# Removal of Chromium from Synthetic Wastewater Using Modified Maghemite Nanoparticles
## 3 Results  
### Characterization of NPs and MNPs  
FTIR analysis determined the specific functionality of the NPs (Figure 1a) and MNPs (Figure 1b). The most abundant functional group observed in our samples was the hydroxyl group, with broad bands at 3300 and 3332 cm-1 (OH stretching mode), respectively, and bands at 1625 and 1587 cm-1 (OH bending modes), respectively. The Fe-O stretching bands appeared at 624.94 and 543.93 cm-1 for both the samples. In the case of MNPs, as shown in Figure 1b, the sulphate ion band appeared at 437.84 cm-1, confirming that the maghemite had been successfully modified [30]. The results of XRD analysis of NPs and MNPs given in Figure 2a,b reveals that all diffraction peaks are consistent with the standard structure of maghemite. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Run**} & \multicolumn{3}{c}{**Actual Level of Factors**} & \multicolumn{3}{c}{**Coded Level of Factors**} & \multicolumn{3}{c}{**Chromium RE (\%)**} \\ \cline{2-7}  & \(X_{\mathbf{I}}\) & \(X_{\mathbf{2}}\) **(g/l)** & \(X_{\mathbf{3}}\) **(mg/L)** & \(X_{\mathbf{I}}\) & \(X_{\mathbf{2}}\) & \(X_{\mathbf{3}}\) & **Experimental** & **Predicted** \\ \hline  
\hline \hline \end{tabular}
\end{table} 
Table 2: Experimental design matrix and results for adsorption of chromium. the coefficient of squared effects of initial chromium concentration (\(X3\)) was insignificant (\(P<0.4\)) on the chromium RE (Y), and (v) the coefficients due to the interaction between pH \(\times\) adsorbent dose and adsorbent dose \(\times\) initial chromium concentration had positive effects (\(P<0.005\)) on chromium removal. As evident from the calculated \(F\) value (144.94) and the low probability value (\(P=<0.001\)), the ANOVA of the regression model demonstrated that it was highly significant (Table 3). Values of \(P<0.05\) indicated that the model terms were highly significant at the 95% confidence interval. In addition, the lack of fit of the model was insignificant (\(P=0.123\)), indicating its accuracy in describing the experimental data. The linear model terms were more significant (\(F=372.05\) and \(P=<0.001\)) than the square (\(F=46.76\) and \(P=<0.001\)) and interaction (\(F=16.02\) and P = \(<0.001\)) model terms. This indicated that the linear model terms, i.e., the main effects of the process variables, significantly affected the % chromium RE. The response surface and contour plots are shown in Figures 3 and 4, respectively. While the response surface plots (Figure 3a) show a clear peak, the plots in Figure 3b,c did not show clear peaks, which suggests that the optimum conditions of the variables were outside the chosen experimental range. For model design, one variable is held at its intermediate level to check the interaction effect of the other two variables. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Model Term Coefficient** & \(t\)**-Value** & \(P\)**-Value** \\ \hline Constant & 132.014 & 0 \\ \(X_{1}\) & \(-\)13.624 & 0 \\ \(X_{2}\) & 27.616 & 0 \\ \(X_{3}\) & \(-\)12.957 & 0 \\ \(X_{1}\)\({}^{2}\) & 3.061 & 0.012 \\ \(X_{2}\)\({}^{2}\) & \(-\)10.939 & 0 \\ \(X_{3}\)\({}^{2}\) & 1.075 & 0.308 \\ \(X_{1}\)\(\times\)\(X_{2}\) & 2.781 & 0.019 \\ \(X_{1}\)\(\times\)\(X_{3}\) & \(-\)3.188 & 0.01 \\ \(X_{2}\)\(\times\)\(X_{3}\) & 5.491 & 0 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Estimated corresponding t- and P-values of the model term coefficients.