Development of the Regression Model Equation and Statistical Analysis
Table 2 showcases the results of the RSM studies obtained with Design Expert 13; the biomass was in the range of 5.03420 mg/L to 19.6730 mg/L. The COD removal efficiency was between 54.0890% and 98.0636%, and the range of power density generation was between 10.9574 mW/m
2 and 47.2064 mW/m
2. The experimental data were fitted to four types of models: cubic polynomial, two-factorial interaction, linear, and quadratic. The statistical findings were found to be significant based on the sequential model sums of squares, as the obtained probability value (“prob > F”) was less than 0.05 (
Table 3). The quadratic model was found to be the most suitable, as to the obtained
p values of biomass, COD removal efficiency, and power density were less than 0.05, indicating their significance.
As shown in
Table 3, the relationship between the three independent factors (biomass, COD removal efficiency, and power density generation) fit the model, as the
p-values of all three responses for the model were less than 0.05, indicating their significance. Furthermore, lack-of-fit tests for all responses resulted in
p-values of more than 0.05, indicating their insignificance.
The experimental data obtained in this study were also compared with the prediction data of the regression models.
Figure 1 shows that the predicted values are generally centered on a straight line relative to the experimental data. This implies that there are relatively few deviations between the experimental values and the predicted values, supporting the quadratic model suggested by the ANOVA test. The normal plot residuals shown in
Figure 2 also showcase the same pattern, in which the normal percentage probability points are centered near their respective straight lines. This indicates that the experimental data were normally distributed, consequently supporting the adequacy of the model [
15].
Monitoring of Biomass, COD Removal Efficiency, and Power Density Generation
The highest biomass concentration observed in this study was 19.6730 mg/L, with ML-MFC parameters of 35 °C, 75% (v/w) moisture content, an electrode distance of 3 cm, and an incubation period of seven days (168 h), as designed with Design Expert 13 software.
The predicted significant interaction between the model terms for biomass was visualized by the previously acquired ANOVA results (
Table 3) presented as response surface plots and contour plots.
Figure 3 displays the response surface plot and contour plot of the interaction between electrode distance and moisture content,
Figure 4 presents the interaction between electrode distance and temperature, and
Figure 5 displays the interaction of temperature with moisture content.
Despite the more visualized aspect and a bigger overview figure provided by the response surface plot, the contour plot is relatively easier to interpret and understand with respect to the optimized values of the independent variables, for which the same level of responding variable can be achieved.
A higher concentration biomass is observed in
Figure 3, wherein the moisture content level is approximately higher than 50%or, more precisely, higher than 60%, with an optimal electrode distance range of 3 cm. This is in line with the fact that a sufficient amount of moisture is required for the micro-organisms within the ML-MFC system to conduct hydrolysis reactions [
15]. Additional water molecules are required by the microbes to break down the complex organic components. This breaking down of larger molecules into smaller molecules could ultimately aid in voltage generation in an ML-MFC system. This is due to the micro-organisms more easily consuming smaller compounds as opposed to the original larger compounds [
15]. Due to the ease of digestion of the microbes, their metabolic reactions are further optimized. Consequently, the growth of biomass is now favorable, resulting in a higher biomass concentration obtained with increased moisture content. This phenomenon is also shown
Figure 5; a higher biomass concentration was obtained at moisture content of more than 50% with an increase in temperature. This is also aligned with the acquired experimental data, as the highest biomass concentration was achieved with 60% moisture content (
Table 2).
Figure 3 and
Figure 4 that the optimal range of electrode distance is 3 cm, as a higher concentration of biomass was attained under such conditions. An appropriate balance of electrode distance is required to achieve maximum performance of the ML-MFC system. This is because an excessive distance would result in undue resistance in the system [
12], which would result in a decrease in voltage generation. This is due to a greater distance and time required for the protons to travel from anode to cathode in order to complete the circuit—also known as ohmic losses [
12].
Temperature levels also play a role in the performance of an ML-MFC system, whereby a temperature slightly higher than room temperature (27 °C) often promotes metabolic reactions of the cells within the MFC system. This could result in an improved growth rate of the cells within the system [
15]. This is aligned with the obtained experimental data presented in
Figure 4 and
Figure 5, with an increased biomass concentration at temperatures slightly below 35 °C. This occurred due to a higher rate of diffusion of organic matter present in the substrate to the bacteria in the ML-MFC. However, an excessive temperature would lead to a decrease in the MFC’s performance, as the temperature-sensitive components within the bacteria, such as nucleic acids and proteins, have the potential to be irreversibly damaged and would no longer function, as reported by Muaz (2019) [
14].
In this research, the ML-MFC system obtained the highest COD removal efficiency at 98.0636% under the conditions of 35 °C, 75% (v/w) moisture content, an electrode distance of 3 cm, and an incubation period of seven days (168 h) as designed with Design Expert 13 software.
The contour plot and response surface plot of the interaction between moisture content and electrode distance are presented in
Figure 6.
Figure 7 and
Figure 8 present the contour and response surface plots of the interactions between temperature and electrodes, as well as between temperature and moisture content, respectively.
The phenomenon induced by an increase in moisture content previously mentioned with respect to biomass was also observed in relation to the COD removal efficiency, as shown in
Figure 6; a higher percentage of COD removal efficiency was obtained with moisture content of more than 50% (closer to 60%). This condition was also paired with an approximate optimal electrode distance of 3 cm. This phenomenon is also shown in
Figure 8; the optimal range of moisture content is also proximately higher than 50%, with an optimal range of temperature of roughly 35 °C to 45 °C. The additional moisture content boosts the COD removal efficiency, as the increased amount of complex matter in the substrate can now be broken down into simpler molecules. This is a result of the increased ease with which microbes can conduct hydrolysis reactions within the ML-MFC system [
14], resulting in higher COD removal efficiency values.
The same phenomenon with respect to the effect of electrode distance is shown in
Figure 7 and
Figure 8; a higher percentage of COD removal efficiency was achieved at approximately 3 cm with paired optimal conditions of moisture content higher than 50% and temperature ranging from 35 °C to 40 °C, respectively.
Temperatures of approximately 35 °C were observed to be optimal, as shown in
Figure 7 and
Figure 8; a higher percentage of COD removal efficiency is shown in both figures. This occurred as a consequence of the enhanced microbial metabolic reactions that took place, as mentioned with respect to biomass, due to the increase in temperature, resulting in improved substrate consumption by the bacteria in the MFC. In a domino effect, an increased amount of complex matter was broken down into smaller matter, resulting in increased COD removal efficiency.
The greatest power density generation obtained by the ML-MFC system in this study was 47.2064 mW/m2, operating at 35 °C, 75% (v/w) moisture content, and an electrode distance of 3 cm, with an incubation period of seven days (168 h), as designed with Design Expert 13 software.
The contour plot and response surface plot of the interactions between moisture content and electrode distance, temperature and electrode distance, and temperature and moisture content are shown in
Figure 9,
Figure 10 and
Figure 11, respectively.
Similar to the impact on biomass concentration and percentage of COD removal efficiency, the ML-MFC system with a higher level of moisture content also generated a higher power density with a moisture content of more than 50%, as shown in
Figure 9 and
Figure 10, with an optimal temperature range of approximately 35 °C and an electrode distance of 3 cm.
As observed with respect to biomass and COD removal, higher power density generation was also observed, as shown in
Figure 9 and
Figure 11, with an electrode distance of 3 cm, similar to the high biomass concentration percentage of COD removal efficiency. This is due to an appropriate distance between the anode electrode and the cathode electrode, avoiding the occurrence of ohmic losses in the system [
12].
A higher power density generation was attained in the temperature range of approximately 27 °C to 37 °C, as shown in
Figure 10 and
Figure 11, accompanied by an optimal electrode distance of about 3 cm and a moisture content of more than 50%. This is due to the ease with which bacteria can carry out their metabolic reactions, leading to increased substrate degradation within the ML-MFC system. Therefore, transfer of electrons from bacteria to the anode electrode increased, enabling a faster reactionand leading to increased power density generation.