Temkin models. These results suggest that the adsorption of MB on ARM is monolayer adsorption process, while multilayer sorption occurs on ARM-200.

Figure 11.

(a) Langmuir, (b) Freundlich, and (c) Temkin isotherms for adsorption of MB onto the ARM and ARM-200.

Adsorption kinetics

To disclose the adsorption kinetics of MB on the ARM and ARM-200, the tests are carried out at three different dye concentrations (100, 200, and 300 mg/L). The pseudo-first-order kinetic model is expressed as follows (Zhou and Haynes, 2012; Zhu et al., 2014b)

\log (q_{e} - q_{t}) = \log q_{e} - k_{1} t / 2.303

(8)

The pseudo-second-order kinetic equation is described as follows (Fu et al., 2011)

t / q_{t} = 1 / k_{2} q_{e}^{2} + t / q_{e}

(9) where k₁ (1/min) and k₂ (g/(mg·min)) are the adsorption rate constants corresponding to the first- and second-order kinetic models, respectively; q_t (mg/g) and q_e (mg/g) represent the adsorption quantity at time t and equilibrium, respectively.

The fitting plots and corresponding parameters of the two kinetic models of MB adsorption by ARM and ARM-200 in three different initial concentrations (100, 200 and 300 mg/L) are shown in Figure 12 and Table 3, respectively. The q_e of the second-order model is very close to the theoretical vales. Moreover, the correlation coefficients (R²) of the two samples calculated by the second-order kinetic model (>0.999) are much larger than that estimated from the first-order kinetics model (<0.93), suggesting a better applicability of the second-order model. As we know, the pseudo-second-order model assumes that the rate limiting step is chemisorption (Fu et al., 2011). So, we can deduce that the dye ions and adsorbent are connected through charge neutralization or electrostatic interaction.

Figure 12.

The pseudo-first-order and pseudo-second-order model of the MB adsorption processes with ARM (a, b), and ARM-200 (a′, b′).

Table 3.

The pseudo-first-order and pseudo-second-order kinetic parameters for the adsorption of MB.

Sample			Pseudo-first-order			Pseudo-second-order
Sample	c₀ (mg/L)	q _e,exp	k ₁	R ²	q _e	k ₂	R ²	q _e
ARM	100	93.0	0.0178	0.8979	39.4	0.0105	0.9999	95.2
ARM	200	175.5	0.017	0.9273	90.5	0.0055	0.9997	181.8
ARM	300	232.2	0.0183	0.9264	137.2	0.0041	0.9992	226.6
ARM-200	100	90.8	0.0189	0.7798	21.7	0.0110	0.9998	90.8
ARM-200	200	189.7	0.0234	0.7589	49.2	0.0052	0.9999	191.6
ARM-200	300	274.0	0.0244	0.8752	115.2	0.0036	0.9998	279.3

Conclusions

The RM was activated by the hydrochloric acid digestion and ammonium hydroxide precipitation, and further thermal treatment, exhibiting excellent adsorption capacity for MB removal. The activation process changed the strong alkalinity of RM, reduced the toxicity, and significantly improved the specific area and porosity. Batch experiments showed that the initial pH could affect the capacity of adsorbents obviously, and the optimum pH was 9.0. The two samples had a fast adsorption rate and could reach equilibrium within 40 minutes. The adsorption behaviors of MB onto the ARM and ARM-200 matched well with Langmuir, Freunlich, and Temkin isotherm indicating that the adsorption process mixed with monolayer and multilayer. The kinetics of the MB adsorption fitted the pseudo-second-order model better indicating that the main mechanism of adsorption was electrostatic interaction. In addition, red mud is derived from industrial waste and has much low cost, which can be used as an alternative adsorbent for dye removal from wastewater.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The National Natural Science Foundation of China (21421001, 21573115), the Natural Science Foundation of Tianjin (15JCZDJC37100), and the 111 project (B12015).

References

Ahmad

Alrozi

(2010) Optimization of preparation conditions for mangosteen peel-based activated carbons for the removal of Remazol Brilliant Blue R using response surface methodology. Chemical Engineering Journal 165: 883–890.

Zhang

Liao

et al. (2011) Removal of methylene blue from aqueous solution with magnetite loaded multi-wall carbon nanotube: kinetic, isotherm and mechanism analysis. Journal of Hazardous Materials 198: 282–290.

Akin

Arslan

Tor

et al. (2012) Arsenic (V) removal from underground water by magnetic nanoparticles synthesized from waste red mud. Journal of Hazardous Materials 235: 62–68.

Al-Futaisi

Jamrah

Al-Hanai

(2007) Aspects of cationic dye molecule adsorption to palygorskite. Desalination 214: 327–342.

Amin

(2009) Removal of direct blue-106 dye from aqueous solution using new activated carbons developed from pomegranate peel: Adsorption equilibrium and kinetics. Journal of Hazardous Materials 165: 52–62.

Asfaram

Ghaedi

Azqhandi

et al. (2016) Statistical experimental design, least squares-support vector machine (LS-SVM) and artificial neural network (ANN) methods for modeling the facilitated adsorption of methylene blue dye. RSC Advances 6: 40502–40516.

Asfaram

Ghaedi

Goudarzi

et al. (2015) Response surface methodology approach for optimization of simultaneous dye and metal ion ultrasound-assisted adsorption onto Mn doped Fe₃O₄-NPs loaded on AC: Kinetic and isothermal studies. Dalton Transactions 44: 14707–14723.

Bhatnagar

Vilar

Botelho

et al. (2011) A review of the use of red mud as adsorbent for the removal of toxic pollutants from water and wastewater. Environmental Technology 32: 231–249.

Cao

Yan

Deng

et al. (2014a) Homogeneous precipitation method preparation of modified red mud supported Ni mesoporous catalysts for ammonia decomposition. Catalysis Science & Technology 4: 361–368.

10.

Cao

Yan

Deng

et al. (2014b) Mesoporous modified-red-mud supported Ni catalysts for ammonia decomposition to hydrogen. International Journal of Hydrogen Energy 39: 5747–5755.

11.

Castaldi

Silvetti

Enzo

et al. (2010) Study of sorption processes and FT-IR analysis of arsenate sorbed onto red muds (a bauxite ore processing waste). Journal of Hazardous Materials 175: 172–178.

12.

Cengeloglu

Tor

Arslan

et al. (2007) Removal of boron from aqueous solution by using neutralized red mud. Journal of Hazardous Materials 142: 412–417.

13.

Cengeloglu

Tor

Ersoz

et al. (2006) Removal of nitrate from aqueous solution by using red mud. Separation and Purification Technology 51: 374–378.

14.

Chen

Feng

Yan

(2016) Influence of metal oxides on the adsorption characteristics of PPy/metal oxides for Methylene Blue. Journal of Colloid and Interface Science 475: 26–35.

15.

Cui

Guo

Wei

et al. (2015) Removal of mercury and methylene blue from aqueous solution by xanthate functionalized magnetic graphene oxide: Sorption kinetic and uptake mechanism. Journal of Colloid and Interface Science 439: 112–120.

16.

de Souza

Antunes

MLP

Couperthwaite

et al. (2013) Adsorption of reactive dye on seawater-neutralised bauxite refinery residue. Journal of Colloid and Interface Science 396: 210–214.

17.

Deng

Ren

Yuan

(2013) Mesoporous manganese oxide nanoparticles for the catalytic total oxidation of toluene. Reaction Kinetics, Mechanisms and Catalysis 108: 507–518.

18.

Song

Mao

et al. (2011) Adsorption of disperse blue 2BLN by microwave activated red mud. Environmental Progress & Sustainable Energy 30: 558–566.

19.

Gao

Zhao

et al. (2016) Direct acid activation of kaolinite and its effects on the adsorption of methylene blue. Applied Clay Science 126: 98–106.

20.

Genç-Fuhrman

Tjell

McConchie

(2004) Adsorption of arsenic from water using activated neutralized red mud. Environmental Science & Technology 38: 2428–2434.

21.

Gupta

(2009) Application of low-cost adsorbents for dye removal – A review. Journal of Environmental Management 90: 2313–2342.

22.

Gupta

Ali

Saini

(2004) Removal of chlorophenols from wastewater using red mud: An aluminum industry waste. Environmental Science & Technology 38: 4012–4018.

23.

Gupta

Suhas Ali

Saini

(2004) Removal of rhodamine B, fast green, and methylene blue from wastewater using red mud, an aluminum industry waste. Industrial & Engineering Chemistry Research 43: 1740–1747.

24.

Hajjaji

Pullar

Labrincha

et al. (2016) Aqueous Acid Orange 7 dye removal by clay and red mud mixes. Applied Clay Science 126: 197–206.

25.

Hamdaoui

(2006) Batch study of liquid-phase adsorption of methylene blue using cedar sawdust and crushed brick. Journal of Hazardous Materials 135: 264–273.

26.

Hou

Deng

Ren

et al. (2013) Adsorption of Cu²⁺ and methyl orange from aqueous solutions by activated carbons of corncob-derived char wastes. Environmental Science and Pollution Research 20: 8521–8534.

27.

Zhao

Gao

et al. (2016a) High-surface-area activated red mud supported Co₃O₄ catalysts for efficient catalytic oxidation of CO. RSC Advances 6: 94748–94755.

28.

Zhu

Gao

et al. (2016b) CuO catalysts supported on activated red mud for efficient catalytic carbon monoxide oxidation. Chemical Engineering Journal 302: 23–32.

29.

Jia

et al. (2016) Adsorption performance and mechanism of methylene blue on chemically activated carbon spheres derived from hydrothermally-prepared poly (vinyl alcohol) microspheres. Journal of Molecular Liquids 220: 56–62.

30.

Kannan

Sundaram

(2001) Kinetics and mechanism of removal of methylene blue by adsorption on various carbons – A comparative study. Dyes Pigments 51: 25–40.

31.

Karaer

Kaya

(2016) Synthesis, characterization of magnetic chitosan/active charcoal composite and using at the adsorption of methylene blue and reactive blue4. Microporous and Mesoporous Materials 232: 26–38.

32.

Liu

Shen

et al. (2014) Performances of methyl blue and arsenic (V) adsorption from aqueous solution onto magnetic 0.8Ni_0.5Zn_0.5Fe₂O₄/0.2SiO₂ nanocomposites. Water, Air, & Soil Pollution 225: 1–10.

33.

Malik

(2003) Use of activated carbons prepared from sawdust and rice-husk for adsorption of acid dyes: A case study of Acid Yellow 36. Dyes Pigments 56: 239–249.

34.

Norzilah

Fakhru'l-Razi

Choong

et al. (2011) Surface modification effects on CNTs adsorption of methylene blue and phenol. Journal of Nanomaterials 2011. http://doi.org/10.1155/2011/495676.

35.

Ozcan

Tor

Aydin

(2011) Removal of organochlorine pesticides from aqueous solution by using neutralized red mud. CLEAN – Soil Air Water 39: 972–979.

36.

Parker

Hunt

Budarin

et al. (2012) The importance of being porous: Polysaccharide-derived mesoporous materials for use in dye adsorption. RSC Advances 2: 8992–8997.

37.

Rafatullah

Sulaiman

Hashim

et al. (2010) Adsorption of methylene blue on low-cost adsorbents: A review. Journal of Hazardous Materials 177: 70–80.

38.

Ratnamala

Shetty

Srinikethan

(2012) Removal of remazol brilliant blue dye from dye-contaminated water by adsorption using red mud: Equilibrium, kinetic, and thermodynamic studies. Water, Air, & Soil Pollution 223: 6187–6199.

39.

Rauf

Bukallah

Hamour

et al. (2008) Adsorption of dyes from aqueous solutions onto sand and their kinetic behavior. Chemical Engineering Journal 137: 238–243.

40.

Ren

Zhu

et al. (2013) Adsorption of methylene blue from aqueous solution by periodic mesoporous titanium phosphonate materials. Adsorption Science & Technology 31: 535–548.

41.

Singh

Talat

Hasan

(2006) Removal of lead from aqueous solutions by agricultural waste maize bran. Bioresource Technology 97: 2124–2130.

42.

Sushil

Batra

(2012) Modification of red mud by acid treatment and its application for CO removal. Journal of Hazardous Materials 203: 264–273.

43.

Tor

Cengeloglu

(2006) Removal of congo red from aqueous solution by adsorption onto acid activated red mud. Journal Hazardous Materials 138: 409–415.

44.

Tor

Cengeloglu

Aydin

et al. (2006) Removal of phenol from aqueous phase by using neutralized red mud. Journal of Colloid and Interface Science 300: 498–503.

45.

Tor

Cengeloglu

Ersoz

(2009) Increasing the phenol adsorption capacity of neutralized red mud by application of acid activation procedure. Desalination 242: 19–28.

46.

Üner

Geçgel

Bayrak

(2016) Adsorption of methylene blue by an efficient activated carbon prepared from citrullus lanatus. Water, Air, & Soil Pollution 227: 1–15.

47.

Wang

Luan

Wei

et al. (2009) The color removal of dye wastewater by magnesium chloride/red mud (MRM) from aqueous solution. Journal of Hazardous Materials 170: 690–698.

48.

Wang

Zhu

(2008) Characteristics of coal fly ash and adsorption application. Fuel 87: 3469–3473.

49.

Wang

Chi

et al. (2013) Removal of cationic dyes: Basic magenta and methylene blue from aqueous solution by adsorption on modified loofah. Research on Chemical Intermediates 39: 3775–3790.

50.

Yuan

Zhuo

Xing

et al. (2007) Aqueous dye adsorption on ordered mesoporous carbons. Journal of Colloid and Interface Science 310: 83–89.

51.

Yue

Duan

et al. (2011) Effect of ZnO loading technique on textural characteristic and methyl blue removal capacity of exfoliated graphite/ZnO composites. Bulletin of Materials Science 34: 1569–1573.

52.

Zhou

Haynes

(2010) Sorption of heavy metals by inorganic and organic components of solid wastes: Significance to use of wastes as low-cost adsorbents and immobilizing agents. Critical Reviews in Environmental Science and Technology 40: 909–977.

53.

Zhou

Haynes

(2012) A comparison of water treatment sludge and red mud as adsorbents of As and Se in aqueous solution and their capacity for desorption and regeneration. Water, Air, & Soil Pollution 223: 5563–5573.

54.

Zhu

Fang

Huo

et al. (2015) A novel conversion of the groundwater treatment sludge to magnetic particles for the adsorption of methylene blue. Journal of Hazardous Materials 292: 173–179.

55.

Zhu

et al. (2014a) Sonochemistry-assisted synthesis and optical properties of mesoporous ZnS nanomaterials. Journal of Materials Chemistry A 2: 1093–1101.

56.

Zhu

Liu

Ren

et al. (2014b) Hollow manganese phosphonate microspheres with hierarchical porosity for efficient adsorption and separation. Nanoscale 6: 6627–6636.

High-surface-area activated red mud for efficient removal of methylene blue from wastewater

Abstract

Keywords

Introduction

Experimental section

Materials and synthesis

Characterization

Adsorption experiments

Results and discussion

Materials and characterization

Effect factors (adsorbent dosage, contact time, dye concentration, and initial pH)

Adsorption isotherm

Adsorption kinetics

Conclusions

Footnotes

Declaration of Conflicting Interests

Funding

References