# Biosorptive Removal of Cadmium(II) and Copper(II) Using Microwave-Assisted Thiourea-ModifiedSorghum bicolor Agrowaste

Authors: Muhammad Salman; Rabia Rehman; Umar Farooq; Anum Tahir; Liviu Mitu
Journal: Journal of Chemistry
 (2020)

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## Abstract

Sorghum bicolor (S.B.) is used in this work for preparing chemically modified adsorbent for toxic metal ions, i.e., cadmium(II) and copper(II). Thiourea is selected for chemical modification of this plant waste by microwave solid fusion methodology, so that its chelating ability for metal ions can be enhanced in both acidic and basic conditions, in a cheaper and quicker way. Characterization was carried out by different physiochemical means using FT-IR, SEM, etc. An increase in pHpzc value was observed in TSB, which is confirmed by FT-IR analysis. The effect of biosorption process parameters was also studied and found that maximum removal of these toxic ions occurred in slightly acidic pH (5-6) conditions, following pseudo-second-order kinetic model. Boyd plots indicated that film dispersion mode was the rate-determining step. Langmuir model indicated that the maximum metal ion removal capacity of TSB was 17.241 mg/g and 15.151 mg/g for cadmium(II) and copper(II) ions. So, TSB can be used on a larger scale for toxic metal ion removal by Sorghum bicolor waste in a cleaner way.


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## Body

## 1. Introduction

Industrial and technological advancements have raised various environmental issues. Contamination of water bodies with heavy metal is one of the most threatening environmental issues [1]. They are highly toxic, nonbiodegradable, and released in the aqueous environment through industrial inefficiencies. Copper and cadmium are among the most toxic heavy metals. Their salts are mostly used in electroplating, textile dyeing, and fertilizer industries. The permissible limit for copper in water is 1.3 mg/L, and for cadmium, it is 5 μg/L [2]. There is an increasing demand to develop/modify processes to substantially reduce the amount of hazardous metal ions present in wastewater effluent before its discharge in water bodies.Biosorption [3] is an emerging technology, in which microbes and dead biomass materials are utilized to remove contaminants from wastewaters [4]. Several biomasses have been utilized to remove copper and cadmium from aqueous solution, and these include wheat straw [5], sawdust [6], banana peels [7], neem bark [8], olive waste [9], and activated sludge [10]. Raw or untreated biomass offers low biosorption capacity [11] and does not provide valuable information about the biosorption mechanism involved in metal binding to its surface [8, 12]. For this, chemical modification of adsorbent by different means was investigated by researchers [13–17]. In this work, thiourea-modified Sorghum bicolor L. was used for removing Cu(II) and Cd(II) ions. In Asian countries, it is a major crop that produces a huge amount of agrowaste [18]. The modification was done in solvent-free environment under microwave radiation. Thus, the modification method was cleaner and eco-friendly in nature.


## 2. Experimental

### 2.1. Materials and Methods

Various acids and cadmium and copper salts along with thiourea were used in this work, which were purchased from Merck. Grinder (Philips), microwave oven (Orient-2450 MHz), AAS (Perkin Elmer Analyst-100), FT-IR (Perkin Elmer Spectrum-RX1), SEM (JEOL-JSM 6480), and CHNS analyzer (Vario EL III Elementar) were used.


#### 2.1.1. Preparation of Biosorbent

Sorghum bicolor L. (local name: Charee) plant waste is used here. It was collected from farms in nearby areas of Sheikhupura, Pakistan. It was washed, dried in sunlight, and converted into a fine powder before chemical treatment. Fine powder (50–60 mesh ASTM) was labeled as SB and stored in plastic jars. For chemical modification, it was mixed with thiourea in a china dish (1 : 2 ratio) and placed in a microwave oven for 5–10 minutes [19]. Some distilled water was sprinkled over the sample before keeping in the oven for proper mixing of both solids. After fusion, the sample was cooled and ground again to a fine powder. Then, it was stored in plastic jars and labeled as TSB (thiourea-modified Sorghum bicolor). Then, both these samples were characterized by FT-IR, SEM, elemental analysis, surface area analysis, Boehm’s titration [20], and point of zero charge values (pH-pzc) by reported methods [21], and the results are compared in Table 1 and Figures 1 and 2.Table 1
Physiochemical analysis of biosorbent samples.
Characterization
Parameters
SB
TSB
Element examination
C (%)
44.47 ± 0.50
44.31 ± 0.29
H (%)
6.94 ± 0.06
7.04 ± 0.03
N (%)
0.85 ± 0.04
9.32 ± 0.06
S (%)
0.17 ± 0.02
4.76 ± 0.04
Boehm’s titration
Total acidic groups (mmol/g)
8.42 ± 0.03
8.04 ± 0.02
Carboxylic (mmol/g)
6.51 ± 0.03
6.16 ± 0.02
Lactones (mmol/g)
1.17 ± 0.03
1.19 ± 0.02
Phenols (mmol/g)
0.74 ± 0.03
0.68 ± 0.02
Total basic groups (mmol/g)
3.18 ± 0.02
3.95 ± 0.02
pHpzc
5.9
6.7Figure 1
SEM image of (a) SB and (b) TSB at ×1000 magnification.Figure 2
FT-IR spectra of (a) SB and (b) TSB.
(a)
(b)


#### 2.1.2. Biosorption Studies on Batch Scale

They were done in a similar fashion as described earlier [22] using metal ion solutions separately with SB and TSB. The difference in initial and final concentrations of metal ions was used to calculate the binding capacity of SB and TSB with metal ions by the following equation:(1)q=Co−Cem×v,where “m (g)” is the biosorbent quantity and “v (L)” is the metal ion solution volume [23].Different factors such as pH, contact interval, and temperature which influence biosorption were monitored one by one using both SB and TSB, and metal ion concentration was monitored by AAS in the remaining solution. All these steps were carried out in triplicate mode. Microsoft® Excel was used for analyzing resulting data and regression analysis. Root mean square error was calculated by the following equation:(2)RMSE=qeexp−qecal2N,where qe(exp) and qe(cal) symbolize sorption capacity calculated from experiments and predicted from adsorption models, respectively. “N” is the number of data points for each dataset.


## 2.1. Materials and Methods

Various acids and cadmium and copper salts along with thiourea were used in this work, which were purchased from Merck. Grinder (Philips), microwave oven (Orient-2450 MHz), AAS (Perkin Elmer Analyst-100), FT-IR (Perkin Elmer Spectrum-RX1), SEM (JEOL-JSM 6480), and CHNS analyzer (Vario EL III Elementar) were used.


### 2.1.1. Preparation of Biosorbent

Sorghum bicolor L. (local name: Charee) plant waste is used here. It was collected from farms in nearby areas of Sheikhupura, Pakistan. It was washed, dried in sunlight, and converted into a fine powder before chemical treatment. Fine powder (50–60 mesh ASTM) was labeled as SB and stored in plastic jars. For chemical modification, it was mixed with thiourea in a china dish (1 : 2 ratio) and placed in a microwave oven for 5–10 minutes [19]. Some distilled water was sprinkled over the sample before keeping in the oven for proper mixing of both solids. After fusion, the sample was cooled and ground again to a fine powder. Then, it was stored in plastic jars and labeled as TSB (thiourea-modified Sorghum bicolor). Then, both these samples were characterized by FT-IR, SEM, elemental analysis, surface area analysis, Boehm’s titration [20], and point of zero charge values (pH-pzc) by reported methods [21], and the results are compared in Table 1 and Figures 1 and 2.Table 1
Physiochemical analysis of biosorbent samples.
Characterization
Parameters
SB
TSB
Element examination
C (%)
44.47 ± 0.50
44.31 ± 0.29
H (%)
6.94 ± 0.06
7.04 ± 0.03
N (%)
0.85 ± 0.04
9.32 ± 0.06
S (%)
0.17 ± 0.02
4.76 ± 0.04
Boehm’s titration
Total acidic groups (mmol/g)
8.42 ± 0.03
8.04 ± 0.02
Carboxylic (mmol/g)
6.51 ± 0.03
6.16 ± 0.02
Lactones (mmol/g)
1.17 ± 0.03
1.19 ± 0.02
Phenols (mmol/g)
0.74 ± 0.03
0.68 ± 0.02
Total basic groups (mmol/g)
3.18 ± 0.02
3.95 ± 0.02
pHpzc
5.9
6.7Figure 1
SEM image of (a) SB and (b) TSB at ×1000 magnification.Figure 2
FT-IR spectra of (a) SB and (b) TSB.
(a)
(b)


### 2.1.2. Biosorption Studies on Batch Scale

They were done in a similar fashion as described earlier [22] using metal ion solutions separately with SB and TSB. The difference in initial and final concentrations of metal ions was used to calculate the binding capacity of SB and TSB with metal ions by the following equation:(1)q=Co−Cem×v,where “m (g)” is the biosorbent quantity and “v (L)” is the metal ion solution volume [23].Different factors such as pH, contact interval, and temperature which influence biosorption were monitored one by one using both SB and TSB, and metal ion concentration was monitored by AAS in the remaining solution. All these steps were carried out in triplicate mode. Microsoft® Excel was used for analyzing resulting data and regression analysis. Root mean square error was calculated by the following equation:(2)RMSE=qeexp−qecal2N,where qe(exp) and qe(cal) symbolize sorption capacity calculated from experiments and predicted from adsorption models, respectively. “N” is the number of data points for each dataset.


## 2.1.1. Preparation of Biosorbent

Sorghum bicolor L. (local name: Charee) plant waste is used here. It was collected from farms in nearby areas of Sheikhupura, Pakistan. It was washed, dried in sunlight, and converted into a fine powder before chemical treatment. Fine powder (50–60 mesh ASTM) was labeled as SB and stored in plastic jars. For chemical modification, it was mixed with thiourea in a china dish (1 : 2 ratio) and placed in a microwave oven for 5–10 minutes [19]. Some distilled water was sprinkled over the sample before keeping in the oven for proper mixing of both solids. After fusion, the sample was cooled and ground again to a fine powder. Then, it was stored in plastic jars and labeled as TSB (thiourea-modified Sorghum bicolor). Then, both these samples were characterized by FT-IR, SEM, elemental analysis, surface area analysis, Boehm’s titration [20], and point of zero charge values (pH-pzc) by reported methods [21], and the results are compared in Table 1 and Figures 1 and 2.Table 1
Physiochemical analysis of biosorbent samples.
Characterization
Parameters
SB
TSB
Element examination
C (%)
44.47 ± 0.50
44.31 ± 0.29
H (%)
6.94 ± 0.06
7.04 ± 0.03
N (%)
0.85 ± 0.04
9.32 ± 0.06
S (%)
0.17 ± 0.02
4.76 ± 0.04
Boehm’s titration
Total acidic groups (mmol/g)
8.42 ± 0.03
8.04 ± 0.02
Carboxylic (mmol/g)
6.51 ± 0.03
6.16 ± 0.02
Lactones (mmol/g)
1.17 ± 0.03
1.19 ± 0.02
Phenols (mmol/g)
0.74 ± 0.03
0.68 ± 0.02
Total basic groups (mmol/g)
3.18 ± 0.02
3.95 ± 0.02
pHpzc
5.9
6.7Figure 1
SEM image of (a) SB and (b) TSB at ×1000 magnification.Figure 2
FT-IR spectra of (a) SB and (b) TSB.
(a)
(b)


## 2.1.2. Biosorption Studies on Batch Scale

They were done in a similar fashion as described earlier [22] using metal ion solutions separately with SB and TSB. The difference in initial and final concentrations of metal ions was used to calculate the binding capacity of SB and TSB with metal ions by the following equation:(1)q=Co−Cem×v,where “m (g)” is the biosorbent quantity and “v (L)” is the metal ion solution volume [23].Different factors such as pH, contact interval, and temperature which influence biosorption were monitored one by one using both SB and TSB, and metal ion concentration was monitored by AAS in the remaining solution. All these steps were carried out in triplicate mode. Microsoft® Excel was used for analyzing resulting data and regression analysis. Root mean square error was calculated by the following equation:(2)RMSE=qeexp−qecal2N,where qe(exp) and qe(cal) symbolize sorption capacity calculated from experiments and predicted from adsorption models, respectively. “N” is the number of data points for each dataset.


## 3. Results and Discussion

### 3.1. Surface Analysis by SEM

Both biosorbent samples were analyzed by SEM for observing surface morphological changes, and the resulting images are compared in Figure1. It is indicating that the surface morphology of both samples is rough and highly porous, which facilitates in physiosorptive removal of metal ions by binding with biosorbents. It is also worth mentioning that thiourea treatment enhanced porosity and roughness of the biosorbent surface, which indicated that modification of material boosted the binding capacity of TSB [24].


### 3.2. Elemental Analysis

It is carried out by CHNS analyzer for finding the percentage of C, H, N, and S and also helps to investigate the quantity of incorporated elements by chemical modification. As evident from Table1, nitrogen and sulfur significantly increased in TSB as compared to SB. These results confirmed the fusion of thiourea into Sorghum bicolor plant waste powder. It means more binding sites were available for chelating metal ions from solution, which enhanced its chemisorptive capacity.


### 3.3. Functional Group Analysis by FT-IR

Both samples were analyzed by FT-IR. The resulting spectrum of SB is shown in Figure2(a). It indicated the presence of various functional groups, such as hydroxyl group indicated by a peak at 3338.78 cm−1, alkyl group by a peak at 2918.30 cm−1, and carbonyl group by a peak at 1637.56 cm−1. Carboxylate ion peaks were observed at 1514.12 cm−1, 1421.54 cm−1, 1246.02 cm−1, and 1157.29 cm−1 [25]. It means diversity of acidic functional groups was existing in SB that can chelate cationic impurities from water, whereas Figure 2(b) presents functional group changes occurred in TSB. It had no peak related to hydroxyl group, but carboxylate ion peaks were there at 1516.05 cm−1, 1460.11 cm−1, and 1417.68 cm−1. Secondary amines’ presence was confirmed by peaks at 3612.67 cm−1 and 1649.17 cm−1. Isothiocyanate group (-N=C=S) peaks at 2380.16 cm−1, 2305.79 cm−1, and 1024.20 cm−1 confirms its existence [26]. So, functional groups increased in TSB that helps in chelation.


### 3.4. Boehm’s Titration Surface Analysis

The number of acidic and basic functional groups was compared by Boehm’s titrations in SB and TSB [24] and is presented in Table 1. Acidic functional group concentration was higher in SB, whereas in TSB both acidic and basic functional groups are prominent. As SB had more carboxylic acid groups, they were converted into amide groups in TSB that can be elucidated from FT-IR spectrum (Figure 2(b)), which enhanced its basic functionalities.


### 3.5. Point of Zero Charge

When solutions containing metal ions have greater pH than point of zero charge, it means biosorbent has more negative functionalities {Dupont, 2003 #88} and vice versa is true for biosorbents having more cationic functional groups that can remove anionic impurities better, like chromate and arsenate ions {Wang, 2008 #89}. Some literature also indicated that lower pH helps in desorption of metal ions and regeneration of adsorbent [27, 28]. pHpzc results are compared in Figure 3 and found to be 5.9 and 6.7 for SB and TSB, respectively.Figure 3
pHpzc determination of SB and TSB.


### 3.6. pH Profile

Solution pH plays a vital role during biosorption. In acidic conditions, more ionization of functional groups occurred that helps in better biosorption. But in highly basic conditions, both Cd(II) and Cu(II) precipitate out from solution as hydroxide. So, this factor was investigated using both biosorbents and the results are presented in Figure4. Strongly acidic conditions hinder biosorptive removal of these metal ions because it results in protonation of active binding sites that can chelate Cu(II) and Cd(II) possibly. More better results were observed in the pH range of 5 to 6. Chelating capacity of TSB is also more than that of SB in this range indicated by higher “q” values.Figure 4
pH effect on the removal of Cu(II) and Cd(II).
(a)
(b)


### 3.7. Reaction Kinetics

It helps in determining the mechanism of metal ion removal during biosorption by different kinetic models [29]. Effect of contact time between SB/TSB and metal ion solution was monitored and is shown in Figure 5 for various concentrations. It is obvious from this figure that metal ion removal by SB and TSB was fast on the initial stage, which becomes constant after some time. It means the rate of biosorption on SB and TSB becomes equal to desorption from chelating sites due to week interactions [30].Figure 5
Time interval effect on biosorption of (a) Cu(II) and (b) Cd(II).
(a)
(b)Various kinetic models were employed on these data. Following equations (3) and (4) speak to the linear types of pseudo-first- and pseudo-second-order models:(3)lnqe−qt=lnqe−k1⋅t,(4)tqt=1k2qe2+tqe.Results are given in Table2. Pseudo-first-order model depended on the hypothesis that biosorption is straightforwardly corresponding to the quantity of free binding sites. Table 2 indicates that sorption studies for Cd(II) did not follow pseudo-first-order kinetics, while for Cu (II) ion removal by TSB, biosorption followed this model as clear from R2 value. But values of qe (experimental and calculated) did not match from this trend. It means this model is not applicable for these systems.Table 2
Kinetic parameters for Cu(II) and Cd(II) biosorption.
Biosorbent
Metal ions
Pseudo-first-order kinetics
q
e (mg/g) (experimental)
Pseudo-second-order kinetics
k
1 (min−1)
R
2
q
e (mg/g)
k
2 (min−1)
R
2
q
e (mg/g)
SB
Cu(II)
0.147
0.943
1.248
2.17
0.253
0.998
2.277
Cd(II)
0.154
0.962
1.557
2.12
0.191
0.998
2.252
TSB
Cu(II)
0.187
0.999
0.756
5.02
0.792
0.999
5.076
Cd(II)
0.271
0.830
4.297
5.40
0.051
0.999
5.19According to the pseudo-second-order model, biosorption rate is related to the square of binding site availability and metal ion amount. Kinetic data for Cu(II) and Cd(II) were used to investigate this model and are presented graphically in Figure6. All values of rate constant, correlation constant, and qe(cal) and qe(exp) matched with this trend. It had indicated the validity of this model for these systems [31]. The best fit of pseudo-second-order model clarifies that one divalent cation joins to two monovalent binding sites [32].Figure 6
Linear presentation of pseudo-second-order graph: (a) Cu(II) and (b) Cd(II).
(a)
(b)Boyd et al. [33] expression was utilized to decide the rate deciding step in biosorption. There are two modes of biosorption: (1) limit layer film dispersion and (2) intramolecule diffusion.Boyd’s kinetic expression is given in the following equation:(5)F=1−63.14162exp−Bbt.“F” is at time t given as follows:(6)F=qtqe.By comparing both equations, they were simplified as follows:(7)Bb=−0.4977−ln1−qtqe.The importance of the Boyd plot is if straight line passing from the origin is observed, then intramolecular diffusion is the predominant rate-determining step and vice versa is true in other cases [34, 35]. So results are given in Figure 7.Figure 7
Boyd plots for the biosorption of (a) Cu(II) and (b) Cd(II).
(a)
(b)As from Figure7, neither of the plots was direct or passed from the origin. So both modes of biosorption (limit layer film dispersion and intramolecular diffusion) were adopted in this study.


### 3.8. Isothermal Studies regarding Initial Metal Ion Concentration

Three diverse adsorption isotherms including Langmuir, Freundlich, and Temkin had been utilized in nonlinear design and had been examined. Volesky revealed that there is no need of increasingly complex adsorption isotherms if basic (Langmuir and Freundlich) isotherms are pursued and give the significant data [36]. Equations (8)–(11) speak to the nonlinear types of Langmuir, Freundlich, Temkin, and Dubinin–Radushkevich (DR) equilibrium models, separately. The expressed models were processed by ascertaining the relative mean square error (RMSE) utilizing (8):(8)qe=b⋅qm⋅Ce1+b⋅Ce,(9)qe=KF⋅Ce1/n,(10)qe=BT⋅lnKT⋅Ce,(11)qe=qm⋅exp−βε2,(12)RMSE=∑qecal−qeexp2N.Langmuir model presumes that binding sites were homogeneously distributed in monolayer fashion over the sorbent surface that will chemisorb metal ions [37]. Langmuir model was utilized on to the equilibrium data for Cu(II) and Cd(II) biosorption by SB and TSB. The Langmuir parameters “qm” (mg/g, the maximum biosorption capacity) and “b” (L/mg) alongside RMSE values are organized in Table 3.Table 3
Equilibrium parameters for Cu(II) and Cd(II) biosorption.
Langmuir isotherm parameters
Adsorbents
Metal
RMSE
b (L/mg)
q
m (mg/g)
S
L (m2/g)
R
L
SB
Cu(II)
0.028
0.111
4.149
2.19
0.311–0.083
Cd(II)
0.038
0.028
8
2.38
0.645–0.267
TSB
Cu(II)
0.162
0.095
15.151
7.98
0.344–0.046
Cd(II)
0.279
0.063
17.241
5.13
0.443–0.067
Freundlich isotherm parameters
Adsorbents
Metal
RMSE
K
F
n
SB
Cu(II)
0.071
0.6531
2.0661
Cd(II)
0.034
0.2805
1.2919
TSB
Cu(II)
0.517
2.4717
2.4752
Cd(II)
0.634
1.1967
1.8149
Temkin isotherm parameters
Adsorbents
Metal
RMSE
B
T (kJ/mol)
K
T (L/g)
SB
Cu(II)
0.034
1.058
0.7733
Cd(II)
0.054
1.460
0.3604
TSB
Cu(II)
0.261
2.860
1.3551
Cd(II)
0.422
3.711
0.3758
Dubinin–Radushkevich isotherm parameter
Adsorbents
Metal
RMSE
E (kJ/mol)
q
m (mg/g)
SB
Cu(II)
0.138
0.469
2.932
Cd(II)
0.153
0.328
2.795
TSB
Cu(II)
0.599
0.572
10.859
Cd(II)
0.754
0.304
10.155The minimum estimations of RMSE were demonstrated that Cu(II) and Cd(II) biosorption component was best trailed by the Langmuir model. The calculated “qm” demonstrated that TSB offered more prominent binding capacity than SB for Cu(II) and Cd(II). For instance, 1 g TSB had the capacity to tie 15.151 mg of Cu(II) while 1 g of SB bound 4.149 mg of Cu(II). This is due to the presence of more functional groups that can chelate Cu(II) ions as indicated in the previous characterization study step. Specific surface area (m2/g) calculated from the Langmuir model is given in the following equation and in Table 3 [38]:(13)S=qmNAM,where “N” is 6.022 × 1023 and “A” is the metal ion cross-sectional zone and “M” is the molar mass. Separation factor “RL” is determined using Langmuir constant “b” value in the following equation:(14)RL=11+b⋅Ce.TheRL value indicates the favorability of the process: RL > 1 means unfavorable, RL = 1 signifies linear, RL = 0−1 entails favorable, and RL < 0 implies irreversible [39]. The values obtained were in between 0 and 1 as shown in Table 3, indicating the favorability of this system.Maximum metal ion removal capacity was compared with the literature in Table4. It indicated the suitability of SB and TSB is comparable with other reported adsorbents for Cu(II) and Cd(II) ions.Table 4
Comparison of maximum removal capacities with reported biosorbents.
Biosorbent
Metal ion
q
max
Reference
Orange peels (nitric acid modified)
Cu (II)
15.27
[40]
O. sativa
12.36
[41]
Olive solid waste
3.81
[9]
P. longifolia leaf powder
1.74
[42]
Thiourea-modifiedSorghum
15.15
Present study
T. aestivum (straw)
Cd (II)
14.56
[43]
Orange peels (nitric acid modified)
13.7
[40]
T. aestivum (straw)
11.56
[44]
Castor seed hull
6.98
[45]
Banana peels
5.71
[7]
A. hypogea shells
2.81
[46]
Thiourea-modifiedSorghum
17.24
Present studyFreundlich model explains multilayer adsorption of metal ions on the heterogeneous surface, mainly due to physiosorption mode [47]. Nonlinear type of Freundlich isotherm was utilized to investigate the equilibrium information for Cu(II) and Cd(II) biosorption. Table 3 contains the constant demonstrative of relative adsorption capacity (KF) and factor characteristic of adsorption intensity (n). Data showed the positivity of the process as the value of “n” is more than 1 [48]. Higher values of its RMSE with respect to Langmuir isotherm demonstrate moderately less wellness to equilibrium data than Langmuir isotherm.Temkin model helps to predict biosorption energy (BT) as shown in Table 3. High values of RMSE demonstrated the low fitness of the Temkin model for this system. Value of BT under 8 indicated that weak interaction occurred during physiosorption, and value more than 8 indicated that chemisorption occurred more during metal ion removal [49]. Here physiosorption mode is predominant during these isothermal studies [50].Dubinin–Radushkevich model (D-R) explains the nature of biosorption, i.e., physical or chemical and the mean free energy of this process. The values of D-R parameters are tabulated in Table3. The parameter β was used to calculate the mean free energy (E, kJ/mol) of the system (equation (11)). The magnitude of mean free energy (E) gives an idea about the physical and chemical nature of the adsorption process. Value less than 8.0 kJ/mol represents physiosorption, whereas value between 8 and 16 kJ/mol symbolizes ion exchange mechanism and more than 16 kJ/mol indicates chemisorption. Table 3 indicates that Cu(II) and Cd(II) removal by SB and TSB was predominantly by physiosorption mode. This corresponds to the prediction of other isothermal as well. Data also indicate that TSB was able to bound more metal ions as compared to SB depicting the beneficial effect of the purposed modification process:(15)E=12β.Nonlinear plot of the studied equilibrium models is shown here in Figures8 and 9. Comparison of RMSE values inferred that equilibrium data of Cu(II) and Cd(II) biosorption by SB and TSB can be best explained by the Langmuir equilibrium model.Figure 8
Nonlinear equilibrium plots for Cu(II) biosorption by (a) SB and (b) TSB.
(a)
(b)Figure 9
Nonlinear equilibrium plots for Cd(II) biosorption by (a) SB and (b) TSB.
(a)
(b)


## 3.1. Surface Analysis by SEM

Both biosorbent samples were analyzed by SEM for observing surface morphological changes, and the resulting images are compared in Figure1. It is indicating that the surface morphology of both samples is rough and highly porous, which facilitates in physiosorptive removal of metal ions by binding with biosorbents. It is also worth mentioning that thiourea treatment enhanced porosity and roughness of the biosorbent surface, which indicated that modification of material boosted the binding capacity of TSB [24].


## 3.2. Elemental Analysis

It is carried out by CHNS analyzer for finding the percentage of C, H, N, and S and also helps to investigate the quantity of incorporated elements by chemical modification. As evident from Table1, nitrogen and sulfur significantly increased in TSB as compared to SB. These results confirmed the fusion of thiourea into Sorghum bicolor plant waste powder. It means more binding sites were available for chelating metal ions from solution, which enhanced its chemisorptive capacity.


## 3.3. Functional Group Analysis by FT-IR

Both samples were analyzed by FT-IR. The resulting spectrum of SB is shown in Figure2(a). It indicated the presence of various functional groups, such as hydroxyl group indicated by a peak at 3338.78 cm−1, alkyl group by a peak at 2918.30 cm−1, and carbonyl group by a peak at 1637.56 cm−1. Carboxylate ion peaks were observed at 1514.12 cm−1, 1421.54 cm−1, 1246.02 cm−1, and 1157.29 cm−1 [25]. It means diversity of acidic functional groups was existing in SB that can chelate cationic impurities from water, whereas Figure 2(b) presents functional group changes occurred in TSB. It had no peak related to hydroxyl group, but carboxylate ion peaks were there at 1516.05 cm−1, 1460.11 cm−1, and 1417.68 cm−1. Secondary amines’ presence was confirmed by peaks at 3612.67 cm−1 and 1649.17 cm−1. Isothiocyanate group (-N=C=S) peaks at 2380.16 cm−1, 2305.79 cm−1, and 1024.20 cm−1 confirms its existence [26]. So, functional groups increased in TSB that helps in chelation.


## 3.4. Boehm’s Titration Surface Analysis

The number of acidic and basic functional groups was compared by Boehm’s titrations in SB and TSB [24] and is presented in Table 1. Acidic functional group concentration was higher in SB, whereas in TSB both acidic and basic functional groups are prominent. As SB had more carboxylic acid groups, they were converted into amide groups in TSB that can be elucidated from FT-IR spectrum (Figure 2(b)), which enhanced its basic functionalities.


## 3.5. Point of Zero Charge

When solutions containing metal ions have greater pH than point of zero charge, it means biosorbent has more negative functionalities {Dupont, 2003 #88} and vice versa is true for biosorbents having more cationic functional groups that can remove anionic impurities better, like chromate and arsenate ions {Wang, 2008 #89}. Some literature also indicated that lower pH helps in desorption of metal ions and regeneration of adsorbent [27, 28]. pHpzc results are compared in Figure 3 and found to be 5.9 and 6.7 for SB and TSB, respectively.Figure 3
pHpzc determination of SB and TSB.


## 3.6. pH Profile

Solution pH plays a vital role during biosorption. In acidic conditions, more ionization of functional groups occurred that helps in better biosorption. But in highly basic conditions, both Cd(II) and Cu(II) precipitate out from solution as hydroxide. So, this factor was investigated using both biosorbents and the results are presented in Figure4. Strongly acidic conditions hinder biosorptive removal of these metal ions because it results in protonation of active binding sites that can chelate Cu(II) and Cd(II) possibly. More better results were observed in the pH range of 5 to 6. Chelating capacity of TSB is also more than that of SB in this range indicated by higher “q” values.Figure 4
pH effect on the removal of Cu(II) and Cd(II).
(a)
(b)


## 3.7. Reaction Kinetics

It helps in determining the mechanism of metal ion removal during biosorption by different kinetic models [29]. Effect of contact time between SB/TSB and metal ion solution was monitored and is shown in Figure 5 for various concentrations. It is obvious from this figure that metal ion removal by SB and TSB was fast on the initial stage, which becomes constant after some time. It means the rate of biosorption on SB and TSB becomes equal to desorption from chelating sites due to week interactions [30].Figure 5
Time interval effect on biosorption of (a) Cu(II) and (b) Cd(II).
(a)
(b)Various kinetic models were employed on these data. Following equations (3) and (4) speak to the linear types of pseudo-first- and pseudo-second-order models:(3)lnqe−qt=lnqe−k1⋅t,(4)tqt=1k2qe2+tqe.Results are given in Table2. Pseudo-first-order model depended on the hypothesis that biosorption is straightforwardly corresponding to the quantity of free binding sites. Table 2 indicates that sorption studies for Cd(II) did not follow pseudo-first-order kinetics, while for Cu (II) ion removal by TSB, biosorption followed this model as clear from R2 value. But values of qe (experimental and calculated) did not match from this trend. It means this model is not applicable for these systems.Table 2
Kinetic parameters for Cu(II) and Cd(II) biosorption.
Biosorbent
Metal ions
Pseudo-first-order kinetics
q
e (mg/g) (experimental)
Pseudo-second-order kinetics
k
1 (min−1)
R
2
q
e (mg/g)
k
2 (min−1)
R
2
q
e (mg/g)
SB
Cu(II)
0.147
0.943
1.248
2.17
0.253
0.998
2.277
Cd(II)
0.154
0.962
1.557
2.12
0.191
0.998
2.252
TSB
Cu(II)
0.187
0.999
0.756
5.02
0.792
0.999
5.076
Cd(II)
0.271
0.830
4.297
5.40
0.051
0.999
5.19According to the pseudo-second-order model, biosorption rate is related to the square of binding site availability and metal ion amount. Kinetic data for Cu(II) and Cd(II) were used to investigate this model and are presented graphically in Figure6. All values of rate constant, correlation constant, and qe(cal) and qe(exp) matched with this trend. It had indicated the validity of this model for these systems [31]. The best fit of pseudo-second-order model clarifies that one divalent cation joins to two monovalent binding sites [32].Figure 6
Linear presentation of pseudo-second-order graph: (a) Cu(II) and (b) Cd(II).
(a)
(b)Boyd et al. [33] expression was utilized to decide the rate deciding step in biosorption. There are two modes of biosorption: (1) limit layer film dispersion and (2) intramolecule diffusion.Boyd’s kinetic expression is given in the following equation:(5)F=1−63.14162exp−Bbt.“F” is at time t given as follows:(6)F=qtqe.By comparing both equations, they were simplified as follows:(7)Bb=−0.4977−ln1−qtqe.The importance of the Boyd plot is if straight line passing from the origin is observed, then intramolecular diffusion is the predominant rate-determining step and vice versa is true in other cases [34, 35]. So results are given in Figure 7.Figure 7
Boyd plots for the biosorption of (a) Cu(II) and (b) Cd(II).
(a)
(b)As from Figure7, neither of the plots was direct or passed from the origin. So both modes of biosorption (limit layer film dispersion and intramolecular diffusion) were adopted in this study.


## 3.8. Isothermal Studies regarding Initial Metal Ion Concentration

Three diverse adsorption isotherms including Langmuir, Freundlich, and Temkin had been utilized in nonlinear design and had been examined. Volesky revealed that there is no need of increasingly complex adsorption isotherms if basic (Langmuir and Freundlich) isotherms are pursued and give the significant data [36]. Equations (8)–(11) speak to the nonlinear types of Langmuir, Freundlich, Temkin, and Dubinin–Radushkevich (DR) equilibrium models, separately. The expressed models were processed by ascertaining the relative mean square error (RMSE) utilizing (8):(8)qe=b⋅qm⋅Ce1+b⋅Ce,(9)qe=KF⋅Ce1/n,(10)qe=BT⋅lnKT⋅Ce,(11)qe=qm⋅exp−βε2,(12)RMSE=∑qecal−qeexp2N.Langmuir model presumes that binding sites were homogeneously distributed in monolayer fashion over the sorbent surface that will chemisorb metal ions [37]. Langmuir model was utilized on to the equilibrium data for Cu(II) and Cd(II) biosorption by SB and TSB. The Langmuir parameters “qm” (mg/g, the maximum biosorption capacity) and “b” (L/mg) alongside RMSE values are organized in Table 3.Table 3
Equilibrium parameters for Cu(II) and Cd(II) biosorption.
Langmuir isotherm parameters
Adsorbents
Metal
RMSE
b (L/mg)
q
m (mg/g)
S
L (m2/g)
R
L
SB
Cu(II)
0.028
0.111
4.149
2.19
0.311–0.083
Cd(II)
0.038
0.028
8
2.38
0.645–0.267
TSB
Cu(II)
0.162
0.095
15.151
7.98
0.344–0.046
Cd(II)
0.279
0.063
17.241
5.13
0.443–0.067
Freundlich isotherm parameters
Adsorbents
Metal
RMSE
K
F
n
SB
Cu(II)
0.071
0.6531
2.0661
Cd(II)
0.034
0.2805
1.2919
TSB
Cu(II)
0.517
2.4717
2.4752
Cd(II)
0.634
1.1967
1.8149
Temkin isotherm parameters
Adsorbents
Metal
RMSE
B
T (kJ/mol)
K
T (L/g)
SB
Cu(II)
0.034
1.058
0.7733
Cd(II)
0.054
1.460
0.3604
TSB
Cu(II)
0.261
2.860
1.3551
Cd(II)
0.422
3.711
0.3758
Dubinin–Radushkevich isotherm parameter
Adsorbents
Metal
RMSE
E (kJ/mol)
q
m (mg/g)
SB
Cu(II)
0.138
0.469
2.932
Cd(II)
0.153
0.328
2.795
TSB
Cu(II)
0.599
0.572
10.859
Cd(II)
0.754
0.304
10.155The minimum estimations of RMSE were demonstrated that Cu(II) and Cd(II) biosorption component was best trailed by the Langmuir model. The calculated “qm” demonstrated that TSB offered more prominent binding capacity than SB for Cu(II) and Cd(II). For instance, 1 g TSB had the capacity to tie 15.151 mg of Cu(II) while 1 g of SB bound 4.149 mg of Cu(II). This is due to the presence of more functional groups that can chelate Cu(II) ions as indicated in the previous characterization study step. Specific surface area (m2/g) calculated from the Langmuir model is given in the following equation and in Table 3 [38]:(13)S=qmNAM,where “N” is 6.022 × 1023 and “A” is the metal ion cross-sectional zone and “M” is the molar mass. Separation factor “RL” is determined using Langmuir constant “b” value in the following equation:(14)RL=11+b⋅Ce.TheRL value indicates the favorability of the process: RL > 1 means unfavorable, RL = 1 signifies linear, RL = 0−1 entails favorable, and RL < 0 implies irreversible [39]. The values obtained were in between 0 and 1 as shown in Table 3, indicating the favorability of this system.Maximum metal ion removal capacity was compared with the literature in Table4. It indicated the suitability of SB and TSB is comparable with other reported adsorbents for Cu(II) and Cd(II) ions.Table 4
Comparison of maximum removal capacities with reported biosorbents.
Biosorbent
Metal ion
q
max
Reference
Orange peels (nitric acid modified)
Cu (II)
15.27
[40]
O. sativa
12.36
[41]
Olive solid waste
3.81
[9]
P. longifolia leaf powder
1.74
[42]
Thiourea-modifiedSorghum
15.15
Present study
T. aestivum (straw)
Cd (II)
14.56
[43]
Orange peels (nitric acid modified)
13.7
[40]
T. aestivum (straw)
11.56
[44]
Castor seed hull
6.98
[45]
Banana peels
5.71
[7]
A. hypogea shells
2.81
[46]
Thiourea-modifiedSorghum
17.24
Present studyFreundlich model explains multilayer adsorption of metal ions on the heterogeneous surface, mainly due to physiosorption mode [47]. Nonlinear type of Freundlich isotherm was utilized to investigate the equilibrium information for Cu(II) and Cd(II) biosorption. Table 3 contains the constant demonstrative of relative adsorption capacity (KF) and factor characteristic of adsorption intensity (n). Data showed the positivity of the process as the value of “n” is more than 1 [48]. Higher values of its RMSE with respect to Langmuir isotherm demonstrate moderately less wellness to equilibrium data than Langmuir isotherm.Temkin model helps to predict biosorption energy (BT) as shown in Table 3. High values of RMSE demonstrated the low fitness of the Temkin model for this system. Value of BT under 8 indicated that weak interaction occurred during physiosorption, and value more than 8 indicated that chemisorption occurred more during metal ion removal [49]. Here physiosorption mode is predominant during these isothermal studies [50].Dubinin–Radushkevich model (D-R) explains the nature of biosorption, i.e., physical or chemical and the mean free energy of this process. The values of D-R parameters are tabulated in Table3. The parameter β was used to calculate the mean free energy (E, kJ/mol) of the system (equation (11)). The magnitude of mean free energy (E) gives an idea about the physical and chemical nature of the adsorption process. Value less than 8.0 kJ/mol represents physiosorption, whereas value between 8 and 16 kJ/mol symbolizes ion exchange mechanism and more than 16 kJ/mol indicates chemisorption. Table 3 indicates that Cu(II) and Cd(II) removal by SB and TSB was predominantly by physiosorption mode. This corresponds to the prediction of other isothermal as well. Data also indicate that TSB was able to bound more metal ions as compared to SB depicting the beneficial effect of the purposed modification process:(15)E=12β.Nonlinear plot of the studied equilibrium models is shown here in Figures8 and 9. Comparison of RMSE values inferred that equilibrium data of Cu(II) and Cd(II) biosorption by SB and TSB can be best explained by the Langmuir equilibrium model.Figure 8
Nonlinear equilibrium plots for Cu(II) biosorption by (a) SB and (b) TSB.
(a)
(b)Figure 9
Nonlinear equilibrium plots for Cd(II) biosorption by (a) SB and (b) TSB.
(a)
(b)


## 4. Conclusions

So, from these results, it is evident that thiourea treatment ofSorghum bicolor L. enhanced its metal ion chelating ability and in turn biosorption capacity. Microwave fusion methodology used here is solvent-free and environmentally benign. It is a cleaner, cheaper, and less time-consuming way to prepare a better adsorbent for cationic impurities. Kinetic and equilibrium modeling represents that the biosorption process followed the pseudo-second-order model and Langmuir model. Boyd plots showed that both film diffusion of metal ions on SB and TSB and intraparticle diffusion were involved during biosorption. Most effective adsorption occurred at pH 5-6 with TSB and Cu(II) and Cd(II) uptake capacity was 15.151 mg/g and 17.241 mg/g, correspondingly, relative to SB (4.149 mg/g and 8 mg/g, in that order). Hence, it can be concluded that modification of Sorghum bicolor with thiourea using microwave solid fusion method produces an effective and eco-friendly biosorbent for Cu(II) and Cd(II) removal.



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