## 3 Results and Discussion
### Multiple Factors' Interaction in EFLP Suspension
#### 3.3.1 Multiple Factors' Interaction in EFLP Suspension at 3-h Reaction  
The test data (Table 2) were analyzed by standard analysis of variance (ANOVA) (Table 3) and the Box-Behnken design was fitted with the second-order polynomial equation (Equation (2)). \[\eta=19.50+23.60\text{A}+18.64\text{B}+17.12\text{C}-7.00\text{AB}-7.82\text{AC }+17.20\text{BC}+44.79\text{A}^{2}+2.42\text{B}^{2}+8.32\text{C}^{2} \tag{2}\]  
The statistical significance of Equation (2) was evaluated by the F-test for ANOVA (Table 3). There was only a 0.01% chance that the model's F-value could occur due to noise. The model's F-value of 70.37 and \(p\)-value (<0.0001) indicated that the model was significant. Hence, Equation (2) could be used in the present study. The \(p\)-values for the three factors were all less than 0.0001, indicating that their influences were significant. The \(p\)-values for AB, AC and BC were 0.0426, 0.0258 and 0.0004, all less than 0.05, showing that their interaction was significant in the order of BC \(>\) AC \(>\) AB [59]. Furthermore, the adjusted R\({}^{2}\) value was approximately 0.975, whereas the predicted R\({}^{2}\) value was higher at around 0.989, which was very close to the experimental level, confirming a satisfactory adjustment of Equation (2) to the test data. The term \"Lack of Fit (LOF)\" refers to the contrast between estimated and obtained values and the repetition of actual value errors [60]. The LOF of Equation (2) stayed at 0.19, which revealed that Equation (2) was well fitted to the experimental findings. \begin{table}
\begin{tabular}{c c c c c c} \hline
**Run** & **B** & **C** & **A** & **\(\eta\) (at 3 h)** & **\(\eta\) (at 36 h)** \\ \hline
1 & NaNO\({}_{3}\) & 10 & 1.9 & 54.77 & 94.34 \\
2 & NaNO\({}_{3}\) & 5 & 3.4 & 65.71 & 94.82 \\
3 & NaNO\({}_{3}\) & 5 & 1.1 & 28.39 & 84.02 \\
4 & NaF & 1 & 3.4 & 15.27 & 80.13 \\
5 & Cu(NO\({}_{3}\))\({}_{2}\) & 10 & 1.9 & 94.27 & 99.18 \\
6 & Cu(NO\({}_{3}\))\({}_{2}\) & 5 & 3.4 & 97.63 & 99.14 \\
7 & NaNO\({}_{3}\) & 1 & 1.9 & 16.09 & 79.15 \\
8 & Cu(NO\({}_{3}\))\({}_{2}\) & 1 & 1.9 & 83.97 & 98.69 \\
9 & NaF & 10 & 3.4 & 87.65 & 97.16 \\
10 & NaF & 10 & 1.1 & 12.44 & 78.98 \\
11 & Cu(NO\({}_{3}\))\({}_{2}\) & 5 & 1.1 & 90.54 & 99.37 \\
12 & NaF & 5 & 1.9 & 9.04 & 85.96 \\
13 & NaF & 5 & 1.9 & 9.52 & 89.03 \\
14 & NaNO\({}_{3}\) & 5 & 1.9 & 14.25 & 90.98 \\
15 & NaNO\({}_{3}\) & 5 & 1.9 & 17.26 & 89.25 \\
16 & NaNO\({}_{3}\) & 5 & 1.9 & 17.96 & 94.02 \\
17 & NaF & 1 & 1.1 & 5.61 & 78.92 \\ \hline \end{tabular}
\end{table} 
Table 2: Box–[PERSON] designed tests and test data at 3-h and 36-h reactions. \begin{table}
\begin{tabular}{c c c c c c} \hline
**Source of Variation** & **Sum of Squares** & **Degrees of Freedom** & **Mean Square** & **F-Value** & **\(p\)-Value** & **Significant/** \\  & & & & & **Non-Significant** \\ \hline Model & 20,397.73 & 9 & 2266.41 & 70.37 & \textless{}0.0001 & significant \\ A & 4240.13 & 1 & 4240.13 & 131.65 & \textless{}0.0001 & significant \\ B & 2662.29 & 1 & 2662.29 & 82.66 & \textless{}0.0001 & significant \\ C & 2329.83 & 1 & 2329.83 & 72.34 & \textless{}0.0001 &Also, variation in the data was measured by the coefficient of variation (CV), which was 13.39%. \"Adequate Precision\" measures the signal-to-noise ratio. A ratio greater than 4 is desirable [39]. In the present study, a ratio of 20.863 was obtained for the 3-h reaction, indicating an adequate signal. All this indicated that Equation (2) had high reproducibility. An assessment of Equation (2)'s desirability was performed through an investigation of residuals. The normal distribution plots revealed whether the residual values were close to a straight line. Figure 4 represents a random scatter plot of the actual and predicted n values, and the actual and predicted points are almost equal. Thus, Equation (2) could be effectively used in the present study. It is worth noting that the negative or positive sign of each term showed antagonistic or synergistic effects of the term on the \(\eta\) value [46].