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SN Applied Sciences

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Fibrous adsorbent derived from sulfonation of cotton waste: application for removal of cadmium sulfide nanoparticles from aquatic media

  • Ghazal Sajednia
  • Erfan Rahimi
  • Nasrin Alvand
  • Abdolreza Karbassi
  • Majid BaghdadiEmail author
Research Article
  • 140 Downloads
Part of the following topical collections:
  1. Chemistry: Polymer, Zeolite, Nanocomposites: Synthesis, Characterization, Application

Abstract

In the present research, the performance of the cellulose sulfate microfibers (CSMFs) was investigated for the removal of cadmium sulfide nanoparticles (CdS NPs). At first, cotton waste was sulfonated by chlorosulfonic acid. The high sulfur content of the CSMFs (6.54%) and the absorbance bands appeared at 610 cm−1 (symmetric stretching vibrations) and 1205 and 1180 cm−1 (asymmetric stretching vibrations) in the FT-IR spectrum of CSMFs confirmed the successful modification of cotton microfibers. Optimizing the adsorption process was achieved using the response surface methodology. The impacts of the initial concentration of CdS NPs, contact time, total dissolved solids (TDS), and adsorbent concentration on the removal efficiency were assessed. The highest removal efficiency (about 100%) was obtained under optimum conditions. By increasing the TDS, the removal efficiency decreased slightly. University of Tehran, Radke–Prausnitz, and Redlich–Peterson models exhibited low error values. The high maximum adsorption capacity of 5533 mg g−1 was due to the high content of anionic surface groups. The kinetics data were consistent with the Elovich, intraparticle diffusion, and pseudo-second-order models. The rate constant of the pseudo-second-order model decreased by decreasing the concentration of CdS NPs. The adsorbent recovery decreased about 10% after four cycles of regeneration.

Keywords

Cadmium sulfide Nanoparticle Cellulose sulfate Adsorption Cotton 

1 Introduction

Over the last decades, nanoparticles (NPs) have been considerably studied by researchers. NPs have been used in water and wastewater treatment and diverse industries such as, paint, cement, sunscreen, and electronics [1, 2, 3, 4, 5, 6]. Increasing the use of nanoparticles has been led to growing the release of nanoparticles into natural aquatic systems. The toxicity of NPs is more than that of larger particles of the same substance due to their higher surface to volume ratio, higher chemical reactivity, and more particles per unit mass [7, 8, 9, 10]. Therefore, NPs, especially metal-containing NPs that are used greatly in industries related to healthcare products, must be controlled properly during their production, use, and disposal to prevent the living organism from the exposure to the wide range of NPs [11].

Among metal-containing NPs, CdS NPs have unique photochemical and photophysical properties [12]. They are classified as semiconductors with a direct band gap of 2.42 eV at room temperature. Their applications have been expanded into fluorescence imaging, biomedical imaging, detectors for laser and infrared, luminescence devices, optoelectronic devices, and solar cells. Therefore, the release of CdS NPs into the environment is inevitable [13, 14, 15].

Cytotoxicity and toxic effects of CdS NPs have been studied in many researches [16]. As mentioned above, the cytotoxicity of CdS NPs is dependent on the particle size. Lowering the size of CdS particles increases the release of Cd2+ ions and exposing animals and human to this toxic heavy metal ion [17, 18]. Many studies have been reported the harmful effects of CdS NPs and other chemical forms of cadmium on the environment and human health [19]. Some researchers reported that CdS NPs are dangerous not only for human health but also for all species [18].

Several methods such as phytoremediation, coagulation and flocculation, membrane filtration, and adsorption have been assessed to find suitable methods for removing metal-containing NPs from water and wastewater [20, 21, 22, 23, 24, 25, 26]. Because of the drawbacks of other methods including fouling in membrane filtration and high volume of sludge in coagulation and flocculation process, the adsorption process has been reported as the most efficient and economical method [27].

Several materials such as clays, modified plant wastes, chitin, and activated carbon have been used as absorbents in adsorptive processes. Cellulose is a cheap, renewable, biodegradable, and the most widely available natural resource; however, it does not have suitable functional groups for the removal of pollutants. Because of its porosity, high surface area, and the presence of hydroxyl groups, cellulose is a suitable material to be converted to an adsorbent through the surface modification [28, 29, 30, 31, 32]. The adsorbents derived from the cellulose have been used for removing dyes [33] and heavy metals [34]. Furthermore, using cellulose wastes, especially hospital cotton wastes, for preparing the adsorbent is feasible if a strong acid is used for the preparation of the adsorbent because it can completely remove all microbial pollutants. There are various methods for recycling and reusing cellulosic wastes that makes them suitable for this purpose.

In this study, cellulose sulfate (CS) synthesized from the cotton waste was applied to remove CdS NPs from contaminated streams. The modified cellulose microfibers were characterized by FTIR, SEM, and EDX. Many factors involved in the process of CdS NPs adsorption, including contact time, pH, TDS, and the initial concentration of CS NPs were investigated. The kinetics and equilibrium experiments were also executed.

2 Experimental

2.1 Chemicals

Natural cotton waste was obtained from the Health Center of the University of Tehran and used as a source of cellulose microfibers. Before modification of its surface, the cotton was dried at 50 °C for 12 h. Other chemicals used in this research were purchased from Sigma-Aldrich (St. Louis, MO, USA) and Merck (Darmstadt, Germany). N, N-Dimethylformamide (DMF, C3H7NO, CAS No. 68-12-2, ≥ 99.5%, Merck) and Chlorosulfonic acid (CSA, HClO3S, CAS No. 7790-94-5, ≥ 97.0%, Merck) were used for functionalization of cotton microfibers. CdS NPs (1100 mg L1) was prepared using cadmium nitrate tetrahydrate (Cd(NO3)2·4H2O, CAS No. 10022-68-1, ≥ 97.5%, Sigma-Aldrich), cetyltrimethylammonium bromide (CTAB, C19H42BrN, CAS No. 57-09-0, ≥ 98%, Merck), and sodium sulfide nonahydrate (Na2S·9H2O, CAS No. 1313-84-4, ≥ 98.0%, Sigma-Aldrich). The pH of the CdS NPs suspension was adjusted using a pH-meter (model B2000, Behine) with NaOH and HCl solutions (0.1 mol L1). MgSO4, CaCl2, NaHCO3, and KNO3 salts were obtained from Merck Co. to attain the stock solution of TDS with the concentration of 2000 mg L1 [35].

2.2 Preparation of CdS NPs

To determine the adsorption removal efficiency of CdS NPS by CSMFs, a suspension of 1100 mg L−1 of cadmium sulfide nanoparticles was synthesized. For the preparation of this solution, about 0.3 g of cadmium nitrate tetrahydrate was added in 25 mL of deionized water and stirred for 15 min. Then 0.1 g of CTAB dissolved in 25 mL of deionized water was added to the cadmium nitrate solution. After that, 0.078 g of sodium sulfide nonahydrate previously prepared in 50 mL deionized water was mixed with the above solution. As a consequence, a bright yellow solution was obtained, indicating the formation of CS NPs.

2.3 Preparation of the adsorbent

Anionic cellulose sulfate was prepared using dried natural cotton soaked in DMF and CSA diluted with DMF as a sulfonation reagent. Briefly, 6 g of dried natural cotton was soaked in 75 mL of DMF for 20 min at room temperature. Then 18 g of CSA was added dropwise to 75 mL of DMF in an ice bath. Subsequently, the mixture was gently added to the cotton immersed in DMF. The ultimate mixture was shaken at the rate of 120 rpm at room temperature in a sealed glass container. After 2 h of shaking, vacuum filtration through a 1 μm membrane was utilized to separate DMF from the product. After that, the residual solid was treated with deionized water and neutralized with sodium bicarbonate solution (2% w/v). Finally, cellulose sulfate sodium salt was filtered following several steps of washing with deionized water.

2.4 Characterization of the adsorbent

FTIR analyses of the natural cotton and CSMFs were performed using a Burker spectrometer. Morphology of CSMFs was investigated with a scanning electron microscope (SEM, model: HITACHI S-4160). Energy dispersive X-ray analysis (EDX) was used for determination of elemental composition of the adsorbent. The size of CdS NPs was determined with dynamic light scattering (DLS, Zetasizer ZEN3600, Malvern Co, England).

2.5 Design of experiments

Box-Behnken design (BBD) was applied to determine the importance of various independent factors and their interactions and to optimize experimental conditions. Some experiments were performed to select the effective factors and their ranges for the CdS NPs removal. In the present study, contact time (A), adsorbent dosage (B), and CdS NPs concentration (C) were selected as variables. Each input factor was set at ‘+ 1’, ‘0’, and ‘− 1’. Table 1 illustrates the three different levels and the experimental ranges of each variable.
Table 1

Different levels of the selected independent variables

Variables

Factor

Unit

Levels

− 1

0

+ 1

Time

A

min

1.0

15.5

30.0

CS dosage

B

g L−1

0.025

0.137

0.250

CdS NPs concentration

C

mg L−1

20

110

200

The number of total experimental runs can be calculated from Eq. 1.
$$ N \, = \, 2k \, \left( {k \, - \, 1} \right) \, + {\text{ N}}_{0} $$
(1)
where N0 and k are the number of central points and factors, respectively. Five central points and three factors were employed herein; as a result, the total number of runs was 17. The center point experiments were conducted to estimate experimental errors. The design matrix and the obtained data are given in Table 2.
Table 2

RSM design containing the predicted and actual values

Run

Factors

Removal efficiency (%)

Time

CS (g L−1)

CdS NPs (mg L−1)

Actual

Predicted

A

B

C

1

15.5

0.137

110

97.5

97.0

2

15.5

0.250

20

92.0

92.1

3

30.0

0.137

20

90.5

95.0

4

1.0

0.137

200

60.0

60.0

5

1.0

0.137

20

70.0

69.7

6

15.5

0.137

110

96.7

97.0

7

15.5

0.137

110

97.0

97.0

8

15.5

0.137

110

95.8

97.0

9

15.5

0.025

20

63.0

63.1

10

30.0

0.250

110

92.0

91.9

11

15.5

0.137

110

98.1

97.0

12

30.0

0.025

110

67.0

66.9

13

1.0

0.025

110

30.2

30.1

14

15.5

0.025

200

46.0

45.9

15

15.5

0.250

200

90.0

89.9

16

1.0

0.250

110

78.0

78.1

17

30.0

0.137

200

85.1

85.2

The validity of the model was evaluated by the analysis of variance (ANOVA). The initial and residual concentration of CdS NPs after the adsorption process was measured using inductively coupled plasma-optical emission spectroscopy (ICP-OES, Spectro, Arcos EOP, Germany). For this purpose, 2 mL of concentrated nitric acid was added to 10 mL of the solution of CdS NPs and then heated for 10 min. Finally, the digested solution was diluted to 25 mL with deionized water. Design-Expert 10 (Stat-Ease Inc., USA) was used to set up experiments.

The kinetics experiments were executed at different CdS NPs concentrations between 20 and 200 mg L−1 in the range of 1–30 min on 40-mL portions of CdS NPs solutions, containing 25 mg L−1 of CSMFs. Adsorption isotherms were examined at the constant CSMFs dose of 25 mg L−1, the initial CdS NPs concentration ranging between 20 and 200 mg L−1, and the equilibrium contact time of 15 min. For the justification of equilibrium features of the adsorption process, several were employed. The consistency between the experimental and predicted data using the investigated models was assessed using the residual root-mean-square error (RMSE) and the Chi square test (χ2) [36].

3 Results and discussion

3.1 Characterization of CSMFs and CdS NPs

The SEM images were recorded to investigate the morphology of the cotton microfibers, CSMFs, and CSMFs containing CdS NPs. The comparison between SEM images of the cotton and CS (Fig. 1a, b) revealed considerable morphological changes due to the sulfonation process. The fibers of the natural cotton were longer and more rigid than those of the CSMFs; which is due to aging in the acidic medium. The same morphology was reported by Rajalaxmi et al. [37] for the sulfonated cellulose derived from hardwood kraft pulp. The CSMFs containing CdS NPs had a rough surface, showing NPs adsorbed on its surface. (Fig. 1c, d).
Fig. 1

SEM images of a cotton, b CSMFs, c, d adsorbent containing CdS NPs with the magnification of 300 × and 1500 × , respectively

EDX analysis was used for the qualitative and quantitative analysis of elements on the surface of the cotton microfibers, adsorbent, and the adsorbent containing CdS NPs. The elemental composition of the cotton, CSMFs, and CSMFs containing CdS NPs are shown in Fig. 2a–c, respectively. The high sulfur content of the CSMFs confirmed the effective modification of the cotton microfibers. The elemental composition of the CSMFs after the adsorption process indicated a great amount of the CdS NPs adsorbed onto its surface. Figure 2d shows the FT-IR spectra of cotton and CSMFs. CSMFs spectrum exhibited bands at 1205 and 1180 cm−1, corresponding to asymmetric stretching vibrations, and 610 cm−1, which is related to the symmetric one of the sulfate group. The mean particle size of CdS NPs determined using DLS method was 52.8 nm (Fig. 2e).
Fig. 2

EDX analysis of a cotton fibers; b CSMFs; c CSMFs containing CdS NPs (CSMFs: 0.1 g L−1; CdS NPs: 100 mg L−1); d FT-IR spectra for cotton and CSMFs; (e) DLS analysis of CdS NPs

3.2 Statistical analysis

The following model attained by the BBD is a quadratic equation, correlating the removal efficiency (%) with variables, adsorption time (A), CSMFs dosage (B) and CdS NPs concentration (C). A2, B2, and C2 are the quadratic effects, and AB, AC, and BC shows double interactions
$$ \begin{aligned} {\text{Y}} & = 97 + 12.625 \times {\text{A}} + 18.25 \times {\text{B}} - 4.875 \times {\text{C}} - 5.750 \times {\text{AB}} - 0.25 \times {\text{AC}} + 3.750 \times {\text{BC}} \\ & \quad - \;12.63 \times {\text{A}}^{2} - 17.62 \times {\text{B}}^{2} - 6.63 \times {\text{C}}^{2} \\ \end{aligned} $$
(2)
The data obtained by the ANOVA for CdS NPs removal are illustrated in Table 3. The larger F-value and smaller p value (< 0.05) represent a great significance of the corresponding coefficient [38]. As a consequence, all three factors were found to be significant. Moreover, the interaction of CSMFs dosage with contact time and CdS NPs concentration was significant; however, there was no interaction between contact time and CdS NPs concentration (p value = 1). The model F-value of 1864.32 confirmed that the model is valid. On the other hand, the model p value was less than 0.0001, showing the validity of the model in the investigated range of variables. The lack of fit p value was 0.9437; as a result, the lack of fit was insignificant, showing that the data obtained by experiments were in agreement with the model output. In addition, the model accuracy was confirmed using the high values of the adjusted R2 (99.9%) and the predicted R2 (99.95%).
Table 3

The ANOVA results for the constructed model

Factor

SSa

dFb

MSc

F-value

p value

Model

6445.50

8

805.69

1861.32

< 0.0001

A-time

1020.10

1

1020.10

2356.67

< 0.0001

B-CSMFs

2664.50

1

2664.50

6155.61

< 0.0001

C-CdS NPs

152.10

1

152.10

351.39

< 0.0001

AB

132.25

1

132.25

305.53

< 0.0001

AC

0.000

1

0.000

0.000

1.0000

BC

56.25

1

56.25

129.95

< 0.0001

A2

604.88

1

604.88

1397.42

< 0.0001

B2

1139.53

1

1139.53

2632.59

< 0.0001

C2

169.53

1

169.53

391.66

< 0.0001

Residual

3.03

7

0.43

  

Lack of fit

0.25

3

0.083

0.12

0.9437

Pure error

2.78

4

0.70

  

Cor total

6448.53

15

   

Model

6445.50

8

805.69

1861.32

< 0.0001

R2 = 0.9995, Adj R2 = 0.9990, Pred R2 = 0.9988

A, contact time; B, CSMFs dosage; C, CdS NPS concentration

aSum of square

bDegree of freedom

cMean square

3.3 Impacts of investigated variables on the removal efficiency

The perturbation plots given in Fig. 3 indicate the effects of three main parameters on the CdS NPs removal. As can be seen, the effects of time (A) and adsorbent dosage (B) on the response were almost the same, which is consistent with the results of the F-test. However, the CdS NP concentration (C) had a less significant impact on the response.
Fig. 3

Perturbation plots for CdS NPs removal by CSMFs

Figure 4a displays the effect of CdS NPs concentration and contact time at a constant adsorbent content on the adsorption process. By increasing the contact time, the removal efficiency raised. In addition, the interaction between contact time and CdS NPs concentration was insignificant (p value > 0.05). Increasing the CSMFs dosage enhanced the removal efficiency (Fig. 4b), which was in accordance with the highest F-value (6155.61) and the low p value (< 0.0001). The initial concentration of CdS NPs had lower F-value in comparison with other variables, indicating its lowest impact in the adsorption process. The significant interaction of CSMFs concentration and time are presented in Fig. 4c. Low p value and the high F-value (< 0.05 and 305.53, respectively) were the meaningful indications of the strong interaction between these two factors.
Fig. 4

The simultaneous interaction of a contact time and CdS NPs concentration; CSMFs dosage at the level of 0, b CdS NPs concentration and CSMFs dosage;contact time at the level of 0, c CSMFs dosage and contact time; CdS NPs concentration at the level of 0

3.4 Effect of pH and TDS

The effect of pH on the CdS NPs removal is shown in Fig. 5a. The removal efficiency reduced by declining the pH value because of high H+ concentration, competing with CdS NPs for adsorption on the adsorbent surface. Maximum removal efficiency was achieved at the neutral medium. As the pH raised, the removal efficiency improved by about 20%.
Fig. 5

The effect of a pH and d TDS on the CdS NPs removal (CSMFs: 125 mg L−1, CdS NPs: 50 mg L−1, contact time: 15 min, and temperature: 298 K)

The impact of TDS (0 to1600 mg L−1) on the adsorption of CdS NPs using CSMFs was also investigated. The remaining CdS NPs in each solution was measured, and the obtained data were presented in Fig. 5b. The slight decrease observed in the removal efficiency by increasing the TDS content may be due to the existence of cations competing with CdS NPs for the anionic active sites.

3.5 Kinetic studies

The pseudo-second-order (PSO) and pseudo-first-order (PFO) models are the well-known empirical models for adsorption kinetics studies. In the PSO model, the adsorption rate is proportional to the square of free active surface sites. When the initial concentration is high, PFO fits better, while PSO fits better when it is not too high. PSO and PFO models are supposed to fit chemical reaction controlled kinetics, but theoretical interpretations have shown that effective fitting of these models alone is not an indication of chemisorption adsorption. Diffusion or combined diffusion–reaction control can be involved in the adsorption process. Unlike the PSO and PFO models, the Elovich model describe the chemisorption well. It is suitable for the kinetics far from the equilibrium state, at which desorption does not take place [39].

The controlling mechanisms of the adsorption process was studied by kinetic models. They were validated using the residual root-mean-square error (RMSE) and the Chi square test (χ2).

The residuals of the studied models and the related error functions are shown in Fig. 6a–e and Table 4, respectively. Elovich, pseudo-second-order, intraparticle diffusion, liquid film diffusion, and pseudo-first-order models fitted the experimental data in the order of high to low fitness degree, respectively.
Fig. 6

Residual plots of investigated kinetic models in different CdS NPs concentrations: a 20 mg L−1, b 65 mg L−1, c 110 mg L−1, d 155 mg L−1, and e 200 mg L−1 (adsorbent: 25 mg L−1 and contact time: 15 min); Effect of the CdS NPs concentration on the f k2 and g kdif; h Intraparticle diffusion kinetics

Table 4

The performance of kinetic models for adsorption of CdS NPs onto CSMFs at different CdS NPs concentrations

Model

Error function

CdS NPs concentration

20

110

200

Pseudo-first-order

R2

0.966

0.954

0.954

RMSE

74.79

320.82

459.86

χ2

496.7

1614.23

1579.57

Pseudo-second-order

R2

0.999

0.999

0.998

RMSE

3.71

20.63

36.8

χ2

0.65

3.58

7.22

Intraparticle diffusion

R2

0.945

0.944

0.944

RMSE

3.741

20.76

37.86

χ2

0.69

3.80

6.91

Liquid film diffusion

R2

0.812

0.777

0.78

RMSE

11.08

41.21

127.72

χ2

8.11

21.93

76.10

R2

0.969

0.969

0.968

Elovich

RMSE

2.81

16.33

30.11

χ2

0.38

2.33

4.46

Table 5 shows kinetic parameters and the corresponding equations. In the Elovich isotherm, the constant “α” represents the rate of chemisorption, and the constant “β” represents the surface coverage. Regarding the results presented in Table 5, by increasing the initial concentration of CdS NPs, the constant “β” decreased, whereas the constant “α” increased, indicating an increase in the rate of chemisorption, and a decrease in the available sorption surface [40].
Table 5

Adsorption kinetic parameters for CdS NPs adsorption onto the CSMFs at different CdS NPs concentrations

Model

Parameters

CdS concentration(mg L−1)

20

110

200

Pseudo-first-order

k1: min−1

0.1951

0.2258

0.2234

\( \log (q_{e} - q_{t} ) = \log (q_{e} ) - \frac{{k_{1} t}}{2.303}\quad (3) \)

qe(calc): mg g−1

68.779

446.416

803.357

Pseudo-second-order

k2: g mg−1 min−1

0.00650

0.00120

0.00063

\( \frac{t}{{q_{t} }} = \frac{1}{{k_{2} q_{e}^{2} }} + \left( {\frac{1}{{q_{e} }}} \right)t\quad (4) \)

qe(calc): mg g−1

148.014

828.16

1336.898

Intraparticle diffusion

kdif: mg g−1 min−1/2

9.88

54.123

98.559

\( q_{t} = k_{dif} t^{1/2} + C\quad (5) \)

C:

94.52

535.51

804.19

Liquid film diffusion

kfd: min−1

0.1951

0.2258

0.2234

\( \ln (1 - F) = - k_{fd} t\quad (6) \)

    

Elovich

β: mg g−1 min−1

0.074

0.0136

0.0075

\( q_{t} = \frac{1}{\beta }\ln (\alpha \beta ) + \frac{1}{\beta }\ln (t)\quad (7) \)

α: g mg−1

2.207 × 104

5.124 × 104

7.78 × 104

α, (mg g−1 min−1) and β, (g mg−1) are the initial adsorption rate of the Elovich equation and the desorption constant; kfd, liquid film diffusion rate coefficients (min−1); C, intercept of intraparticle diffusion; kdif, rate constant of intraparticle diffusion (mg g−1 min−1/2); k2, second-order rate constant of adsorption (g mg−1 min−1); k1, Rate constant of pseudo-first order adsorption (min−1)

The Variation of k2 and kdif by changing the initial concentration of CdS NPs are illustrated in Fig. 6f, g. According to Fig. 6f, by rising initial CdS NP concentration, the second-order rate constant, k2, decreased, confirming the higher adsorption rate at the higher initial concentration of CdS NPs. In intraparticle diffusion plots (Fig. 6g), the first region represents the external surface adsorption. A slow adsorption rate was recognized in the second region where intraparticle diffusion was the rate-limiting step. The third region is related to the equilibrium stage, where the intraparticle diffusion rate begins to slow down because of the lower active sites available [41]. According to Fig. 6g, h, by increasing the initial concentration of CdS NPs, the diffusion rate constant increased as a result of increasing the adsorption driving force [42].

3.6 Equilibrium study

To describe the interactive behavior between CdS NPs and CSMFs, equilibrium adsorption experiments were executed. For the selection of the best fit line, the error analysis was applied. The model with the minimum residual root-mean-square error was considered as the best model. The residuals of experimental and calculated qe for these three isotherm models were lower than those for other models as shown in Fig. 7. According to the errors shown in Table 6, the fitness extent followed the following order:
Fig. 7

Residual plots of investigated models (CSMFs: 25 mg L−1, contact time: 15.5 min)

Table 6

Error values and R2 for adsorption of CdS NPs onto CSMFs at 298 °C

Models

Error function

R2

RMSE

χ2

UT isotherm

0.9996

9.09

0.13

Redlich–Peterson

0.9996

9.39

0.13

Radke–Prausnitz

0.9998

19.81

0.50

Dubinin–Radushkevich

0.9818

102.43

16.41

Langmuir

0.9857

123.18

24.14

Temkin

0.9678

141.23

29.25

Freundlich

0.9377

216.75

65.84

UT isotherm > Redlich–Peterson > Radke–Prausnitz > Dubinin–Radushkevich > Langmuir > Temkin > Freundlich.

The equation of the investigated models and the related parameters are presented in Table 7. In the Langmuir isotherm, active sites covering with a monolayer of adsorbates are identical, and the maximum adsorption capacity (qm) is related to monolayer adsorption [36]. The Langmuir model can also determine the maximum adsorption capacity of the adsorbent corresponding to the monolayer adsorption on the surface of the adsorbent. The value of RL can be calculated as below:
Table 7

Isotherm parameters for the adsorption of CdS NPs onto CSMFs at 298 K

Isotherm

Equation

Parameters

Values

Langmuir

\( \frac{{C_{e} }}{{q_{e} }} = \frac{1}{{K_{L} q_{m} }} + \frac{{C_{e} }}{{q_{m} }}\quad (10) \)

qm: mg L−1

5850

KL: L mg−1

0.0272

Freundlich

\( \ln q_{e} = \ln K_{F} + \frac{1}{{n_{F} }}\ln C_{e} \quad (11) \)

1/nF

0.458

KF: (mg g−1)(L mg−1)1/n

547.61

Temkin

\( q_{e} = B_{1} \ln A + B_{1} \ln C_{e} \quad (12) \)

B1: mg g−1

1446.04

A: L mg−1

0.204

Dubinin–Radushkevich

\( \ln q_{e} = \ln q_{s} - \beta \varepsilon^{2} \quad (13) \)

qs: mg g−1

4223.12

\( \varepsilon = RT\ln \left( {1 + \frac{1}{{C_{e} }}} \right)\quad (14) \)

β: mol2 J−2

7.12 × 10−5

\( E = \frac{1}{{\sqrt {2\beta } }}\quad (15) \)

E: kJ mol−1

0.08

Radke–Prausnitz

\( \frac{{C_{e} }}{{q_{e} }} = \frac{1}{{K_{RP} q_{m} }} + \frac{{C_{e}^{m} }}{{q_{m} }}\quad (16) \)

m:

1.69

KRP: L mg−1

0.00061

qm: mg g−1

168,774

Redlich–Peterson

\( \ln \left( {K_{R} \frac{{C_{e} }}{{q_{e} }} - 1} \right) = g\ln C_{e} + \ln \alpha_{R} \quad (17) \)

g

1.69

KR: L g−1

101.63

αR: (L mg−1)g

0.00061

UT isotherm

\( \ln \left( {\frac{{C_{e} }}{{q_{e} }} - \frac{{K_{d} }}{{q_{m} }}} \right) = \ln \frac{{D^{1 - b} }}{{q_{m}^{b} }} + b\ln C_{e} \quad ({\text{S14}}) \)

b

1.69

FCF

0.07

Kd: mg L−1

54.44

qm: mg g−1

5533

T, absolute temperature (K); R, 8.314 gas constant (J mol−1 K−1); b, UT isotherm exponent; Kd, desorption constant; KRP, Radke–Prausnitz constant (L mg−1); β, constant of Dubinin–Radushkevich (mol2 J−2); E, related to free energy (kJ mol−1); qs, adsorption capacity (mg g−1), 1/n and KF, Freundlich isotherm constant; KL, Langmuir constant (L mg−1); KR, (L g−1); αR (L mg−1) and g, Redlich–Peterson constants

$$ R_{l} = \frac{1}{{1 + K_{L} \cdot C_{0} }} $$
(8)
where KL (L mg−1) is the Langmuir constant and Co is the initial concentration (mg L−1). According to the following criteria, the adsorption is classified irreversible (RL = 0), linear (RL = 1), unfavorable (RL > 1), and favorable (0 < RL < 1). The RL in this work was 0.25; therefore, the sorption was favorable. Freundlich isotherm describes a multilayer adsorption process [43]. In this study, n-value was 2.2, indicating that the sorption was favorable [44]. Temkin isotherm considers that the binding energies are distributed uniformly [41]. In Dubinin-Radushkevich isotherm a heterogeneous surface is considered for adsorption According to Eq. S11, the mean free energy of 0.08 kJ mol−1 represents a physisorption process. Radke–Prausnitz, University of Tehran (UT), Redlich–Peterson models can be applied for heterogeneous and homogeneous surfaces. The UT isotherm is a novel adsorption isotherm having the capability to predict the qm of the heterogeneous systems [45]. According to the UT isotherm, the free capacity fraction (FCF) can be calculated using Eq. 4.
$$ FCF = \frac{{k_{d} }}{{D.q_{m} }} $$
(9)
where Kd is the UT desorption constant, and D is the adsorbent dosage (g L−1). The high FCF-value (0.07) was an indication of the homogeneous surface [45].

3.7 Desorption studies

To study the regeneration of the CSMFs for future uses, desorption experiments were done. For this purpose, a solution of CdS NPs (110 mg L−1) containing 0.25 g L−1 of CSMFs was stirred for 15 min. After that, the CSMFs was separated and washed with HCl 0.1 mol L−1 and then with deionized water. The recovered adsorbent was used for the removal of CdS NPs under the mentioned-above conditions. The adsorption and desorption cycle was repeated four times, and the results are presented in Fig. 8. The recovered CSMFs indicated a good performance even after four cycles of the regeneration.
Fig. 8

The regeneration of the CSMFs with HCl 0.1 mol L−1

3.8 Performance comparison of techniques for NPs removal

The performance of the CSMFs and other methods are reported in Table 8. The high removal efficiency of CSMFs is an indication of its effectiveness for CdS NPs removal from polluted streams. In addition, the equilibrium was achieved less than 10 min.
Table 8

The efficiency comparison of the reported techniques for NPs removal

Method

Nanoparticle

Removal efficiency (%)

References

Coagulation

CdTe QDs

80

[44]

Coagulation

CNT

97

[45]

Coagulation

TiO2

80

[46]

Adsorption (adsorbent: modified paper)

Ag

80

[47]

Coagulation

CuO

80

[48]

Adsorption (adsorbent: CS)

CdS

100

Present study

4 Conclusion

In this research, the cellulose sulfate microfibers prepared by sulfonation of the cotton waste was introduced as an efficient adsorbent for the removal of CdS NPs from contaminated streams. The high sulfur content of the CSMFs (6.54%) and the absorbance bands appeared at 1205 and 1180 cm−1 (asymmetric stretching vibrations) and 610 cm−1 (symmetric stretching vibrations) in the FT-IR spectrum of CSMFs confirmed the successful modification of cotton microfibers. The maximum adsorption capacity of 5500 mg g−1 and the maximum removal efficiency of 100% were obtained. The TDS and pH did not affect the performance of the CSMFs. The adsorption process followed the UT and Redlich–Peterson isotherms. Moreover, the adsorption kinetic data followed the Elovich and pseudo-second-order models. The adsorbent recovery was performed with HCl 0.1 mol L−1, and the removal efficiency dropped by approximately 10% after four cycles of the regeneration. In conclusion, the cellulose sulfate derived from the cotton waste is an efficient adsorbent for the removal of nanoparticles with the positive surface charge. Due to the large particle size, CSMFs can be easily separated from the contaminated streams after the treatment process. On the other hand, the prepared adsorbent exhibited a considerable adsorption capacity due to the high content of anionic surface groups.

Notes

Acknowledgements

The authors would like to acknowledge the research Grant received from University of Tehran.

Compliance with ethical standards

Conflict of interest

The authors confirm that this article content has no conflict of interest.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.School of Environment, College of EngineeringUniversity of TehranTehranIran
  2. 2.Department of Chemistry, Arak BranchIslamic Azad UniversityArākIran

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