Introduction

Water pollution and its related problems have already generating considerable interest, and Trying to deal with this pollutant has become a priority nowadays1. industrial development and their following wastewater production have raised many problems in aquatic sources2. Many industries such as textile, paper, plastic, leather, cosmetics, food products, and pharmaceuticals3 widely use synthetic dyes and generate a highly colored wastewater4,5. One of the main causes of water pollution is synthetic dyes6 and consist of several different groups including of reactive dyes, direct dyes, basic dyes, azo dyes and other groups7. One of the main section of synthetic dyes are azo dyes which formed by an azo group (N=N) that can have carcinogenic and mutagenic impact and aesthetic problems8,9,10. Some dyes are toxic, non-degradable and affect human, animal and environmental health6. It is visible even in concentrations less than 1 ppm in water3. However, azo dyes even at low concentrations can lead to a disorder in the photosynthesis process and cause some problem in oxygen solubility in water sources11,12. Acid Red 18 is categorized as an azo dye13. About 10–15% of the produced colors in dying process discharge to the sewage14,15,16,17. Due to environmental pollutions which are the result of releasing untreated colored-wastewater to water sources, the importance of its removal from water solutions has increased. That is why the removal of such dyes from industrial effluents is extremely important; Conventional treatment methods for removing dyes from wastewater are less effective18. Methods physical and chemical like adsorption, photocatalytic process, coagulation and flocculation, biological treatments, advanced oxidation precipitation19 electrochemical technique18 have been applied for colored wastewater treatment20. Among all prenominated methods, adsorption is a more used and an economical method for contaminated waters treatment21; and ease operation, and low energy consumption22. This method It has attracted a lot of attention because of high efficiency, environmentally and higher quality effluent1,8. Researchers have used different adsorbent for this aim. Granular Ferric Hydroxide (GFH) is mainly formed by Akaganeite, a poorly crystallized β-FeOOH and was used as an adsorbent for effective removal of arsenic23 NOM24 fluoride25 and bromate26. High removal efficiency and relatively low cost have been observed in the group of iron compounds (oxides and hydroxides, including amorphous hydrated ferric oxide (FeOOH) and goethite27. In a few researches, application of Moringa seeds and coagulation by alum for treatment of textile wastewaters have shown promising results as well28. In present study application of GFH in removal of Acid Red 18 was assessed. In most studies, the efficiency of this adsorbent in the removal of heavy metals, especially arsenic and anions, has been studied, and there is few studies on its performance in relation to organic compounds and the aim of this study was to investigate the structure of granules GFH and optimize the removal of acid red 18 by RSM method and genetic algorithm.

Material and method

Materials

AR18 dye was provided from Alvan Sabet Company, Hamedan, Iran. Also Granular Ferric Hydroxide from GEH Wasserchemie GmbH & Co. KG Company. All other chemicals were purchased from Merck (Darmstadt, Germany).

Adsorbent characterization

To determine surface morphology of GFH, Field Emission Scanning Electron Microscope (FESEM) was used. Phase identification of a crystalline material done with X-ray diffraction (XRD) and The Functional groups of the adsorbent were studied by a Fourier transformed infrared (FTIR) spectrometer.

Analytical measurements

AR18 dye stock solution (500 mg/l) was made by dissolving AR18 powder in distilled water and desired concentrations of AR18 were prepared. The initial and residual concentration of dye solution were determined by UV–visible spectrophotometer (Perkin Elmer Lambda 25) at λ = 507 nm. The calibration curve was plotted by 4 concentrations of dye between 0 and 100 mg/l which is shown in Fig. 1. Also molecular structure of Acid red 18 anionic dye is drawn in Fig. 2. As can be seen in Table 1, due to the presence of moisture in the structure of this adsorbent, it was placed in an oven (memmert) for 24 h in order to prepare for the adsorption process, and then cooled in a desiccator.

Figure 1
figure 1

AR18 calibration curve.

Full size image
Figure 2
figure 2

Acid red 18 molecular structure.

Full size image
Table 1 GFH properties.
Full size table

Batch adsorption studies

Dye adsorption studies were performed in 100 ml glass Erlenmeyer flasks with 25 ml of dye solution. Desirable pH was adjusted by 0.1 N NaOH and HCL by Kent EIL7020 pH meter, a certain amount of adsorbent weighted and added to the dye solution and then samples were shaken at room temperature at 200 rpm. After that flask contents were centrifuged in 4500 rpm for 5 min in Universal Premium PIT320 model and the residual dye concentration read by spectrophotometer Perkin-Elmer lambda25. The amount of adsorbed dye onto the adsorbent surface was calculated by using the mass balance equation:

$${\mathrm{q}}_{\mathrm{e}}=\left({\mathrm{C}}_{0}-{\mathrm{C}}_{\mathrm{e}}\right)\frac{\mathrm{v}}{\mathrm{m}}$$

C0 is the initial concentration of dye (mg/l), Ce is the residual concentration of dye (mg/l), M is the mass of adsorbents (g), V is the volume of AR18 solution (l).

Furthermore, dye removal efficiency was obtained from:

$${y}_{\%}=\frac{{c}_{0-{\mathrm{C}}_{\mathrm{e}}}}{{c}_{0}}\times 100$$

where C0 is the initial concentration of dye (mg/l), Ce is the residual concentration of dye (mg/l).

Isotherm studies were carried out at different dye concentration, and the kinetic was determined at different contact time. Thermodynamic studies were performed at various temperatures for understand the nature of the process.

Experimental design

Design-Expert11 (Stat.Ease.Inc. Minneapolis, USA) software with Response Surface Methodology (RSM) package applied to design experimental runs and optimum conditions and the impact of various independent variables (pH, initial concentration, contact time, adsorbent dosage). Dye adsorption was evaluated by using central composite design (CCD) which can minimize the numbers of total experiments. Likewise, to determine a total number of runs the following equation is presented: N = 2k + 2k + C0.

In which K is the number of experimental variables, 2k is the cubic runs, 2k is the axial runs, and C0 is the center point's runs29. CCD matrix and coded values of variables is shown in Tables 2 and 3.

Table 2 Independent variables and the levels of each variable.
Full size table
Table 3 CCD design for AR18 removal.
Full size table

This approach was suggested 30 trials. The following are some of the benefits of this design:

(i) It proves to be a two-level or fractional factorial design extension. (ii) Determine the nonlinearity of responses in the data set. (iii) Assists in estimating curvature in continuous answers received. (iv) In a minimum experimental run, the most information is obtained.

Isotherm studies

Adsorption isotherms provide quantitative information on an adsorbent's adsorption capacity and behavior with the adsorbate19. Experimental data were analyzed and fitted to Freundlich, Langmuir, and Temkin isotherm models to achieve this goal.

Langmuir isotherm

The Langmuir isotherm is used to describe monolayer adsorption on a homogenous adsorbent surface30. The following equations reflect its nonlinear model:

$$ q_{e} = \frac{{q_{m} K_{L} C_{e} }}{{1 + K_{L} C_{e} }} $$

where qe is the amount of AR18 adsorbed per gram of GFH, Ce is the dye concentration at equilibrium (mg/l), and qmax is the maximum amount of Acid red18 adsorbed. The Langmuir equilibrium constant in l/mg is denoted by KL. Non-linear models were used to estimate the parameters.

Freundlich isotherm

Adsorption is not monolayer in the Freundlich isotherm, which is formulated for equilibrium on inhomogeneous surfaces31.

The nonlinear version of the Freundlich isotherm model is as follows:

$${q}_{e}={K}_{f}{C}_{e}^\frac{1}{n}$$

Adsorption capacity is represented by KF (l/mg), while adsorption intensity is represented by 1/n. The nonlinear plot of qe versus Ce and the linear plot of log qe vs. log Ce were utilized to calculate KF and n.

Temkin isotherm

A heterogeneous surface with adsorption sites with the same bond energy is studied in the Temkin isotherm model. A linear reduction in adsorption heat occurs in this isotherm due to the contact effects of the adsorbent and adsorbate on each other31. The following equation expresses the non-linear Temkin models:

$$ {\text{q}}_{{\text{e}}} = \frac{RT}{{b_{{}} }}{\text{lnK}}_{T} {\text{C}}_{{\text{e}}} { } $$

B is the isotherm constant (J/mol). The maximal bond energy (l/mg), the gas constant (8.314 J/mol K), the temperature in degrees Kelvin, and the heat of adsorption (J/mol) are all represented by the letters KT, R, T, and b.

Kinetic studies

The pace and mechanism of the reaction are revealed by a kinetic examination of the adsorption process32. Ion adsorption from solution has been studied using a variety of kinetic models. The adsorption kinetic of AR18 onto GFH was studied using pseudo-first order, pseudo-second order, and intraparticle diffusion kinetic models. These three models' nonlinear forms are written as:

$$ {\text{Nonlinear Pseudo first order kinetic equation:}}\quad Q_{t} = Q_{e } \left( {1 - e^{{ - k_{1} t}} } \right) $$
$$ {\text{Nonlinear}}\;{\text{Pseudo}}\;{\text{second}}\;{\text{order}}\;{\text{kinetic}}\;{\text{equation:}}\quad Q_{t} = \frac{{k_{2} Q_{e}^{2} t}}{{1 + k_{2} Q_{e} t}} $$
$$ {\text{Intraparticle diffusion:}}\quad {\text{q}}_{{\text{t}}} = {\text{k}}_{{\text{i}}} {\text{t}}^{0.5} + {\text{C}} $$

where qe (mg/g) is the adsorption capacity at equilibrium and qt (mg/g) is the adsorption capacity at time t. Adsorption rate constants are k1 (/min) for pseudo-first-order kinetic, k2 (g/mg min) for second-order kinetic, and ki (mg/g min0.5) for intraparticle Diffusion kinetic30.

Thermodynamic study

Thermodynamic parameters include changes in the free energy of Gibbs (ΔG), enthalpy (ΔHo), and entropy (ΔS). ΔG is free energy change (kJ/mol) can be calculated from the following equation

$$\Delta G=-RT\left(\mathrm{ln}{K}_{c}\right)$$

where R is the universal gas constant (8.314 J/K mol), T is the absolute temperature (K). The distribution adsorption coefficient, Kc, is calculated from the following equation:

$$\frac{{q}_{e}}{{C}_{e}}={kc=\frac{C0-ce }{ce} \frac{\mathrm{v}}{m}}$$

where C0 is the initial concentration (mmol/l), Ce is the equilibration concentration after centrifugation (mmol/l), V is the volume of the suspension (l), and m is the mass of adsorbent (g). The adsorption equilibrium constant (K) can be calculated by plotting lnKd versus Ce and extrapolating Ce to 0. The value of the intercept is that of lnK. ΔHo (J/mol—kJ/mol) and ΔS0 (J/mol °K—kJ/mol K) according to Equation are calculated.

$$-\frac{\Delta H^\circ }{RT}\mathrm{ln}{ K}_{c}=\frac{\Delta S^\circ }{R}$$

where ΔH0 is the isosteric enthalpy change, ΔS is the entropy change, where ΔH0 and ΔS0 were obtained from the slope and intercept of the linear plot of lnKd against 1/T32. The number of tests for isotherm, kinetic and thermodynamic studies was selected in range, above which, the qe alter not significantly. In this regard, the number of tests was 8 for each kinetic model, 7 for each isotherm models, and 3 for thermodynamic study based on the temperatures selected.

Results and discussion

Granular ferric hydroxide characterization

XRD studies

X-ray diffraction of GFH was analyzed in the range of 2θ = 5–80° at 0.02 step size, and the result is shown in Fig. 3.

Figure 3
figure 3

XRD pattern of GFH.

Full size image

Akaganeite was found to be the main compound in GFH structure and also there was hematite in lower content. Baseline noise and peak broadening related to akaganeite reveals the poor crystallinity in GFH structure which is in line with previous reports on GFH characteristics that defined β-FeOOH as a poor crystallized similar to mineral akaganeite. akaganeite is a tetragonal mineral formed by a double chain octahedral23. On the other hand with existing a low amount of chloride in GFH sample, broadening of peaks in XRD is observable23. The peaks at 24.22 (220), 25.68 (310), 33.2 (104), 35.8 (110), 36.42 (330), 46.84 (311), 49.8 (530), 54.15 (116) and 64.11° (541) indexed and matching with JCPDS file no. 34-1266 and 33-0664.

FESEM

Figure 4a shows the surface morphology of GFH. It displays uniform round edge of GFH particles and also has a porous structure which can provide suitable adsorption sites for dye removal as shown in Fig. 4b these sites are appropriately filled with dye molecules, and sorbent particles have become more agglomerated. EDX analysis (Fig. 5) determined to contain elements in GFH. The result indicates that Fe and O are the two main constituent of GFH with 69 and 31% respectively.

Figure 4
figure 4

GFH FESEM (a). Raw (b). After AR18 adsorption.

Full size image
Figure 5
figure 5

GFH EDS spectrum.

Full size image

FTIR analysis

The Fourier transform infrared (FTIR) analysis was used to identify functional groups of GFH sample by PerkinElmer, Spectrum Two. Samples were studied at the range of 400–4000/cm, Fig. 6 shows the FTIR spectra of Granular Ferric Hydroxide before and after adsorption of AR18.

Figure 6
figure 6

AR18 FTIR before and after of adsorption.

Full size image

Bands at 2928 and 2858/cm are associated with symmetric and anti-symmetric stretching vibrations of the carbon chain33, while the O–H stretching vibration may be related to the bands around 3417 and 3411/cm33, also the band at 584/cm can be related to Fe–O stretching vibrations34, Gong et al. Indicated that the bands assigned to Fe–O appear between 400 and 700/cm35 and a weak band at 1123/cm was observed related to Fe−OH34. The bending vibration of adsorbed water and surface hydroxyl and O–H stretching mode was situated at 1631\cm36.

AR18 adsorption

Statistical analysis

In the present study, four different statistical models and their fitting with obtained experimental data were investigated. Quadratic model with and lack of fit 0.17 was suggested by software analysis. According to the presented data in a Table 4 Quadratic model with adjusted and predicted R2 value 0.989 and 0.972 was the best-fitted model for AR18 removal by GFH.

Table 4 Fit Summary models of AR18 removal.
Full size table

Effect of experimental parameters on adsorption process

The effect of four different variable on AR18 adsorption were studied. From the Table 5, it can understand that pH, Dose, Initial concentration and time with the F-value 851,729,284,186 respectively had the most to the lowest effect on adsorption process efficiency. Also, the interaction of studied variable investigated in which AC showed the bigger F-value it means that the interaction between pH and time had the most impact on dye removal while BC with the lowest F-value was negligible. Also, the high F-value of the quadratic function of D implies the significant effect on adsorption.

Table 5 ANOVA for quadratic model.
Full size table

Predicted vs actual efficiency comparison is shown in Fig. 7a. As it can be seen, there was a good correlation between them. Also residual of runs was in the range of − 3 to 3, which is indicant of a close value to the predicted one (Fig. 7b).

Figure 7
figure 7

Predicted vs. actual (a) and residual vs run (b).

Full size image

Effect of pH

The negative coefficient of pH was indicative of decreasing removal efficiency with increase in pH; this can be explained that at acidic pH, the higher AR18 uptake will occur. Due to the presence of the large number of positive charges on the adsorbent's surface at lower pHs while on the other hand the AR18 Molecules are negatively charged and this lead to an Electrostatic sorption2 The calculated pHZPC value for GFH was determined 7.5–8 based on previous studies. The sorbent surface charge is more positive at pH < pHZPC while at pH > pHZPC the AR18 adsorption shows decrease, and as a consequence, the removal efficiency will be decreased.

Effect of initial dye concentration

One of the effective parameters on adsorption process in this study was the initial concentration of AR18. The impact of this parameter was studied. The result showed that with an increase in initial concentration of dye, the efficiency improved. It might be because of more availability of pollutant for adsorbent particles.

Effect of adsorbent dosage

As it can be seen adsorbent dosage is the most important parameters effects on AR18 adsorption on GFH. Understandably, GFH provides more surface area for adsorption of dye; besides, it was found that a higher amount of GFH, a higher removal efficiency could be achieved.

Effect of contact time

Contact time was found to be the less effective parameter in the adsorption process. The impact of contact time in present study was assessed from 10 to 110 min and the best removal efficiency obtained at 85 min of contact time (79%) whereas by increasing contact time from 10 to 60 min, uptake rate increased around 10%; generally, it can be said that the adsorption process of AR18 almost depends on pH and in non-acidic pH, the effect of time on the process was not found to be tangible. Figure 8 demonstrates the interaction effects of studied variables, (a,c) pH and adsorbent dose contours confirmed that decrease pH value from 11 to 3 and increase dose from 0.5 to 2.5 g/l can have a positive effect on the uptake rate of AR18, Meanwhile reducing pH value from 11 to 5 did not show any significant effect on removal efficiency. (b,d) Time and concentration contours represented the better dye removal at higher concentration and longer contact time.

Figure 8
figure 8

contour plots for effect of pH and adsorbent dose (a, c) and initial concentration of AR18 and time (b, d).

Full size image

Development of regression model equation

Final Equation in Terms of Coded Factors was obtained, as shown the highest efficiency was 79.71%. The final equation shows the empirical relationship between AR18 removal (Y), based on pH (A), dosage (B), time (C) and initial dye concentration (D):

$$ \begin{aligned} {\text{AR18 removal efficiency:}}\; & {16}.{5617} - {12}.{\text{6342A}} + {11}.{\text{69B}} + {5}.{\text{91C}} + {7}.{3}0{\text{5D}} - {1}.{\text{73375AB}} \\ & \quad - {4}.{6}0{\text{25AC}} + {3}.{\text{2475AD}} - 0.{\text{5925BC}} + {3}.{\text{2125BD}} + 0.{\text{66375CD}} \\ & \quad + {5}.{\text{45125A}}^{{2}} + {3}.{\text{155B}}^{{2}} + {1}.{\text{46875C}}^{{2}} + {8}.0{\text{4125D}}^{{2}} \\ \end{aligned} $$

Determining optimal settings

The optimum condition is the value of each variable in which the maximum uptake rate is obtained. These conditions were determined by the numerical optimization method. According to the software (RSM) the maximized efficiency expected to be 78.59% at pH = 5, adsorbent dose = 2 g/l, contact time = 85 min and initial AR18 concentration = 77.5 mg/l. The experimental RE under-designed optimum conditions was achieved 79.71%. Table 6 shows the range of prediction interval, which is 72.9–84.2%, the actual value for this investigation was 79.71%.

Table 6 Confidence interval of efficiency prediction.
Full size table

Also optimization of the process parameters was accomplished by using the GA method. In this approach, the solutions created by one population are applied to generate a new population. The generation of the new population is continued to find a better solution or fitness value. The operation is sopped as the best fitness value shows no impressive improvement by the further populations and be approximately constant. The proposed approach was performed in the Matlab GA toolbox. (Matlab2018).

To optimize the RSM-CCD model based on the GA approach, the minimum and maximum levels of the independent variables were set at the upper and lower levels. As seen in Fig. 9, the results evidently show that the best fitness value was improved rapidly until about generation 50, and after that, shows no impressive improvement and be approximately constant because whose populations become close to the optimal point. As given in Fig. 9, the current best individuals plot demonstrates that the maximum removal efficiency of about 76.43% is achieved at the optimum condition.

Figure 9
figure 9

AR18 optimization using genetic algorithm.

Full size image

Optimum condition based on GA results obtained pH = 5, Adsorbent dose = 2 g/l, Contact time = 81 min and Dye Concentration = 77.5 mg/l. These results was found very close to RSM Optimization method.

Isotherm studies

For better understating of adsorption mechanism, isotherm studies are essential. The equilibrium distribution of AR18 on GFH was found by isotherms, which were performed at seven different initial AR18 concentration with 2 g/l of adsorbent, at pH = 7 for 60 min of contact time at room temperature. In this study, three isotherm models were investigated included: Langmuir, Freundlich and Temkin, the model'. Also, the coefficient constants of each model are listed in the Table 7.

Table 7 The parameters of isotherm models for AR18 adsorption.
Full size table

Based on the obtained data in the Table 7, adsorption data was better fit to Freundlich Isotherm. The maximum capacity for dye adsorption was found 29.13 mg/g while the adsorption energy was 1.175 which shows that the affinity of dye molecules on GFH is not such a strong binding because a higher kL value for adsorbent shows a stronger affiliation to sorbate. Also, the coefficient 1/n (generally 0–1) indicates the favorable adsorption of the adsorbate to the adsorbent.37 The 1/n value tends to zero; the adsorbent surface is more heterogenic38. The affinity of the adsorption sites between AR18 and GFH is determined by RL constant, which is dimensionless. The value of RL shows the nature of adsorption as follow:

RL value

Description

RL > 1

Unfavorable

RL = 1

Linear

0 < RL < 1

Favorable

RL = 0

Irreversible

The Calculated RL value is between 0.14 and 0.54 as all of these values are between 0 and 1. It can understand that AR18-GFH have favorable adsorption. The non-linear fitting Isotherm models are presented in Fig. 10A.

Figure 10
figure 10

(A) AR18 non-linear isotherm model. (B) AR18 non-linear kinetic model.

Full size image

Kinetic studies

To understand adsorption mechanism and dye uptake rate, kinetic studies were investigated. Pseudo-first-order, Pseudo-second-order and Intra-particle diffusion models were used to analyze the adsorption kinetics. K1 (g/mg min), K2 (/min) and Kdif (mg/g min1/2) are the rate constants of pseudo-first-order, second order and Intra-particle diffusion models, respectively. In this study data of experiments was fit better with Pseudo-second-order Kinetic model (R2 = 0.0984) The non-linear fitting kinetic curves of these kinetic are presented in Fig. 10B. Result of Kinetics of this study is agreement with previous study2,39,40. The pseudo-first-order kinetic assumes that the adsorption process is affected by the physiosorption, and the rate-limiting step in adsorption depends on collision between solute molecules of ions with unoccupied single sites at the surface of the adsorbent material The intraparticle diffusion kinetic assumes that the intraparticle diffusion of dye molecules on the adsorbent is the rate-limiting step in the adsorption process41. The pseudo-second-order kinetic assumes that the rate-limiting step of adsorption is chemisorption, which is probably ascribed to ion-exchange or sharing of electrons between adsorbents and adsorbate. Another assumption in this model is that the rate of occupation of adsorption sites is proportional to the square of the number of unoccupied sites42,43. Also, the intraparticle diffusion kinetic assumes that the intraparticle diffusion of dye molecules on the adsorbent is the rate-limiting step in the adsorption process15. parameters of Kinetic models is shown in Table 8.

Table 8 The parameters of Kinetic models for AR18 adsorption.
Full size table

Thermodynamics of adsorption

Temperature is one of the factors affecting the adsorption process. Thermodynamic studies help us to understand recognize the process as much as possible, as well as information about changes in the internal energy associated with adsorption and, thus, to take measures to increase the efficiency of adsorption. In this study, the efficacy of GFH in the removal of acid red 18 at temperatures (298, 293, and 303° K) was investigated. The thermodynamic parameters at three different temperatures are listed in Table 9. The enthalpy change (ΔH0) obtained are Positive and demonstrates the endothermic nature the adsorption of Acid Red 18 onto GFH; this also supports the observed increase in the adsorption capacity of Acid Red 18 with increasing temperature so increasing temperature is favorable for the adsorption. The positive value of standard entropy change (ΔS) suggests stability, good affinity and decrease of randomness of Acid Red 18 by GFH in the whole removal process. The negative value of ΔG at all temperatures indicated that the adsorption was a spontaneous process. Additionally, the increase in absolute values of ΔG with increasing the temperature reveals that higher temperature facilitated the adsorption.

Table 9 Thermodynamic parameters of AR18 adsorption onto the GFH.
Full size table

In the Table 10 comparison of maximum adsorption capacity of Acid Red 18 and other adsorbents has been investigated.

Table 10 Comparison of maximum adsorption capacity of AR18 between various adsorbents.
Full size table

Conclusion

In this study removal of Acid red 18 anionic dye by granular ferric hydroxide (GFH) with RSM-CCD method design with 30 runs investigated. The results showed GFH Nanocrystal can effectively reduce AR18 concentration in adsorption process (78.59%). Optimization of process performed with RSM and Genetic Algorithm method. Results of two procedure was very close together, RSM: 78.59% vs GA:76.43%. The adsorption process can be better fitted with Freundlich isotherm (R2 = 0.98) and Pseudo-second-order (R2 = 0.98) kinetic models. Maximum adsorption capacity determined 29.13 mg/g. Also thermodynamic studies indicated that the reaction process was endothermic and spontaneous. According to the obtained results, GFH can be considered as having a good efficiency in removing Acid red18 dye.