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. 2020 Jun 19;5(25):15229–15239. doi: 10.1021/acsomega.0c01234

N(4)-Morpholinothiosemicarbazide-Modified Cellulose: Synthesis, Structure, Kinetics, Thermodynamics, and Ni(II) Removal Studies

Huy T Vu †, My T D Phan †, Uyen T T Tran †, Giao D Nguyen ‡, Vu B Duong †, Dang B Tran †,*
PMCID: PMC7331069  PMID: 32637796

Abstract

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In this study, cellulose extracted from straw was modified using N(4)-morpholinothiosemicarbazide to generate a novel adsorbent as a chelate-complex-based material. The effects of pH, time, temperature, and mass ratios of KIO4: cellulose on the yield of the oxidation were analyzed using iodometric titration and photometric methods. The accuracy and precision of the above two methods were evaluated using Student and Fisher statistical distribution. The structure of the material was characterized by Fourier-transform infrared spectroscopy, thermogravimetric analysis, X-ray diffraction, scanning electron microscopy, and Brunauer–Emmett–Teller surface area analysis. The kinetic order of Ni(II) adsorption was dependent on the concentration of Ni(II). The surface response design enabled to optimize the condition for Ni(II) adsorption at 58 °C, pH of 4.98, within 106 min. The maximum Ni(II) adsorption capacity was 90 mg g–1. This kind of adsorbent can be reused at least five times without a significant decrease in its adsorption efficiency.

1. Introduction

Nowadays, land and water sources are polluted with heavy metals from industrial and agricultural wastes. Cr, Ni, As, and Cd at high concentrations can damage the health of people through daily activities. It is considerable that the frequent exposure of Ni(II) ions can cause skin allergies, pulmonary fibrosis, respiratory cancers, bone problems, and dermatitis of the skin (nickel allergy).1 Also, Ni(II) poisoning leads to headache, dizziness, nausea, and vomiting, and so on.2 Thus, water pollution by Ni(II) ions is alarming at present.

Currently, there are many resources of adsorbents such as bagasse, peanut shells, corn cobs, coconut fiber, rice husks, straw, and so forth, that are used to remove heavy metal ions from polluted water. Straw is the potential candidate for manufacturing adsorbents to treat environmental pollution. Straw is mainly composed of lignin (5–24%), hemicellulose (19–27%), and cellulose (32–47%).3 Cellulose and hemicellulose can adsorb many solutes, especially metal ions.3 To improve the absorption capacity of cellulose fibers, cellulose has been modified using many different agents such as β-cyclodextrin (β-CD) and NH2–HBP,4 chloroacetic acid,5 macrocyclic pyridone pentamer with succinic acid,6 dithiocarbamate,7 2-acrylamido-2-methylpropane sulfonic acid,8 Sulfonate,9,10 polyacrylamide, and polyacrylic acid.11 They can adsorb azo dyes,4 dyes in the form of adsorbents,5 Ba(II),9 As(III),7 Cr(VI),8 Pb(II),9,10 methylene blue, and Pb(II).11 Recently, scientists have modified cellulose by using new agents such as thiosemicarbazide and phenyl thiosemicarbazide. The phenyl groups on the N(4) position of the thiosemicarbazide skeleton support quick removal of precious metal ions [Au(III), Pd(II), and Ag(I)] from aqueous solutions.12 The splitting of the carbon–carbon bond of the vicinal diols of the cellulose chains forms Schiff base intermediates. This intermediate is condensed with thiosemicarbazide to obtain a product that can coordinate effectively with heavy metal ions because of the presence of nitrogen and sulfur atoms. The advantages of cellulose modified with thiosemicarbazide are the increase in the number of active sites, mechanical strength, and thermal stability.

Although there have been many studies on cellulose modification with thiosemicarbazide and phenyl thiosemicarbazide, modified cellulose with N(4)-morpholinothiosemicarbazide (TSCZ) has not been widely researched and developed.12−16 In this study, N(4)-morpholinothiosemicarbazide-modified cellulose (MTC) was synthesized, its structure was characterized, and the Ni(II) adsorption capacity was evaluated. The synthetic and adsorption processes were optimized by single variable analysis and response surface design (Box–Hunter model), respectively. The Student and Fisher statistical distribution was applied to evaluate the precision and accuracy of experimental data.

2. Results and Discussion

2.1. Analysis of the Material Structures

The IR spectrum of the materials is shown in Figure 1. After oxidation, the absorptions at 1640 and 895 cm–1 were assigned to the vibration of carbonyl groups and hemiacetal bonds, respectively.16−18 In addition, the C=O peak was not sharp, indicating that there were a few number of the C=O groups on the surface of materials. Besides, the broad absorption of OH groups appeared at a range from 3300 to 3400 cm–1. This shows that the oxidation by KIO4 in an acidic environment occurred at some sites on the surface. After condensation, there was not much change in the signal of functional groups in the IR spectrum. The signal at 1640 cm–1 shifted to 1635 cm–1, which shows the formation of C=N groups. Finally, after the adsorption of Ni(II) ions, the wavenumber and the intensity of the OH groups was slightly reduced. The wavenumber of the C=N vibration reduced from 1635 to 1627 cm–1, and the intensity of the remaining signals decreased. Therefore, the adsorption of Ni(II) ions was chemical adsorption due to OH groups and nitrogen atoms of C=N.

Figure 1.

Figure 1

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FTIR spectroscopy of (A) cellulose BOC, (B) AOC, (C) AOC after condensation (MTC), and (D) MTC after adsorption (MTC–Ni).

For X-ray diffraction (XRD), the crystalline indices (CIs) of the samples were calculated from XRD using the following equation.

2.1. 1

where I002 is the overall intensity of the peak at about 22°, and Iam is the intensity of the baseline at about 18°. Figure 2 shows XRD patterns of three samples. Before oxidation (BOC), cellulose after oxidation (AOC), and MTC have two characteristic diffraction peaks of cellulose microcrystalline at 15.13 and 22.34°. In the XRD patterns, crystalline index (CI) values of BOC, AOC, and MTC were 97.56, 97.43, and 97.23%, respectively. The same CI values indicated that oxidation and condensation took place at some sites on the surface.19−22 Moreover, the crystalline phase of cellulose is stabilized by the hydrogen bonding of hydroxyl groups.23 Although the oxidation led to the decrease in the number of hydroxyl groups, it produced the carbonyl (CHO) groups that can interact with the remaining hydroxyl groups through hydrogen bonds. Furthermore, the condensation supplied the NH groups that were responsible for the hydrogen bond formation between the NH and OH groups. Therefore, CI of MTC was slightly less than that of BOC. This conclusion is supported by the observation from scanning electron microscope (SEM) images.

Figure 2.

Figure 2

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XRD patterns of (a) BOC, (b) AOC, and (c) MTC.

SEM images of four samples are shown in Figure 3. As compared to raw cellulose, AOC has a bundle of fibers and a rough surface. It is because the oxidation broke the glycosidic bridges in the structure of BOC. The fiber has a smoother surface after the condensation. The abnormal pores are connected to form matrix layers. This cross-linked system shows the adsorption capacity of Ni(II) ions. The Ni(II) adsorption process also did not significantly change the structure. These proved that oxidation, condensation, and adsorption occurred on the surface at active sites.16,18

Figure 3.

Figure 3

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SEM reports of the material (a) BOC, (b) AOC, (c) MTC, and (d) MTC–Ni.

Table 1 shows the results of surface area and Ni(II) content adsorbed. Although the surface area in the MTC sample was reduced by about 1/3 times, the adsorption capacity of MTC was fourfold higher than that of BOC or AOC. The presence of sulfur and nitrogen centers increases the adsorption capacity significantly because of the dative bonds of Ni–Sthioketone and Ni–Nimine. Thus, the adsorption of Ni(II) is a chemical adsorption, which depends mainly on donor atoms.

Table 1. Results of Surface Area and Ni(II) Content Adsorbed.

adsorbent surface area (m2 g–1) Ni(II) content (mg g–1)
BOC 9.331 19.02
AOC 6.216 18.10
MTC 2.589 88.88
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As can be seen from Figures 4, S36, S37, and S38, generally, four samples have common patterns. First, all four samples began to decompose at temperatures around 80–90 °C. The mass loss from 7.5 to 9% was assigned to the dehydration on the surface of materials. Second, in a range of 260–500 °C, most materials lost over 80% of their mass with exothermic effects. It was assigned to the combustion of organic compounds to release CO2, CO, and H2O. Finally, when the temperature was higher than 500 °C, most of the samples were decomposed, leaving only carbon powder. The residue of MTC–Ni was composed of carbon powder, NiO, and NiS. The presence of NiO and NiS caused the amount of the sediment to increase by 2.7% compared to MTC. The presence of NiO and NiS shows the adsorption of Ni(II) ions of MTC. BOC and MTC were decomposed completely at 520 °C, whereas AOC decomposition ended at 470 °C. This explained why the hydrogen bonds of HO···HO and HO···HN in BOC and MTC are stronger than that of CHO···HO in AOC.

Figure 4.

Figure 4

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TGA–DSC curves of MTC.

2.2. Effects of Factors on the Yield of the Oxidation of Cellulose

As can be seen from Table 2, the calculated F and t values were less than the critical F and t values. This proves that the errors of data between two analytical methods were insignificant with a confidence of 95%. Some random factors such as the effects of changes in the surroundings such as temperature variations and the readability of the measuring instrument could cause this observation. Therefore, the difference in the two curves in each graph of Figure 5 can be negligible. The two-way analysis of variance (ANOVA) with interaction was applied to evaluate the effects of factors on the yield of CHO formation. As observed in Table 3, the calculated F values of all (A) factors were greater than the critical F values. Thus, the differences in data in the same curve of Figure 5 were significant with a confidence of 95%. It meant that the trends of graphs provided information about the optimized condition for the oxidation process. Therefore, cellulose extracted from straw was oxidized by KIO4 with a mass ratio of KIO4/cellulose = 8:1 in a solution with pH = 3 for 4 h at 30 °C to generate the greatest number of CHO groups.

Table 2. Fisher and Student Statistical Distribution.

  F t   F t
pH factor KIO4/cellulose mass ratio
2 2.34 0.37 0.25 3.92 0.84
2.5 1.95   0.5 4.09  
3 5.14   1 5.14  
3.5 5.48   2 1.67  
4 5.97   4 1.32  
4.5 7.62   6 3.93  
5 3.73   8 12.79  
critical 19.00 2.45 10 11.05  
time (h) 12 8.11  
1 3.25 1.35 critical 19.00 2.31
2 11.08   temperature (°C)
3 1.68   30 12.79 0.54
4 12.79   40 13.26  
5 7.89   50 12.58  
6 2.94   60 12.30  
critical 19.00 2.57 70 11.24  
      critical 19.00 2.78
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Figure 5.

Figure 5

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Effects of (a) pH, (b) mass ratio of KIO4/cellulose, (c) time, and (d) temperature on the −CHO content.

Table 3. F Values from Two-Way ANOVA with Interaction.

  F F crit   F F crit
pH and method mass ratio and method
pH (A) 205.93 2.45 mass ratio (A) 71.67 2.21
method (B) 5.93 4.20 method (B) 3.17 4.11
interaction (AB) 44.92 2.45 interaction (AB) 1.42 2.21
time and method temperature and method
time (A) 14.27 2.62 temperature (A) 4.29 2.87
method (B) 7.02 4.26 method (B) 0.65 4.35
interaction (AB) 3.86 2.62 interaction (AB) 1.45 2.87
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The different contact time or pH can cause an over-redox reaction between cellulose and IO4– to produce byproducts.23 These byproducts can affect results from the titration, whereas they were not able to cause an impact on the photometric method. This evaluation of two-way ANOVA also supported this conclusion. The calculated F(B) and F(AB) values from the contact time method and pH method were greater than the critical F values.

2.3. Effect of Each Independent Factor on the Adsorption Performance

As can be seen from Figure 6, at a low pH, the positive charges on the surface of MTC repelled the cations.24 Hence, the adsorption performance decreased. When the pH increased, the protonation of basic nitrogen sites in MTC decreased. Therefore, there were more basic nitrogen sites to form complexes with Ni(II), leading to increased adsorption capacity. The adsorption performance decreased at pH = 6–8 because of the hydrolysis of Ni(II). In addition, Figure 6 also shows that there are two peaks at pH = 3 (33.08 mg g–1) and pH = 5 (33.43 mg g–1). Therefore, for facilitating the pH adjustment, all reactions are always maintained at pH = 5.

Figure 6.

Figure 6

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Influence of pH on adsorption capacity.

For the contact time, as shown in Figure 7, the adsorption performance is proportional to the increase in the contact time from 30 to 90 min. Initially, there were more free active sites on the surface of MTC, which increased the rate of the adsorption. This can lead to the promotion of the concentration gradient between the Ni(II) ions in the solution and on the surface of MTC. Thus, the adsorptive force overcame the mass transfer resistance of Ni(II) ions from the aqueous phase to the solid phase. After 90 min, the adsorption performance decreased slightly, which indicates that the adsorption reached the equilibrium at 90 min. Therefore, the following experiments were carried out for 90 min because it was the economical and logical option.23,25,26

Figure 7.

Figure 7

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Effect of (a) contact time and (b) temperature on adsorption capacity.

From 30 to 60 °C, the adsorption performance increased because the increase in temperature promoted diffusion and penetration of heavy metal ions and increased the probability of successful collision between Ni(II) ions and active sites.59 When the temperature was greater than 60 °C, the adsorptive forces between the active sites and the metal ions on the surface of the adsorbent material weakened. Therefore, the optimal condition for adsorption was at 60 °C.

2.4. Optimization of the Absorption Performance by the Box–Hunter Model

Using the Box–Hunter model with a confidence of 95%, the regression equation was built using MODDE 5.0 software. A total of 20 random experiments were performed to eliminate uncontrollable factors. The statistical factors are presented in Table 4.

Table 4. Statistics Values of the Regression Equation.

variable coefficient student error p confidence interval
x0 86.81 4.84 <0.0001 10.80
x1 –9.31 3.21 0.0159 7.16
x2 7.98 3.21 0.0323 7.16
x3 4.06 3.21 0.2357a 7.16
x12 –16.68 3.13 0.0003 6.97
x22 –7.00 3.13 0.0492 6.97
x32 –23.47 3.13 <0.0001 6.97
x1x2 4.06 4.20 0.3560a 9.36
x1x3 4.26 4.20 0.3350a 9.36
x2x3 –8.47 4.20 0.0714a 9.36
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a

Insignificant values; R2 = 0.910; R2 adjusted = 0.829; RSD = 11.88%.

All the variables x3, x1x2, x1x3, and x2x3 had p values that were greater than 0.05, and so they were not significant in the regression equation. Therefore, the resulting regression equation was y = 86.81 – 9.31x1 + 7.98x2 – 16.68x12 – 7.00x22 – 23.47x32. Through the equation, it was found that the interaction of the pH, temperature, and time factors does not affect the adsorption performance, but the adsorption depends on each independent factor. In particular, the temperature factor has the most significant impact on the equation, which determines the adsorption capacity.

The correlation coefficient R2 obtained from the equation is 0.910, showing that the results of the Box–Hunter model can describe the experimental results well. There was a good correlation between experimental values and predicted values. Therefore, the above model was used to determine the optimal conditions for Ni(II) ion adsorption. The three-dimensional (3D) model of the equation obtained was drawn from software MODDE 5.0 (Figure 8). The optimal point was recorded from the derivation of each variable. The maximum adsorption capacity of Ni(II) per 1 g of the material is around 90 mg at 58 °C, pH = 4.98, within 106 min.

Figure 8.

Figure 8

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3D models of the regression equation at pH = 4.5, 5, 5.5, respectively.

The results obtained above were compared with other adsorbents in terms of the adsorption capacity of Ni(II) ions.

As can be seen from Table 5, thiosemicarbazone-modified cellulose in this study possessed a high adsorption capacity of Ni(II) at 90.0 mg g–1. Despite being about a half of Am-WS and lower than cell—PAB by 20 mg g–1, the adsorption capacity Ni(II) of MTC was higher than some cellulose-based adsorbents and other adsorbents. Therefore, MTC has great potential for adsorption of heavy metal ions such as Ni(II).

Table 5. Results of Adsorption Capacities of Ni(II) for Each Adsorbent.

adsorbent capacity (mg g–1) references
chemically modified lignocellulosic Am-WS 187.8 (27)
modified cellulose para-aminobenzoic acid (cell—PAB) 110.4 (28)
modified cellulose (cellulose–g–GMA–imidazole) 48.5 (29)
modified cellulose thiosemicarbazone 90.0 this study
cellulose-containing groundnut shells 3.83 (30)
sawdust 8.05 (30)
Mucor rouxii (fungal biomass) 11.09 (live)  
20.49 (dead) (31)  
modified silica gel (2,4-dichlorophenoxy acetic acid) 17.6 (32)
bacterially produced metal sulfides 0.0079 (33)
urea-modified activated carbon derived from Pennisetum alopecuroides, PUAC-4 29.5 (34)
almond husk activated carbon 18.84 (35)
amine-modified fireweed activated carbon, AFWC 10.12 (36)
commercially powdered activated carbon, PAC 2.29 (36)
activated carbon residue from biomass gasification, ACR 62.9 (37)
activated carbon from doum seed (Hyphaene thebaica) coat, DACI 4.93 (38)
activated carbon from doum seed (Hyphaene thebaica) coat, DACII 13.51 (38)
multiwalled carbon nanotubes 18.08 (39)
multiwalled oxidized carbon nanotubes 49.26 (39)
activated carbon from coffee husk, HAC 57.14 (40)
activated carbon from coffee spent, SAC 51.91 (40)
kaolinite 2.79 (41)
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2.5. Optimized Condensation Conditions

It is impossible to directly determine the content of N(4)-TSCZ. Therefore, in this study, the optimization of condensation conditions was based on the evaluation of Ni(II) adsorption performance.

As can be seen from Figure 9, when the condensation time increases, the adsorption capacity also increases to reach the maximum capacity at t = 4 h. Then, the adsorption capacity decreases after 4 h for the condensation. The condensation reaction between the carbonyl group and NH2 to form the C=N group is a reversible reaction. Therefore, for a long time, there is an increase in the number of C=N groups hydrolyzed. It results in a decrease in the number of active sites in MTC.42 In addition, temperature also has a similar effect on the condensation process, and at 80 °C, the product exhibited the best adsorption performance.

Figure 9.

Figure 9

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Effects of condensation conditions on adsorption capacity (a) time and (b) temperature of the water bath.

2.6. Adsorption Kinetics

The kinetic values of the adsorption process are tabulated in Table 6. The sum of squared error (SSE), sum of absolute errors (SAE), χ2, and standard deviation (SD) were also used to examine the goodness of fit for the models at varying concentrations. At Ni(II) concentration of 75 and 50 mg L–1, the correlation coefficient values (R2) of the first-order equation are greater than that of the second-order equation. This proves that first-order equations fit the empirical data best. On the other hand, at Ni(II) concentration of 100 mg L–1, the correlation coefficient values obtained from the second-order equation are greater than that of the first-order equation. This proves that the adsorption was in good agreement with the second-order model. The change in concentration of Ni(II) leads to a change in the reaction rate. This confirms the concentration influences the kinetic equation.16

Table 6. Values of Reaction Rate Constants for the Ni(II) Adsorption Process.

no. Ni(II) concentration (mg L–1) k1 (min–1) k2 (g mg–1 min–1) qe,cal R2 SSE SAE χ2 SD
1 100 0.0979   108.77 0.9472 25.06 75.00 0.90 30.69
2 75 0.0119   31.18 0.9982 0.54 1.38 0.40 0.66
3 50 0.0363   11.06 0.9997 0.70 1.63 0.16 0.86
1 100   0.0055 85.72 0.9956 2.61 5.85 0.07 3.20
2 75   0.0002 48.30 0.9293 17.53 52.58 1.71 21.47
3 50   0.0012 16.89 0.9696 6.39 19.12 1.83 7.82
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2.7. Adsorption Thermodynamics

Table 7 shows the thermodynamic parameter values of the Ni(II) ion adsorption process at different temperatures. The negative value of ΔG° also confirms a spontaneous process. As the temperature increases, the value of ΔG° decreases gradually, which explains the results of the effect of temperature on the adsorption performance. The heat of physical adsorption is less than 4 kJ mol–1 and that of chemical adsorption is more than 83 kJ mol–1. Compared to the ΔH° values in Table 8, most of the adsorbents give ΔH° at the values from 9 to 53 kJ mol–1, proving that the Ni(II) adsorption of MTC included chemical and physical adsorption. The enthalpy change of the Ni(II) adsorption of MTC is 191.21 kJ mol–1 which is greater than 83 kJ mol–1. These confirm that the Ni(II) adsorption of MTC was chemical adsorption.43,44 In addition, because of the endothermic process, the adsorption shifted to the right when the temperature increased from 30 to 60 °C. Therefore, the adsorption performance increased as observed in the batch experiments for the effect of temperature. The positive entropy change indicates that the Ni(II) adsorption of MTC was enthalpy-driven.26

Table 7. Thermodynamic Parameters of the Ni(II) Adsorption at Varying Temperatures.

metal ion temperature (K) ΔG° (kJ mol–1) ΔH° (kJ mol–1) ΔS° (J mol–1 K–1)
Ni(II) 323 1.33 191.21 588.38
  328 –2.12    
  333 –4.54    
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Table 8. Thermodynamic Parameter Values of Ni(II) Adsorption Processes of Some Adsorbents.

adsorbent ΔH0 (kJ mol–1) ΔS0 (J mol–1 K–1) references
kaolinite 37.27 107 (41)
baggage fly ash 15.41 22.32 (45)
orange peel 53.89 192.3 (46)
blast furnace slag 9.28 91 (47)
modified cellulose (cellulose–g–GMA–imidazole) 27.416 116.53 (29)
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2.8. Adsorption Isotherm of MTC for Ni(II) Ions

The Langmuir adsorption model describes the formation of a single adsorption layer on the outer surface of the adsorbent quantitatively. This reflects the equilibrium distribution of metal ions between the liquid and solid phase.48 For the Freundlich model, processes with adsorption characteristics of heterogeneous surfaces were investigated.49 As for the Temkin model, by omitting the value of extremely low and large concentrations, the model assumes that the adsorbed heat of all molecules in the layer would decrease linearly with an increase in the surfactant coverage, and that adsorption is characterized by a uniform distribution of binding energy, up to a maximum energy.50,51 The Dubinin–Radushkevich isotherm is often applied to express the mechanism of adsorption with Gaussian energy distribution on a heterogeneous surface,49,52,53 and the investigation on adsorption of Ni(II) ions to MTC was conducted using the four models mentioned above.

From Table 9, it can be observed that the value of the correlation coefficient R2 of the Temkin model is the greatest, which demonstrates the adsorption of Ni(II) ions onto MTC correlated with the Temkin model best. This proves that the adsorption process of Ni(II) ion is a chemical adsorption process.

Table 9. Constants of Ni(II) Adsorption.

Langmuir
 Freundlich
qm (mg g–1) KL (L mg–1) R2 n Kf (L mg–1) R2
9.9900 –0.0762 0.6421 –0.6238 5658.42 0.8870
Temkin
 Dubinin–Radushkevich
AT (L mg–1) B (J mol–1) R2 qm (mg g–1) Kad (mol2kJ–2) R2
0.0190 –57.289 0.9837 14.1781 –5 × 10–5 0.7512
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2.9. Recovery and Regeneration

Figure 10 shows the effect of time and HCl concentration on the desorption process. The desorption was carried out using a solution of 0.1 M HCl for 20 min. However, the desorption capacity was low (approximately 20%) because the Ni(II) ion adsorption process is a chemical adsorption process. Ni(II) ions can bind active sites on the surface of MTC by strong coordination. This process is different from physical adsorption in which the ions interact with active sites on the surface by weak intermolecular forces.

Figure 10.

Figure 10

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(a) Effect of time on the ability of desorption and (b) influence of HCl concentration on the ability of desorption.

Because of the low removal ability of HCl, ethylenediaminetetraacetic acid (EDTA) 5 × 10–3 M was used as the desorbent.27 From the above data in Figure 11, EDTA possessed a better desorption ability owing to the chelate-complex formation with Ni(II). Therefore, Ni(II) was effectively removed from the surface of MTC. In addition, after five cycles, the adsorption capacity was reduced by around 6%. It shows that MTC is a potential material for the removal of Ni(II) ions in water samples.

Figure 11.

Figure 11

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Performance of MTC by multiple regeneration cycles.

3. Conclusions

In this study, MTC was prepared, its structure was characterized, and Ni(II) adsorption was evaluated. Kinetic studies show that the adsorption was of pseudo-second-order at 100 mg L–1, whereas it was of pseudo-first-order at 50 and 75 mg L–1. The thermodynamic parameters indicate that the Ni(II) adsorption of MTC was enthalpy-driven and a spontaneous process. The positive value of ΔH° explained the main effect of temperature on the adsorption performance. The adsorption isotherm of MTC was best fitted to the Temkin model. The Box–Hunter model was applied to estimate the optimized conditions for the adsorption of MTC. The adsorption was observed at 58 °C, pH = 4.98, within 106 min with a maximum adsorption capacity of 90 mg g–1. MTC can be completely reused five times without the loss of its adsorption capacity by using EDTA 5 × 10–3 M for 10 min. Therefore, MTC is a potential material for removing Ni(II) ions from wastewater.

4. Materials and Methods

4.1. Materials and Characterization

C4H9NO (morpholine), ClCH2COONa, and CH3C(=NOH)C(=NOH)CH3 were purchased from Sigma-Aldrich, USA. NiCl2·6H2O, NaOH, KCl, HCl, KMnO4, CH3COONa, CH3COOH, C2H5OH, CS2, NH3, N2H4·H2O, H2SO4, and (NH4)2S2O8 were provided by Xilong, China. KIO3 was provided by BDH, England. Straw was collected from Vietnam.

The structure analysis of MTC and other materials was conducted by using Fourier-transform infrared spectroscopy (FTIR) with a scan range 4000–450 cm–1, using TENSOR 27—BRUKER, Germany. Changes in the surface shape were analyzed based on the results obtained from the SEM pictures, using the HITACHI S-4800 HI-9039-0006. In addition, the surface area was determined using parameters obtained from the Brunauer–Emmett–Teller (BET) method, measured using a Nova Station A—Quantachrome. XRD studies were carried out using a ECO Bruker AXS,Germany, with a scanning angle of 2θ = 10–80° in order to determine the crystal structure of the sample material. The thermal properties were determined by thermogravimetric analysis (TGA) using a Labys Evo (TGA–DSC-1600 °C) instrument. Samples were measured under the condition of 25–900 °C, with the speed of heating at 10° per minute. Besides, ultraviolet–visible (UV–vis) spectra were used to determine the −CHO content formed after oxidation, Ni(II) ion concentration before and after adsorption, performed on a PerkinElmer Lambda 25 UV–vis spectrophotometer, with wavelength 200–800 cm–1. The pH value of the solution was adjusted by using a pH meter (WinLab Dataline pH meter, Windaus, Germany). A magnetic stirrer (IKA C-MAG HS 7, Germany) was used to stir the solution. The temperature of the solution was adjusted by using a water bath (water bath WNE 29, Memmert, Germany).

4.2. Effect of Each Factor on the Yield of the Oxidation of Cellulose

The process of refining cellulose from straw was conducted in accordance with purifying treatments.54 Following the traditional method,55 KIO4 for the oxidation reaction was synthesized, and 10 g of KI and 20 g of KOH were added into a 100 mL beaker containing 60 mL of water and then stirred with a magnetic stirrer. The chlorine generated by the reaction between KMnO4 and concentrated HCl was bubbled in the abovementioned solution for 3 h. The precipitate was filtered and dried at 70 °C.

The effect of pH on the −CHO content: 0.04 g KIO4 and 0.04 g cellulose were reacted for 4 h, at 30 °C at pH 2, 2.5, 3, 3.5, 4, 4.5, and 5, adjusted using H2SO4 and NaOH.

The effect of the KIO4: cellulose mass ratio to the −CHO content (R): the mixture of KIO4 and cellulose with R of 0.25, 0.5, 1, 2, 4, 6, 8, 10, and 12 was reacted for 4 h, at 30 °C and pH = 3.

The effect of time on the −CHO content: 0.32 g KIO4 and 0.04 g cellulose were reacted for 1, 2, 3, 4, 5, and 6 h, at 30 °C and pH = 3.

The effect of temperature on the −CHO content: 0.32 g KIO4 and 0.04 g cellulose were reacted for 4 h, at pH = 3, and the temperature was 30, 40, 50, 60, and 70 °C.

Based on iodine generated, the aldehyde content in the product was determined using iodometric titration and photometric methods.16,56

4.3. Synthesis of MTC

N(4)-morpholinothiosemicarbazide was synthesized using an ordinary procedure based on the traditional method.58 Then, m (g) of the oxidized material and 3m (g) of TSCZ were put into a glass flask. Next, 150 mL of distilled water was added, and the pH of the mixture was adjusted to 5 using H2SO4 and NaOH. After placing the mixture in a water bath at 80 °C for 4 h, the product was filtered, washed by distilled water several times, and dried at 50 °C.

4.4. Ni(II) Adsorption Studies

A dose of 1g L–1 MTC was examined for adsorption capacity with a Ni(II) concentration of 100 mg L–1. The pH of the solution was adjusted with acetate buffer. After the proposed time, the solution was filtered and the remnant equilibrium concentration of the Ni(II) ion was determined by UV analysis. The metal ions adsorbed per unit mass of MTC were calculated by the following formula.

4.4. 2

where Ci and Cf represent the initial and final concentration of metal ions (mg mL–1), respectively. v and m are the volumes of the solution (mL) and the mass of MTC (g), respectively.

4.4.1. Effect of Factors on the Adsorption Performance

The effect of pH: the adsorption took place for 30 min at 30 °C and pH of 2, 3, 4, 5, 6, 7, and 8.

The effect of time: the adsorption took place at 30 °C and pH 5 for 0.5, 1, 1.5, 2, 2.5, and 3 h.

The effect of water bath temperature: the adsorption took place for 1.5 h, at pH 5 with a temperature of 30, 40, 50, 60, and 70 °C.

4.4.2. Effect of Condensation Conditions

The effect of condensation time: the condensation process was carried out in a water bath at 80 °C for 2, 3, 4, 5, and 6 h. The obtained MTC was then tested its adsorbed performance in the aqueous Ni(II) solution at 60 °C, pH = 5 within 1.5 h.

The effect of the water bath temperature of the condensation process: the condensation process was carried out for 4 h at 60, 70, 80, 90, and 100 °C. The product was then adsorbed Ni(II) ions at 60 °C, pH = 5 within 1.5 h.

4.4.3. Adsorption Kinetics

The adsorption took place from 0 to 50 min at 60 °C. The pH of the solution was adjusted using acetate buffer to 5. The adsorption kinetics of Ni(II) were analyzed by pseudo-first- and pseudo-second-order equations corresponding to the following equation, respectively.

4.4.3. 3
4.4.3. 4

where qt and qe (mg g–1) are the adsorptions at time t (min) and the adsorption capacity, respectively, and k1 and k2 are the rate constants.

4.4.4. Adsorption Thermodynamics

The adsorption took place at temperatures from 50 to 60 °C, for 1.5 h. The pH of solution was adjusted using acetate buffer to 5. The exothermic or endothermic nature of adsorption could be determined by analyzing the enthalpy (ΔH°) and standard free energy (ΔG°). The given eqs 5–7 were used to obtain the different thermodynamic parameters.

4.4.4. 5
4.4.4. 6
4.4.4. 7

where R is the gas constant (8.314 J K–1 mol–1), T is the temperature in kelvin (K), Kc is the thermodynamic equilibrium constant, qe is the solid phase equilibrium concentration (mg g–1), Ce is the equilibrium concentration of the solution (mg L–1), ΔH° is enthalpy change, and ΔS° is the randomness of the system.

4.4.5. Adsorption Isotherm of MTC for Ni(II) Ions

The adsorption took place at 60 °C, within 90 min, with Ni(II) concentration changing from 50 to 100 mg·L–1. The pH of the solution was adjusted using acetate buffer to 5. The adsorption isotherm was analyzed using four models, namely, Langmuir eq 8, Freundlich eq 9, Temkin eq 10, and Dubinin–Radushkevich eq 11. ε in eq 11 is shown by eq 12.

4.4.5. 8
4.4.5. 9
4.4.5. 10
4.4.5. 11

with

4.4.5. 12

where qe is the metal ion content adsorbed per unit mass of material in equilibrium (mg g–1), qm is the maximum metal ion content adsorbed per unit mass of material (mg g–1), Ce is the equilibrium concentration of the solution (mg L–1), KL is the Langmuir constant (L mg–1), KF is the Freundlich constant (L mg–1), B is the thermal constant of adsorption (J mol–1), AT is the Temkin isothermal equilibrium constant (L mg–1), Kad is the Dubinin–Radushkevich constant (mol2 kJ–2), R is the gas constant (8.314 J K–1 mol–1), and T is the temperature in kelvin (K).

4.4.6. Optimization of Adsorption Capacity of Ni(II) Ions Using the Box–Hunter Model

Based on the results of each independent factor affecting Ni(II) adsorption capacity, the levels of the influencing factor are shown in Table 10.

Table 10. Levels of Factors.
  –1 0 +1
temperature (°C) 50 60 70
time (min) 60 90 120
pH 4.5 5 5.5
Open in a new tab

The regression equation shows the dependence of the amount of Ni(II) ions on the surface of the material (y) on the factors of temperature (x1), time (x2), and pH (x3). The optimal conditions for adsorption were determined using the Box–Hunter model, and 20 experiments were performed as shown in Table 11.

Table 11. Results of 20 Experiments of the Box–Hunter Model.
no. temperature (x1) time (x2) pH (x3) qe (mg g–1) (y)
1 50 60 4.5 37.84
2 70 60 4.5 4.43
3 50 120 4.5 54.39
4 70 120 4.5 50.21
5 50 60 5.5 56.60
6 70 60 5.5 53.18
7 50 120 5.5 52.24
8 70 120 5.5 52.11
9 43.18 90 5 57.46
10 76.82 90 5 6.28
11 60 39.54 5 43.75
12 60 140.46 5 74.76
13 60 90 4.16 16.19
14 60 90 5.84 9.14
15 60 90 5 87.50
16 60 90 5 86.97
17 60 90 5 85.66
18 60 90 5 85.59
19 60 90 5 88.89
20 60 90 5 88.88
Open in a new tab

4.4.7. Recovery and Regeneration

Ni(II) ion-loaded MTC (MTC–Ni, 0.05 g) was added to HCl solution (50 mL, 0.1 M) for 10, 20, 30, and 40 min for desorption of Ni(II) ions. HCl concentration was 0.025, 0.05, 0.1, 0.2, and 0.4 M, respectively. Besides, desorption of MTC–Ni was also conducted using EDTA 5 × 10–3 M for 10 min.

Acknowledgments

This study was carried out, thanks to the fund raised by the Ho Chi Minh City University of Education.

Supporting Information Available

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acsomega.0c01234.

  • ANOVA data for influence of each factor on the oxidation of cellulose, SEM images, figures describing TGA, BET, and adsorption isotherms, thermodynamics, and ANOVA results of the Box–Hunter model (PDF)

Author Contributions

The manuscript was written through contributions of all authors. All authors have given approval to the final version of the manuscript. All these authors contributed equally. The authors declare that they have no conflict of interest that could influence this work.

The authors declare no competing financial interest.

Supplementary Material

ao0c01234_si_001.pdf (5.6MB, pdf)

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