Scanning electron microscopy (SEM)
At 180 °C, nucleation speed is faster than growth speed of nanostructures, indicating that the products were composed of numerous separate, small, and uneven particles. The bond length of the carbon atoms in each layer's honeycomb lattice is 0.142 nm, while the spacing between planes is 0.335 nm. The carbogenic material exhibits a high voltage value of N-CDs of 10.0k at 5.00 µm. It also demonstrates this value at 10.0 µm (4.00 k), 30.0 µm (1.50 k), and 500 µm (8.4 k).
Transmission electron microscopy (TEM)
CDs were monodispersing, rang in size from approximately 8 to 15 nm, according to a transmission electron microscope (TEM) image. The TEM image of N-CDs, exhibited fluorophore like morphology. The size of the CDs is approximately smaller; it is most likely that the CDs are difficult to see on the surface material. Carbon dots are simple and dispersed like dots as shown in figure 4.
x-ray diffraction (XRD)
Crystallinity of CDs was investigated by X-ray diffraction (XRD). The average particle size of the crystallite in XRD is 60.12nm. The XRD pattern of CDs revealed a large diffraction peak located at 20.54°. This peak corresponds to the (100) lattice spacing of the carbon-based materials that has, layered, planar structure made up of carbon atoms arranged in a hexagonal way are present in the structure of prepared CDs. Additionally, the XRD pattern is likely responsible for the chaotic structure and amorphous nature of CDs. The average particle size was evaluated by using Debye sheerer formula;
D=kλ/βcosθ eq. (2)
Fourier transformed infrared spectroscopy (FTIR):
Nitrogen metal was successfully doped into the carbon core of carbon dots, as shown by the Fourier-transform infrared (FT-IR) spectroscopy results. The presence of hydroxyl (–OH) functionality is indicated by a broad peak at 3274.5 cm⁻¹. C≡C and C=C stretching vibrations are represented by the peaks at 2215.11 cm⁻¹ and 1623.11 cm⁻¹, respectively. Notably, the peak at 2161.11 cm⁻¹ confirms the existence of C≡O stretching vibrations, further supporting nitrogen metal doping. These observations suggest that nitrogen doped carbon dots have abundant carboxyl and hydroxyl functionalities, potentially allowing for interaction with a wide range of analytes.
Statistical design analysis:
For the optimization of different parameters including dye concentration, time irradiation, pH, and oxidant concentration a central composite design by using response surface methodology (RSM) was applied to check the relationship between variables and percentage degradation of Congo red dye. Design expert 13 pro software was used for the evaluation of these optimized parameters. RSM facilitates the evaluation of various interaction parameters at their optimized degradation efficiency in each thirty runs. The validation of results evaluated by the significance of the model statistically probe value "Prob > F" which was less than 0.005. The model showed excellent correlation between predicted and observed value (R2= 0.4529 adjusted R2= 0.3653). The difference between these R2 values is less the 0.2 so the model was reliable for further analysis. By comparing the factor coefficients, the coded equation can be used to determine the relative impact of the components. The final equation in terms of coded each factors in which highest level is coded as positive and lower level coded as negative is given below:
The significance of the model is indicated by its F-value of 5.17. This kind of high F-value has a 1.10% chance of being caused by noise. P-values of less than 0.0500 indicate the significance of the model terms. When the value surpasses 0.1000, the model terms lose their significance. Model reduction can aid your model if it has a lot of unnecessary terms (beyond those needed to preserve hierarchy).
The 0.8912 When compared to pure error, the Lack of Fit F-value suggests that the Lack of Fit is not statistically significant. The probability that a substantial Lack of Fit F-value is due to noise is 13.51%. The model exhibits a "Good Fit" with a non-significant lack of fit.
The statistical parameters that were acquired point to a solid model for forecasting dye degradation in the system under study. Finally, a viable model with good predictive power and sufficient precision is suggested by the examination of these scientific concepts and statistical metrics. This makes it possible to use it to investigate and enhance the dye degradation system's design space.
Table 2: Experimental design which shows level of variables and percentage degradation
|
Runs
|
pH
|
Dye concentration
(ppm)
|
Oxidant concentration
(Mm)
|
Irradiation time
(hrs)
|
Percentage Degradation
(%)
|
1
|
9
|
50
|
10
|
5
|
89.86
|
2
|
6
|
5
|
30
|
3
|
75.75
|
3
|
3
|
10
|
10
|
5
|
72.78
|
4
|
9
|
10
|
10
|
1
|
73.33
|
5
|
6
|
30
|
30
|
3
|
78.76
|
6
|
3
|
50
|
50
|
1
|
78.35
|
7
|
9
|
10
|
10
|
5
|
69.01
|
8
|
7
|
30
|
30
|
3
|
70.93
|
9
|
12
|
30
|
30
|
3
|
77.79
|
10
|
6
|
30
|
30
|
3
|
76.74
|
11
|
3
|
10
|
50
|
5
|
89.17
|
12
|
6
|
30
|
30
|
3
|
66.67
|
13
|
3
|
10
|
10
|
1
|
65.55
|
14
|
9
|
50
|
10
|
1
|
81.22
|
15
|
6
|
30
|
30
|
3
|
66.56
|
16
|
9
|
10
|
50
|
1
|
62.76
|
17
|
3
|
50
|
10
|
5
|
67.11
|
18
|
3
|
50
|
10
|
1
|
62.11
|
19
|
9
|
50
|
50
|
5
|
85.05
|
20
|
6
|
30
|
30
|
7
|
70.93
|
21
|
6
|
30
|
70
|
3
|
89.57
|
22
|
9
|
10
|
50
|
5
|
89.17
|
23
|
6
|
30
|
30
|
3
|
81.39
|
24
|
6
|
30
|
30
|
3
|
77.61
|
25
|
3
|
50
|
50
|
5
|
70.27
|
26
|
6
|
30
|
30
|
3
|
78.77
|
27
|
9
|
50
|
50
|
1
|
89.17
|
28
|
6
|
30
|
10
|
3
|
77.77
|
29
|
6
|
70
|
30
|
3
|
77.09
|
30
|
3
|
10
|
50
|
1
|
75.55
|
Table 3: ANOVA for Linear model (RSM)
source
|
SS
|
df
|
Mean square
|
F-value
|
p-value
|
|
Model
|
1292.77
|
10
|
129.28
|
3.23
|
0.0134
|
Significant
|
A-pH
|
410.52
|
1
|
410.52
|
10.27
|
0.0047
|
|
B-dye conc.
|
1.33
|
1
|
1.33
|
0.0333
|
0.8572
|
|
C-oxidant conc.
|
161.89
|
1
|
161.89
|
4.05
|
0.0586
|
|
D-time irradiation
|
139.25
|
1
|
139.25
|
3.48
|
0.0775
|
|
AB
|
405.82
|
1
|
405.82
|
10.15
|
0.0049
|
|
AC
|
51.55
|
1
|
51.55
|
1.29
|
0.2703
|
|
AD
|
1.27
|
1
|
1.27
|
0.0317
|
0.8607
|
|
BC
|
19.76
|
1
|
19.76
|
0.4942
|
0.4906
|
|
BD
|
86.30
|
1
|
86.30
|
2.16
|
0.1581
|
|
CD
|
15.25
|
1
|
15.25
|
0.3814
|
0.5442
|
|
Residual
|
759.65
|
19
|
39.98
|
|
|
|
Lack of Fit
|
547.02
|
14
|
39.07
|
0.9188
|
0.5911
|
not significant
|
Pure Error
|
212.63
|
5
|
42.53
|
|
|
|
Cor Total
|
2052.42
|
29
|
|
|
|
|
Table 4: Coefficient of variance (C.V.%) and R-squared confirmation values
Std. Dev.
|
6.32
|
|
R²
|
0.6299
|
Mean
|
76.02
|
|
Adjusted R²
|
0.4351
|
C.V. %
|
8.32
|
|
Predicted R²
|
-0.0831
|
|
|
|
Adeq Precision
|
6.5709
|
Interactions between different parameters evaluated by RSM
- Interaction between pH and oxidant concentration
Hydrogen peroxide (H2O₂) addition is crucial to the photocatalytic breakdown process [60]. It accomplishes two things; Firstly, it increases the production of hydroxyl radicals (OH˙), strong oxidizing agents that cause color deterioration. Second, on the photocatalyst surface, H₂O₂ aids in reducing the recombination of electron-hole pairs (e⁻/h⁺). This recombination process lowers the photocatalyst’s overall efficiency. In figure 7 (a), interaction among oxidant concentration and pH are given in which maximum degradation occurred at 81.39% at pH (6) and oxidant concentration (30mM).
- Interaction between dye concentration and pH.
The graphical interface between ph and dye concentration and in figure 7 (b) which depicts the optimum ranges of these two parameters at which Congo red dye degraded maximum. The Congo red dye gave optimum degradation (76.74%) at pH 6 and concentration of dye at 30ppm, beyond this level, there was no further degradation observed [61, 62]. The rate of dye degradation is highly sensitive to pH; dye degraded more rapidly when the pH value went from acidic to basic; on the other hand, if the pH of the wastewater sample was raised, decreased rate of dye degradation because the surface charge of the dye was negative at acidic pH and positive at basic ph. Maximum degradation of congo red dye was achieved in acidic media.
3. Interaction between dye concentration and oxidant concentration
The amount of dye concentration also impacts degradation [63-65]. As illustrated in Figure 7 (c), increasing dye concentration from 10 ppm to 30 ppm increases degradation since there are more dye molecules accessible for the catalyst to attack. However, adding significantly more dye (beyond 30 ppm) reduces efficiency. This is because extra dye molecules can clump together, inhibiting the catalyst's active sites and preventing light from reaching them, which lowers the formation of OH˙ radicals. So maximum degradation (78.79) was achieved at 30ppm dye concentration and 30Mm of oxidant concentration [66-68].
4. Interaction between time irradiation and pH
The relationship between time and and pH gave maximum degradation (78.76) at pH (6) and irradiation time (3hrs) by keeping other two factors constant as shown in figure 7 (b). The most important factor influencing the degradation rate, according to an analysis of the 3D surface and contour diagrams (fig. 7 (d)), was the irradiation period [69, 70]. The findings showed that when the irradiation time was increased from three to five hours, the deterioration efficiency gradually increased. An ideal irradiation time of three hours was suggested at 30ppm dye concentration, as further extending the irradiation time beyond five hours did not result in any further improvements in the degradation rate.
5. Interaction between time irradiation and oxidant concentration
Figure 7 (e) presents a graphical depiction of the change in oxidant concentration over time. The level of H₂O₂ concentration was also determined to be a factor that affects the rate at which degradation occurs. An increase in the concentration of H₂O₂ resulted in a sharp rate of degradation, possibly due to the self-dissociation or reduction of H₂O₂ facilitated by light at the conduction band of the photocatalyst. Nevertheless, beyond the ideal concentration of 30 mM H₂O₂ led to a negative impact on the effectiveness of degradation, irrespective of the duration of irradiation. This decrease can be explained by the consumption of reactive hydroxyl radicals and valence band gaps by an excessive amount of H₂O₂. In addition, the process of radical recombination, which is a competitive reaction, may potentially contribute to impeding the degradation process when larger quantities of H₂O₂ are present.
6. Interaction between time irradiation and dye concentration
The 3hrs of irradiation time with 30ppm concentration of dye investigated by keeping oxidant concentration and pH constant as given in fig 7 (f). The percentage degradation enhances with consumption of time. With the passage of time OH ions gives maximum number of active sites. However, the active sites on the photocatalyst surface were saturated, additional increases led to a drop in the efficiency of degradation. The catalyst absorbs light energy when exposed to light, which causes it to produce reactive oxygen species (ROS), especially hydroxyl radicals (OH˞), on its surface. The dye molecules in the solution are attacked and degraded by these extremely reactive ROS species.
Measurement of untreated and treated textile wastewater treatment:
The measurement carried out by UV spectroscopy in which the sample shows certain absorbance upon which a curve is formed which depicts degradation percentage of the sample. The peak of untreated sample shows that there is no degradation occur at this point. The sample remained unchanged. After treatment of the sample shows a lower curve then untreated sample which means that degradation occurred completely. The sample after treatment gives maximum results of percentage degradation. The maximum degradation occurred at maximum absorbance when we take UV spectra of the sample.
Measurement of water quality parameters (COD, BOD, TOC):
Digestion solution of 1.5mL, 3.5mL of catalytic solution and 2.5mL of sample solution was mixed and then placed the sample into the COD meter for 2hrs at 150 ͦC. Both before treatment and after treatment samples were placed in COD meter. The absorbance was taken from UV spectra of the samples. The mixture of 1.6mL of concentrated sulphuric acid and 2N of 1mL potassium dichromate solution mixture was added into 4mL of sample solution placed into TOC meter for 1.5hrs at 120 ͦC. the absorbance before and after treatment of the samples was evaluated by UV spectra. The biochemical oxygen demand was measured using calibrated digital BOD meter. The special BOD bottles washed with deionized water and 56mL deionized water added into first bottle as blank. Time out of the five bottles filled with 56mL of sample solution and added drops of standard KOH solution before capping them. Then they were placed in their specific position and placed for five days. UV spectra was taken for both before and after treatment of the samples,The decreased in BOD (78%), COD (94%), and TOC (89%) value was observed.
Measurement of photocatalytic activity with time
The sample was placed under sunlight for three hours and investigated its photocatalytic activity with varying time range by using UV spectrometry. The kinetic activity of sample shows the following curve with absorbance on y-axis and time on x-axis.
Measurement of reusability
The reusability of substrate (pumice) was checked. In first seven cycles, the efficiency of substrate remained constant and then decreases gradually up to fourteen cycle. This shows that pumice is efficiently work as substrate for the degradation of wastewater. The reusability factor also depends on sunlight i.e if light intensity poor then it will minimize the results vice versa.