**2. Materials and methods**

#### **2.1 Reagents**

purposes. Consequently, methanolysis reaction has been proposed to constitute three consecutive irreversible stages, more especially by the usual condition of using high methanol to oil ratio (>3:1) which shifts the reaction methyl to the right [8, 9].

*Terminalia catappa*; belongs to *combietaccea* family with meridional Asian origin. It occurs in nature and widespread in the sub-tropical zones of India. It is called sea almond or tropical almond or Indian almond. In Nigeria, it is grown basically for

*Sea almond fruit biomass, a. the fruit, b. fruit cut section, c. dried fruit pulp, d. inner seed with coat. e. the seed,*

*f. the fruit husk, g. the ground pulp (raffinnate and 600 μm particle size).*

**Figure 2.**

Prunus

**106**

All the reagents used were all of analytical grade and purchased from the popular BriDGe-Head Chemical market in Onitsha, Anambra State Nigeria.

#### **2.2 Biomass collection and preparation**

#### *2.2.1 Sourcing of seeds/seed meal preparation*

The ripped fruits were collected from Abakaliki city of Nigeria. They were subsequently washed to remove dirt before the pulp was peeled out to release the kernel. The kernels were placed on solar drier for one (1) week. The seeds were extracted by cracking the kernels. Electric milling machine was used to grind the seeds into microsized meals before being sieved using an electric powered mechanical sieve to obtain a fine size of the meal. The remaining moisture in the sieved ground meal was removed by further sun drying the meal for a period of 5 days.

#### **2.3 Oil extraction and degumming**

The oil extraction followed the same method previously applied by the authors [1] but with slight modification. The extracted oil was further degummed by mixing the raw oil with 3 wt% by weight of warm water and the mixture was mechanically agitator coupled with using magnetic stirrer for 30 minutes at a temperature of 60° C to ensure that the emulsifiers were easily separated from the oil [13].

#### **2.4 Physico-chemical characterization of the oil**

The quality of the seed oil was determined in accordance with Association of Official Analytical Chemist [14] method. Other properties such as moisture, viscosity and density content were ascertained by using oven method, Oswald viscometer apparatus and density bottle respectively. The ash content and the refractive index were also measured with Veisfar muffle furnace and Abbe refractometer respectively. All the analyses were repeated three times and the average values were calculated and reported.

#### **2.5 Base methanolysis process**

The process follows the approach previously applied in Ofoefule et al. [13] with slight deviations. The extracted and pre-treated oil (100 ml) was first preheated to 80°C for 30 min before adding sodium methoxide. Sodium methoxide is more effective than direct mixing of sodium hydroxide due to the fact that direct mixing of NaOH with methanol produces water through hydrolysis and this affects the biodiesel yield. Therefore, sodium methoxide was prepared using the method previously reported by the authors [1]. Then the seed oil mixed with sodium methoxide at methanol/oil molar ratio of 6:1 was kept at 65°C for 65 min. This process was conducted in a 500 ml reflux condenser fitted with heater and stirrer. The process was conducted at atmospheric pressure and 140 rpm.

The biodiesel mixed with glycerine was separated, washed and dried according to the method previously applied by the authors [1]. The percentage biodiesel yield was calculated by using Eq. (1)

$$FAME\ yield(\forall \epsilon) = \frac{W\_{FAME}}{W\_{sed\ oil}} \propto 100\tag{1}$$

to 300 k to give a digital resolution of 0.366 Hz/point. Proton nuclear

*2.5.2.2 Fourier transform infrared spectroscopic analysis of the oil and biodiesel*

to peak with a maximum resolution of 0.5 cm<sup>1</sup> in the region of 400 cm<sup>1</sup>

100 mg sample 1 ml of deuterated chloroform solution and analysis using a Brucker model AC-250 spectrometer. Chemical shifts were measured in ppm downfield from internal tetramethyl siltane. The following instrumental parameters were applied. Spectrum width – 5000 Hz; acquisition time – 3.2775; delay time – 1 s and

*Sea Almond as a Promising Feedstock for Green Diesel: Statistical Optimization and Power Rate…*

FT-IR analysis was performed to monitor the functional groups in the seed oil. The mid infrared spectra of oil samples were obtained in Fourier transform spectrometer by IR Affinity-1 Shimadzu, model No: 3116465. The FT-IR has SN ratio of its class of 30,000:1, 1 minute accumulator in the neighborhood of 2100 cm<sup>1</sup> peak

introduction was through sample cell. Cleaning of the cell was done with trisolvent mixture of acetone-toluene-methanol before background collection. About 0.5 ml of the sample (oil) was taken using the sample cell and introduced into the cell unit of the system. The scan results were obtained on the incorporated computer system as spectra. The peaks of the spectra obtained were identified and interpreted to identify the functional groups in the molecules of the oil with the aid of structure

*2.5.2.3 Gas chromatographic-mass spectroscopic (GC: MS) analysis of the fatty acid*

The process followed the method reported by Esonye et al. [4]. The fatty acid composition of the biodiesel samples was in accordance with AOAC official method Ce2–66 using GCMS-QP2010 plus, Shimadzu. GC–MS is faster than the conventional GC; it equally provides molecular weight information and requires an aliquot sample. The GC–MS fragments the analyte to be identified on the basis of its mass and the column was calibrated by introducing methyl ester standards while good separations were achieved by diluting the sample in a little quantity of ethyl acetate. In this study, hydrogen served as the carrier gas and its flowrate was controlled at 41.27 ml/min while the flowrate of the column was 1.82 ml/min. Oven temperature was fixed at 80°C prior ramping up at 6°C/min and then up till 340°C. The Peaks identification was carried out by comparing their retention time and mass spectra

Central composite design (CCD) was applied in developing the design of experimental (DOE) for the base methanolysis of the *Terminalia catappa* seed oil. The matrix of the DOE based on the full factorial pattern provided sixteen (16) factorial points, eight (8) axial points and six (6) center points and these clearly present the required information on the inner conditions of the experimental circle. Design expert 7.0.0 software was employed for the design of the four (4) independent variables (n = 4), each with two (2) different levels. The total number of experiments (N) was worked out as N = (n2 + 2n + nc) = 16 + 2(4) +6 = 30. This includes the standard 2n factorial points with their origin at the centre, 2n axial points fixed

. It has microlab software as supporting software. The method of sample

H NMR) spectra were recorded by dissolving approximately


magnetic resonance (<sup>1</sup>

*DOI: http://dx.doi.org/10.5772/intechopen.93880*

pulse width – 7 μsec.

4000 cm<sup>1</sup>

**109**

correlation chart [15].

*profile of the biodiesel*

with Mass Spectra Library (MSL) [16].

*2.6.1 Design of Experimental and Statistical Analysis*

**2.6 Optimization using RSM-desirability function techniques**

where *WFAME*¼*weight of fatty acid methyl ester after methanolysis*

*Wseedoil*¼*weight of seed oil used for the base methanolysis:*

#### *2.5.1 Physico chemical characterization of the biodiesel*

The necessary fuel related physico-chemical properties of the biodiesel produced were determined using ASTM and AOAC [14] standard methods. ASTM D standards were used to determine the kinematic viscosity, density, pour, cloud, flash points, acid value and calorific values while AOAC methods were used to determine specific gravity, Iodine value and refractive index. ASTM D-445 method, the density was determined by ASTM D � 1298 method. The pour, flash and cloud points determinations were done using ASTM D-97, ASTM D-93, ASTMD-2500b methods respectively while acid value was measured by ASTM D-664 method. The refractive index was determined using AOAC 921.08. The specific gravity was ascertained using AOAC 920.212 and iodine value using AOAC 920:159 while moisture content was obtained using air-oven method. The cetane index (CI), cetane number (CN) and higher heating values were ascertained using standard correlations previously applied in [13].

#### *2.5.2 Chemical characterization of seed oil and biodiesel*

#### *2.5.2.1 Nuclear magnetic resonance (NMR) analysis*

The 13C NMR of the sample was recorded on a Bruker Am-400 spectrometer operating at 100.6 MHz. The gated decoupling pulse sequence was used with the following parameters: Number of seans 512, acquisition time 1.366 s pulse with 10.3 s delay time 1.0 s. FID (free induction decay) was transformed and zero filled *Sea Almond as a Promising Feedstock for Green Diesel: Statistical Optimization and Power Rate… DOI: http://dx.doi.org/10.5772/intechopen.93880*

to 300 k to give a digital resolution of 0.366 Hz/point. Proton nuclear magnetic resonance (<sup>1</sup> H NMR) spectra were recorded by dissolving approximately 100 mg sample 1 ml of deuterated chloroform solution and analysis using a Brucker model AC-250 spectrometer. Chemical shifts were measured in ppm downfield from internal tetramethyl siltane. The following instrumental parameters were applied. Spectrum width – 5000 Hz; acquisition time – 3.2775; delay time – 1 s and pulse width – 7 μsec.

#### *2.5.2.2 Fourier transform infrared spectroscopic analysis of the oil and biodiesel*

FT-IR analysis was performed to monitor the functional groups in the seed oil. The mid infrared spectra of oil samples were obtained in Fourier transform spectrometer by IR Affinity-1 Shimadzu, model No: 3116465. The FT-IR has SN ratio of its class of 30,000:1, 1 minute accumulator in the neighborhood of 2100 cm<sup>1</sup> peak to peak with a maximum resolution of 0.5 cm<sup>1</sup> in the region of 400 cm<sup>1</sup> - 4000 cm<sup>1</sup> . It has microlab software as supporting software. The method of sample introduction was through sample cell. Cleaning of the cell was done with trisolvent mixture of acetone-toluene-methanol before background collection. About 0.5 ml of the sample (oil) was taken using the sample cell and introduced into the cell unit of the system. The scan results were obtained on the incorporated computer system as spectra. The peaks of the spectra obtained were identified and interpreted to identify the functional groups in the molecules of the oil with the aid of structure correlation chart [15].

#### *2.5.2.3 Gas chromatographic-mass spectroscopic (GC: MS) analysis of the fatty acid profile of the biodiesel*

The process followed the method reported by Esonye et al. [4]. The fatty acid composition of the biodiesel samples was in accordance with AOAC official method Ce2–66 using GCMS-QP2010 plus, Shimadzu. GC–MS is faster than the conventional GC; it equally provides molecular weight information and requires an aliquot sample. The GC–MS fragments the analyte to be identified on the basis of its mass and the column was calibrated by introducing methyl ester standards while good separations were achieved by diluting the sample in a little quantity of ethyl acetate. In this study, hydrogen served as the carrier gas and its flowrate was controlled at 41.27 ml/min while the flowrate of the column was 1.82 ml/min. Oven temperature was fixed at 80°C prior ramping up at 6°C/min and then up till 340°C. The Peaks identification was carried out by comparing their retention time and mass spectra with Mass Spectra Library (MSL) [16].

#### **2.6 Optimization using RSM-desirability function techniques**

#### *2.6.1 Design of Experimental and Statistical Analysis*

Central composite design (CCD) was applied in developing the design of experimental (DOE) for the base methanolysis of the *Terminalia catappa* seed oil. The matrix of the DOE based on the full factorial pattern provided sixteen (16) factorial points, eight (8) axial points and six (6) center points and these clearly present the required information on the inner conditions of the experimental circle. Design expert 7.0.0 software was employed for the design of the four (4) independent variables (n = 4), each with two (2) different levels. The total number of experiments (N) was worked out as N = (n2 + 2n + nc) = 16 + 2(4) +6 = 30. This includes the standard 2n factorial points with their origin at the centre, 2n axial points fixed

apparatus and density bottle respectively. The ash content and the refractive index were also measured with Veisfar muffle furnace and Abbe refractometer respectively. All the analyses were repeated three times and the average values were

The process follows the approach previously applied in Ofoefule et al. [13] with slight deviations. The extracted and pre-treated oil (100 ml) was first preheated to 80°C for 30 min before adding sodium methoxide. Sodium methoxide is more effective than direct mixing of sodium hydroxide due to the fact that direct mixing of NaOH with methanol produces water through hydrolysis and this affects the biodiesel yield. Therefore, sodium methoxide was prepared using the method previously reported by the authors [1]. Then the seed oil mixed with sodium methoxide at methanol/oil molar ratio of 6:1 was kept at 65°C for 65 min. This process was conducted in a 500 ml reflux condenser fitted with heater and stirrer. The process

The biodiesel mixed with glycerine was separated, washed and dried according to the method previously applied by the authors [1]. The percentage biodiesel yield

*Wseedoil*¼*weight of seed oil used for the base methanolysis:*

The necessary fuel related physico-chemical properties of the biodiesel produced were determined using ASTM and AOAC [14] standard methods. ASTM D standards were used to determine the kinematic viscosity, density, pour, cloud, flash points, acid value and calorific values while AOAC methods were used to determine specific gravity, Iodine value and refractive index. ASTM D-445 method, the density was determined by ASTM D � 1298 method. The pour, flash and cloud points determinations were done using ASTM D-97, ASTM D-93, ASTMD-2500b methods respectively while acid value was measured by ASTM D-664 method. The refractive index was determined using AOAC 921.08. The specific gravity was ascertained using AOAC 920.212 and iodine value using AOAC 920:159 while moisture content was obtained using air-oven method. The cetane index (CI), cetane number (CN) and higher heating values were ascertained using standard correlations previously

The 13C NMR of the sample was recorded on a Bruker Am-400 spectrometer operating at 100.6 MHz. The gated decoupling pulse sequence was used with the following parameters: Number of seans 512, acquisition time 1.366 s pulse with 10.3 s delay time 1.0 s. FID (free induction decay) was transformed and zero filled

*WFAME Wseed oil*

*x*100 (1)

*FAME yield*ð Þ¼ %

calculated and reported.

Prunus

**2.5 Base methanolysis process**

was calculated by using Eq. (1)

applied in [13].

**108**

was conducted at atmospheric pressure and 140 rpm.

where *WFAME*¼*weight of fatty acid methyl ester after methanolysis*

*2.5.1 Physico chemical characterization of the biodiesel*

*2.5.2 Chemical characterization of seed oil and biodiesel*

*2.5.2.1 Nuclear magnetic resonance (NMR) analysis*

at a distance ɑ from the centre to generate the quadratic terms and nc replicate points at the centre. After defining the range of each of the process variable, they were coded to lie at �1 for the fractional points, 0 for the centre point, �ɑ for the axial points. The numerical values of the variables were transferred into their respective coded values as shown in Eq. (2). The factor levels were coded as -ɑ to +ɑ as shown in the **Table 1** based on fuel factorial composite design (FFCDD). Xmin (�ɑ) and Xmax (+ɑ) are minimum and maximum values of X respectively, �1 and + 1 have a level of variance of (Xmin + Xmax)/2 (Xmax - Xmin)/2b and 0 has a level of variance of (Xmin + Xmax)/2. The effects of selected factors on the biodiesel yield were investigated based on the experimental conditions of the thirty set that were conducted. The main operating conditions (reaction time, alcohol to oil molar ratio, catalyst weight and reaction temperature) that conventionally affect methanolysis for biodiesel production were studied. **Table 1** contains the levels and range of the four independent variables. The variables range was chosen based on results obtained from previous works [17]. The presence of a clear curvature for the methanolysis resulted in selecting a second-order (Eq. (3)) for the transesterification [13].

$$X\_i = \frac{2X - (X\_{\text{max}} - X\_{\text{min}})}{X\_{\text{max}} - X\_{\text{min}}} \tag{2}$$

Where di is individual response desirability*, Yi* is the response values, *Yi-min* is the minimum acceptable value for response i and *Yi-max* is the maximum acceptable value for response i. *D* is the overall desirability, *wi* is a weighed composite desirability. The statistical methods used to ascertain the degree at which the models represent the experimental data were done by determining the coefficient of determina-

*Sea Almond as a Promising Feedstock for Green Diesel: Statistical Optimization and Power Rate…*

(MSE), root mean squared error (RMSE), the standard error prediction (SEP) and

The rate of reaction and its mechanism as regards to the methanolysis process of

It has been reported that the conventional transesterification mechanism could be represented by three consecutive irreversible [8] reactions as represented in

> CH2OH CHOH CH2OH <sup>þ</sup>

), the mean squared error

! *DG* <sup>þ</sup> *BD* (6)

! *MG* <sup>þ</sup> *BD* (7)

! *Gl* <sup>þ</sup> *BD* (8)

(9)

R'COOR R"COOR R"'COOR

) adjusted coefficient of determination (Adj. R2

the seed oil were investigated by considering irreversible conditions.

Eqs. (6)–(8) with Eq. (9) being the summary of the Equations.

CH2OCOR <sup>þ</sup> 3ROH \$

were processed under the following assumptions [2, 8, 9]:

CH2OCOR CHOCOR

Glycerol, AOH is alcohol and BD is Biodiesel.

*2.7.2 Irreversible model assumptions*

reaction [9].

negligible.

**111**

value of the oil.

*2.7.3 The kinetic experimental conditions*

*TG* þ *AOH k*<sup>1</sup>

*DG* þ *AOH k*<sup>2</sup>

*MG* þ *AOH k*<sup>3</sup>

Triglycerides Alcohol Glycerol Biodiesel

Where MG is monoglycerides, DG is Diglyceride, TG is Triglyceride, Gl is

1.The methanolysis reaction is constituted by three consecutive stages but assumed irreversible because of the excessive presence of methanol in the

Since simplified kinetic models suffice for practical purposes, experimental data

2.The free fatty acid neutralization was insignificant since the free fatty acid was

3.The saponification reaction was considered insignificant because of low acid

Kinetics experimental design (KED) of the methanolysis process of the sea almond seed oil followed the method previously reported by the authors in

average absolute deviation (AAD) [13].

*DOI: http://dx.doi.org/10.5772/intechopen.93880*

*2.7.1 Equation of methanolysis reaction*

**2.7 Chemical kinetic study**

tion, (R2

$$Y = \beta\_0 + \sum\_{i=1}^{n} \beta\_i \mathbf{x}\_i + \sum\_{i=1}^{n} \beta\_{ii} \mathbf{x}\_i^2 + \sum\_{i=1} \sum\_{j=1}^{n} \beta\_{ij} \mathbf{x}\_{ij} \tag{3}$$

where, *Xi* - required coded value of a variable*, Xmin* and *Xmax* - the low and high values of *X* respectively, Where *β<sup>0</sup>* - a constant, *β<sup>i</sup> -* the linear coefficient, *βii* – the quadratic coefficient*, βij*-interactive coefficients, *X*<sup>i</sup> and *Xij* are the uncoded independent variables and *Y*- predicted response (%). The fitted quadratic model equations obtained from regression analysis were used for the successful development of the response surface plots. The desirability function method was employed in order establish an efficient approach for achieving maximum FAME production. The application of one side transformation (Eq. (4)) followed by overall desirability (*D*) (Eq. (5)) using univariate technique was adopted [5, 13].

$$d\_i = \left\{ \left[ \frac{Y\_i - Y\_{i-min}}{Y\_{i-max} - Y\_{i-min}} \right] Y\_{i-min} < Y\_i < Y\_{i-max} \right\} \tag{4}$$
 
$$\mathbf{0} \ Y\_i \ge Y\_{i-max}$$

$$D = \left(d\_1^{w1} d\_2^{w2} d\_3^{w3} d\_4^{w4} d\_5^{w6}\right)^{1/\sum wi} \tag{5}$$


#### **Table 1.**

*Variables, their symbols and CCD coded levels for* Terminalia catappa *seed oil methanolysis.*

*Sea Almond as a Promising Feedstock for Green Diesel: Statistical Optimization and Power Rate… DOI: http://dx.doi.org/10.5772/intechopen.93880*

Where di is individual response desirability*, Yi* is the response values, *Yi-min* is the minimum acceptable value for response i and *Yi-max* is the maximum acceptable value for response i. *D* is the overall desirability, *wi* is a weighed composite desirability.

The statistical methods used to ascertain the degree at which the models represent the experimental data were done by determining the coefficient of determination, (R2 ) adjusted coefficient of determination (Adj. R2 ), the mean squared error (MSE), root mean squared error (RMSE), the standard error prediction (SEP) and average absolute deviation (AAD) [13].

#### **2.7 Chemical kinetic study**

at a distance ɑ from the centre to generate the quadratic terms and nc replicate points at the centre. After defining the range of each of the process variable, they were coded to lie at �1 for the fractional points, 0 for the centre point, �ɑ for the axial points. The numerical values of the variables were transferred into their respective coded values as shown in Eq. (2). The factor levels were coded as -ɑ to +ɑ

as shown in the **Table 1** based on fuel factorial composite design (FFCDD).

fication [13].

Prunus

**Table 1.**

**110**

Xmin (�ɑ) and Xmax (+ɑ) are minimum and maximum values of X respectively, �1 and + 1 have a level of variance of (Xmin + Xmax)/2 (Xmax - Xmin)/2b and 0 has a level of variance of (Xmin + Xmax)/2. The effects of selected factors on the biodiesel yield were investigated based on the experimental conditions of the thirty set that were conducted. The main operating conditions (reaction time, alcohol to oil molar ratio, catalyst weight and reaction temperature) that conventionally affect methanolysis for biodiesel production were studied. **Table 1** contains the levels and range of the four independent variables. The variables range was chosen based on results obtained from previous works [17]. The presence of a clear curvature for the methanolysis resulted in selecting a second-order (Eq. (3)) for the transesteri-

> *Xi* <sup>¼</sup> <sup>2</sup>*<sup>X</sup>* � ð Þ *Xmax* � *Xmin Xmax* � *Xmin*

> > *i*¼1

where, *Xi* - required coded value of a variable*, Xmin* and *Xmax* - the low and high values of *X* respectively, Where *β<sup>0</sup>* - a constant, *β<sup>i</sup> -* the linear coefficient, *βii* – the quadratic coefficient*, βij*-interactive coefficients, *X*<sup>i</sup> and *Xij* are the uncoded independent variables and *Y*- predicted response (%). The fitted quadratic model equations obtained from regression analysis were used for the successful development of the response surface plots. The desirability function method was employed in order establish an efficient approach for achieving maximum FAME production. The application of one side transformation (Eq. (4)) followed by overall desirability (*D*)

*βiix*<sup>2</sup>

*<sup>i</sup>* <sup>þ</sup>XX*<sup>n</sup>*

*i*¼1

*Yi*� *min* < *Yi* < *Yi*� *max* (4)

**-ɑ -1 0 1 +ɑ**

<sup>P</sup>*wi* (5)

*<sup>β</sup>ixi* <sup>þ</sup>X*<sup>n</sup>*

0 *Yi* ≤*Yi*� *min*

0 *Yi* ≥*Yi*� *max*

� �<sup>1</sup>*<sup>=</sup>*

Temperature (°C) X1 30 40 50 60 70 Catalyst conc. (%wt) X2 0.5 1.0 1.5 2.0 2.5 Reaction time (min.) X3 45 50 55 60 65 Alcohol/Oil molar ratio X4 3:1 4:1 5:1 6:1 7:1

<sup>1</sup> *dw*<sup>2</sup> <sup>2</sup> *dw*<sup>3</sup> <sup>3</sup> *<sup>d</sup><sup>w</sup>*<sup>4</sup> <sup>4</sup> *<sup>d</sup>wn* 5

**Parameters/Units Symbols Coded levels**

*Variables, their symbols and CCD coded levels for* Terminalia catappa *seed oil methanolysis.*

*Yi* � *Yi*� *min Yi*� *max* � *Yi*� *min* � �

*<sup>D</sup>* <sup>¼</sup> *<sup>d</sup><sup>w</sup>*<sup>1</sup>

*<sup>Y</sup>* <sup>¼</sup> *<sup>β</sup>*<sup>0</sup> <sup>þ</sup>X*<sup>n</sup>*

(Eq. (5)) using univariate technique was adopted [5, 13].

*di* ¼

8 >>>><

>>>>:

*i*¼1

(2)

*βijxij* (3)

The rate of reaction and its mechanism as regards to the methanolysis process of the seed oil were investigated by considering irreversible conditions.

#### *2.7.1 Equation of methanolysis reaction*

It has been reported that the conventional transesterification mechanism could be represented by three consecutive irreversible [8] reactions as represented in Eqs. (6)–(8) with Eq. (9) being the summary of the Equations.

$$\text{TG} + \text{AOH} \underset{\rightarrow}{\text{k}\_{\cdot}} \text{DG} + \text{BD} \tag{6}$$

$$\text{DG} + \text{AOH} \underset{\rightarrow}{k\_2} \text{MG} + \text{BD} \tag{7}$$

$$\text{MG} + \text{AOH} \underset{\rightarrow}{k\_{\text{\tiny}}} \text{Gl} + \text{BD} \tag{8}$$


Where MG is monoglycerides, DG is Diglyceride, TG is Triglyceride, Gl is Glycerol, AOH is alcohol and BD is Biodiesel.

#### *2.7.2 Irreversible model assumptions*

Since simplified kinetic models suffice for practical purposes, experimental data were processed under the following assumptions [2, 8, 9]:


#### *2.7.3 The kinetic experimental conditions*

Kinetics experimental design (KED) of the methanolysis process of the sea almond seed oil followed the method previously reported by the authors in

Esonye et al. [1] with slight deviations to ascertain the kinetics and thermodynamic requirements. To examine the temperature dependency of the reaction rate constants, three (3) level temperatures (55–65°C) and twelve (12) intervals of reaction time (0-100 min) were considered at 6:1 alcohol (methanol)/sea almond seed oil molar ratio. About 2 ml aliquot sample were withdrawn at specified time intervals from the reactor, introduced into a test tube in an ice bath to quench the reaction. The content of the composite sample was obtained using a gas chromatography [1]. The G.C was equipped with split/splitless injection system operating at 185 degree Celsius, split ratio of 100:1, sample volume of 0.3 μL. High purity hydrogen gas was used as drag.

#### *2.7.4 Second: order irreversible kinetic model*

The best kinetic model for an irreversible model has been proposed to be a second-order based on TG hydrolysis especially during the early stages of the reaction [8]. To test the above report, a model developed based on TG hydrolysis and the second-order reaction rate for TG would be as shown in Eq. (10) [18].

$$\frac{-\mathbf{d}[\mathbf{TG}]}{\mathbf{dt}} = \mathbf{k}[\mathbf{TG}]^2 \tag{10}$$

�*rTG* <sup>¼</sup> �*d TG* ½ �

*DOI: http://dx.doi.org/10.5772/intechopen.93880*

written as in Eq. (15).

[TG] against time was obtained.

*2.7.6 Thermodynamic requirement*

K = rate constant, KO = frequency factor.

**3.1 Physico-chemical characterization result**

**3. Results and discussion**

Eq. (16):

of TG.

**113**

*dt* <sup>¼</sup> *<sup>k</sup>*<sup>0</sup>

*Sea Almond as a Promising Feedstock for Green Diesel: Statistical Optimization and Power Rate…*

�*rTG* <sup>¼</sup> �*d TG* ½ �

triglyceride concentration was [TG0] at time t = 0, and at time t it falls down [TGt]. The integration of Eq. (15) for t = 0, [TG] = [TG0] and at t = t, [TG] = [TGt] gives

In order to test the rate equation in Eq. (16), the experimental data were fitted to a straight line while the coefficient of determination was ascertained. A plot of –ln

In order to ascertain the process thermodynamic requirement, the values of rate constants were used to determine the Arrhenius activation energy from the plots of

2*:*303*R*

The fuel related properties of the biodiesel and its parent oil obtained from this work at the optimum conditions are presented in **Table 2**. The properties of the biodiesel compared well with the American standards, European specification and other feedstocks recently applied for biodiesel production [4, 21]. The viscosity of the sea almond compared well with standards and other similar varieties. This is very important for the efficiency of its engine application since many diesel engines used injection pumps that do not accept high viscous fluids that clog the fuel filteration units. Also, sea almond had a better cetane number than Iranian bitter

1 *T*

(17)

reaction rate constant (k) versus the reciprocal of absolute temperature (T) (Eq. (17)). DG and MG relationship with time followed the same trend with that

logk <sup>¼</sup> *<sup>k</sup>*<sup>0</sup> � *Ea*

Where Ea = Activation energy, R = Gas constant (8.314 � <sup>10</sup>�<sup>3</sup> J/Kmol),

Where k is modified rate constant and k = k<sup>0</sup>

Where [TG] is the concentration of triglycerides and [ROH] that of methanol and k<sup>0</sup> is the equilibrium rate constant. This overall reaction follows a second-order reaction rate law. However, due to the high molar ratio of methanol to oil, the change in methanol concentration can be considered as constant during reaction. This means that by taking methanol in excess, its concentration does not change the reaction order and it behaves as a first-order chemical reaction. Hence, the reaction would obey pseudo-first order kinetics [19] and finally, the rate expression can be

*:*½ � *TG :*½ � *ROH* <sup>3</sup> (14)

*dt* <sup>¼</sup> *<sup>k</sup>:*½ � *TG* (15)

. Assuming that the initial

[ROH]3

� ln ½ �þ *TG* ln ½ �¼ *TG*<sup>0</sup> *kt* (16)

Resolving Eq. (10) further yields Eq. (11).

$$k\_{\rm TG}t = \frac{1}{[\rm TG]} - \frac{1}{[\rm TG0]}\tag{11}$$

Where k is the overall rate constant, t is the reaction time, TG0 is the initial triglyceride concentration.

A plot of reaction time (t) against <sup>1</sup> ½ � TG will give a straight line if the model is valid. Where k is the overall rate constant, t is the reaction time; TG0 is the initial triglyceride concentration. A plot of reaction time (t) against <sup>1</sup> ½ � TG will give a straight line if the model is valid. Similar approach was applied on the monoglycerides and diglycerides hydrolysis to get Eqs. (12) and (13).

$$k\_{DG}t = \frac{1}{[DG]} - \frac{1}{[DG\_0]}\tag{12}$$

$$k\_{\rm MG}t = \frac{1}{[\rm MG]} - \frac{1}{[\rm MG\_0]}\tag{13}$$

#### *2.7.5 First-order irreversible kinetic model*

To determine the kinetics of the reaction based, the effect of reaction temperature and time were measured. It was assumed that the catalyst was used in sufficient amount with respect to oil to shift the reaction equilibrium towards the formation of fatty acid methyl esters. Thus, the reverse reaction could be ignored and change in concentration of the catalyst during the course of reaction can be assumed to be negligible [19]. Also, since the concentrations of both DG and MG were found to be very low (DG < 2.9 wt%, MG < 1.45 wt%) compared to those of TG (TG > 94 wt%) in the crude vegetable oils used in this research, the reaction could be assumed to be a single-step transesterification [20]. Therefore, the rate law of the transesterification reaction for forward reaction can be expressed by Eq. (14).

*Sea Almond as a Promising Feedstock for Green Diesel: Statistical Optimization and Power Rate… DOI: http://dx.doi.org/10.5772/intechopen.93880*

$$-r\_{TG} = \frac{-d[TG]}{dt} = k'.[TG].[ROH]^3\tag{14}$$

Where [TG] is the concentration of triglycerides and [ROH] that of methanol and k<sup>0</sup> is the equilibrium rate constant. This overall reaction follows a second-order reaction rate law. However, due to the high molar ratio of methanol to oil, the change in methanol concentration can be considered as constant during reaction. This means that by taking methanol in excess, its concentration does not change the reaction order and it behaves as a first-order chemical reaction. Hence, the reaction would obey pseudo-first order kinetics [19] and finally, the rate expression can be written as in Eq. (15).

$$-r\_{TG} = \frac{-d[TG]}{dt} = k.[TG] \tag{15}$$

Where k is modified rate constant and k = k<sup>0</sup> [ROH]3 . Assuming that the initial triglyceride concentration was [TG0] at time t = 0, and at time t it falls down [TGt]. The integration of Eq. (15) for t = 0, [TG] = [TG0] and at t = t, [TG] = [TGt] gives Eq. (16):

$$-\ln\left[TG\right] + \ln\left[TG\_0\right] = kt \tag{16}$$

In order to test the rate equation in Eq. (16), the experimental data were fitted to a straight line while the coefficient of determination was ascertained. A plot of –ln [TG] against time was obtained.

#### *2.7.6 Thermodynamic requirement*

Esonye et al. [1] with slight deviations to ascertain the kinetics and thermodynamic requirements. To examine the temperature dependency of the reaction rate constants, three (3) level temperatures (55–65°C) and twelve (12) intervals of reaction time (0-100 min) were considered at 6:1 alcohol (methanol)/sea almond seed oil molar ratio. About 2 ml aliquot sample were withdrawn at specified time intervals from the reactor, introduced into a test tube in an ice bath to quench the reaction. The content of the composite sample was obtained using a gas chromatography [1]. The G.C was equipped with split/splitless injection system operating at 185 degree Celsius, split ratio of 100:1, sample volume of 0.3 μL. High purity hydrogen gas was

The best kinetic model for an irreversible model has been proposed to be a second-order based on TG hydrolysis especially during the early stages of the reaction [8]. To test the above report, a model developed based on TG hydrolysis and the second-order reaction rate for TG would be as shown in Eq. (10) [18].

dt <sup>¼</sup> k TG ½ �<sup>2</sup> (10)

½ � TG will give a straight line if the model is

½ � TG0 (11)

½ � TG will give a straight

(12)

(13)

�d TG ½ �

*kTGt* <sup>¼</sup> <sup>1</sup>

*kDGt* <sup>¼</sup> <sup>1</sup>

*kMGt* <sup>¼</sup> <sup>1</sup>

be very low (DG < 2.9 wt%, MG < 1.45 wt%) compared to those of TG

triglyceride concentration. A plot of reaction time (t) against <sup>1</sup>

½ � TG � <sup>1</sup>

Where k is the overall rate constant, t is the reaction time, TG0 is the initial

valid. Where k is the overall rate constant, t is the reaction time; TG0 is the initial

line if the model is valid. Similar approach was applied on the monoglycerides and

½ � *DG* � <sup>1</sup>

½ � *MG* � <sup>1</sup>

To determine the kinetics of the reaction based, the effect of reaction temperature and time were measured. It was assumed that the catalyst was used in sufficient amount with respect to oil to shift the reaction equilibrium towards the formation of fatty acid methyl esters. Thus, the reverse reaction could be ignored and change in concentration of the catalyst during the course of reaction can be assumed to be negligible [19]. Also, since the concentrations of both DG and MG were found to

(TG > 94 wt%) in the crude vegetable oils used in this research, the reaction could be assumed to be a single-step transesterification [20]. Therefore, the rate law of the transesterification reaction for forward reaction can be expressed by Eq. (14).

½ � *DG*<sup>0</sup>

½ � *MG*<sup>0</sup>

used as drag.

Prunus

*2.7.4 Second: order irreversible kinetic model*

Resolving Eq. (10) further yields Eq. (11).

A plot of reaction time (t) against <sup>1</sup>

*2.7.5 First-order irreversible kinetic model*

**112**

diglycerides hydrolysis to get Eqs. (12) and (13).

triglyceride concentration.

In order to ascertain the process thermodynamic requirement, the values of rate constants were used to determine the Arrhenius activation energy from the plots of reaction rate constant (k) versus the reciprocal of absolute temperature (T) (Eq. (17)). DG and MG relationship with time followed the same trend with that of TG.

$$\text{logk} = k\_0 - \frac{E\_a}{2.303R} \left(\frac{1}{T}\right) \tag{17}$$

Where Ea = Activation energy, R = Gas constant (8.314 � <sup>10</sup>�<sup>3</sup> J/Kmol), K = rate constant, KO = frequency factor.

#### **3. Results and discussion**

#### **3.1 Physico-chemical characterization result**

The fuel related properties of the biodiesel and its parent oil obtained from this work at the optimum conditions are presented in **Table 2**. The properties of the biodiesel compared well with the American standards, European specification and other feedstocks recently applied for biodiesel production [4, 21]. The viscosity of the sea almond compared well with standards and other similar varieties. This is very important for the efficiency of its engine application since many diesel engines used injection pumps that do not accept high viscous fluids that clog the fuel filteration units. Also, sea almond had a better cetane number than Iranian bitter

#### Prunus


biodiesel iodine value indicates less unsaturation. It equally shows that sea almond biodiesel will be comparatively less prone to oxidation instability and glyceride polymerization that normally leads to formation of deposits. The flash point, cloud point and pour point of Iranian bitter almond were very high compared to standards and the values recorded for both sea and sweet almond varieties. It implies that Iranian bitter almond variety will be safer to transport and handle in terms of flammability status and as well as be less suitable for winter season operations when compared with the hazardous and cold flow properties of sea almond. The parent oil characteristics of sea almond exhibited improved properties as a result of the base

*Sea Almond as a Promising Feedstock for Green Diesel: Statistical Optimization and Power Rate…*

**Table 3** contains peaks identified from the spectrum of the sea almond seed oil

**Sea almond seed oil Sea almond seed oil biodiesel**

892.50 Bending =C-H 892.50 Bending =C-H

1076.70 Bending C-O-C 1041.96 Stretching C-O 1188.64 Stretching C-O 1134.60 Split rocking C-O 1317.66 Bending/rocking CH2 1197.20 Split rocking C-O 1474.28 Bending/rocking CH2 1317.66 Bending/Rocking CH2 1500.50 Bending/rocking CH2 1474.28 Bending/Rocking CH2 1734.60 Stretching C=O 1555.12 Bending/Rocking CH2 1860.18 Stretching C=O 1734.60 Stretching C=O

**Wave number (cm<sup>1</sup> )**

**Functional group**

3373.44 Stretching O-H 2411.21 Symmetrical/

*FT-IR main characteristic band positions for se almond seed oil and its biodiesel.*

3495.74 Stretching O-H 3365.18 Stretching O-H

1734.60 cm<sup>1</sup> - 1819.44 cm<sup>1</sup> for the oil and its biodiesel respectively can be ascribed to the stretching vibrations of C=O group. It shows the conversion of the triglyceride in the parent oil to biodiesel (methyl esters). Also, the specific bands of 2421.18 cm<sup>1</sup> and 2411.21 cm<sup>1</sup> appear with alkenes group for triglyceride and its biodiesel respectively. Also, the band regions between 3373.44–3495.22 cm<sup>1</sup> and 3365.18–3598.44 cm<sup>1</sup> for the parent seed oil and its biodiesel respectively can be ascribed to single-bonded hydroxyl group (O–H) stretching vibrations, appearing at high energy positions [4]. The single bond functional group O-H was observed to be prevalent in the biodiesel with stretch vibrations [4]. The presence of water molecule was evidenced by the hydrogen bonding [22]. The presence of C-H at 1357.64, 1474.28 and 1522.72 cm<sup>1</sup> regions of the biodiesel spectrum can be attributed to the properties such as pour and cloud points that influence the performance of biodiesel during cold weather engine operation [22]. However, the presence of carbon to


**Type of vibration**

C=C 1819.44 Stretching C=O

Stretching

3598.44 Stretching O-H

**Functional group**

(alkenes)

C=C

methanolysis [1].

**Wave number (cm<sup>1</sup> )**

2421.18 Symmetrical/

**Table 3.**

**115**

Stretching

**Type of Vibration**

**3.2 FTIR characterization result**

*DOI: http://dx.doi.org/10.5772/intechopen.93880*

and its biodiesel. The band regions between 1734.60 cm<sup>1</sup>

*b Based on viscosity.*

*c Based on density, min-minimum, max- maximum.*

*1 This study.*

*2 [4].*

#### *3 [21]*

**Table 2.** *Physico-chemical properties of the sea almond seed oil and its FAME, sweet almond biodiesel and Iranian bitter almond biodiesel versus standards.*

almond but compared well with sweet almond variety and standard specifications. This shows that sea almond oil is less unsaturated than Iranian bitter almond sea oil which has been reported to have 84.7% unsaturation [21] against 55.32% from sea almond and 52.42% for sea almond. The iodine value of sea almond was observed to be five (5) times less than Iranian bitter almond. Although Iranian bitter almond biodiesel iodine value is similar to that of tiger nut oil, the low value of sea almond

*Sea Almond as a Promising Feedstock for Green Diesel: Statistical Optimization and Power Rate… DOI: http://dx.doi.org/10.5772/intechopen.93880*

biodiesel iodine value indicates less unsaturation. It equally shows that sea almond biodiesel will be comparatively less prone to oxidation instability and glyceride polymerization that normally leads to formation of deposits. The flash point, cloud point and pour point of Iranian bitter almond were very high compared to standards and the values recorded for both sea and sweet almond varieties. It implies that Iranian bitter almond variety will be safer to transport and handle in terms of flammability status and as well as be less suitable for winter season operations when compared with the hazardous and cold flow properties of sea almond. The parent oil characteristics of sea almond exhibited improved properties as a result of the base methanolysis [1].

#### **3.2 FTIR characterization result**

**Table 3** contains peaks identified from the spectrum of the sea almond seed oil and its biodiesel. The band regions between 1734.60 cm<sup>1</sup> -1860.18 cm<sup>1</sup> and 1734.60 cm<sup>1</sup> - 1819.44 cm<sup>1</sup> for the oil and its biodiesel respectively can be ascribed to the stretching vibrations of C=O group. It shows the conversion of the triglyceride in the parent oil to biodiesel (methyl esters). Also, the specific bands of 2421.18 cm<sup>1</sup> and 2411.21 cm<sup>1</sup> appear with alkenes group for triglyceride and its biodiesel respectively. Also, the band regions between 3373.44–3495.22 cm<sup>1</sup> and 3365.18–3598.44 cm<sup>1</sup> for the parent seed oil and its biodiesel respectively can be ascribed to single-bonded hydroxyl group (O–H) stretching vibrations, appearing at high energy positions [4]. The single bond functional group O-H was observed to be prevalent in the biodiesel with stretch vibrations [4]. The presence of water molecule was evidenced by the hydrogen bonding [22]. The presence of C-H at 1357.64, 1474.28 and 1522.72 cm<sup>1</sup> regions of the biodiesel spectrum can be attributed to the properties such as pour and cloud points that influence the performance of biodiesel during cold weather engine operation [22]. However, the presence of carbon to


**Table 3.** *FT-IR main characteristic band positions for se almond seed oil and its biodiesel.*

almond but compared well with sweet almond variety and standard specifications. This shows that sea almond oil is less unsaturated than Iranian bitter almond sea oil which has been reported to have 84.7% unsaturation [21] against 55.32% from sea almond and 52.42% for sea almond. The iodine value of sea almond was observed to be five (5) times less than Iranian bitter almond. Although Iranian bitter almond biodiesel iodine value is similar to that of tiger nut oil, the low value of sea almond

*Physico-chemical properties of the sea almond seed oil and its FAME, sweet almond biodiesel and Iranian bitter*

**Parameters Sea**

Density (kg/m3

Prunus

Iodine value (mgKOH/g)

Saponification value (mgKOH/g)

Kinematic viscosity

Higher heating value (HHV)a (MJ/kg)

Higher heating value (HHV)<sup>b</sup> (MJ/kg)

Higher heating value (HHV)<sup>c</sup> (MJ/kg)

*almond biodiesel versus standards.*

*Based on density, min-minimum, max- maximum.*

*Based on flash point.*

*Based on viscosity.*

*a*

*b*

*c*

*1 This study. 2 [4]. 3 [21]*

**Table 2.**

**114**

(mm<sup>2</sup> /s) **almond seed oil<sup>1</sup>**

**Sea almond seed oil FAME<sup>1</sup>**

**Sweet almond seed oil FAME<sup>2</sup>**

Oil/Biodiesel yield (%) 60.57 94.21 94.90 ——— —

Moisture content (%) 0.66 0.02 0.02 ——— — Refractive index 1.4471 1.441 1.4402 ——— — Acid value (mgKOH/g) 2.701 0.37 0.46 0.44 0.062 0.50 0.50 Free fatty acid (%) 1.35 0.18 0.23 — 0.31 0.25 0.25

Ash content (%) 1.00 0.01 0.01 — 0.01 0.02 0.02

Smoke point (**°**C) 40 36 34 ——— — Fire point (**°**C) — 40 40 ——— — Flash point (**°**C) 156 138 136 173 60–80 100–170 120 Cloud point (**°**C) 3 -3 2 10 20 3 to 12 — Pour point (**°**C) — 7 6 3 35 15 to 16 — Calorific value (KJ/Kg) — 32,188.50 31,178.39 — 42–46 — 35 Conductivity (Us/CM) — 0.45 0.40 ——— — Cetane index — 72.0 73.0 ——— — Cetane number — 70.60 70.40 44.6 40–55 47 min. 51 min.

**Iranian bitter almond seed oil FAME3**

38.11 27.11 28.02 117.29 42–46 — 120max.

— 2.40 2.52 4.68 2.6 1–9-6.0 3.5–5.0

— 35.62 34.72 ——— —

— 41.66 40.76 ——— —

— 64.65 63.75 ——— —

166.21 162.3 161.05 185.35 ———

) 856.10 855.3 849.1 887 850 880 860–900

**ASTM D 9751**

**Standards**

**ASTMD 6751**

**EN 14214**

carbon (C=C) unsaturated bonds can cause the biodiesel samples to remain in liquid state but may be liable to poor storage stability due to oxidation. This implies that the biodiesel would not need cold flow improver for better performance. All the absorptions corresponding to C-O and C=O stretches indicate that the biodiesel product contains ester functional groups typical to any biodiesel type, while the following groups: C–H, C=H, and O–H indicated biodegradability of the oil and produced biodiesel [11]. Significant differences were effected by the ester groups. The specific peak that appeared at 892.50 cm<sup>1</sup> possesses bending type of vibrations appearing at low energy and frequency region in the spectra. It indicates the presence of = C–H functional groups [4]. It is part of fatty acid methyl ester with unsaturated bond in the seed oil and ester [23]. The specific peaks found in the region of 1088.80 cm<sup>1</sup> and 1197.20 cm<sup>1</sup> show split stretching and rocking vibrations of the carbonyl group (C–O) for the triglyceride and its methyl ester respectively [24]. The bending and rocking vibrations of methyl group in the parent oil and its methyl ester appeared between 1317.66–1500.50 cm<sup>1</sup> and 1317.66– 1555.12 cm<sup>1</sup> respectively [25].

monounsaturated fatty acids in methyl esters translates to high biodiesel quality [26]. Therefore, the high levels of monounsaturated fatty acids (39.92%) contained in the sea almond seed oil methyl ester is expected to make it possess excellent fuel qualities. Also, the higher the amount of unsaturated fatty acid in a biodiesel sample, the better the cloud point but lower the oxidation stability which implies that the higher composition of unsaturated fatty acids in the methyl ester (52.42%) would therefore enhance its cold flow properties [27]. It is reported that the high viscous nature of waste frying oils is because of their high saturated and less unsaturated fatty acids and this could cause micro-crystal formations that are dangerous to engine fuel injection units [28, 29]. Therefore, the application of biodiesel derived from the kernel seed of sea almond would possess no inherent viscosity problem. According to the present investigation, the cetane number of sea almond seed oil methyl ester is 63.39, and this shows the presence of high amount of monounsaturated fatty acids [30]. Methyl esters derived from animal sources has cloud point of about 17°C which is quite above 13°C obtained from palm oil sourced biodiesel while conversely feedstocks with lower concentrations of saturated fatty acids produces methyl esters with very low cloud point (< 0°C) [30]. Basically, biodiesel properties such as cetane number, kinematic viscosity, oxidative stability and cold flow properties are the specifications that are required to be satisfied and these have high relationship with the biodiesel fatty acid structural composition [31, 32]. Knothe [33] has reported that exhaust emission, and heat of combustion are likewise influenced by the fatty acid composition while methyl oleate is reported to be the most desired fatty acid to furnish produced

*Sea Almond as a Promising Feedstock for Green Diesel: Statistical Optimization and Power Rate…*

Nuclear magnetic resonance spectroscopy (NMR) is one of the instrumental analytical techniques used to quantify the conversion of triglycerides in vegetable oils into s [34, 35]. It is therefore, considered as one of the promising techniques for the characterization of biodiesel. The percentage conversion of the parent oil into its biodiesel using integration values for methoxy and ɑ - carbonyl methylene protons [35] was found to be 95.7%%. Experimentally, the maximum sea almond yield obtained numerically as presented in **Table 2** and by GC maximum determination after 1 hr. were 94.21% and 93.01% respectively. All results are quite in good agreement and validate each other. The slight variation in conversion could be due to incomplete separation of FAME s from glycerine (by-product) and minor system errors as in the case of experimental and GC determinations respectively. The <sup>1</sup>

NMR spectrum of biodiesel from sea almond seed oil biodiesel is shown in **Figure 3a**. The specific peaks appearing at 0.452 ppm and 0.811 ppm for terminal

**3.5 RSM optimization of sea almond seed oil methanolysis process**

A central composite design (CCD) was applied to develop a correlation between the factors affecting transesterification reaction and the yield. The complete design

0.452 are from the terminal alkyl methyl in the s [36]. **Figure 3b** shows the 13C NMR spectrum of biodiesel from the sea almond seed oil. The 13C NMR shows significant aliphatic composition (CH3) at the 24–28 ppm resonance [37] and for terminal carbon methylene at 17.774 pp. The peak at 124.629 ppm is typical of polycyclic aromatics structures [38]. Also, the peak at 167.288 ppm shows the presence of carbonyl carbon (-COO-) and O-aromatics (C-O) [34]. The peaks at 17.774–28.907 ppm could be attributed to terminal methyl groups. The unsaturation characteristics of s was confirmed by peaks appearing at δ124.629 ppm [34].

H

H NMR, the peak around

biodiesel with the above expected fuel properties [1].

methyl protons (C-CH3) appears as singlet. From the <sup>1</sup>

**3.4 NMR characterization result**

*DOI: http://dx.doi.org/10.5772/intechopen.93880*

**117**
