Statistical Modeling and Optimization of Biodiesel Production from Azadirachta Indica (Neem) Using Co-Solvent Technique

International Journal of Advanced Engineering, Management and Science (IJAEMS) [Vol-4, Issue-3, Mar- 2018]
https://dx.doi.org/10.22161/ijaems.4.3.8 ISSN: 2454-1311
www.ijaems.com Page | 182
Statistical Modeling and Optimization of Biodiesel
Production from Azadirachta Indica (Neem) Using
Co-Solvent Technique
Nnodim1
C. J., Nwakaudu1
M. S., Kamen1
F. L., Nwakaudu1
A. A., Ikhazuangbe1
P.M.O.,
Haruna2
I.
1
Department of Chemical Engineering, Federal University of Technology, Owerri, Nigeria
2
Petrochemicals and allied department National Research Institute for Chemical Technology, Zaria, Nigeria
Abstract— In this work, statistical modeling and
optimization of biodiesel production from Azadirachta
Indica(neem) using co-solvent technique via a two-step
transesterification process was carried out. Neem oil was
extracted from neem seeds and properties such as moisture
content, specific gravity, acid value, saponification value
and iodine value were determined. The experimental design
used was Central Composite Design. The range of factor
levels used for the Central Composite Design were reaction
temperature (30°C to 46°C), catalyst amount (0.8% to
1.2%, w/w), reaction time (20 to 40min) and methanol-to-
oil molar ratio (5:1 to 9:1). The co-solvents used were
methanol and diethyl ether. The co-solvent-to-methanol
volume ratio for all the experimental runs was kept constant
at 1:1. Also the biodiesel produced was characterized for
some important properties including acid value, specific
gravity, saponification value, iodine value, cetane number,
ester value, kinematic viscosity, flash point, pour point and
cloud point. Optimized biodiesel yield of 84.77% was
obtained for reaction time of 35 min, catalyst amount of
1.10g, reaction temperature of 34°C, and oil-to-methanol
molar ratio of 6:1. The cetane number (51.733), specific
gravity (0.8881g/cm3
), flash point (134o
C) and kinematic
viscosity (5.86mm2
/s) of the produced biodiesel met the
ASTM specifications. The results of characterization of the
biodiesel revealed that biodiesel can be produced at lower
reaction conditions and with comparable fuel property with
biodiesel produced using conventional methods.
Keywords— Biodiesel, Co-solvent, Modeling,
Optimization, Transesterification.
I. INTRODUCTION
The continual degradation of the environment by pollutants
associated with the combustion of fossil fuels remains a
great challenge to the society and researchers have
continued to develop alternative cleaner and cheaper fuels
to fossil fuels. Among the various alternatives, biodiesel
has received greater interest. Biodiesel is an alkyl
ester(usually mono-alkyl ester) derived from vegetable oils
through transesterification process between triglycerides
and alcohol solvent (usually methanol solvent) in the
presence of acid or alkaline catalyst. Short-chain alcohols
such as methanol, ethanol and butanol are the most
frequently employed. Selection of the alcohol is based on
cost and performance consideration [11]. Methanol was
dominating in most of the literature reviewed [6,7,11,12].
Methyl, rather than ethyl, ester production is usually
prevalent because methyl esters are the predominant
commercial products. Methanol is considerably cheaper and
more available than ethanol and the downstream recovery
of un-reacted alcohol is much easier (Pinto et al., 2005).
Ethanol maintains its capability of being renewable as an
advantage.
Biodiesel have been produced from different vegetable oils
like Jatropha, mustard, chicken fat, waste vegetable oil,
cotton seed and neem[1,4,5,6,7,8]. Biodiesel can be used to
power diesel engine vehicles as its fuel properties has been
shown to be comparable with those of petroleum
diesel[2,4]. The effects of process variables on the yield of
biodiesel has been studied and it has been showed that the
major factors that affect the yield of biodiesel are:
methanol-to-oil molar ratio, catalyst weight, reaction
temperature and reaction time [8].
Researchers have investigated and developed various
techniques and strategies for optimization of biodiesel
production process in Nigeria in order to justify its
feasibility and economic viability for adoption and
commercialization as an alternative fuel and fuel blend(1).
Various optimum conditions for biodiesel production have
been obtained by researchers using conventional solvents

[4,6,7]. Also biodiesel has been produced from different oils
by several researchers using alkaline-catalized
transesterification process in the presence of co-solvents,
and the transesterification process has been shown to take
place at lower reaction temperature and shorter time
[2,3,4,5].
Since the presence of co-solvent allows the
transesterification process to take place at lower
temperature and in a shorter time, there is need to optimize
the reaction conditions that affect the yield of biodiesel in
other to evaluate the economic viability of biodiesel
production with neem oil using co-solvents. The aim of this
work is to optimize biodiesel production from Azadirachta
Indica (neem) using co-solvent technique.
II. MATERIALS AND METHODS
The major raw materials used for this work are neem oil,
methanol and diethyl ether. The seeds were cleaned to
remove the dirt and impurities contained in them. The oil
was extracted from the neem seeds using a screw oil
expeller machine (model: 6YL-100).
Experimental design
A four-factor-five-level central composite design was
employed for this study, which generated thirty
experimental runs. The factors investigated in this study
were methanol-to-oil mole ratio, catalyst amount (w/w),
reaction temperature (°C) and reaction time (minutes). The
experimental range and Levels of the independent variables
are shown in Table 1 below.
Table.1: Experimental Range and Levels of the Independent Variables
Variables Symbols Coded factor levels
low (-1) 0 High (+1)
Methanol-to-oil mole ratio X1 5.0:1 6.0:1 7.0:1 8.0:1 9.0:1
Catalyst weight (grams) X2 0.80 0.90 1.00 1.10 1.20
Temperature (o
C) X3 30 34 38 42 46
Reaction time (minutes) X4 20 25 30 35 40
Free Fatty Acid Reduction Procedure
The oil was first heated to 1000
C and then cooled to remove
any water content present in the oil. The neem oil had a
high free fatty acid value. The free fatty acid reduction of
the neem oil was done via esterification of the oil with
methanol in the presence of tetraoxosulphate (VI)
acid(H2SO4) as catalyst. The esterification was done in
batches. 450g of the oil was poured into a 1-litre capacity
conical flask and heated to a temperature of 60°C while
stirring at 1000rpm. 1% w/w acid was mixed with 30% w/w
methanol and the mixture was heated to temperature of
60°C.
The methanol-acid mixture was added to the heated oil and
the conical flask was sealed with a foil. The process was
allowed to take place for one hour for the acid esterification
to take place. After the esterification process, the acid value
was determined to ensure that it is below maximum
acceptable limit specified by the ASTM standard. The
procedure was repeated for all the batches of the oil sample.
Alkaline catalyzed transesterification
The oil was first heated to 1000
C for 10 minutes and then
cooled to remove any water content present in the oil. For
the first run, 100g of the esterified neem oil was weighed
using an electronic weighing balance and poured into a
conical flask which served as a continuously stirred reactor.
The reactor was initially charged with only the neem oil and
heated up to 340
C.The hot plate was set to give a stirring
speed of 400rpm. 0.9 grams of sodium hydroxide were
dissolved in 68.06 grams of methanol. To this solution was
added 85.93 cm3
of diethyl ether. The resulting solution was
added to the oil being stirred in the conical flask at 340
C.
The reaction was allowed to proceed for 25 minutes. The
mixture was poured into a separating funnel and allowed to
stand overnight to ensure complete separation of methyl
esters and glycerol phase. The layer on the top was the
biodiesel while the bottom layer was the glycerol. The
procedure was repeated for other combination settings from
the guidelines established by the experimental design as
shown in table 2.
The glycerol phase (bottom phase) was drained off from the
separation funnel and collected in a separate container.
Biodiesel washing and drying
The methyl ester (biodiesel) was continuously washed with
hot distilled water at 800
C to eliminate residual catalyst,
glycerol, methanol and diethyl ether retained in the
biodiesel.

The biodiesel was then heated at 383k in a fume cupboard
to remove retained methanol, catalyst, diethyl ether and
water.
The mass of the biodiesel obtained was determined and
recorded in Table 2. The procedure was repeated for all the
30 experimental runs.
Statistical Modelling of the biodiesel production
Quadratic polynomial equation was generated by the
Design-Expert software. The data obtained in the
experiments (Table 2) were analyzed using response surface
methodology so as to fit the response surface quadratic
model. The general form of the quadratic model in terms of
the coded variables to be fitted to the data is given by the
equation 1
+ e (1)
Where,
Y is response factor (% yield), i and j are integers, k is the number of independent variables involved, a0 is the intercept term, ai
are the first order model coefficients for the ith factors, aii are the second order model coefficient for the ith factor,
aij are regression coefficients of double factor interactions and e is the experimental error. The independent variables which were
used were coded according to equation 2.
2
2
XbXa
XbXa
Xi
xi




(2)
i = 1,2,3,…,k
where, xiis the coded value symbol for the ith factor while Xi is the corresponding natural or real factor value symbol for the
ith factor. Xa and Xbrepresent the minimum and maximum values of natural variable Xi respectively.
The fitted quadratic response model is show in Equation 3.
Ŷ = 72.55–2.93 x 1–0.75 x 2+0.77 x 3–1.62 x 4+0.51 x 1
2
–1.38 x 2
2
+5.14 x 3
2
+0.84 x 4
2
–0.65 x 1 x 2–1.07 x 1 x 3–1.20 x 1 x 4– 2.07
x 2 x 3+3.05 x 2 x 4–1.77 x 3 x 4 (3)
The quality of the fit of the model was evaluated using analysis of variance (ANOVA) as shown in table 3.
𝑎0 + ∑ 𝑎𝑖 𝑋𝑖
𝑘
𝑗=1
+
Y =
2
+ ∑ 𝑎𝑖𝑖 𝑋𝑖 +
𝑘
𝑗=1
∑
𝑘
𝑖 < 𝑗
∑ 𝑎𝑖𝑗 𝑋𝑖 𝑋𝑗
𝑘

Table.2: Experimental Results for the Central Composite Design
Methanol/oil
molar ratio %
(W/W) (X1)
Catalyst weight
%
(X2)
Temperature(o
C)
( X3)
Time (mins)
(X4)
Biodiesel Yield
w/w (%)
Run
Order
Coded
Value
Real
Value
Coded
Value
Real
Value
Coded
Value
Real
Value
Coded
Value
Real
Value
Exp.
Value
Pred.
Value
Residual
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
-1
1
-1
1
-1
1
-1
1
-1
1
-1
1
-1
1
-1
1
-2
2
0
0
0
0
0
0
0
0
0
0
0
0
6.0
8.0
6.0
8.0
6.0
8.0
6.0
8.0
6.0
8.0
6.0
8.0
6.0
8.0
6.0
8.0
5.0
9.0
7.0
7.0
7.0
7.0
7.0
7.0
7.0
7.0
7.0
7.0
7.0
7.0
-1
-1
1
1
-1
-1
1
1
-1
-1
1
1
-1
-1
1
1
0
0
-2
2
0
0
0
0
0
0
0
0
0
0
0.90
0.90
1.10
1.10
0.90
0.90
1.10
1.10
0.90
0.90
1.10
1.10
0.90
0.90
1.10
1.10
1.00
1.00
0.8
1.2
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
-1
-1
-1
-1
1
1
1
1
-1
-1
-1
-1
1
1
1
1
0
0
0
0
-2
2
0
0
0
0
0
0
0
0
34
34
34
34
42
42
42
42
34
34
34
34
42
42
42
42
38
38
38
38
30
46
38
38
38
38
38
38
38
38
-1
-1
-1
-1
-1
-1
-1
-1
1
1
1
1
1
1
1
1
0
0
0
0
0
0
-2
-2
0
0
0
0
0
0
25
25
25
25
25
25
25
25
35
35
35
35
35
35
35
35
30
30
30
30
30
30
20
40
30
30
30
30
30
30
79.10
78.70
76.10
73.27
89.04
86.00
80.16
73.33
74.35
69.60
84.80
78.62
79.90
70.61
81.01
68.89
80.70
68.28
68.63
65.20
91.99
94.04
78.53
73.05
72.52
73.04
72.60
71.88
72.17
73.08
78.47
78.47
76.33
73.70
89.84
85.56
79.40
72.50
75.07
70.26
85.14
77.70
79.36
70.27
81.13
69.42
80.46
68.74
68.52
65.53
91.58
94.67
79.14
72.66
72.55
72.55
72.55
72.55
72.55
72.55
0.63
0.23
-0.23
-0.43
-0.80
-0.44
0.76
0.83
-0.72
-0.66
-0.34
0.92
0.54
0.34
-0.12
-0.53
0.24
-0.46
0.11
-0.33
0.41
-0.63
-0.61
0.39
-0.03
0.49
0.05
-0.67
-0.38
0.53
Table.3: Analysis of Variance for the Response Surface Model
Source of
Variables
Sum of
squares
DF Mean squares F-value P-value
Prob> F
Comment
Model
X1
X2
X3
X4
X1
2
X2
2
X3
2
X4
2
X1X2
X1X3
X1X4
X2X3
X2X4
X3X4
Residual
1471.1
208.45
12.80
13.85
64.45
7.14
52.51
721.86
19.13
6.29
19.29
24.23
67.04
151.84
51.73
7.71
14
1
1
1
1
1
1
1
1
1
1
1
1
1
1
15
105.08
208.45
12.80
13.85
64.45
7.14
52.51
721.86
19.13
6.29
19.29
24.23
67.04
151.84
51.73
0.51
204.54
405.76
24.92
26.95
125.46
13.89
102.22
1405.18
37.24
12.24
37.56
47.17
130.49
295.58
100.70
<0.0001
<0.0001
0.0002
0.0001
<0.0001
0.0020
<0.0001
<0.0001
<0.0001
0.0032
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
Significant
Significant
Significant
Significant
Significant
Significant
Significant
Significant
Significant
Significant
Significant
Significant
Significant
Significant
Significant

Lack of fit
Pure Error
Cor Total
6.59
1.12
1478.80
10
5
29
0.66
0.22
2.95 0.1222 Not Significant
Optimization
The quadratic model was used for optimization with the
help of Design Expert software. The optimum values of the
independent variable obtained are 6:1 methanol/oil molar
ratio, 34°C reaction temperature, 1.1% catalyst
concentration, and 35-min reaction time.
Determination of the properties of the biodiesel
The fuel properties of the neem oil biodiesel were carried
out using the ASTM methods and the results are presented
in table 4. The properties determined include: Physical state
at 250
C, Colour, moisture content, acid value, % FFA,
specific gravity @ 250
, iodine value, saponification value,
kinematic viscosity @ 400,
, flash point(closed cup),
, cloud
point, pour point and cetane number.
Chromatography - Mass Spectrometry (GC-MS) Analysis
The presence of methyl ester in the biodiesel was
determined using a Gas Chromatography - Mass
Spectrometry (GC-MS) machine.
III. RESULTS AND DISCUSSION
Results of Characterization of Neem Oil and Biodiesel
The neem oil was seen to have high acid content after its
characterization which necessitated the pre-treatment of the
oil through esterification before the transesterification
process. The result of characterization of the neem oil also
revealed that the neem oil has a relatively high iodine value
which implies that the biodiesel produced from the neem oil
has the tendency to undergo oxidation and polymerization
and when stored for a very long time.
Analysis of Variance for the Response Surface Model
The results of analysis of variance (ANOVA) for the
response surface model are shown in Table 3. The result
shows that the model has a high F-ratio(i.e F-value). From
table 3, the calculated F-value for the model(204.54) is
greater than the tabulated critical value (2.42). The large F-
value of the model(204.54) implies that the model is
significant. The associated P-value of 0.0001 implies that
there is only a 0.01% chance that the Model “F-value” this
large could occur due to noise. "Prob > F" for each of the
model terms is less than 0.05 which indicates that the terms
in the model have a significant effect on the response. In
this case X1, X2, X3, X4, X1
2
, X2
2
, X3
2
, X4
2
, X1X2, X1X3,
X1X4, X2X3, X2X4, X3X4 are significant model terms. The
"Lack of Fit F-value" of 3.08 implies the Lack of Fit is not
significant relative to the pure error. The "Prob > F" value
associated with the lack of fit implies that there is a 12.22%
chance that a "Lack of Fit F-value" this large could occur
due to noise. The Non-significant lack of fit is good as it is
desired for the model to fit the data well.
Model Summary Statistics
Table 5 contains the result of the model summary statistics.
The Coefficient of determination(R-Squared=0.9948)
shows that the fit of the model is good. The closer the value
to unity, the better the empirical model fits the actual data.
It implies that 99.48% of the total variability in the response
is explained by the model. The "Pred. R-Squared" of 0.9733
is in reasonable agreement with the "Adj R-Squared" of
0.9899 which shows high accuracy of the model in
predicting the yield of the biodiesel for given factor
combination settings. The Adj. R-Squared is a statistic that
is adjusted for the “size” of the model, i.e the number of
factors. The Adj. R-Squared value can actually decrease if
non-significant terms are added to a model. The PRESS
Statistic is a measure of how well the model will predict
new data. The low prediction error sum of squares(PRESS)
value indicates that the model is likely to be a good
predicator.
Comparison of the Biodiesel Properties with the ASTM
Standards
The biodiesel was characterized in terms of moisture
content, specific gravity, acid value, iodine value,
saponification value, ester value cloud point, pour point,
kinematic viscosity, flash point and cetane number. The
results are presented in Table 4. The values obtained were
compared to the ASTM specifications. All the properties
met the ASTM specifications except the flash point(1340
C).
The high flash point could be attributed to the presence of
retained di-ethyl ether in the fuel. Fuels with flash point
higher than specifications in ASTM standards pose hazards
during storage and transportation. Better means of removing
the retained co-solvent should be employed in large scale
production of the neem biodiesel using co-solvent
technique. The low moisture content and acid value of the

neem biodiesel is desirable as it will prevent corrosion of
the fuels to engine parts and growth of micro-organisms.
The acid value is below the lower limit which makes it safe
for use in diesel engine. The density value of the neem
biodiesel was obtained to be 0.8881kg/m3
which falls within
the ASTM acceptable limits. The kinematic viscosity,
which determines how well the fuel is atomized prior to
combustion, is seen to meet the ASTM standard. The low
pour point will allow the fuel to be used in extremely cold
weather conditions without gelling and blocking fuel filters
and fuel lines. The cetane number also falls within the
ASTM specification. This property shows that the neem
biodiesel has a good quality as fuels with high cetane
numbers burn smoothly and more efficiently than fuels with
low cetane number
Experimental Results for the Central Composite Design
Table 1 shows the design considered in this study in terms
of coded and natural values. The experiment was carried out
based on the design guidelines in table 1. The methanol:
diethyl ether volume ratio of 1:1 was used based on the
optimum established results obtained in previous works
involving co-solvent technology transesterification
(Mohammed, 2012). The experimental results and the
predicted values are also recorded. The optimum yield
obtained in this study (84.77w/w) is in comparison with
85.13% obtained in literature for the alkaline catalysed
transesterification using the conventional method(Awolu et
al., 2013).
The values of the predicted yield using the fitted quadratic
model are compared to the experimental results and the
residuals recorded as seen in table 2. The small values of
the residuals indicate that the model fits the experimental
data well.
The optimum yield (w/w) was obtained to be 84.77grams at
optimum variable values of 6.00:1 for methanol-to-oil
volume ratio, 1.10grams for catalyst weight, 34.000
C for
reaction temperatures and 35.00 minutes for reaction time.
The optimum time obtained in this study is in agreement
with that obtained by Felicia et al, 2014. The lower yield of
biodiesel compared to those in literature could be as a result
of excessive addition of the diethyl ether for the reaction
leading to dilution effect of the reactants.
Table.4: Comparison of the Biodiesel Properties with the ASTM Standards
S/n Properties Units ASTM Test
method
Neem Biodiesel
values
ASTM D675
specification
1
2
3
4
5
6
7
8
9
10
11
12
13
Physical state at 250
C
Colour
Moisture Content
Acid value
% FFA
Specific gravity @ 250
C
Iodine value
Saponification value
Kinematic viscosity @ 400
Flash point(closed cup)
Cloud point
Pour point
Cetane number
-
-
% wt
mg KOH/g
%
kg/m3
mg iodine/g
mg KOH/g
mm2
/s
0
C
0
C
0
C
min
-
-
2709
D664
-
D4052
D1959
AOAC Cd 3-25
D2983
D93
D2500
D97
D613
Liquid
Reddish Brown
0.04
0.491
0.246
0.8881
73.728
193.195
5.86
134
7
4
51.733
-
-
0.05max.
0.05max.
-
0.87 – 0.90
-
-
1.9-6.0
130min
-3 to 12
-5 to 10
47 min
Table.5: Model Summary Statistics
S/n Statistic Value
1
2
3
4
5
6
7
8
Standard Deviation
Mean
C.V%
Press
R-Squared
Adjusted R-Squared
Pred R-Squared
Adeq precision
0.72
76.62
0.94
39.56
0.9948
0.9899
0.9733
57.289

IV. CONCLUSION
The maximum neem oil methyl ester (NOME) conversion
yield was validated as 84.77% (w/w) under the optimal
reaction condition of 6:1 methanol/oil molar ratio, 34°C
reaction temperature, 1.1% catalyst concentration, and 35-
min reaction time. The fuel properties of neem oil methyl
ester satisfied the ASTM D6751 specification. The present
study demonstrates the importance of economic effect of
biodiesel production from neem oil using co-solvent
technique. It also suggests that neem biodiesel can be
produced at lower cost in the presence of diethyl ether
solvent.
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