Central Composite Design Method for the Preparation, Stability and Properties of Water-in-Diesel Nano Emulsions

Water in diesel nano-emulsion (WiDNE) due to their nano size, kinetically stable gives its beneficial in commercial and environmental aspects. However, the capability of this fuel strongly depends on the method of preparation, stability and their physic-chemical properties. Central composite design (CCD) method was used to optimize variable interactions in order to obtain maximum stability. Methodology RSM method with six independent variables was selected in order to understand the impacts on droplet size. The response surface and 3D plots of the quadratic polynomial model were created for studying the combination effect on response. Dynamic light scattering DLS technique was used for measuring of droplet sizes. The analysis result by ANOVA was with 95% confidence displaying F value model was 52.82. The results displayed model was fulfilled with the assumptions of ANOVA. This study has relied on Design Expert software to locate the optimum droplet size situations. The measured diameter is 26 nm, with 0.0297 errors between actual conditions and measured value. The optimum blend properties of prepared WiDNE fuel were compared with conventional diesel. Improvements in physical properties were observed in presence of water in WiDNE.


Advances in Chemical Engineering and Science
Nano-emulsion is a class of high stability emulsions with extremely small droplets in the range of 20 -200 nm with no apparent flocculation or coalescence [4], and this makes them a useful applications for example in the pharmaceutical, cosmetics, agrochemicals, and in the chemical industries [5] [6] [7] [8] [9].
The most common process in the preparation of nanoemulsions is high energy method [10]. Recently also a neat low-energy method [11] has been developed, by taking advantage of phase behavior and properties, to promote the formation of ultra-small droplets. These low energy techniques include self-emulsification [12] [13], phase transition [1] [14] [15] and Phase Inversion Temperature methods (PIT) [16] [17].
In this study, WiDNE fuel preparation by using high shearing method. The emulsification process includes simulating droplet model for the optimum condition based on the Central Composite Design (CCD) [18] [19]. Consequently, CCD method is the best for illustration of these influences [20]. Both of the droplets size and distributions inside the WiDNE fuel were measured through DLS technique.
The path for implementing experimental design was evaluated for two purposes. The first is to identify a subset of the original processes factors that have substantial main and interaction impacts on the final WiDNE fuel properties achieved. Second, factors have to be significant optimized statistically to determine the best WiDNE properties, according to the assumed Response Surface Method (RSM) model.

Diesel Fuel
Conventional diesel fuel produced from local Daura Refinery was used as continuous phase of WiDNE fuel. The characterization of diesel fuel is shown in Table 1.

Process of Emulsification
WiDNE were generated by dispersing water content into diesel fuel according to Table 3. The formation was done in three steps: 1) Surfactants Tween80 (HLB = 15) and Span80 (HLB = 4.3) were blended to get the desired Tween80/Span80 ratio (HLB = 8).
2) The prepared blend was added into the diesel fuel, and homogenized at 15,000 rpm for 10 min.
3) Distilled water was added gradually, into the mixture of diesel and surfactants, and mixed according to Table 3.

CCD Experimental Design
Consequently CCD is a combination of both mathematical and statistical technique used to design experiments; evaluate the factors of process; obtaining the model; interaction between variables and find optimum condition to analyze the problem [21] [22]. Response Surface Methodology RSM was applied to study the impacts of the independent factors: applied water percent (w%), Tween80/Span80 ratio (TS%), mixing time (min), homogenizer speed rpm, alkalinity (pH) and HLB of WiDNE. The experiments were designed using a 54 factorial with five central points as shown in Table 3. The individual experiments were carried out in random order

Analysis of Variance
The sum of square sequential model was used to compare different models. It showed the statistical significance of adding new terms step by step in increasing order. It provided accounts of variation and associated P-values (Prob > F). The model was selected based on the highest order that was significant (P-value small) and not aliased, on lack of fit (P-value > 0.10) and reasonable agreement between adjusted R-squared and predicted R-squared (within 0.2 of each other). The summary table of the sequential model sum of square is shown on Table 4.
Equation (1)  It was observed from Figure 1 that the extent of proximity of the results with the expected values, through which we concluded that the mathematical relationship between the factors affecting the size of droplets already corresponds to reality and confirmed the compatibility of the results of the process and arithmetic.
The results displayed fulfilled with the model assumptions of ANOVA. It indicates no sign presented that the error terms were correlated with each other.

Effect of Emulsification Variables
The most significant step in the preparation of WiDNE is selection of an appropriate variables and the effect of each one on the response. In this study, RSM method with six variables was selected in order to understand the impacts on droplet size. Each of these variables had a different effluent and limited impact except W%, all other factors were associated to reduce droplet size. Figure 2 shows the effect and interaction of factors on the droplets size starting from the most influential factor and ending with the least impact. It has been found that the rpm has a direct impact on the size of droplets.
Therefore, the 3D plots are the best method for illustrating the interaction between variables and effect of each others as can be shown in Figure 3.
In order to clarify the impact of the independent variables according to the results, response surface and 3D plots of the quadratic polynomial model were     According to Equation (1) the impact of mixed surfactant is −1.25. More increasing the time of splitting droplets to mixing, much less size of droplets will be obtained, but this factor will effect to specific limit and more than it would be useless or don't have benefit economically. The effluents of mixing time are investigated through Figure 3(e) combined with W% on droplets size.

Optimum Stability Condition Specifications
Obtaining the best conditions for the WiDNE fuel preparation process is one of the advantages of using this study. As shown in Figure 4, the optimum condi-   Optimum blend of prepared WiDNE fuel are compared with conventional diesel, as shown in Table 6.
The optimum water ratio was 12%, based on weight percent. The proportion of water inside the emulsified fuel must be kept within the specified limits, be-

Viscosity
The effect of the presence of water on the viscosity of WiDNE fuel is shown in Table 5. It was observed that viscosity increases from 3.268 to 4.56 cSt. The increasing in viscosity leads to more power requirement for pumping of fuel and poor atomization.

Density
The impact of water on density of WiDNE fuel is shown in Table 5. Density was increased from 0.87 g/cm 3 to 0.882 g/cm 3 for WiDNE. It is known that the water is heavier than diesel fuel. The impact of water is obvious in increases the density when blending with diesel. However, more fuel density means less volume will be taken for storing purpose.

Pour Point
Pour point of WiDNE fuel +7˚C were less compared with net diesel +9˚C. Increasing water content on WiDNE fuel caused reduction in pour point as shown in Table 6. With formation of WiDNE fuel, this pour point can be lowered significantly in order to confirm safe transportation of these types of oils.

Conclusions
1) Response surface methodology (RSM) was used to enhance process variables for preparation of WiDNE fuel.
2) Surfactant concentration has very positive effect on emulsion stability.
3) Increasing in water content decreased the emulsion stability.
4) Mixing and time have enhanced the stability significantly up to a certain limit beyond which it remains the same.