Journal of the Association of Arab Universities for Basic and Applied ...

Journal of the Association of Arab Universities
for Basic and Applied Sciences (JAAUBAS)
http://www.ees.elsevier.com/jaaubas
JAAUBAS is a biannual peer-refereed international research journal specialized in the basic and applied sciences. It is issued by the
College of Science at the University of Bahrain, Kingdom of Bahrain, in accordance to the resolution of the Association of Arab
Universities Council (Jordan), and the resolution of the University of Bahrain council (834/2000).
JAAUBAS scope is to publish original research and reviews in the field of basic and applied sciences including; Biology, Chemistry,
Physics, Mathematics, Operation Research, Statistics, Astronomy, Geology and Engineering. JAAUBAS will assist researchers, from
local, regional and international universities and institutions, in publishing original research results and studies in basic and applied
sciences, and having their finding internationally visible and available.
EDITORIAL BOARD
Editor-In-Chief (EIC)
Dr. Hashim A. Al-Sayed
General Secretary of Society of Colleges of Science in
Arab Universities, Dean of College of Science,
University of Bahrain. P.O. Box 32038,
Kingdom of Bahrain.
Halsayed4122@hotmail.com
Managing Editor (ME)
Prof. Waheeb E. Alnaser
Vice President for Planning and Development,
University of Bahrain. P.O. Box 32038,
Kingdom of Bahrain.
alnaser@gmail.com
Editorial Secretary (ES)
Dr. Mohammad El-Hilo
Department of Physics, University of Bahrain.
P.O. Box 32038, Kingdom of Bahrain.
mhilo@rocketmail.com
University of Bahrain Board Members
Prof. Mohamed S. Akhter,
Dept. of Chemistry, Univ. of Bahrain, Kingdom of Bahrain.
Prof . Jameel A. Alkhuzai ,
Dept. of Biology, Univ. of Bahrain, Kingdom of Bahrain.
Prof. Mahmoud Abdel-Aty,
Dept. of Mathematics, Univ. of Bahrain, Kingdom of Bahrain.
Dr. Haifa A Al-Maskati,
Dept. of Biology, Univ. of Bahrain, Kingdom of Bahrain.
AAU Colleges of Science Society Advisory Board Members
Prof. Ghassan Owamerain, Dept. of Chemistry, King Fahad Univ., Saudi Arabia.
Prof. Redha Al Hassan, Dept. of Biology, Kuwait University, Kuwait.
Prof. Ismail A Taqi, Dept. of Mathematics, Kuwait University, Kuwait.
Prof. Lateefa E. Al Hoti, Dept. of Physics, Qatar University, Qatar.
Prof. Hala K. Horani, Dept. of Bilogy, Jordanian University, Jordan.
Prof. Sami M. Hussain, Dept. of Physics Jordanian University, Jordan.
Prof. Ahmed H. Abu Hilal, Dept. of Earth and Envi. Sci., Yarmouk Univ., Jordan.
Prof. Mohammad S. Abu Saleh, Dept. of Mathematics, Yarmouk Univ., Jordan.
Prof. Safwan Ashoor, Dept. of Chemistry, Allepo University, Syria.
Prof. Mahmoud Kroom, Dept. of Bilolgy, Allepo University, Syria.
Prof. Mohammed Othman, Dept. of Biology, Damascus University, Syria.
Prof. Mohammed A. Al Najar, Dept. of Biology, Lebanese University, Lebanon.
Prof. Huda Hashim, Dept. of Chemistry, Lebanese University, Lebanon.
Prof. Adel M. Awad Allah, Dept. of Chemistry, Islamic Univ. of Gaza, Palestine.
Prof. Mohammed M. Shabat, Dept. of Physics, Islamic Univ. of Gaza, Palestine
Prof. Mohammed El Sayed Othman, Dept. of Biology, Helwan Univ., Egypt.
Prof. Hassan M. El-Hawart, Dean of science, Assiut University, Egypt.
Prof. Bader E. Ahmed, School of Appl. Earth Science, Al Neelain Univ. Sudan.
International Advisory Board Members
Prof. Ahmed H. Zewail (Nobel laureate), California Institute of Technology, US
Prof. Farouk El-Baz (Geology), Centre for Remote Sensing, Boston Univ., USA.
Prof. El-Sayed Mustafa Amr (Chemistry), Florida State University, USA.
Prof. Mourad E.H. Ismail (Mathematics), University. of South Florida, USA.
Prof. Ahmed Sameh (Computer Science), Minnesota University, USA.
Prof. Munir H. Nayfeh (Physics), Illinois University, USA
Prof. Riyad Y. Hamzah, Biochemistry, Arabian Gulf Univ., Kingdom of Bahrain.
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Editor- in-Cheif, Journal of the Association of Arab
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Sakhir, Kingdom of Bahrain.
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Bahrain Publishing Permission: MAAU 394
ISSN 1815-3852
Imprint: University of Bahrain
Printed at the University of Bahrain Printing Press 2012-085960

Journal of the Association of Arab Universities
for Basic and Applied Sciences
Volume 11, April 2012
Published by
University of Bahrain

Foreword
It fills me with great satisfaction to see the 11 th issue of
JAAUBAS being published in April 2012. This issue
contains 9 articles from the Kingdom of Bahrain,
Algeria, Palestine, Yemen, Sudan, France, Iraq and
Malaysia. The articles cover various areas of research
such as electric power load forecast, energy saving, steal
mechanical properties, radioactivity measurement in
water, CdS thin films, spectrophotometric study of
pyrimethamine, improved hardness of resin, purification
of biodiesel and effect of herbal extracts on lactic acid
bacteria.
Now and after having JAAUBAS hosted by Elsevier, the flow of papers have
increased rapidly and we started to receive research work from various countries in
addition to Arab countries. Also the published papers are now recognized by various
international data basis like Scopus, Science Direct, Web Science. JAAUBAS starts
to achieve its aims in publishing original research and assisting researchers from the
Arab and international universities and institutions to make their findings
internationally visible and available.
It is a well known fact that scientific research is a key issue in the university ranking.
Thus now any published work in JAAUBAS appear as a record for the university or
the institution since it will be picked up by the international data basis. Our next step
is to establish the link with the ISI (Thomson Reuters) to have the journal evaluated
after two years and obtain the impact factor (IF). This only can be done with your
contribution in publishing your first class scientific research in JAAUBAS. Looking
forward to receive your most recent research work.
Dr. Hashim Al Sayed
Editor-in-Chief, JAAUBAS

Journal of the Association of Arab Universities for Basic and Applied Sciences (2012) 11, iii
University of Bahrain
Journal of the Association of Arab Universities for
Basic and Applied Sciences
www.elsevier.com/locate/jaaubas
www.sciencedirect.com
CONTENTS
Enhancement, evaluation and implementation of a load forecasting method
M.R. Qader and I. Qamber . . . ........................................................................................... 1
A self-controlled energy efficient office lighting system
M. Taleb and N. Mannsour . . . ........................................................................................... 9
Fracture process of C–Mn steel embrittled by hydrogen
N. Saidani, A. Mihi and R. Benbouta .................................................................................... 16
Radioactivity measurements in tap water in Gaza Strip (Al-Naser Area)
M.O. El-Ghossain and A.A. Abu Shammala . . . .......................................................................... 21
Synthesis, structure, and optical properties of CdS thin films nanoparticles prepared by chemical bath technique
A.M.A. Al-Hussam and S.A.-J. Jassim . . . ................................................................................ 27
Spectrophotometric determination of pyrimethamine (PYM) in pharmaceutical formulation using 1,2-naphthoquinone-4-
sulfonate (NQS)
A.A. Elbashir and A.H.E. Elwagee . . ..................................................................................... 32
Kinetic study of the RTM6/TiO 2 by DSC/TGA for improved hardness of resin
L. Merad, P. Bourson, Y. Guedra, F. Jochem and B. Benyoucef ......................................................... 37
Purification of biodiesel using activated carbons produced from spent tea waste
A.B. Fadhil, M.M. Dheyab and A.-Q.Y. Abdul-Qader ................................................................... 45
Viability of lactic acid bacteria and sensory evaluation in Cinnamomum verum and Allium sativum-bio-yogurts made from
camel and cow milk
A.B. Shori and A.S. Baba ................................................................................................ 50

Journal of the Association of Arab Universities for Basic and Applied Sciences (2012) 11, 1-8
تعزيز و تقييم و تنفيذ طريقة التنبؤ بالحمل الكهربائي
1
محمد رضا قادر ،
2
عيسى سلمان قمبر
قسم
1
الهندسة الكهربائية و اإللكترونية ، كليه الهندسة ، جامعة البحرين،‏ ص.ب
22023، البحرين مملكة
،22023
2
عمادة البحث العلمي ،
جامعة البحرين،‏ ص.ب
البحرين مملكة
الملخص:‏
أثر عدم اليقين لتوقعات الحمل الكهربائي تكون واضحة المعالم إذا كان بعض من سعة االحتياطي
المخزون يتم االستعانة بها لتوفير حمولة زائدة عن الكمية المتوقعة و بالتالي فان االحتياطي المخزون
يخفض.‏ النموذج تم تطويره للحصول على الحمل المتوقع لمملكة البحرين.‏
طريقة الحساب تمت باستخدام طريقة مونت كارلو لنمذجة الحمل الكهربائي.‏ النموذج المستخدم يستطيع أن
يتنبأ بالحمل الكهربائي مع مرور الزمن خالل فترات سنوية بحيث تم تقسيم كل سنة الى
النموذج المعد للتنبؤ يقوم بحساب الحد األدنى لمتوسط الخطأ التربيعي
25
)MMSE(
اسبوعا.‏
لمتوسط القدرة المخزونة
المشروط واالنحراف المعياري المشروط في كل فترة محددة للتنبؤ باألحمال الكهربائية المتوقعة.‏ لعمل ذلك،‏
وضحت النتائج المتوسط المشروط و نماذج التغاير من منظور تصفية خطيه وطبقت تكرار التوقعات
المشروطة على المعادالت العودية لكل فترة تنبؤ عند كل زمن.‏ وقد تم استنباط النتائج وتمت مناقشتها في
هذه الدراسة.‏
M.R. Qader, I. Qamber

Journal of the Association of Arab Universities for Basic and Applied Sciences (2012) 11, 1–8
University of Bahrain
Journal of the Association of Arab Universities for
Basic and Applied Sciences
www.elsevier.com/locate/jaaubas
www.sciencedirect.com
ORIGINAL ARTICLE
Enhancement, evaluation and implementation
of a load forecasting method
M.R. Qader a, *, I. Qamber b
a Department of Electrical and Electronics Engineering, University of Bahrain, P.O. Box 32038, Isa Town, Kingdom of Bahrain
b Deanship of Scientific Research, University of Bahrain, P.O. Box 32038, Sakhir, Kingdom of Bahrain
KEYWORDS
Monte Carlo;
Load forecast;
MMSE;
Kingdom of Bahrain
Abstract The effect of load forecast uncertainty may be well-defined if some of the spinning reserve
capacity is needed to supply the load in excess of the amount predicted and, thereby the spinning
reserve is reduced. The model was developed for load estimation of Kingdom of Bahrain. The calculation
method involves a Monte Carlo technique for the simulation of the load. The model enables the
predication of the load against the time during years, where each year is divided into 52 weeks. The
forecasting model, computes minimum mean square error (MMSE) forecasts of the conditional mean
of reserve power and conditional standard deviation of the innovations in each period over a userspecified
forecast possibility. To do this, it views the conditional mean and variance models from a
linear filtering perspective, and applies iterated conditional expectations to the recursive equations,
one forecast period at a time. The results are obtained and discussed.
ª 2012 University of Bahrain. Production and hosting by Elsevier B.V. All rights reserved.
1. Introduction
The prediction method used in the present paper is based on
Monte-Carlo simulation in which it is well known that any
approach using the Monte Carlo simulation method does
not solve the equations describing the model. The Monte Carlo
simulation uses a random number generator. And this generator
is needed to bring the stochastic element in the calculations.
* Corresponding author.
E-mail address: mrqader@eng.uob.bh (M.R. Qader).
1815-3852 ª 2012 University of Bahrain. Production and hosting by
Elsevier B.V. All rights reserved.
Peer review under responsibility of University of Bahrain.
doi:10.1016/j.jaubas.2012.02.001
Production and hosting by Elsevier
The researcher could use a physical random-number generator
such as electrical load variation through a certain period.
The Monte-Carlo simulation requires the creation of random
numbers, in this paper, the generated numbers were chosen
to follow the normal distribution with average value and
standard deviation of the electrical load of Bahrain.
In Bordalo et al. (2006) they presented a probabilistic shortcircuit
approach to generate the probability distributions of
the system average variation index. The methodology followed
is based on the combination of the Monte-Carlo simulation
and the admittance summation method.
In El-Khattam et al. (2006) they presented a novel algorithm
to evaluate the performance of electric distribution systems,
including distributed generation. Monte Carlo simulation is
employed to solve the system operation randomness problem.
The simulation is implemented to perform the analysis of all
possible operations of the system under study. The system loading
follows several typical load curves.
In Ionescu et al. (2006), the purpose of their study was to
obtain a performable tool based on generalized stochastic Petri

2 M.R. Qader, I. Qamber
1800
1600
Load (MW)
1400
1200
1000
800
600
0 10 20 30 40 50 60
WEEKS
Figure 1 Load forecasts of one year in Kingdom of Bahrain (year of 2002).
0.25
0.2
0.15
0.1
reserve MW
0.05
0
-0.05
-0.1
-0.15
-0.2
-0.25
0 5 10 15 20 25 30 35 40 45 50
WEEKS
Figure 2
Translation of weekly power to weekly reserve.
Nets (GSPN). After description and implementation through
GSPN, each configuration has been evaluated, in order to
choose the most appropriate structure.
Batlle and Barquín (2004) in their paper (2004) present a
fuel prices scenario generator in the frame of a simulation tool
developed to support risk analysis in a competitive electricity
environment. A multivariate Generalized Autoregressive Conditional
Heteroskedastic model has been designed in order to
allow the generation of future fuel prices paths. The model
makes use of a decomposition method to simplify the consideration
of the multidimensional conditional covariance. An
example of its application with real data is also presented.
Gonos et al. (2003)present in their paper (2004), a method
which estimates the lightning performance of high voltage transmission
lines based on the Monte-Carlo simulation technique.
On several operating Greek transmission lines, the method is applied
and showing good correlation between predicted and field
observation results. The proposed method can be used as a useful
tool in the design of electric power systems, aiding in the right
insulation dimensioning of a transmission line.
In Zhaohong and Xifan (2002) study (2002) they present a
new variance reduction technique of Monte Carlo simulation
– fission and roulette method. The proposed method reduces
the variance of simulation and speeds up the computation
dramatically.
Wehenkel et al. (1999), the authors deal with probabilistic
approach to the design of power-system special stability controls.
They used Monte-Carlo simulations, which take into ac-

Enhancement, evaluation and implementation of a load forecasting method 3
0.5
Innovations
Innovation
0
-0.5
0 5 10 15 20 25 30 35 40 45 50
Conditional Standard Deviations
Standard Deviation
0.2
0.1
0
0 5 10 15 20 25 30 35 40 45 50
Forecast of STD of Residuals
Standard Deviation
0.08
0.075
forecast results
simulation results
0 5 10 15 20 25 30 35 40 45 50
Forecast Period
Figure 3
Application of Monte Carlo simulation.
0.08
Approximate Versus Exact Secondary Standard Deviations
0.075
0.07
0.065
0.06
0.055
0.05
0.045
0.04
0 10 20 30 40 50 60 70 80 90 100
Figure 4
Graphical comparisons of the first realization of the approximate and the exact secondary conditional standard deviations.
count all the potential causes of blackouts. The approach is
tested on a large-scale study on the South–Eastern part of the
extra-high-voltage system of Electricite´ de France.
2. Methodology
A wide variety of forecasting methods are available to the
management. The evaluation of soft computing techniques
has increased the understanding of various aspects of the
problem environment and consequently the predictability
of many events. The concept of a time series, an ordered
set of observations of a time-series correspond to timetagged
indices, or observations, and correspond to sample
paths, independent realizations, or individual time series.
In any given column, the first row contains the oldest observation
and the last row contains the most recent observation.
In this representation, a time-series array is said to
be column-oriented.

4 M.R. Qader, I. Qamber
0.0755
0.075
Forecast of STD of Residuals
forecast results
simulation results
0.0745
Standard Deviation
0.074
0.0735
0.073
0.0725
0.072
0.0715
0.071
0 5 10 15 20 25 30 35 40 45 50
Forecast Period
Figure 5 Compare the first forecast output, i.e., the conditional standard deviations of future innovations, with its counterpart derived
from the Monte Carlo simulation.
1 x 10 -3 Forecast of reserve MW
0.5
0
MMSE
-0.5
-1
-1.5
-2
forecast results
simulation results
-2.5
0 5 10 15 2 2 3 3 4 4 50
Forecast Period
Figure 6 Compare the second forecast output, the minimum mean square error forecasts of the conditional mean of the Kingdom of
Bahrain reserves power series, with its counterpart derived from the Monte Carlo simulation.
In the present model, it is assumed that time-series vectors
and matrices are time-tagged series of observations. If we have
a power series, the model lets you convert it to a reserve series
using either continuous compounding or periodic compounding.
If it denotes successive power observations made at times
t and t +1asP t and P t+1 , respectively, continuous compounding
transforms a power series P t into a reserve series y t as (Bollerslev,
1987; Bollerslev, 1986; Box et al., 1994; Enders, 1995).
y t ¼ log P tþ1
P t
Periodic compounding defines the transformation as:

Enhancement, evaluation and implementation of a load forecasting method 5
0.7
Forecast of STD of Cumulative Holding Period
0.6
0.5
Standard Deviation
0.4
0.3
0.2
0.1
forecast results
simulation results
0
0 5 10 15 20 25 30 35 40 45 50
Forecast Period
Figure 7 Compare the third forecast output, cumulative holding period power reserves, with its counterpart derived from the Monte
Carlo simulation.
y t ¼ log P tþ1
1
P t
Our modeling is typically based on relatively high frequency
data (i.e. weekly observations). The models are designed to
capture certain characteristics that are commonly associated
with time series. Probability distributions for quality reserve
often exhibit fatter tails than the standard normal, or Gaussian
distribution. In addition, power time series usually exhibit a
characteristic known as volatility clustering, in which large
changes tend to follow large changes, and small changes tend
to follow small changes. In either case, the changes from one
period to the next are typically of unpredictable sign. Large
disturbances, positive or negative, become part of the information
set used to construct the variance forecast of the next period’s
disturbance. In this manner, large shocks of either sign
are allowed to persist, and can influence the volatility forecasts
for several periods.
3. Forecasting of power time series
If we treat a financial time series as a sequence of random
observations, this random sequence, or stochastic process,
may exhibit some degree of correlation from one observation
to the next. This correlation structure can be used to predict
future values of the process based on the past history of observations
(Engle, 1982; Engle et al., 1987; Glosten et al., 1993;
Hamilton, 1994). The following equation uses these components
to represent a model of an observed time series y t .
y t ¼ fðt 1; XÞþe t
where
f(t 1,X) represents the forecast, of the current reserve as a
function of any information known at time t + 1 , including
past innovations. The variable e t is the random component.
The autoregressive (AR) models include past observation of
the dependent variable in the forecast of future variances, and
for the conditional mean apply to all variance models:
y t ¼ C þ XR
i¼1
/ i y t 1 þ e t þ XM
j¼1
h j e t
j þ XNx
k¼1
b k Xðt; kÞ
With autoregressive coefficients / i , moving average coefficients
h j , regression coefficients b k , innovations e t , and reserve y t , C
represents the constant. X is an explanatory regression matrix
in which each column is a time series and X(t,k) denotes the t-
th row and k th column. Where, R and M represent the order
of the conditional mean model.
4. Probability estimation
Given models for the conditional mean and variance, and an
observed reserve series, the estimation concludes the innovations
(i.e., residuals) from the reserve series, and estimates,
by maximum probability, the parameters needed to fit the
specified models to the reserve series (Nelson, 1991).
Given the vector of current parameter values and the observed
data series, the log-probability functions conclude the
process innovations by inverse filtering (Engle, 1982; Engle
et al., 1987; Glosten et al., 1993). This inference, or inverse filtering,
operation rearranges the conditional mean equation to
solve for the current innovation e t :
X R X M X Nx
y t ¼ C þ y t / i y t 1 h j e t j b k Xðt; kÞ
i¼1
j¼1
This equation is a whitening filter, transforming a correlated
process into an uncorrelated white noise process. The logprobability
function then uses the inferred innovations e t to infer
the corresponding conditional variances r 2 t
via recursive
k¼1

6 M.R. Qader, I. Qamber
Standard Error of Forecast
0.078
0.077
forecast results
simulation results
0.076
Standard Deviation
0.075
0.074
0.073
0.072
0.071
0 5 10 15 20 25 30 35 40 45 50
Forecast Period
Figure 8 Compare the fourth forecast output, the root mean square errors of the forecasted power reserves, with its counterpart derived
from the Monte Carlo simulation.
substitution into the model-dependent conditional variance
equations. Finally, the function uses the inferred innovations
and conditional variances to evaluate the appropriate logprobability
objective function. If the Gaussian, the log-probability
function is:
LLF ¼ T 2 logð2pÞ 1 X T
2
t¼1
log r 2 t
1 X T
2
t¼1
e 2 t
r 2 t
where, T is the sample size, i.e., the number of rows in the series
y t .
5. Minimum mean squire error volatility forecasts of reserve
This is designed to minimize the variance of the estimation or
forecast error. The volatility forecasts of reserve over multi
period holding intervals. That it contains the expected stan-
1400
Cumulative Holding Period at Forecast Horizon
1200
1000
800
Count
600
400
200
0
-3 -2 -1 0 1 2 3
reserve MW
Figure 9 Histogram illustrates the distribution of the cumulative holding period reserve obtained if a quality was held for the full 52-
week forecast possibility. Notice that this histogram is directly related to the final of the root mean square error.

Enhancement, evaluation and implementation of a load forecasting method 7
1400
Simulated at Forecast Horizon
1200
1000
Count
800
600
400
200
0
-0.4 -0.3 -0.2 -0.1 0 0.1 0.2 0.3
reserve MW
Figure 10 Histogram illustrates the distribution of the single-period power reserve at the forecast possibility. Notice that this histogram
is directly related to the final of the minimum mean square error and root mean square errors.
dard deviation of reserve for assets held for one period for each
realization of series. It also contains the standard deviation of
reserve for assets held for two periods as shown in the results
obtained during the present study. Thus, last contains the forecast
of the standard deviation of the cumulative reserve obtained
if an asset was held for the entire forecast horizon.
Therefore it computes the elements of r by taking the square
root of:
" # 2 ! 2
3
X s
var t ¼ Xs
4 1 þ Xs¼1
w j Eðr 2 tþi Þ 5
i¼1
y tþ1
i¼1
j¼1
where s is the forecast horizon of interest, and w j is the coefficient
of the jth lag of the innovations process in an infinite-order
representation of the conditional mean model.
6. Simulation results
To compute the load forecasts for the Kingdom of Bahrain reserve
the power for 52 weeks for expecting the power in the future.
First setting the forecast possibility to 52 weeks (i.e., one
year), then the forecasting engine, with the estimated model
parameters, coefficient, the Kingdom of Bahrain reserve, and
the forecast possibility. Possibility = 52% which define the
forecast possibility.
This will simulate reserve forecasts of conditional standard
deviations of the residuals forecasts of the Bahrain reserve
power. Forecasts of the standard deviations of the cumulative
holding period reserve power and standard errors associated
with forecasts of reserve power.
Monte Carlo simulation uses the same estimated model
coefficient which is used in the forecast part of the data simulated,
forecasting, to simulate 20,000 realizations for the same
52 week period. In this context, referred to as dependent-path
simulation, all simulated sample paths share a common conditioning
set and evolve from the same set of initial conditions,
thus enabling Monte Carlo simulation of forecasts and forecast
error distributions. For this application of Monte Carlo
simulation, the simulation generates a relatively large number
of realizations, or sample paths, so that it can aggregate across
realizations. The following code simulates 20,000 paths as a result;
each time-series output that reserves are an array of size
possibility, 52-by-20,000.
In the present paper, we will compare data of the Kingdom
of Bahrain reserve power graphically. It compares the
forecasts results with their counterparts derived from the
Monte Carlo trial described above. Fig. 1 shows the load
forecasts of one year (year of 2002) in the Kingdom of Bahrain
which clearly shows that power consumption is high between
weeks 20 and 40 of high season. Fig. 2 is the
translation of weekly power to weekly reserve. To segment
the data in an effort to compare estimation results obtained
from a relatively stable period to those from a period of relatively
high instability. By examining the reserve power, it
can be seen there is a distinct increase in instability starting.
Fig. 3 shows application of Monte Carlo simulation, the figures
show the production of a relatively large number of sample
paths, so that it can aggregate across realizations. Because
each understanding corresponds to a time-series output, the
outputs are large. The model simulates 20,000 paths. Fig. 4
is a graphical comparison of the first realization of the
approximate and the exact secondary conditional standard
deviations reveal the distinction between automatically generated
and user-specified pre sample data. Notice that the
approximate and exact standard deviations are asymptotically
identical. The only difference between the two curves
is attributable to the transients induced by the default initial
conditions. Although the figure highlights the first realization
of conditional standard deviations, the comparison holds for
any realization and for the inferred residuals as well.

8 M.R. Qader, I. Qamber
7. Comparing forecasts with simulation results
Figs. 5–8 directly compare each of the forecast outputs, in
turn, with the corresponding statistical result obtained from
simulation. Figs. 9 and 10 illustrate histograms from which
approximate probability density functions and empirical confidence
bounds can be computed.
This illustration merely highlights the range of possibilities,
and provides a deeper understanding of the interaction between
the simulation, forecasting, and estimation model.
Fig. 5 shows the convergence of standard deviation with respect
to the forecast period. For developing the forecasting
models, the load demand data for 52 week period was tested
from the first day of January to the last day of the year 2002
which is the end of December in the Kingdom of Bahrain.
8. Conclusion
The paper presents estimation of the load of the Kingdom of
Bahrain using the Monte Carlo simulation. Satisfactory results
for one year of Bahrain network was presented and verifying
the accuracy of the method used. The presented method can
be easily used for any electric power utilities in order to predict
the electric load. The result consists of the MMSE forecasts of
the conditional standard deviations and the conditional mean
of the reserve power is modeled and illustrated. Note that the
calculation of the standard deviation is strictly correct for continuously
compounded reserve. Therefore, it is clear that the
used technique is useful tool for electric power system for load
estimation.
References
Batlle, Carlos, Barquín, Julián, 2004. Fuel prices scenario generation
based on a multivariate GARCH model for risk analysis in a
wholesale electricity market. International Journal of Electrical
Power and Energy Systems 26 (4), 273–280.
Bollerslev, T., 1986. Generalized autoregressive conditional heteroskedasticity.
Journal of Econometrics 31, 307–327.
Bollerslev, T., 1987. A conditionally heteroskedastic time series model
for speculative prices and rates of return. Review of Economics and
Statistics 69, 542–547.
Bordalo, U., Rodrigues, A., Silva, M., 2006. A new methodology for
probabilistic short-circuit evaluation with applications in power
quality analysis. IEEE Transactions on Power Systems 21 (2),
474–479.
Box, G.E.P., Jenkins, G.M., Reinsel, G.C., 1994. Time Series Analysis:
Forecasting and Control, third ed. Prentice Hall.
El-Khattam, W., Hegazy, Y., Salama, M., 2006. Investigating distributed
generation systems performance using Monte Carlo simulation.
IEEE Transactions on Power Systems 21 (2), 524–532.
Enders, W., 1995. Applied Econometric Time Series. John Wiley &
Sons.
Engle, R.F., 1982. Autoregressive conditional heteroskedasticity with
estimates of the variance of United Kingdom inflation. Econometrica
50, 987–1007.
Engle, R.F., Lilien, D.M., Robins, R.P., 1987. Estimating time varying
risk premia in the term structure: the ARCH-M model. Econometrica
59, 391–407.
Glosten, L.R., Jagannathan, R., Runkle, D.E., 1993. On the relation
between expected value and the volatility of the nominal excess
return on stocks. The Journal of Finance 48, 1779–1801.
Gonos, I.F., Ekonomou, L., Topalis, F.V., Stathopulos, I.A., 2003.
Probability of backflashover in transmission lines due to lightning
strokes using Monte-Carlo simulation. International Journal of
Electrical Power and Energy Systems 25 (2), 107–111.
Hamilton, J.D., 1994. Time Series Analysis. Princeton University
Press.
Ionescu, D.C., Ulmeanu, A.P., Constantinescu, A.C., Rotaru, I., 2006.
Reliability modelling of medium voltage distribution systems of
nuclear power plants using generalized stochastic petri nets.
Computers and Mathematics with Applications 51 (2), 285–290.
Nelson, D.B., 1991. Conditional heteroskedasticity in asset returns: a
new approach. Econometrica 59, 347–370.
Wehenkel, L., Lebrevelec, C., Trotignon, M., Batut, J., 1999.
Probabilistic design of power-system special stability controls.
Control Engineering Practice 7 (2), 183–194.
Zhaohong, Bie, Xifan, Wang, 2002. Studies on variance reduction
technique of Monte Carlo simulation in composite system reliability
evaluation. Electric Power Systems Research 63 (1), 59–64.

Journal of the Association of Arab Universities for Basic and Applied Sciences (2012) 11, 9-15
نظام إنارة مكتبي
ذو تحكم ذاتي و
الطاقة استهالك في مجدي
1
معمر طالب ،
2
نورالدين منصور
قسم
1
الهندسة الكهربائية وااللكترونية،‏
قسم
، كلية الهندسة
جامعة البحرين،‏ ص.ب 32038
،
2
الهندسة الكميائية ، كلية الهندسة ، جامعة البحرين،‏ ص.ب ، 32038 البحرين
البحرين
الملخص:‏
من دون شك أن ألشعة الشمس
فمن هذا المنطلق
المكتب.‏
مساهمة
قام الباحثون باستخدام
غير مهملة
تتبلور فكرة التحكم في تحقيق االستراتيجية التالية:‏
مستوى شدة ضوء الشمس
في تحديد كمية وشدة الضوء داخل
المحيط بالمكتب للتحكم في
المكاتب اإلدارية.‏
مستوى إنارة
حين تزداد شدة أشعة الشمس المحيط بالمكتب ينبغي
تخفيف استهالك الطاقة الكهربائية،‏ وحين تنخفض شدة أشعة الشمس المحيطة بالمكتب ينبغي رفع استهالك
الطاقة الكهربائية.‏
حالن تحكميان طبقا
وبغية تحقيق االستراتيجية السابقة
قام الباحثون باقتراح
عمليًا باستخدام برنامج حاسوبي معروف باسم
بانجاز أو تركيب دائرة كهربائية اعتمد في بنائها على عناصر الكترونية متفرقة.‏
الثالثة بميزة التحكم الذاتي.‏
عن تمخض
مع ثبات مستوى االنارة
تطبيق الحلول التحكمية
داخل المكتب.‏
بأحد مكاتب جامعة البحرين
في
ثالث حلول تحكمية عملية:‏
) ،(LABVIEW بينما طبق حل ثالث
%5.04 توفير
تتميز الحلول
التحكمية
من الفاتورة الكهربائية
M. Taleb, N. Mannsour

Journal of the Association of Arab Universities for Basic and Applied Sciences (2012) 11, 9–15
University of Bahrain
Journal of the Association of Arab Universities for
Basic and Applied Sciences
www.elsevier.com/locate/jaaubas
www.sciencedirect.com
A self-controlled energy efficient office lighting system
Maamar Taleb a, *, Noureddine Mannsour b
a Department of Electrical and Electronics Engineering, University of Bahrain, P. O. Box 32038, Isa Town, Bahrain
b Department of Chemical Engineering, University of Bahrain, P. O. Box 32038, Isa Town, Bahrain
Available online 14 December 2011
KEYWORDS
Electric energy saving;
Office lighting control;
LABVIEW
Abstract The fact that ambient sunlight can add significant contribution to the lighting level of an
office, has motivated the authors into using the level of sunlight to control the demand of the electric
lighting in an office. The control strategy is such that the level of the surrounding light increases
the supply voltage, hence electric power consumption, to the electric lighting system is reduced. Similarly,
when the surrounding sunlight decreases the supply voltage, the electric power consumption,
to the electric lighting system is increased. The objective is to save the overall electric energy used for
office lighting. Three controllers have been proposed to fulfill the previous control strategy. Two
controllers were implemented and tested using LABVIEW. A third controller designed and constructed
using discrete electronic components. All three controllers were self-regulated. The implementation
of the control strategy in a university office showed that a 5.40% saving in the electricity
bill was achieved whilst maintaining an almost constant lighting level.
ª 2011 University of Bahrain. Production and hosting by Elsevier B.V. All rights reserved.
1. Introduction
Most of the offices worldwide have shifted from using incandescent
bulbs to fluorescent lamps. The primary reason behind
such a shift is that fluorescent lamps are more energy-efficient.
As a matter of fact, standard incandescent bulbs use three to
four times more electricity than fluorescent lamps (Chugach
Electric Association, 2011). Moreover, fluorescent lamps last
up to six times longer than incandescent lamps. In spite of
* Corresponding author.
E-mail addresses: maamar@eng.uob.bh (M. Taleb), nmansour@
eng.uob.bh (N. Mannsour).
1815-3852 ª 2011 University of Bahrain. Production and hosting by
Elsevier B.V. All rights reserved.
Peer review under responsibility of University of Bahrain.
doi:10.1016/j.jaubas.2011.10.002
Production and hosting by Elsevier
the tremendous cut in the energy requirement by the fluorescent
lamps those days, research had not stopped from looking
further in saving more energy. One alternative of the saving is
the development of compact fluorescent lamps (CFLs). CFLs
own several advantages (Greenfeet, LLC, copyright 1999–
2008) when compared to their counterpart lamps: classic fluorescent
lamps as well as incandescent lamps.
The present contribution treats office lighting electric energy
saving from another perspective. Such a perspective is documented
as follows: It is well recognized that when an
employee enters his/her office, the first thing that he/she will
do is to switch-on the light and let it shining fully during the
whole working hours period. A careful glance at the working
hours period, can easily make one notice that there is an additional
free source of energy that can be considered as a second
contributor to the overall office lighting. This second contributor
consists of the surrounding natural sunlight (i.e., sunlight or
day light). The sunlight intensity is probably low at the earliest
hours of the working-hours period but starts increasing as time
passes. It reaches a maximum point around noon time. In the
afternoon, the natural sunlight starts decreasing. This
increase and decrease behaviors of the sunlight are actually

10 M. Taleb, N. Mannsour
dependent on the location of the office towards the sun
position.
This paper uses the variation of the surrounding sunlight in
saving some electric energy needed by the lighting system of an
office during working-hours periods.
2. Problem motivation and rationale
In order to evaluate the contribution of the surrounding sunlight
to the overall light of an office, a small experiment was
held in a university office. The office light is provided by 6
pairs of florescent lamps. Each florescent is rated 36 W. The
experiment consisted of recording the effects that may occur
on any light sensor device during the office working hours.
In this investigation, the office working hours were pretended
to be between 08:00 and 16:00. A light dependent resistance
(LDR) was considered to be the light sensor device. It is worth
mentioning that the LDR presents large resistance value at low
levels of light (i.e., dark environment) and small resistance value
at high levels of light (i.e., shining environment) (Radio
Spares (RS) Components, 1997).
Four LDRs are connected to four potentiometers as shown
in Fig. 1. The LDRs are located in four different places in the
office. This was done in purpose to find out which LDR was
the most sensitive to the light. The most sensitive LDR will
be taken as a reference signal in the controllers that will be discussed
later. The DC voltage supply was fixed at a 12 V. Each
potentiometer of the four legs of Fig. 1 was adjusted so that its
resistance was close to the corresponding LDR resistance value
at 08:00 on the day of the experiment. It is expected that the
voltage across the potentiometer to be near 6 V at 08:00. It
is worth stating that once each potentiometer resistance is set
at 08:00, it is left unaltered during the day of experiment.
The voltage across the four potentiometers terminals were recorded
during the time from 08:00 to 16:00 h on December 17,
2008. The day of December 17, 2008 was a clear and bright day
in the kingdom of Bahrain. Measurements were taken using
LABVIEW software facilities and PCI-6221 as a data acquisition
card (National Instruments, 2008). Voltage measurements
across the four potentiometers were recorded every second as
depicted in Fig. 2.
After a glance at the obtained patterns of the measurements,
the next remarks can be noted:
All voltage drops across the four potentiometers have been
set to be near 6 V at the start-up of the measurements (i.e.,
at 08:00).
LDR1 and LDR2 indicate that the surrounding sunlight
peaks up around 10:00.
LDR4 measurements indicate that the surrounding light
exhibits a maximum contribution at the sensor position
around 13:30. This can be justified by the fact that the
LDR4 will face the sun in the afternoon rather than the
morning. This was not the case for LDR1 and LDR2.
The contribution of the surrounding light is manifested by
4 V voltage drop between 10:00 and 16:00 for LDR1 and
LDR2. The last two LDRs seem to be more sensitive than
LDR4 and LDR3.
The main observation that can be deduced from the measurements
is that any anticipated occupant of this office will
witness more light in the morning and less light in the afternoon
but what is interesting is that the office occupant(s) will
feel comfort in both sessions. Therefore, it might be a good
idea to reduce the main electric supply partially in the morning
session and use it fully in the afternoon session.
Potentiometer 1
Potentiometer 2
Potentiometer 3
Potentiometer 4
LDR 1
LDR2
LDR 3
LDR 4
12 V
Data Acquisition Card
(PCI 6221Card
manufactured by National Instrument )
PC
Figure 1
Effect of the surrounding light on the overall office lighting system: circuit layout to record the online sunlight effects.

A self-controlled energy efficient office lighting system 11
9
Mesurements recorded on Thursday December 17, 2008
LDR4
Voltage across the potentiometer terminals
8
7
6
5
4
LDR2
LDR1
LDR3
3
8 9 10 11 12 13 14 15 16
Time (hour)
Figure 2
Effect of the surrounding light on the overall light in the office under test.
3. Control strategy
The transition from full use to partial use of the main electric
supply is possible through the application of power electronics
circuitry. This is possible through the implementation of the
circuit of Fig. 3. Fig. 3 represents actually the schematic diagram
of an AC converter. The theory and analysis of an AC
converter using a triac are documented in several power electronics
textbooks (e.g., Mohan et al., 2003). Three firing angle
controllers are suggested to control the operation of the triac
of Fig. 3.
3.1. Firing angle controller
This controller serves at monitoring the instant of firing the
gate triac with a periodic train of pulses. The controller is
designed in such a way that the firing angle can be adjusted
between 0° and 90° and between 180° and 270° during the
positive and negative cycles of the main voltage supply, respectively.
This is possible through designing a block diagram
similar to the one shown in Fig. 4a. Fig. 4a can be split into
two parts: an upper part and a lower part. The upper part guarantees
a train of pulses to triac gate when the mathematical
12 V
Office Light Level
Potentiometer 1
LDR
1
Triggering
Circuit
Firing Angle Controller
Figure 3
6 pairs of lamps
Triac
Controllable AC converter.
240 V
50 Hz
+
+
product of the main supply voltage signal with its derivative
is negative. This is possible between 90° and 180° and between
270° and 360°, respectively. Note that 0° corresponds to the
zero-crossing point of the main voltage supply. The lower part
provides a train of pulses when the absolute value of the main
supply voltage is greater than a certain level. The latter level is
actually the output of a limited integrator. The integrator is
positive and it is adjusted online during the working office
hours period. That depends on the input sign to the integrator.
The input to the integrator is a constant. It can be positive,
or negative or zero. It is positive when the overall office lighting
is above an upper limit level, negative when the overall office
lighting is below a lower limit level, and zero when the office
lighting is between the two upper and lower limits. The upper
limit and the lower limit levels correspond to V reference + DV
and V reference DV, respectively. In this paper, V reference and
DV were taken as 6 V and 0.2 V, respectively. When the voltage
across the potentiometer terminals (V potentiometer ) of the left
sensor exceeds V reference + DV (i.e., 6.2 V), the integrator output
level increases and consequently the generation of firing pulses
to the triac gate will be delayed. Delaying firing pulses generation
will lower the office light level. Similarly, when the measured
voltage across the potentiometer terminals of the left
sensor is below V reference DV (i.e., 5.8 V), the integrator output
level decreases and consequently an early generation of firing
pulses to the triac gate is noted. Early generation of firing
pulses results in an increase in the office lighting level.
Fig. 4b depicts the different waveforms that can be expected
at the output of the different blocks of Fig. 4a. In Fig. 4b, it is
assumed that the office lighting level is above an upper limit
(i.e., 6.2 V) and the firing angle needs to be increased. The
firing angle keeps increasing automatically until the office
lighting falls below a preset upper limit.
It is worth mentioning that the proposed firing angle controller
provides a zero firing angle at minimum office overall
lighting level and 90° at maximum office overall lighting level.
The firing angle controller of Fig. 4a has been translated to
a LABVIEW code. The developed LABVIEW code is used to

12 M. Taleb, N. Mannsour
Out
Towards Triac
Gate Driver
π
X
X2
2 π
3 π
ωt
4 π
Sign Indicator
Upper Part
X1
Output =1 if u ≤0
Pulses Generator
Output = 0 if u >0
X4
du
----
dt
X
X5
X2 X3
From Main
Supply
+
a
Z1
+
X6
Voltage
Transformer
Z
|u|
Y6
Output =1 if u1 ≥ u2
Lower Part
Output = 0 if u1

A self-controlled energy efficient office lighting system 13
From Sensor
(Potentiomer
Terminals)
From VT
National Instrument Data
Acquisition Card PCI 6221
+ 5 V
Optocoupler
Mosfet
+12 V
Pulse
Transformer
G
MT2
MT1
To predict the performance of the integral cycle controller
of Fig. 6a and b visualizes the expected waveforms that can
be generated at the output of the different blocks of Fig. 6a.
The waveforms are drawn by pretending a 25% value for
the duty cycle for a generated periodic pulse of frequency
2.5 Hz. The last waveform of Fig. 6b can be interpreted by
the fact that the triac of Fig. 3 will be off for 0.1 s (i.e., 0.1 s
corresponds to 5 cycles of the 50 Hz main supply) and conducting
for the following 0.3 s (i.e., 0.3 s corresponds to 15 cycles
of the 50 Hz main supply). The integral cycle controller of
Fig. 6a has been also written in another LABVIEW code. Such
LABVIEW code is insulated from the power circuit through
the hardware of Fig. 5.
Figure 5
Insulating firing angle controller from power circuit.
3.3. Conduction period controller
the duty cycle reaches 100% value, no firing pulses will be provided
to the triac gate and consequently no contribution is
marked from the main electric outlet.
The intended task from this controller is to provide conducting
and non-conducting portions for the triac during each half
cycle of the main supply. Fig. 7 suggests a practical circuit that
can provide such intended task. The task is made possible
Out
X
5
0.2 0.3
0.6 0.8
Time (s)
X3
Upper Part
Pulses Generator of
High Frequency
X2
NOT
Output =1 if u ≥ 0
X X1
Output = 0 if u < 0
Square wave
2.5 Hz
Y4
Duty Cycle
a
Lower Part
1
-0.2
y1 Y2 1 Y3 100
0.2
+ k
-----
- S
Y
0
-1
Integrator Limiter
Vreference
-5
1
0
X1
X2
1
0
6.3
6.0
1
0.3
25
%
5
5
out
X3
0.1
0.4
0.1
0.4
0.1 0.4
V potentiometer
V reference
Y1
Y
Y2
Y3
0.1
0.4
0.1
0.4
b
0.5
0.5
0.5
0.5
0.5
0.8
Time (s)
0.8
Time (s)
0.8
Time (s)
Time (s)
Time (s)
0.8
Time (s)
0.8
Time (s)
Figure 6
Integral cycle controller: (a) control block diagram, (b) expected waveforms at different stages of the control block diagram.

14 M. Taleb, N. Mannsour
Vrectified
Comparator
+VCC
+
-
R discharching
B
V control
B’
V measured
NO
Oscillator
Timer
+VCC
8
4
3
+VCC
7
pulses
6
2 1 5
Out
Vs
π
2π
V up
3π
V measured
4π
5π
6π
ωt
Vc
V down
A A’
R charging
NO
X1
X2
ωt
ωt
+VCC
Upper Relay
Upper Comparator
+VCC
LED
+
-
X1
+VCC
X2
+
LED
-
Lower Comparator
LDR
Lower Relay
V rectified
V control
Vs
π
π
2π
2π
3π
3π
4π
4π
5π
5π
6π
6π
ωt
ωt
Pulses
+VCC
Vup
+VCC
Vdown
π
2π
3π
4π
5π
6π
ωt
Vs
Out
L
240 V
N
π
2π
3π
4π
5π
ωt
6π
Figure 7
diagram.
Conduction period controller: (a) control block diagram, (b) expected waveforms at different stages of the control block
through the result of comparing a rectified signal of the main
voltage supply with a voltage level across a capacitor. The voltage
level across the capacitor is monitored by the operation of
two comparators. The principle of operation of the different
active devices in the figure (i.e., Fig. 7a) can be obtained from
Maini (2007).
When the office lighting exceeds a pre-set upper limit (i.e.,
6.2 V), the upper comparator will allow the upper relay to close
its contacts and consequently the capacitor voltage starts
increasing through the charging resistance (R charging ). Increasing
the capacitor voltage shortens the conducting periods of the triac.
Similarly, when the office lighting falls below a pre-set lower
limit (i.e., 5.8 V), the lower comparator allows the lower relay to
close its contacts and consequently the capacitor voltage starts
decreasing through the discharging resistance (R discharging ).
Decreasing the capacitor voltage level extends the duration of
the triac conduction periods. When the office lighting is between
the preset upper and lower limits, both relays contacts are found
open and there is a no-need to either shorten or extend the conduction
periods.

A self-controlled energy efficient office lighting system 15
Table 1
Controller
Controllers performance.
Increasing the conducting period means that more contribution
of the main supply to the office lighting is expected
and decreasing the conducting period means that less contribution
of the main supply is expected.
Fig. 7b depicts the different signals that can be expected at
the output of the different block of Fig. 7a. The output port
termed ‘‘Out’’ in Fig. 7a is linked to the gate of the triac of
Fig. 3 through the insulating gate circuit of Fig. 5.
4. Controllers performance
Electric energy Electric energy
consumed by the saving index (%)
office light system
No-controller 2.98 kW h –
Firing angle controller 2.90 kW h 2.68%
Integral cycle controller 2.82 kW h 5.37%
Conduction period controller 2.85 kW h 4.36%
The main target of this investigation is to take advantage of
the surrounding sunlight in lighting up an office. Excess
of the surrounding sunlight means that a partial cut of the
main electric supply can be practiced and therefore some
savings in electric energy consumption can be expected. The
partial cut is done by field implementation of the previous
three controllers and testing their performance. The performance
consists of recording how much electric energy can be
consumed by the electric lighting system of the office during
the office working hours period. Table 1 reflects energy consumption
when testing the previous three controllers.
As seen from the obtained results, a 5.37% of electric
energy can be saved when using the integral controller. The
saving energy index in the third column of Table 1 was calculated
as: (Energy consumed without using controller Energy
consumed when using a particular controller) * 100/(Energy
consumed without using controller).
It should be emphasized that the energy saving is reached
while the office lighting level is kept between two pre-set upper
and lower limits (i.e., 6.2 V and 5.8 V, respectively). Note that
the two pre-set limits do not harm the comfort of the anticipated
office occupants. The drawback that was encountered
when implementing such controllers is the creation of some
minor flickering in the florescent lamps. Such phenomenon
has been relatively visible when implementing the integral cycle
controller.
5. Conclusion
The presence of the natural sunlight around an office has a significant
contribution to the overall lighting of the office. The
contribution consists of cutting partially some of the electric
energy consumption needed presumably by the office lighting
system. The partial cut in the electric energy consumption in
this paper has been fulfilled by field implementation of three
suggested controllers. In performing the partial cut in the electric
energy consumption, a 5.37% as an index of electric energy
saving has been reached whilst the overall light level in the
office is kept nearly comfortable to the office occupants. Some
flickering phenomenon has been encountered when implementing
the three controllers. The idea presented in this paper can
be extended to a number of real life processes that may require
a controlled light level to produce a desired optimum output/
level.
Acknowledgment
The financial assistance of the Deanship of Research at
University of Bahrain in performing the different tasks of
the present contribution is appreciated by the authors.
References
Chugach Electric Association, Alaska, USA.
(accessed 4.08.11).
Greenfeet, LLC (copyright 1999–2008). The Benefits of Compact
Fluorescent Lighting, California, USA. (accessed 4.08.11).
Maini, Anil K., 2007. Digital Electronics: Principles, Devices, and
Applications. John Wiley & Sons Ltd, West Sussex, England.
Mohan, N., Undeland, T., Robbins, W., 2003. Power Electronics:
Converters, Applications, and Design. John Wiley & Sons Ltd.,
West Sussex, England.
National Instruments Corporation (2008). Introducing LABVIEW
8.6. Austin, Texas, USA.
Radio Spares (RS) Components, Part 232-3816 (March 1997), Light
Dependent Resistors.

Journal of the Association of Arab Universities for Basic and Applied Sciences (2012) 11, 16-20
)C – Mn(
عملية الكسر لفوالذ الكربون –
المنجنيز
الهش بالهيدروجين
نور الدين
سعيداني،‏ عبدالقادر ميحي،‏ رشيد بن بوتة
قسم الميكانيك،‏ كلية التكنولوجيا،‏ جامعة باتنة،‏ باتنة 00000،
الجزائر
و
الملخص:‏
تم فحص بنية عينات تكسرت عن طريق اختبار إجهاد الشد بسرعة تشوه بطيئة،‏ بهدف دراسة أصناف
الكسر ‏)التقصف(‏ باستخدام مجهر مسح إلكتروني.‏
أرشدت هذه الدراسة إلى تحديد ثالثة أصناف من العينات:‏ عينات غير هشة،‏ عينات خفيفة الهشاشة
وعينات هشة جدا.‏ وتتألف الفئة األولى من عينات االختبار التي تمت تجربتها في الهواء بجهد
08.0-
08.0-
08.0-
فولط مع معدل الهش
فولط.‏ وذلك بسبب هشاشة
08.0 ≥
.08..
كما تم اختبار العينات خفيفة الهشاشة بجهد
أما بالنسبة للعينات المعنية بنسبة الهش أقل من
08..
فتدخل في الفئة
ذات العينات الهشة جدا.‏
أثبتت دراسات صور االنكسار أن هش الفوالذ الصلب ناتج عن الهش بواسطة الهيدروجين.‏ كما لوحظ
أن البنية ‏)بين الحبيبات وعبر الحبيبات(‏ لمقاطع االنكسار،‏ بالنسبة للفوالذ الهش،‏ هي نموذجية ودالة
الهش بالهيدروجين.‏
N. Saidani et al.

Journal of the Association of Arab Universities for Basic and Applied Sciences (2012) 11, 16–20
University of Bahrain
Journal of the Association of Arab Universities for
Basic and Applied Sciences
www.elsevier.com/locate/jaaubas
www.sciencedirect.com
ORIGINAL ARTICLE
Fracture process of C–Mn steel embrittled by hydrogen
N. Saidani, A. Mihi, R. Benbouta *
University of Batna, Faculty of Technology, Mechanical Engineering Department, Batna 05000, Algeria
Available online 31 January 2012
KEYWORDS
Fracture;
Hydrogen embrittlement;
Morphologies;
Fracture modes;
Scanning electron microcopy
(SEM)
Abstract Fracture morphologies of tested specimens, by means of the slow strain rate tensile testing,
were examined to study fracture modes by using scanning electron microscopy.
This study has led to the determination of three categories of specimens: unembrittled specimens,
slightly embrittled specimens and severely embrittled specimens. The first category of unembrittled
specimens includes specimens tested in air, at potentials of 0.80 and 0.85 V (SCE) with embrittlement
ratio (ER) P 0.97. In the category of specimens slightly embrittled, only the specimen
tested at 0.9 V with an embrittlement ratio (ER) of 0.69 is included. The last category of severely
embrittled specimens includes the specimens with embrittlement ratio (ER) < 0.69.
The fractographic studies are consistent with the embrittlement of steel being due to hydrogen
embrittlement. The intergranular and transgranular quasicleavage fracture surface morphologies
observed with embrittled specimens are typical and characteristic of hydrogen embrittlement.
ª 2012 University of Bahrain. Production and hosting by Elsevier B.V. All rights reserved.
1. Introduction
* Corresponding author. Tel./fax: +213 0 33 81 21 43.
E-mail address: r_benbouta@yahoo.fr (R. Benbouta).
1815-3852 ª 2012 University of Bahrain. Production and hosting by
Elsevier B.V. All rights reserved.
Peer review under responsibility of University of Bahrain.
doi:10.1016/j.jaubas.2012.01.001
Production and hosting by Elsevier
The detrimental effect which hydrogen produces in metals,
generally known as hydrogen embrittlement (HE), has always
been one of the main problems of practical and theoretical
material technology of corrosion and protection of metals.
Hydrogen is the cause of damage whenever metal hydrogen
systems are involved in the production, transport and storage
of hydrogen, or fluids containing hydrogen, and in the presence
of electrochemical processes such as pickling, electroplating,
cathodic protection and corrosion. Hydrogen when
present either as an external gas environment or as a dissolved
proton can produce internal cracking or a dramatic loss of
toughness in a variety of metals (Takeda and McMahon,
1981; Gooch, 1974; Woodward and Procter, 1988; Hirth and
Johnson, 1976; Luu and Wu, 2001; Wu and Wu, 2002).
When considering the hydrogen embrittlement phenomenon,
one of the areas that is of most interest is the mode of
hydrogen fracture.
In the present work the objective was to study the fracture
process of the specimens tested under slow strain rate testing
(SSRT).
2. Experimental procedure
2.1. Material
The material investigated in the present study was low carbonmanganese
structural steel BS 4360 grade 50D. The nominal
composition of this material and its mechanical properties in
the condition in which it has been tested are given in Table 1.
The cylindrical tensile specimens with a 25.0 mm gauge length

Fracture process of C–Mn steel embrittled by hydrogen 17
Table 1 Mechanical properties and chemical composition of
steel.
Mechanical properties Heat treatment
r 0.2 = 1220 MPa Austenitization for 1 min at 1200 °C
U.T.S = 1440 MPa Water quench
RA = 48% Tempered for 30 min at 170 °C
Chemical composition wt%
C Si Mn S P Ni Cr Mo
0.16 0.34 1.44 0.011 0.026 0.03 0.06

18 N. Saidani et al.
3.1.2.3. Tests at 0.95 to 1.3 V. The tests carried out at
potentials of 0.95 to 1.3 V showed high degree of embrittlement
(ER ranged from 0.063 to 0.323). Examination of the
fracture surfaces indicated similarities between the fracture
morphologies. The fracture surfaces appeared to have a flat
fracture profile normal to the loading direction and shear type
fracture oriented at about 45° to the tensile axis. Typical photomicrographs
of fracture are shown in Fig. 5.
In general, the fracture surfaces consisted mainly of a large
ductile region and small brittle area. The brittle area was generally
localized at or near the edge of the fracture surface with
a predominantly intergranular cracking along the prior austenite
grain boundaries and limited areas of quasicleavage. Fig. 6
is characteristic of the features observed on many fracture surfaces
in this potential range. It was noticed that as the potential
became more negative the proportion of the brittle region
increases.
4. Discussion
Figure 3 SEM photomicrograph of fractured specimen tested at
0.85 V (SCE).
4.1. Fracture process
4.1.1. Unembrittled specimens
All these specimens fractured in a similar pattern of microvoids
coalescence. Usually, the microvoids nucleate at regions
of highly localized plastic deformation such as inclusions and
grain boundaries. As the stress on the specimen increases,
the microvoids expand and intersect one another and finally
break up when the reduced cross sectional area cannot withstand
the load any longer.
4.2. Slightly embrittled specimens
(a) Gauge section
(b) Fracture surface edge
Figure 4 SEM photomicrographs of the gauge section and
fracture surface edge of steel at 0.9 V (SCE).
dimples contained in the central cup of the fracture surfaces is
shown in Fig. 2. These dimples are the result of the growth and
coalescence of microvoids which nucleate at particles such as
inclusions and precipitates.
3.1.2. Fracture in 3.5% NaCl
3.1.2.1. Tests at 0.8 and 0.85 V. For the tests performed at
0.8 and 0.85 V the fracture surface of specimens had also a
cup and cone appearance similar to that obtained in the air
test, Fig. 3.
3.1.2.2. Test at 0.9 V. In this test, some embrittlement was noticed.
Failure occurred with an amount of plastic deformation
lower than that observed in tests in air, and at 0.8 and
0.85 V, Fig. 4a. The fracture surface consisted of a ragged
fracture path and smoother fracture path inclined at about
45° from the loading direction. A few patches, consisted
predominantly of intergranular cracking along the prior
austenite grain boundaries, were observed at the edge of the
ragged fracture path. A photomicrograph of the brittle area
is shown in Fig. 4b.
In this case, brittle type of failure, predominantly intergranular
cracking along prior austenite grain boundaries and some quasicleavage
features, accompanied the ductile type of failure such
as dimples and ductile tearing. The proportion of the brittle region
was minimal, only one or two patches localized at the
edges of the specimen. It is believed that the presence and
growth of these brittle types of fracture cause the cross section
of the specimen, already reduced by necking, to be reduced even
more, and thus, the specimen will fail earlier than in their
absence. Because of the limited amount of hydrogen available
under these conditions, the cracks do not grow long enough
to cause an earlier reduction in the net cross sectional area.
4.3. Severely embrittled specimens
In this category of tests, the hydrogen availability is very high,
it diffuses into steel through the lattice and accumulates at defect
sites such as dislocations, inclusions, grain boundaries,
microvoids, phase interface and carbides. Its interaction with
certain of these defects results in intergranular or transgranular
quasicleavage cracking. Since the availability of hydrogen is
high, the number of sites for crack nucleation increases and
they grow long enough so that they could link more easily,
resulting in a surface covered with a large fraction of brittle
types of failures. Also, as the cracks grow faster, the reduction
in the net cross sectional area occurs at an earlier stage than
when insufficient hydrogen is available.
In summary the reduced ductility of the C–Mn structural
steel when tested in NaCl solution at cathodic applied

Fracture process of C–Mn steel embrittled by hydrogen 19
(a) Gauge section (- 1. 1 V ) (b) Fracture surface(- 1. 1 V )
(c) Gauge section (- 1.3 V ) (d) Fracture surface(- 1.3 V )
Figure 5 Typical SEM photomicrographs of the gauge sections and fracture surfaces of specimens tested at potentials between 0.95
and 1.3 V (SCE).
(a) Tested at –0.95 V
(b) Tested at – 1.1 V
(c) Tested at – 1.3 V
Figure 6 Selected SEM photomicrographs of the fracture surface edge of specimens tested at potentials between 0.95 and 1.3 V
(SCE).

20 N. Saidani et al.
potentials is the result of the presence of mainly intergranular
cracks induced by cathodically evolved hydrogen. The hydrogen
which has diffused through the lattice accumulates at susceptible
interfaces, and probably lowers the cohesive strength of
the lattice after a critical concentration has been reached, thereby
initiating an embrittling event at room temperatures in
ductile steel (Yoshino and McMahon, 1974; Wang et al., 2007).
5. Conclusion
This work is devoted to fractographic investigation of C–Mn
structural steel under slow strain rate tensile testing. Examination
of the fracture surfaces using SEM revealed the following
results:
1. The intergranular and transgranular quasicleavage fracture
surface morphologies observed with embrittled specimens
are typical and characteristic of hydrogen embrittlement.
2. The reduction in ductility of steel is attributed to the
appearance of brittle modes of fracture such as intergranular
and transgranular quasicleavage features on the fracture
surface.
References
Gooch, T.G., 1974. Stress corrosion cracking of welded joints in high
strength steels weld. Welding Journal 53, 2877.
Hirth, J.P., Johnson, H.H., 1976. Hydrogen problems in energy related
technology. Corrosion 32, 3.
Luu, W.C., Wu, J.K., 2001. Influence of aluminium content on
retarding hydrogen transport in Fe–Al binary alloys. Corrosion
Science 43, 2325.
Takeda, Y., McMahon, C.J., 1981. Strain controlled vs stress
controlled hydrogen induced fracture in a quenched and tempered
steel. Metallurgical Transactions 12A, 1255.
Wang, M., Akiyama, E., Tsuzaki, K., 2007. Effect of hydrogen on the
fracture behavior of high strength steel during slow strain rate test.
Corrosion Science 49, 4081.
Woodward, J., Procter, R.P.M., 1988. Fatigue of offshore structures.
In: Dover, W.D., Glinka, G. (Eds.), Proceedings of International
Conference, London.
Wu, T.I., Wu, J.K., 2002. Effects of thiourea and its derivatives on the
electrolytic hydrogenation behavior of Ti–6Al–4V alloy. Materials
Letters 53, 193.
Yoshino, K., McMahon Jr., 1974. The cooperative relation between
temper embrittlement and hydrogen embrittlement in a high
strength steel. Metallurgical Transactions 5A, 363.

Journal of the Association of Arab Universities for Basic and Applied Sciences (2012) 11, 21-26
قياسات األشعة في مياه الشرب في منطقة النصر بغزة
ماهر عمر الغصين،‏
عبد القادر أبوشمالة
الجامعة اإلسالمية
في غزة،‏
قسم الفيزياء،‏ ص.‏ ب 801،
فلسطين غزة،‏
الملخص:‏
إن األشعة المؤينة تأتي من الكون ومن األرض و حتى من داخل أجسامنا،‏ فهي موجودة في الهواء الذي
نتنفسه وفي الطعام الذي نأكله وفي الماء الذي نشربه وفي مواد البناء التي نبني بها بيوتنا.‏
ان التعرض لغاز الرادون ومخلفاته يعتقد بأنه يعمل على زيادة خطر االصابة بالعديد من انواع السرطان
ومنها سرطان الرئة في حال استنشاق الغاز.‏ أما في حال تناول ماء يحتوي على غاز الرادون فإنه يعتقد
بان يكون مصاحبا الى زيادة خطورة االصابة بأورام للعديد من االعضاء الداخلية و خاصة المعدة.‏
في هذه الدراسة،‏ لقد تم قياس شدة النشاط اإلشعاعي لجسيمات ألفا ويبتا وأشعة جاما في مياه الشرب في
منطقة النصر شمال غرب مدينة غزة
.
للقيام بهذا العمل تم استخدام كاشف المسارات النووية
)CR-93(
وبعض الكواشف األخرى مثل عداد جيجر وصوديم أيودين.‏ متوسط النشاط اإلشعاعي لجسيمات ألفا كان
95.53
بيكرل لكل متر مكعب
,
لكل متر مكعب وأصغر قيمة كانت
أي مايعادل
تعرض وتقارن بالمتوسط العالمي وهو
االشعاعي.‏
0.35.
بيكو كوري لكل لتر,‏ أكبر قيمة كانت
46.46
46.43
55
بيكرل
بيكرل لكل متر مكعب ‏.النتائج من الكواشف األخرى سوف
بيكو كوري لكل لتر,‏ جميع النتائج تدل علي تدني النشاط
M.O. El-Ghossain, A.A. Abu Shammala

Journal of the Association of Arab Universities for Basic and Applied Sciences (2012) 11, 21–26
University of Bahrain
Journal of the Association of Arab Universities for
Basic and Applied Sciences
www.elsevier.com/locate/jaaubas
www.sciencedirect.com
ORIGINAL ARTICLE
Radioactivity measurements in tap water in Gaza Strip
(Al-Naser Area)
Maher O. El-Ghossain *, Abedalqader A. Abu Shammala
Physics Department, The Islamic University of Gaza, Gaza, Occupied Palestinian Territory
Available online 23 November 2011
KEYWORDS
CR-39;
Tap water;
Radiation;
Alpha concentration
Abstract Ionizing radiation comes from outer space (cosmic), the ground (terrestrial), and even
from within our own bodies. It is present in the air we breathe, the food we eat, the water we drink,
and in the construction materials used to build our homes. Exposure to radon and its progeny is
believed to be associated with increased risks of several kinds of cancer. When radon or its progeny
is inhaled, lung cancer accounts for most of the total incremental cancer risk. Ingestion of radon in
water is suspected of being associated with increased risk of tumors of several internal organs, primarily
the stomach.
In this work, the activity of alpha, beta and gamma radiation, in tap water in the north-east of
Gaza (Al-Naser area) were measured. For this purpose we used a solid state nuclear track detectors
(CR-39) and some other detectors (Geiger counter, NaI detector). The average gross alpha concentration
from C4-39 is 35.50 Bq/m 3 (0.95 pci/L), the maximum concentration is 64.67 Bq/m 3 , and
minimum concentration is 24.20 Bq/m 3 . Results obtained from all detectors, and their methods will
be shown, and compared with the word average of 15 pci/L, all results indicate low level of activity.
ª 2011 University of Bahrain. Production and hosting by Elsevier B.V. All rights reserved.
1. Introduction
Most water sources have very low levels of radioactive contaminants
(radio nuclides), levels low enough to not be considered
a public health concern. Radio-nuclides emit ‘‘ionizing radiation’’,
a known human carcinogen, when they naturally decay.
* Corresponding author.
E-mail address: ghossain@iugaza.edu.ps (M.O. El-Ghossain).
1815-3852 ª 2011 University of Bahrain. Production and hosting by
Elsevier B.V. All rights reserved.
Peer review under responsibility of University of Bahrain.
doi:10.1016/j.jaubas.2011.10.003
Production and hosting by Elsevier
Long-term exposure to radionuclides in drinking water may
cause cancer. Of particular concern are naturally occurring
uranium and the naturally occurring radium isotopes, radium-226
and radium-228, which have been observed to accumulate
to levels of concern in drinking water sources. Most of
the naturally occurring radionuclides are alpha particle emitters
(e.g., the uranium isotopes and radium-226), naturally
occurring beta particle emitters do occur (e.g., radium-228
and potassium-40) (Environmental Protection Agency (EPA),
2000; Beir, 2000). The source of naturally occurring radionuclides
is the earth’s crust. Among these radionuclides there exist
three radioactive series originating from 238 U, 235 U and 232 Th
being one of the most abundant sources of naturally occurring
radioactivity, the 238 U series has been widely investigated.
Exposure to radionuclides from drinking water results in
the increased risk of cancer. The radioactive particles (alpha,
beta) and gamma photons emitted by radionuclides are called
‘‘ionizing radiation’’ because they ionize (‘‘destabilize’’) nearby

22 M.O. El-Ghossain, A.A. Abu Shammala
atoms as they travel through a cell or other material. In living
tissue, this ionization process can damage chromosomes or
other parts of the cell. This cellular damage can lead to the
death of the cell or to unnatural reproduction of the cell. Exposure
to elevated uranium levels in drinking water has been
shown to lead to changes in kidney function that are indicators
of potential future kidney failure (Beir, 2000; Sources and
health effect of ionizing radiation 1980).
EPA has promulgated a limit for uranium as required by
the 1986 amendments to the Safe Drinking Water Act. The
current standards (‘‘Risk Assessment of Radon in Drinking
Water’’, released September 15, 1998,) are: combined radium
226/228 of 5 pci/L; a gross alpha standard for all alphas of
15 pci/L, not including radon and uranium; a combined standard
of 4 mrem/year for beta emitters (Risk assessment of radon
in drinking water, 1998).
2. Experimental methods
Samples were collected from 40 places, from the north-west region
of Gaza city, Al-Naser region of Gaza, which was divided
into four regions in our survey, included Nasser west (A), Nasser
east (B), Nasser shakhradwan (C), Nasser south (D). We
have obtained ten samples from the houses of each area. After
that, each sample was put in a one liter plastic jar to do the test
of radiation activity, the detectors that used for making the
measurements are:
(a) Solid State Nuclear Track Detectors (SSNTDs) are passive,
low cost, long term method, most widely used for measuring
radon and can be used for site assessment both indoors and
outdoors. (Durani and Ilic, 1997).
The detectors are placed inside the dosimeters 1.5 cm above
water. Detectors are usually exposed for 2–12 months. When
alpha particles from the decay of radon and its progeny strike
the detector, they cause damage tracks. After the exposure, the
detector is chemically treated and the number of tracks over
area counted by an optical microscope and radon concentration
or gross alpha concentration is determined (David Bodansky
et al., 1989). The water samples are placed in a calibrated
(El-Ghossain and Abusaleh, 2007) plastic cup with plastic cover,
the diameter of the cover equals 6 cm and the height of the
cup is 11 cm as shown in Figs. 1 and 2. The CR-39 detector is
fixed under the cover facing the water sample and the radium
source at the same distance of 1.5 cm, same volume, same
geometry, and same temperature.
The detector should remain undisturbed above the sample
for at least 3 weeks. Solid State Nuclear Track Detector
(CR-39) is used to measure Radon-222 or gross alpha concentration
in water, soil & air at the collected sample. Each sample
was put inside the cup as shown in Fig. 2. Forty detectors were
exposed to forty samples which concern the north-west region
Figure 1
Measurement technique for a solid radium source.
Figure 2 Measurement technique using CR-39 to measure alpha
activity in water.
of Gaza Strip. This distribution of detectors is based on the
nature of the tap water type and geological location. The
detectors are left in isolated place in the laboratory, about
74 days during the months April, May and June of 2005; this
is the exposure time to allow radon gas to come to an equilibrium
level with radioactive parents. After the exposition was
finished, the forty detectors were collected and chemically
etched using a 6 M (Mole) solution of NaOH, at the temperature
of 70 °C, for 6 h, (standard etching condition). The CR-39
detectors were mounted vertically in a stainless steel spring and
then immersed in the etching solution. At the end of the etching
process the detectors were washed thoroughly with distilled
water and then left to dry. Tracks in each detector counted
visually using an optical microscope with a power of
(40 · 10). We counted the average number of tracks in 1 cm 2 .
(b) Another method used to measure alpha and beta activity
in water samples was using the Electra Plus (DP6AD, measured
CPM as Geiger counter, LLD 3-12 CPM) (Nuclear
Energy and Radiation Protection (NERP), 2005). It is a portable
rate meter based on the variety of GM and scintillation
probes. A rectangular wooden box was filled with a water sample.
The scintillation probes were put on the surface of the
water sample the window area equals to 100 cm 2
(c) Also field space digital spectrometer (Dose rate 10 nSv/
h-10 Sv/h) (Nuclear Energy and Radiation Protection
(NERP), 2005) was used to measure the activity of gamma
radiation in water. The probe of the device was put over the
surface of the water. The distance between the probe and the
water sample in the cup equals 0 cm.
(d) The scintillation counter (Na I) (Nuclear Energy and
Radiation Protection (NERP), 2005) is a very common tool
in nuclear and particle physics. It is used for measuring the
energies of gamma-ray photons and other elementary particles
(Bell, 2005). The intensity of the light is proportional to the
amount of energy deposited in the crystal by radiation. The
cup of the sample was used to taking a spectrum which resulted
from the water by using scintillation counter where
the probe of the device was put on the surface of water. The
distances between the probe and the water sample in the cup
equals 1 cm. The measurements obtained from the scintillation
counter confirm there is low level radiation of gamma radiation
in the water in north-west of Gaza Strip. The basic technique
for this measurement is to count the number of pulses
during a fixed time interval as a function of pulse height,
and make a graph of the number of pulses versus pulse height.
(e) Geiger-Mu¨ller counters are used where the mechanism
and methods are based on the interaction of the radiation with
matter. Since ionization is an important process for radioactivity,
most detectors exploit the signals generated due to ions

Radioactivity measurements in tap water in Gaza Strip (Al-NASER) 23
Table 1 Final results for the four regions are of min, max and mean (E) concentrations from CR-39 detectors for (A), (B), (C) and (D)
regions.
Location No. of detectors Min. concentr. (Bq/m 3 ) Max. concentr. (Bq/m 3 ) E (Bq/m 3 ) S.D. (Bq/m 3 )
A 10 21.32 46.33 32.59 1.77
B 10 24.19 71.34 33.08 3.10
C 10 24.22 103.73 45.59 7.60
D 10 24.20 38.95 30.48 1.40
Average 24.20 64.67 35.50 3.45
and electrons all these detectors calibrated with normal radioactive
sources Co, Cs, and Na.
3. Calculations of gross alpha concentration using CR-39
Gross alpha contamination (El-Ghossain and Abusaleh, 2007)
in water sample is measured in terms of Bq/m 3 . Determination
of gross alpha concentration C w and the standard deviation r
(S.D.) in a sample of water using nuclear track detector is done
by the following Eq. (1).
Bq
C w ¼
C
RT R qw
ð1Þ
m 3 q R Tw
sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
P n
k
r n ðS:D:Þ ¼
ðX k
XÞ 2
ð2Þ
n 1
where C w , Concentration of activity of 222 Rn in a water sample;
C R , Concentration of activity of 226 Ra (solid radon source)
equal 800 Bq/m 3 ; q R , Track density (number of tracks/m 2 )in
detectors exposed to 226 Ra; T R , Exposure time (in days) of
detectors exposed to 226 Ra, equal 72 days; q w , Track density
(number of tracks/m 2 ) in detectors exposed to water samples;
T w , Exposure time (in days) of detectors exposed to in water
samples, equal 74 days; X K , Activity concentration of a sample;
X, Mean activity concentration of n samples; N, number
of samples and r n (S.D.): standard de´viation.
4. Calibration of CR-39 detectors
Two detectors were exposed to a known activity of 226 Ra (solid
radon source) for a determined period of time. Then these
detectors were treated by chemical etching. The average numbers
of tracks/cm 2 were calculated. These detectors were inserted
in the same volume (plastic cup) of the investigated
sample, so they considered as a calibration standard. (El-
Ghossain and Abusaleh, 2007; Raed M. Abusaleh 2005; Mahmoud
Rasas, 2003; Nabil Hamed, 2005). Similar method is
also used for detector technique as in (El-Ghossain and Abusaleh,
2007) to determine the calibration constant (factor) K.
This is derived by dividing the track density by the total exposure
of radon source as in Eq. (3).
K ¼
C RT R
q R
; ð3Þ
Then Eq. (1) for radon concentration becomes as follows.
Bq q
C w ¼ K w
m 3 1;2
ð4Þ
T w
where
k 1;2 ¼ðk 1 þ k 2 Þ=2
The calibration factor (K) is determined, where two CR-39
detectors are exposed to 226 Ra (Radium Source) of activity
concentration 800 Bq/m 3 (from factory) for 72 days. The calibration
process for detectors used in this survey was carried
out at the nuclear laboratory at physics department in The Islamic
University of Gaza (IUG). The density of tracks for the
two detectors equals 19.6 · 10 6 tracks/m 2 and
18.6 · 10 6 tracks/m 2 , and the average calibration factor K is
3.06 · 10 3 [Bq/m 3 day/tracks/m 2 ], and the standard deviation
is 10.5%. Substituting calibration constant in equation, the
activity concentration of alpha particles in water becomes:
Bq
C w ¼ 3:06 10 3 q w
ð5Þ
m 3
T w
Where 1 pci/L = 37 Bq/m 3 is used as conversion unit. E in the
Table 1 is the average concentration and (S.D.) is the standard
deviation.
4.1. Results from CR-39 detector and other detectors
Gross alpha concentration in water samples were calculated
using Eq. (5) for various locations. The minimum and the maximum
gross alpha concentration in tap water samples measured
in Bq/m 3 units are tabulated in the Table 1 as well as
the mean value of gross alpha concentration (E) and Standard
Deviation (S.D.) for each location in this study which is mentioned
(El-Ghossain and Abusaleh, 2007).
The gross alpha concentration for each location was calculated
by summing individual gross alpha concentration values
of each detector, and the sums of the values were divided by
the total number of detectors, results shown in Table 2. The
standard deviation was also (El-Ghossain and Abusaleh,
2007) calculated by Eq. (2). Fig. 3 shows the average gross alpha
concentration for C and B locations found higher than D.
The results indicate the range: from minimum 24.20 Bq/m 3 to
maximum 64.67 Bq/m 3 in gross alpha concentration in each
location which is very low level radiation, if to compare with
the world average of 10 kBq/m 3 . This variation in gross alpha
concentration inside the locations is mainly due to the different
places, and different contamination level of tap water from
environment.
The results obtained from field space mentioned above
showed the relation between the gamma activity in water sample
in unit of (n Sv/h) as in Fig. 4, the minimum, maximum
gamma concentration in tap water, mean value concentration
and standard deviation, we see that, gamma activity in all Naser
having the same values due mainly to the same exposed
background radiation.
Results of the alpha activities in water sample in unit of
(CPS) (which can be converted CPM) obtained from Electra

24 M.O. El-Ghossain, A.A. Abu Shammala
Table 2 All results calculated from CR-39 for (A), (B), (C)
and (D) regions.
Cw Bq/m 3 No. of tracks 1 cm 2 Slides no. Regions
24.19 59 1 Part ‘‘A’’ (Nasser West)
39.77 97 2
27.06 66 3
38.13 93 4
31.98 78 5
21.32 52 6
31.98 78 7
33.21 81 8
46.33 113 9
31.98 78 10
31.16 76 11 Part ‘‘B’’ (Nasser East)
24.19 59 12
25.42 62 13
71.34 174 14
27.88 68 15
24.19 59 16
25.42 62 17
38.13 93 18
38.13 93 19
25.01 61 20
31.98 78 21 Part ‘‘C’’ (Nasser South)
74.21 181 22
27.88 68 23
27.47 67 24
37.72 92 25
27.06 66 26
24.19 59 27
27.88 68 28
103.73 253 29
73.80 180 30
38.95 95 31 Part ‘‘D’’
24.19 59 32 (Nasser Shakhradwan)
27.06 66 33
30.75 75 34
24.19 59 35
37.31 91 36
35.67 87 37
28.29 69 38
27.06 66 39
31.16 79 40
35.50 86.50 Mean value ‘‘E’’
3.45 7.19 Standard deviation
Gross Alpha Contamination(Bq/m3)
120
100
80
60
40
20
0
Figure 3
A B C D Avg
The Regions of Nasser
Min.con.
Max.con.
Mean v."E"
S.D.
Gross alpha concentration in each location and S.D.
Gamma contamination (nSv/h)
80
70
60
50
40
30
20
10
0
A B C D avg
The Region of Nasser
min.con
max.con
E
S.D
Figure 4 Gamma concentration (nSv/h) in each location and S.
Alpha Activity (C.P.S)
Beta Activity (C.P.S)
0.07
0.06
0.05
0.04
0.03
0.02
0.01
0
Figure 5
4
3.5
3
2.5
2
1.5
1
0.5
0
Figure 6
A B C D Avg
The Regions of Nasser
Alpha activity in Nasser regions (Electra Plus).
A B C D Avg
The regions of Gaza
min
max
mean
S.D
min.con
max.con.
E
S.D.
Beta activity in Nasser regions (from Electra Plus).
Plus and the relation among regions are shown in the Fig. 5.
We can see that the alpha activity in Nasser Shakhradwan
(C) is greater than in other regions and in Nasser East (B) –
lower than in other region in activity values and the difference
is still less than the standard deviation.
Fig. 6 shows results of the beta activity in water samples in
unit of (CPS) obtained from Electra Plus and the relation
among regions. The results obtained from Electra Plus show
that the beta radiation level in these regions is very low if to
compare with other regions.
The results obtained from Geiger counter showed the relation
between the radiation activities in water in unit of (CPM)
and (kBq) calibrated. (The 37 kBq of Cesium radioactive
source is used for calibration by multiplying by X (0.102) kBq).
The results from all detectors indicate that, there is low level
radiation in the studied area, because it is below 10 kBq/m 3 .
Fig. 7 shows there is low level radiation in water samples in
the studied area in comparison to each other. The activities

Radioactivity measurements in tap water in Gaza Strip (Al-NASER) 25
The concentration of Radiation
Activity (C.P.M)
14
12
10
8
6
4
2
0
A B C D Avg
The Regions of Nasser
min.con.
max.con
E
S.D.
Figure 7 Radiation activity in Nasser regions in CPM for
comparison.
Figure 8 Spectrum of water sample number-25 in Nasser
Shakhradwan (C).
Figure 9
Spectrum of background in surrounding air.
in these samples are very low because it is far away from rocks
which contain Uranium and other radioactive material.
The results obtained from scintillation counter showed that
there is low level radiation in the studied area. (Region, y-axis
is the number of counts of radiation and x-axis is the channel
number (energy), spectrum from background, sources were taken
for calibration, 137 Cs and 60 Co)
In Fig. 8, the energy spectrum obtained for a water sample,
each spectrum compared with each sample spectra and the calibration
spectra, which showed no peaks appear in the sample
spectra, that indicates that the water contain very low level of
radiation.
The measurements of gamma rays made by means of the
scintillation counter confirm that there is low level of radiation
because the water sample level differs slightly from the background
level, see Fig. 9.
5. Conclusion
The study purpose was to measure the radiation activity and to
find out an approximate mean and range of radiation concentration
in tap water at Nasser region in Gaza city. Only CR-39
determines concentration of alpha particles in terms of quantity
in Bq/m 3 , all other methods give the activity of radiation
water samples in terms CPM.
Nasser region was divided into four areas, in our survey, included,
Nasser west (A), Nasser east (B), Nasser shakhradwan
(C), and Nasser south (D). We used five types of detectors.
These detectors and their methods are already explained earlier:
Solid State Nuclear Track Detectors (CR-39), Geiger
counter, Portable Gamma Spectrometer, Scintillation counter
and Portable Electra Plus.
In the present work all detector results indicate the low level
of radiation activity in the Al-Nasser area. In general most
water samples have very low levels of the natural radionuclides,
and the average alpha concentration was 35.95 Bq/m 3
or 0.95 pci/L for Al-Nasser for the four regions of study, levels
low enough to not be considered a public health concern as
mentioned earlier in this reference. (‘‘Risk Assessment of Radon
in Drinking Water’’, released September 15, 1998).
We are interested mainly in measuring alpha concentration
which measured in Bq/m 3 using CR-39 accurately by counting
alpha tracks, but in general way beta and gamma are measured
for comparison purposes of samples with each other and with
the calibration sources and not exactly like CR-39.
It is shown that the results of the measurements, the radiation
concentration in water vary in the low level scale.
The main results of radiation measurements in water observed
in the present study can be summarized as follows:
1. The radiation concentration in the tap water at Nasser is
typically in values close to those normally found in other
countries and much lower than the word average 10 kBq/
m 3 (UNSCEAR, 1986).
2. The higher radiation concentration in water at Nasser
south 103.75 Bq/m 3 or 2.8 pci/L, does not create any special
environment and or health problem because it is less than
the average of 10 k Bq/m 3 hopefully, and EPA of 15 pci/L
for gross of all alpha standards, and 5 pci/L for alphas from
combined radium 226/228.
3. We would like to do more specific measurements on some
of naturally occurring radioactive isotopes like potassium,
uranium, radium and others. This required more equipment
which should be more accurate for this low level of
radiation.
Acknowledgments
Thanks to the department of physics, and the dean of scientific
research at the Islamic University of Gaza, for the partial sup-

26 M.O. El-Ghossain, A.A. Abu Shammala
port and help. We thank also the Palestinian Energy Authority
for their help in using their equipments.
References
Abusaleh, Raed M., 2005. Measurement of Radiation concentration in
soil at middle of Gaza Strip. thesis, Islamic University of Gaza.
Beir, V., 2000. National Research Council report on Health Effects of
Low Levels of Ionizing Radiation.
Bell, J., 2005. Modern Physics Lab: The Scintillation Counter,
Department of Physics & Computer Science, Presbyterian College,
Clinton SC 29325, http://web.presby.edu/.jtbell/classes/phy217/
labs/ScintCounter.pdf.
David Bodansky, Maurice, A. Robkin, Stadler, David R., 1989.
Indoor Radon and Its Hazards, second ed. Univ. of Washington
Press Seattle and London, printed in the USA.
Saeed A. Durrani and Radomir Ilic, 1997, Radon measurements by
etched track detectors. Applications in radiation protection, earth
science and the environment, printed in Singapore.
El-Ghossain, M.O., Abusaleh, Raed M., 2007. Measurement of
radiation concentration in soil at middle of Gaza Strip using
different type of detectors. The Islamic University Journal 15 (1),
23–37.
Environmental Protection Agency (EPA), November 2000. Fact sheet
about final Radionuclides rule
or, ; EPA 815-F-
00-013.
Mahmoud Rasas, 2003. Measurement of Radon and its Daughter’s
Concentration Indoor and Outdoor throughout Gaza Strip, thesis,
Islamic University of Gaza.
Nabil Hamed, 2005, Measurement of Radon Concentration in Soil at
North Gaza, thesis, Islamic University of Gaza.
Nuclear Energy and Radiation Protection Directorate (NERP), 2005.
Palestinian Energy Authority.
Risk Assessment of Radon in Drinking Water, released September 15,
1998, by the National Academy of Sciences.
Sources and Health Effects of Ionizing Radiation, A/AC-82/
R,441:113-120, Unclear-US Scientific Committee on Atomic Radiations,
Washington, DC, 1980.
UNSCEAR-United Nation Scientific Committee on Atomic Radiations:
Sources and effects of ionizing radiation, A/AC-82/R,
441:113-120, 1986.

Journal of the Association of Arab Universities for Basic and Applied Sciences (2012) 11, 27-31
تركيب
أغشية رقيقة من كبريتيد الكادميوم بلوراتها الجسيمية في حدود النانو
بتقنية الحمام الكيميائي ودراسة خواصها التركيبية والضوئية
عبد اهلل
2
1
الحسام ، صالح عبد الجبار جاسم
1
قسم الكيمياء
، كلية العلوم التطبيقية ، جامعة ذمار،‏ اليمن
2
قسم الفيزياء ، كلية العلوم التطبيقية ، جامعة ذمار،‏ اليمن
الملخص :
رسبت أغشية رقيقة
من كبريتيد الكادميوم بلوراتها الجسيمية في حدود النانو بطريقة الحمام الكيميائي على
شرائح زجاجية وكانت درجة حرارة الترسيب
اليوريا الكبريتية.‏
الجسيمية في حدود النانو.‏
الى
80 o C
وزمن الترسيب
6h
باستخدام تركيبتين
وقد تم التعرف على جميع متغيرات الحمام الكيميائي والتي أعطت أغشية
مختلفتين من
رقيقة بلوراتها
أثبتت تحليالت الخواص الضوئية أن فجوة الطاقة لألغشية المحضرة عانت
انحراف باتجاه اللون األزرق كما حسبت البلورات الجسيمية لألغشية المحضرة وتراوحت قيمها بين
62823
نانومتر.‏ 8
A.M.A. Al-Hussam, S.Abdul-Jabbar Jassim

Journal of the Association of Arab Universities for Basic and Applied Sciences (2012) 11, 27–31
University of Bahrain
Journal of the Association of Arab Universities for
Basic and Applied Sciences
www.elsevier.com/locate/jaaubas
www.sciencedirect.com
Synthesis, structure, and optical properties of CdS thin films
nanoparticles prepared by chemical bath technique
Abdullah M.A. Al-Hussam a , Salah Abdul-Jabbar Jassim b, *
a Chemistry Department, Faculty of Applied Science, Thamar University, Thamar, Yemen
b Physics Department, Faculty of Applied Science, Thamar University, Thamar, Yemen
Available online 13 January 2012
KEYWORDS
Chemical bath deposition;
CdS thin films;
Nanoparticles;
Structural and optical studies
Abstract CdS nanocrystalline thin films were deposited onto glass substrates by chemical bath
deposition (CBD). The films deposited at 80 °C for 6 h with two different concentrations of
thiourea. The deposition parameters were optimized. The obtained films were characterized for
structural and optical properties, X-ray diffraction patterns revealed that the films were nanocrystalline
in nature with cubic structures. A blue shift in the band gap was observed in the UV–visible
absorption spectra indicating the formation of nano particles of sizes between 3.826 and 8 nm.
ª 2011 University of Bahrain. Production and hosting by Elsevier B.V. All rights reserved.
1. Introduction
Semiconductors nano-particles (also known as quantum dots),
belong to state of matter in the transition region between
molecules and solids, have attracted a great deal of attention because
of their unique electrical and optical properties, compared
to bulk materials (Alivisatos, 1996). Their electrical and optical
properties are directly associated with the quantum confinement
of charge carriers leading to the blue shift of the band gap with
the shrinkage of their size (Kotkata et al., 2009). Particularly
When the dimension of the semiconductor quantum dots
* Corresponding author.
E-mail address: salahjassim200@yahoo.com (S.A-J Jassim).
1815-3852 ª 2011 University of Bahrain. Production and hosting by
Elsevier B.V. All rights reserved.
Peer review under responsibility of University of Bahrain.
doi:10.1016/j.jaubas.2011.10.001
Production and hosting by Elsevier
reduced close to characteristic length known as the exciton Bohr
diameter, these characteristic lengths are usually in the range of a
few nanometers, there will be large changes in their properties,
this effect changes the surface to volume ration and it also shifts
electronic energy levels towards higher energy leading to an increase
in the band gap (Alivisatos, 1996). CdS as a semiconductor
material has received much attention due to its direct band
gap resulting in emission in the visible wavelength. CdS nanostructures
are being widely investigated for applications in semiconductor
laser (Dunan et al., 2003), nonlinear optical devices
(Grohs et al., 1994), biological applications (Santos et al.,
2008) display devices (Schmitt-Rink et al., 1989) and as window
materials for hetero-junction solar cells because it has a high
absorption coefficient (Xiaoxia et al., 2010).
In recent years, considerable efforts have been made to
synthesize CdS nanostructures by several methods such as,
dc- sputtering (Ghosh et al., 2006), solvothermal route (Ujjal
et al., 2003), sonochemical (Raghvendra et al., 2010) and chemical
bath deposition (Dongre et al., 2009). The chemical bath
deposition (CBD) is the deposition technique most widely employed
to obtain CdS thin films .The CBD process is a simple
and inexpensive technique to obtain homogeneous, hard,
adherent, transparent and stoichiometric CdS thin films.
Typically, chemically deposited CdS thin films are formed from

28 A.M.A. Al-Hussam, S.Abdul-Jabbar Jassim
the reaction between a cadmium salt and thiourea in an ammoniacal
alkaline solution. The main role of ammonia in the CBD
process is as complexing agent for the cadmium ions in the
reaction solution. It has been reported that CdS may have either
cubic or hexagonal structure depending on the synthesis
conditions.
In this work, we report the CBD preparation of nanostructure
CdS thin films deposited on the glass substrates using a
mixed aqueous solution of cadmium chloride, thiourea and
ammonium chloride. Structural and optical properties have
been investigated.
2. Experimental detail
CdS thin films are deposited on glass substrates using CBD at
various concentrations of thiourea. The substrates used for the
deposition of CdS thin films were (35 · 25 · 1) mm commercial
glass slides. Before the deposition the substrates must be
cleaned using nitric acid for 48 h, scoop water followed by distilled
water and finally dried in air. Aqueous solutions of
0.02 M cadmium chloride with 0.05 M ammonium chloride
NH3Cl in 100 ml distilled water. Then ammonia solution of
0.55 M as a complexing agent in 50 ml distilled water was
added to the solution to adjust the PH value of the bath to
9. The solution was continuously stirred. Then add 0.05 M
thiourea (NH 2 ) 2 CS. Solution was mixed with a magnetic stirrer
and after obtaining a clear homogenized bath, the stirrer
was turned off and glass slides were placed in the bath vertically.
The solution temperature was kept constant at 80 °C
for given time of deposition 6 h .After the deposition the samples
were pulled out from the bath and washed with distilled
water and dried in air. The CdS films were deposited for different
concentrations of (NH 2 ) 2 CS as shown in Table 1.
The possible chemical reaction that takes place to produce
CdS films may be as follows:
CdCl 2 þ 4NH 3 ! CdðNH 3 Þ 4
Cl 2
ð1Þ
½CdðNH 3 Þ 4
Š þ2 ! Cdþ 2 þ 4NH 3
NH 3 þ H 2 O ! NH 4 þ 2 þ OH
Cdþ 2 þ 2OH ! CdðOHÞ 2
ð4Þ
ðNH 2 Þ 2
CS þ 2OH !½HSŠ þ þ H 2 O þ CH 2 N 2 ð5Þ
½HSŠ þ þ OH ! S 2 þ H 2 O ð6Þ
½CdðNH 3 Þ 4
Š þ2 þ S 2 ! CdS þ NH 3
ð7Þ
The deposited CdS thin films are uniform, light yellow in
color, highly adhesive, smooth and reflecting. For thickness
measurement, gravimetric weight different method with the
ð2Þ
ð3Þ
relation t = m/(q·A) where, m is the mass of the film
deposited on the substrate in g, A the area of the deposited film
in cm 2 and q the density of the deposited material (CdS =
4.84 g/cm 3 ).thickness of the films were 434.7 nm and
453.36 nm for samples (a) and (b) respectively.
Optical properties of chemical bath deposited CdS thin
films were measured at room temperature by using UV/VIS
spectrophotometer Cary 50 Cm-Exlena in the wavelength
range of (300–900 nm). X- ray diffraction pattern of the dry
nanopartical powder was obtained using Siemens D5005
X-ray diffract meter with CuKa radiation (k = 0.1542 nm).
3. Results and discussion
3.1. Optical studies
The optical studies of the CdS films were performed using the
transmission and absorption spectra observed in the wavelength
range 300–900 nm.
Fig. 1 shows the transmission spectra of CdS films, it can be
seen that the films present high transmission (72–85%) in the
visible range which is good for opt-electronic devices, especially
for solar cell window layers. and have sharp fall at the
band edge, which is an indication of good crystallinity of
CdS in the films.
Absorption spectra of the two synthesized CdS films are
shown in Fig. 2 it can be seen that the films show peaks at
478,470 for sample (a) and (b) respectively that means the
absorption edge shifted toward blue .The blue shift can be
attributed to the exitonic absorbance due to the quantum confinement
at low dimensions compared to its bulk counterparts.
The band-gap value (E g ) of the deposited films were determined
by analyzing the optical data with the expression for
the optical absorbance a and the photon energy ht using Taucs
formula relation (Tauc and Abeies, 1970).
aht ¼ Cðht E g Þ n ð8Þ
where C is a constant and the exponent n depends on type of
transition, n may have values 1/2, 2, 3/2 and 3 corresponding
to allowed direct, allowed indirect, forbidden direct and forbidden
indirect transitions, respectively. As CdS nanoparticles
have direct allowed transitions we choose n = 1/2 .The band
gap of CdS nanoparticals was determined by extrapolating
the straight line portion of the (aht) 2 vs. (ht) graphs to the
(ht) axis as shown in the Fig. 3. It can be observed from
Fig. 3 that the band gap of CdS nanoparticales is 3.2 eV and
2.6 eV for sample (a) and (b), respectively. These values of the
energy gaps reflect a considerable blue-shift relative to the corresponding
absorption band edge of bulk CdS, such observed
shift reveals quantum size effect in the synthesized CdS thin
films. Our present E g values were in a good agreement with
those reported by (Raghvendra et al., 2010; Dongre et al., 2009).
Table 1
The compositions of the sample in the start solution.
Reaction bath pH CdCl 2 (NH 2 ) 2 CS NH 4 Cl NH 3 H 2 O
Mol. (M) Vol. (ml) Mol. (M) Vol. (ml) Mol. (M) Vol. (ml) Mol. (M) Vol. (ml)
Sample-a 9 0.03 50 0.1 50 0.05 50 0.6 50
Sample-b 9 0.03 50 0.05 50 0.05 50 0.6 50

Synthesis, structure, and optical properties of CdS thin films nanoparticles prepared by chemical bath technique 29
Figure 1
Plot of transmittance with wavelength for CdS films.
Figure 3 The variation of (aht) 2 vs. ht to determine the direct
band gap of CdS thin films.
Figure 2 The variation of optical absorbance vs. wavelength for
CdS films.
The values of the band-gap were higher than the band gap
of bulk CdS (2.42 eV) (Enriques and Mathew, 2003) therefore,
the blue shift of band gap edge is 0.78 eV and 0.18 eV for samples
(a) and (b) respectively. The increased effective band gap
makes nanocrystalline CdS a more effective window material
in photovoltaic applications like the CdS/CdTe solar cells.
For CdS nanoparticles (Brus, 1986) proposed the effective
mass approximation formal (EMA) to explain the theory of
blue shift, which gives energy E nd for lowest 1s states as a function
of nanoparticle radius, shows as follows:
E np ¼ E bluk
g
þ E comf þ E coul ð9Þ
where E np is the band gap of CdS nanoparticle, E g is the band
gap of the bulk of CdS, E comf is the electron–hole pair confinement
kinetic energy and E coul is the coulomb interaction energy
between the hole and the electron, which is given by
E coul ¼ 1:8e 2 =pe o e s R ð10Þ
And E comf ¼ðh 2 p 2 =2R 2 Þð1=m e þ 1=m hÞ corresponding to the
lowest energy transition.
Now the above equation can be written as
E np ¼ E bulk
g
þðhp 2 =2R 2 Þð1=m e þ 1=m h Þ
ð1:8e 2 =4pe o e s RÞ
ð11Þ
where h =h/2p, h is plank constant, R is the radius of nanoparticles,
m e
is the effective mass of electron (m e ¼ 0:19m e),
m h is the effective mass of hole (m h ¼ 0:8m e), m e is the mass
of electron, e s is the dielectric constant of material (5.7) and
e o is the permittivity of free space. In the EMA formula, the
coulomb term of electron–hole interaction was small compared
to electron - hole confinement kinetic energy, which supported
the blue shift result.
Applying Eq. (11), values 4 nm (the diameter is 8 nm) and
1.913 nm (the diameter 3.826 nm) have been estimated for
the radius of the two nanoparticales CdS samples (a) and (b)
respectively.
It can be seen clearly that the decreasing particle size (as the
thiourea concentrations increases) causes increase in the band
gap. Similar observation of the decrease in particle size as the
thiourea concentrations increased was reported by Yao et al.
(2003). The dependence of band gap on particle size in semiconductor
nanocrystals has been extensively studied by Brus
(1984). Particles whose dimensions become comparable to
the bulk excition Bohr radius (a B ), equal to 5.3 nm for CdS,
are observed to exhibit strong quantum confinement effect,
which result in increase in the band gap with decreasing particle
size. So there is a very good agreement with our result.
These values are in good agreement with the sizes determined
from XRD.
3.2. X-ray diffraction studies
Fig. 4 shows the XRD pattern of CdS powered nanoparticles
for sample b. Comparing with the data of the JCPDS file (Powder
Diffraction File Card, No. 10-454), it was found that the
CdS nanoparticles are identified as b-CdS, which belong to

30 A.M.A. Al-Hussam, S.Abdul-Jabbar Jassim
4. Conclusion
An aqueous solution system for growing CdS thin film nanocrystals
network was investigated. The present method is simple,
economic and easy .The crystal structure and grain size of
the particles was determined using XRD. The radius of the
particle was calculated using an effective mass approximation
mode. The calculated radius of CdS nanoparticles was found
to be similar to that obtained from XRD through Scherer’s
formula.
UV–VIS spectra of the films showed blue shift in absorption
edge compared with bulk CdS. The nanocrystals size
was observed in the range of 3.826–8 nm.
References
Figure 4
sample b.
XRD of powder CdS nanoparticales for sample for
the cubic crystal system. The XRD peaks are found to be
broad indicating fine size of the sample grains. The XRD pattern
of a typical CdS sample exhibits prominent broad peaks at
2h values of 26.7°, 44° and 52° which could be indicated as
scattering from the (111), (220), and (311) cubic phase CdS
plans, respectively, suggesting that the nanoparticles are in cubic
(Zinc blend phase) form and are in good agreement with
the reported data on CdS (Rodrgues et al., 2008; Wang
et al., 2001). No peaks attributable to other phases were observed.
The broadening of the diffraction peak provides information
about crystallite size. As the width increases, the
particle size decreases and vice versa (Banerjee et al., 2000).
From the position of different peaks and by the Bragg
condition,
nk ¼ 2d sin h
ð12Þ
where n is the order of diffraction, k the wavelength of the incident
X-rays, d the distance between the plans parallel to the
axis of the incident beam and h is the diffraction angle, d-spacing
has been evaluated, the obtained value is (3.139 A˚ ).
Nanoparticle lattice constant is calculated using the following
formula (Kittel, 1996).
1=d 2 ¼ðh 2 þ k 2 þ l 2 Þ=a 2 ð13Þ
where (a) is the lattice constant, and (h,k,l) miller indices, (a)
was calculated to be (0.59 nm) for our sample, which matches
with the earlier reported lattice constant for cubical zinc blend
structures of CdS nanoparticles (Rodrgues et al., 2008).
The average size of the crystallites (D) has been calculated
using Scherer’s equation as (Cullity, 1972)
D ¼ Kk=b cosðhÞ
ð14Þ
where the constant K is a shape factor usually =0.94, k is of
X-ray wavelength (0.15418 nm), b is the full-width at halfmaximum
(FWHM) of the peak which has maximum intensity
and h is the Bragg’s angle. The estimated X-ray domain size of
this sample was 6.27 nm derived from FWHM of peak corresponding
to 2h 26.7° for sample (b).
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Journal of the Association of Arab Universities for Basic and Applied Sciences (2012) 11, 32-36
تحديد بيرمثامين في المتحضرات الصيدالنية عن طريق المطيافئة
باستخدام نافثوكوينون
1 – 2
عبداهلل احمد البشير
، علوية حسين الحسين الوقيع
ص.ب 321
قسم الكيمياء،‏
كلية العلوم،‏ جامعة الخرطوم،‏
الخرطوم
، السودان
المخلص:‏
في هذه الدراسة تم وصف طريقة تمتاز بالدقة والبساطة لتحديد بيرمثامين في المستحضرات الصيدالنية.‏
تعتمد الطريقة على تكوين مركب ملون نتيجة لتفاعل بيرمثامين مع
–
2-1
مئوية.‏ درجة 06
الطول الموجي
384
لالمتصاصية والتركيز مطاعة
المعايرة ص
نافثوكوينون في درجة حرارة
تمت متابعة التفاعل عن طريق المطيافية الضوئية بقياس الزيادة في االمتصاصية عند
نانوميتر بدالة زمنية.‏
‏)ممتثلة(‏
عند
في المدى
–
الظروف المثلى للتفاعل كانت العالقة بين قانون بيرز
36
12
606142
+
60763
=
ج مع معامل االرتباط
مايكرو جرام/مل ومعادلة االنحدار للبيانات
)60..0(
وامتصاصية مولية بمقدار
*5.8
لتر مول 4 16
1-
ملليتر على التوالي.‏
-1. سم
كانت النسبة المئوية لبيرمثامين للدفعة
وكان الحد من الكشف النوعي والكمي
4025
وقد طبقت الطريقة المقترحة بنجاح لتحديد بيرمثامين في
16084 و
هي 26
+
-16103
طريقة األداء العالية للفصل الكروماتوغرافي السائل الرسمية.‏
.%6015
مايكرو جرام لكل
أقراص الدواء مع دقة جيدة.‏
وكانت النتائج في اتفاق جيد مع
A.A. Elbashir, A.H.E. Elwagee

Journal of the Association of Arab Universities for Basic and Applied Sciences (2012) 11, 32–36
University of Bahrain
Journal of the Association of Arab Universities for
Basic and Applied Sciences
www.elsevier.com/locate/jaaubas
www.sciencedirect.com
ORIGINAL ARTICLE
Spectrophotometric determination of pyrimethamine
(PYM) in pharmaceutical formulation using
1,2-naphthoquinone-4-sulfonate (NQS)
Abdalla A. Elbashir *, Alawia H.E. Elwagee
University of Khartoum, Faculty of Science, Chemistry Department, P.O. Box 321, Khartoum, Sudan
Available online 24 January 2012
KEYWORDS
UV–visible
spectrophotometry;
Pyrimethamine;
NQS;
Pharmaceutical formulation
Abstract A simple and sensitive spectrophotometric method for the quantitative analysis of pyrimethamine
(PYM) in pharmaceutical formulations has been described. The method is based on the
formation of colored product between PYM and 1,2-naphthoquinone-4-sulfonate (NQS) at 60 °C.
The reaction is followed spectrophotometrically by measuring the increase in absorbance at 483 nm
as a function of time. Under the optimized reaction condition, Beer’s law correlation for the absorbance
(A) with PYM concentration (C) was obeyed in the range 12–40 lgmL 1 the regression
equation for the calibration data was A = 0.704 + 0.0132C, with correlation coefficient (0.996).
The molar absorptivity (e) was 5.8 · 10 3 L mol
1 cm 1 . The limits of detection and quantification
were 3.25 and 10.83 lgmL 1 , respectively. The proposed method was successfully applied to the
determination of PYM in pharmaceutical tablets with good accuracy and precision; the percentage
for PYM was 101.4 ± 1.47% for batch 20 and 100.4 ± 0.51% for batch 13. The results were in
good agreement with those obtained with the official high performance liquid chromatography
(HPLC) method.
ª 2012 University of Bahrain. Production and hosting by Elsevier B.V. All rights reserved.
1. Introduction
* Corresponding author.
E-mail address: hajaae@yahoo.com (A.A. Elbashir).
1815-3852 ª 2012 University of Bahrain. Production and hosting by
Elsevier B.V. All rights reserved.
Peer review under responsibility of University of Bahrain.
doi:10.1016/j.jaubas.2011.12.003
Production and hosting by Elsevier
Pyrimethamine (PYM), 5-(4-chlorophenyl)-6-ethyl-2,4-pyrimidineamine
(Fig. 1) is a drug widely used in the treatment of
parasitic diseases such as malaria and toxoplasmosis (Bosch-
Driessen et al., 2002).
The mechanism of action of PYM is the inhibition of dihydrofolate
reductase (DHFR), an essential enzyme responsible for the
conversion of folic acid into folinic acid in the nucleic acid biosynthesis
(Anderson, 2005). Some major drawbacks of PYR therapy
include a relatively weak inhibitory activity and severe side effects
such as nausea and neutropenia, which are caused by the low
selectivity toward the parasite enzyme (Katlama et al., 1996).
Literature survey reveals that various methods have been
reported for the analysis of PYM in pharmaceutical and bio-

Spectrophotometric determination of pyrimethamine (PYM) 33
N
NH 2
Cl
of NaOH (0.2 M) in 100 mL volumetric flask, and adjusted by
the pH meter. Other buffer solutions of different pH values
were also prepared. Amifan tablets were kindly donated by
AMIPHARMA Laboratories Ltd. (Sudan, Khartoum).
Milli-Q water was used for preparing all solutions used.
H 2 N
N
2.3. Preparation of standard and sample solution
Figure 1
logical samples such as microbiological method (Weidekamm
et al., 1982), gas–liquid chromatography (Cala et al., 1972;
Jones et al., 1981; Midskov, 1984b), thin layer chromatography
(DeAngelis et al., 1975), spectrophotometry (Schmidt
et al., 1953; Sastry et al., 1986; Berzas Nevado et al., 1993;
Khalil et al., 2000; Onah and Odeiani, 2002; Zayed et al.,
2005; Nagaraja et al., 2010), fluorimetry (Parimo, 1988) and
HPLC(Midskov, 1984a,b; Bergqvist and Eriksson, 1985;
Timm and Weidekamm, 1982; Edstein, 1948a,b) individually
and in combination dosage form with other drugs.
Spectrophotometry is considered the most convenient analytical
technique, because of its inherent simplicity, low cost,
and wide availability in most quality control laboratories.
Spectrophotometric methods have been reported for PYM.
These methods were associated with some major drawbacks
such as laborious multiple extraction steps in the analysis by
ion-pair based methods (Khalil et al., 2000; Nagaraja et al.,
2010) Furthermore, the analytical reaction was long and thus
the procedure was time-consuming (Onah and Odeiani, 2002).
1,2-Naphthoquinone-4-sulfonate (NQS) has been used for
the determination of many compounds containing primary
amine group (Gallo-Martinez et al., 1998; Wang et al., 2004;
Saurina and Herna´ndez-Cassuo, 1993). Use of NQS as a colored
reagent for the determination of PYM by spectrophotometry
has not been reported yet. Therefore, the present work
was devoted to study the reaction between PYM and NQS
and employment of the reaction in the development of a simple
method for the determination of PYM in dosage form.
2. Material and methods
Chemical structure of PYM.
2.3.1. PYM standard solutions
An accurately weighed 10 mg of PYM was dissolved in methanol,
transferred into a 10 mL standard flask and completed to
the mark with methanol. This stock solution was further diluted
with the same solvent to obtain working solutions in
the range 6–60 lgmL 1 .
2.3.2. Tablets sample solution
Twenty tablets were weighed, and finely powdered. An accurately
weighed quantity of the powdered tablets equivalent to
4.25 mg of PYM was transferred into a 25 mL calibrated flask,
and dissolved in methanol. The prepared solutions were diluted
quantitatively with methanol to obtain a suitable concentration
for the analysis.
2.3.3. General recommended procedure
Accurately measured 1 mL of PYM solution containing 12–
40 lgmL 1 was transferred into a 10 mL volumetric flask.
3 mL of buffer solution pH (13.0) was added, followed by
1 mL of NQS solution (0.5%, w/v). The reaction solution
was allowed to proceed at 60 °C for 15 min. The reaction mixture
was completed to volume with water, and the resulting
solution was measured at 483 nm against reagent blank.
2.4. Determination of PYM by HPLC
According to the United States Pharmacopoeia, PYM was
determined in two batches number (batch number 20 and
13). The analysis was performed on a Phenomenex C18-column;
5 lm (250 mm 4.6 mm i.d.) with a guard column
3
2.1. Instrumentation
All absorbance measurements were made with a Double beam
UV-1800 (SHIMADZU, Japan) ultraviolet–visible spectrophotometer
provided with matched 1-cm quartz cells and also
temperature controller was used for the spectrophotometric
measurements. pH meter model pH211 (HANNA, Italy).
Thermostatically controlled water bath type RE 220 (LAU-
DA, Germany).
Absorbance (Arb.
1.00
0.50
1
2
2.2. Reagents and materials
Pyrimethamine (PYM) (AMIPHARMA Laboratories Ltd.,
Khartoum) were obtained and used as received; its purity
was 99.7%. A solution of 0.5% (w/v) of 1,4-naphthoquinone-4-sulfonate
(NQS) (Aldrich chemical Co., St. Louis,
USA) was prepared by dissolving 125 mg in 25 mL double distilled
water. The solution was freshly prepared and protected
from light during use. Buffer solution of pH 13.0 was prepared
by mixing 25 mL solution of KCl (0.2 M) and 66 mL solution
0.00
200.0 300.0 400.0 500.0 600.0 700.0
Wavelength (nm)
Figure 2 Absorption spectra of Pyrimethamine (20 lgml
1 )
against methanol (1). NQS (0.5% w/v) against water (2). And
the reaction product of primethamine (30 lgml
1 ) with NQS
against reagent blank (3).

34 A.A. Elbashir, A.H.E. Elwagee
Absorbance
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0
0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6
NQS (% w/v)
Figure 3 Effect of NQS concentration on the reaction of PYM
with NQS. PYM (40 lg/ml): 1 ml; buffer solution (pH 13.0); 3 ml;
temperature 60 °C; reaction time: 15 min.
(4.0 mm · 3.0 mm i.d.). The mobile phase consisting of 80%
glacial acetic acid (1:100), 20% acetonitrile and 500 lL triethylamine
was delivered as an isocratic elution at a flow rate of
2 mL/min and 10 lL of the sample was injected. Before use
the mobile phase was degassed by an ultrasonic bath and filtered
by a Millipore vacuum filter system equipped with a
0.45 ml HV filter.
3. Results and discussion
3.1. Optimization
The absorption spectrum of the reaction product between
NQS and PYM with an absorption maximum at 480 nm is
shown in Fig. 2. Clearly from this figure a broad absorption
band at longer wavelengths is obtained for the reaction between
NQS and PYM.
The optimum conditions for the development of method
were established by varying the parameters one at a time while
keeping the others fixed and observing the effect produced on
the absorbance of the colored product. In order to establish
experimental conditions, the effect of various parameters such
as concentration of NQS, pH, temperature, and time of heating
were studied.
The effect of NQS concentration was studied over the range
0.1–1.5 w/v% as shown in Fig. 3. Increasing the concentration
of NQS results in more products up to an amount of 0.5%
Table 1 Parameters for the performance of the proposed
method.
Parameter
Value
Measurement wavelength (nm) 483
Linear range (lg mL 1 ) 12–40
Intercept 0.704
Standard deviation of the intercept 0.014
Slope 0.013
Standard deviation of the slope 0.001
Correlation coefficient (r) 0.996
Limit of detection, LOD (lgmL 1 ) 3.25
Limit of quantification, LOQ (lg mL 1 ) 10.83
Molar absorptivity, e (1 mol
1 cm 1 ) 5.8 · 10 3
after which the absorbance remained almost constant. Therefore
a concentration of 0.5% NQS was considered optimum.
The influences of pH on the absorbance of product I was
investigated in the range 1.0 to 14. At pH 1.0–7.0, the
absorbance of the product is close to 0, indicating that under
high acidity, PYM does not react with NQS. The possible
reason may be that the amino group ( NH 2 ) of PYM is
protonated (pk a = 7.26 G.S. La´zaro et al., 2008) and converted
into protonated amine salt ð NH þ 3
Þ. So it loses nucleophilic
capability for 4-sodium sulfonate of NQS, and the
nucleophilic substitution reaction cannot take place easily.
At pH > 10.0, the absorbance of the solution increases rapidly
up to pH 13.0. It may be that protonated amine salt
ð NH þ 3 Þ of PYM turns into amino group ( NH 2) again
when the acidity of the solution becomes low. The higher
the pH, the more effectively the protonated amino group removes
the proton, and more easily the nucleophilic substitution
reaction happens. At pH 13.0, the absorbance reaches
its maximum; in other words, the degree of the nucleophilic
substitution reaction is also maximal. At pH > 13.0, the
absorbance of solution decreases sharply again. Presumably
it may be that the increase of hydroxide ion holds back
the nucleophilic substitution reaction between PYM and
the chromogenic reagent. Consequently, the absorbance of
the solution reduces. In order to keep the high sensitivity
for the determination of PYM, pH 13.0 was selected for
optimal experimental conditions. Reaction of NQS with
compound bearing primary amines at pH 13.0 was reported
(Li and Zhang, 2008).
The effect of temperature on the reaction was studied in the
range 20–80 °C. About 60 °C was found to be optimal for
maximum color development.
O
N
NH 2
Cl
+
O
O
N
NH
O
Cl
+ NaHSO 3
H 2
N
N
SO 3
Na
H 2
N
N
Figure 4
Scheme for the reaction pathway of PYM with NQS.

Spectrophotometric determination of pyrimethamine (PYM) 35
Table 2
Recovery studies for the determination of PYM, by the proposed method.
Sample No. +SD Sample content (lgmL 1 ) Pyr. added (lgmL 1 ) Found Recovery (%)
1 10 14 14.0 100.0 ± 0.01
2 – 18 18.3 101.7 ± 0.03
3 – 26 26.1 100.5 ± 0.01
4 – 32 42.8 101.9 ± 0.09
The influence of the time of heating was also investigated in
the range 5–30 min. The experimental results show that heating
in the range 15–20 min gave the optimal values in kinetic
studies. The color product was stable for at least two days at
room temperature.
From the above experiments, the optimized conditions used
for the assay were: NQS concentration 0.5% w/v, buffer (pH
13.0), reaction time 20 min and temperature 60 °C.
Under the optimum conditions, the stoichiometry of the reaction
between PYM and NQS was studied by the Job’s (1964)
method. The symmetrical bell shape of Job’s plot indicated that
the ratio of PYM:NQS is 1:1. Based on this ratio, the reaction
pathway was proposed to proceed as shown in Fig. 4.
3.2. Analytical methods validation
As can be seen from Table 1, linear relationship was found between
absorbance at k max (483) and the concentration of the
PYM in the range 12–40 lg mL 1 . The regression equation
was found as A = 0.0132C + 0.704 (r 2 = 0.996). The limits
of detection (LOD) and limit of quantitation (LOQ) were
determined using the formula:LOD or LOQ = KS.D.a/b,
where k = 3 for LOD and 10 for LOQ, SDa is the standard
deviation of the intercept, and b is the slope.
The accuracy of the proposed method was carried out by
applying standard addition technique. A different amount of
standard solution was added to a known concentration of
the drug sample. The average percent recoveries obtained in
range 100.04–101.9. Table 2.
Robustness was examined by evaluating the influence of
small variation of method variables including the concentration
of analytical reagent and reaction time on the performance
of the proposed methods. In these experiments, one
parameter was changed whereas the others were kept unchanged,
and the recovery percentage was calculated each
time. It was found that small variation of method variables
did not significantly affect the procedures; recovery values
were 98.43 101.40 (Table 3).
3.3. Application to the pharmaceutical dosage forms
Table 3 Influence of small variation in the assay conditions
on the analytical performance of the proposed spectrophotometric
method for the determination of pyr. using NQS
reagent.
Parameters
Recovery (% ± SD)
Recommended conditions 101.4 ± 1.5
NQS concentration (%, w/v) 0.45 100.2 ± 0.1
NQS concentration (%, w/v) 0.55 99.7 ± 0.1
Buffer (pH) 12.75 100.8 ± 0.1
Buffer (pH) 13.25 99.7 ± 0.3
Temperature (°C) 58 99.6 ± 0.2
Temperature (°C) 60 99.9 ± 0.1
Reaction time (min) 14 98.4 ± 0.2
Reaction time (min) 100.5± 0.1
PYM tablets were subjected to the analysis by the proposed as
well as with the official HPLC method (United States pharmacopeia,
2006) and the obtained results were statistically
compared with each other. The label claim percentage was
101.40 ± 1.47 and 102.38 ± 0.51 for batch 20 and batch 13
respectively (Table 4). With respect to t- and F-tests, no significant
differences were found between the calculated and theoretical
values of both the proposed and the reported methods at
95% confidence level. This indicated similar accuracy and
precision in the analysis of PYM in tablets. Common tablet
excipients such as talc, lactose, starch, avisil, gelatine and
magnesium stearate did not interfere with the assay.
4. Conclusions
The present paper described the evaluation of NQS as an analytical
reagent in the development of simple, sensitive, and
accurate spectrophotometric methods, for the determination
of PYM in pharmaceutical formulations. The described method
is superior to the previously reported spectrophotometric
methods in terms of simplicity and sensitivity. The proposed
method has comparable analytical performances and is devoid
of any potential interference. This gives the advantage of flexibility
in performing the analysis on any available instrument.
Therefore, this method can be recommended for the routine
analysis of PYM in quality control laboratories.
Table 4
Analysis of PYM containing dosage forms by the proposed and official HPLC methods (United States Pharmacopoeia).
Dosage form Recovery % + RSD (n =5) t-value f-value
Proposed
Official
AMIFAN batch 20 101.4 ± 1.5 102.5 ± 1.4 1.21 1.09
AMIFAN batch 13 100.4 ± 0.5 99.7 ± 0.5 2.40 1.18
The tabulated values for t and f at 95% confidence limit are 2.78 and 6.26, respectively.

36 A.A. Elbashir, A.H.E. Elwagee
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Weidekamm, E., Plozza-Nottebrock, H., Forgo, I., Dubach, U.C.,
1982, B. World Health Organ 60, 115.
Zayed, M.A., Shaban, M.K., Hoda, M.El., 2005. Spectrophotometric
study of the reaction mechanism between DDQ p- and iodine r-
acceptors and chloroquine and pyrimethamine drugs and their
determination in pure and in dosage forms. Spectrochim. Acta Part
A 62, 461–465.

Journal of the Association of Arab Universities for Basic and Applied Sciences (2012) 11, 37- 44
/
دراسة حركية راتنج م 6 ثاني أكسيد التيتاني وم
عن طريق التحليل بالقياس الوزني الحراري المسح التفاضلي الحراري
لتحسين صالبة راتنج
/
4
4
3
باتريس بورسون ، يانيك قد ار ، فريدريك جوشام ،
2
بن يوسف بومدين
1
مراد لعرج ،
1
جامعة معسكر ، كلية العلوم والتكنولوجيا،‏ معهد العلوم والتقنيات
صندوق البريد
363
وحدة البحث ‏"المواد والطاقات المتجددة"‏
صندوق البريد
طريق المامونية،‏ معسكر‎20222‎‏،‏ الجزائر
،110
مخبر المواد الضوئية والفوتونية واالنضمة
قطب بالستيكي الشرق
2
، جامعة تلمسان،‏ كلية العلوم،‏ معهد الفيزياء
تلمسان
،13222
الجزائر
3
، جامعة بول فرالن ماتز،‏
،3132
53522
4
،
فرنسا ، سان تافولد
فرنسا
الملخص:‏
الهدف من هذا البحث هو الحصول على إيبوكسي راتنج بأفضل الخصائص باستخدام ‏)التحليل بالقياس
الوزني الحراري
/
المسح التفاضلي الحراري(.‏ االستقرار الحراري والخصائص الحركية لإلبوكسي راتنج
باالستخدام غير المتساوي للحرارةthermogravimetry thermogravimetry/derivative وذلك
من أجل سلسلة من النسب المئوية المختلفة
Tio2-PC500
وهي كالتالي:‏
%5 ،%2 ،%1
تم تقدير مقدار متغير القيمة الحركية بطرق التكامل و التقريب.‏
أشارت النتائج إلى أن هذه الخصائص تعتمد على النسب المختلفة لثاني أكسيد التيتانيوم
%11. و
وفقا Tio 2
لمنحنيات قياس ‏)الوزني الحراري(‏ التي تظهر أن طاقة التنشيط ‏)طاقة الحفز(‏ تتزايد مع تزايد النسب
المئوية لجسيمات ثاني أكسيد التيتانيوم ( 2 ،)Tio و راتنج االبوكسي التحليل بمجهر المسح االلكتروني
أوفي بأن توزيع جسيمات ثاني أكسيد التيتانيوم
Tio 2
كان بشكل منتظم ومتجانس ضمن المادة ‏)إيبوكسي
راتنج(‏ هذا من جهة ومن جهة أخرى فالخاصية الميكانيكية التي هي الصالبة تحسنت مع زيادة النسب
لجسيمات
.Tio 2
L. Merad et al.

Journal of the Association of Arab Universities for Basic and Applied Sciences (2012) 11, 37–44
University of Bahrain
Journal of the Association of Arab Universities for
Basic and Applied Sciences
www.elsevier.com/locate/jaaubas
www.sciencedirect.com
ORIGINAL ARTICLE
Kinetic study of the RTM6/TiO 2 by DSC/TGA
for improved hardness of resin
L. Merad a,b, *, P. Bourson c , Y. Guedra d , F. Jochem d , B. Benyoucef b
a Universite´ de Mascara, Faculte´ des Sciences et Technologie, De´partement des Sciences et Techniques, BP: 763,
Route de Mamounia, Mascara 29000, Algeria
b Unite´ de Recherche «Mate´riaux et Energies Renouvelables», URMER, Universite´ de Tlemcen, Faculte´ des Sciences,
BP: 119, Tlemcen 13000, Algeria
c Laboratoire Mate´riaux Optiques, Photoniques et Syste`mes, Universite´ Paul Verlaine-Metz, Supelec, UMR CNRS 7132,
Metz, France
d Poˆle de Plasturgie de l’Est, Saint Avold 57500, France
Available online 9 January 2012
KEYWORDS
DSC;
TG/DTG;
RTM6;
TiO 2 ;
Kinetic parameter;
Mechanical property
Abstract The aim of this paper is to obtain an epoxy resin with best properties such as good cure
of polymer (by using DSC and TGA). The thermal stability and kinetic parameters of epoxy resin
RTM6 using non-isothermal thermogravimetry/derivative thermogravimetry (TG/DTG) analysis
with a series of different ratios of TiO 2 -PC500 1%, 2%, 5% and 10% with epoxy resin were evaluated.
The kinetic parameter was evaluated by integral and approximation methods. Results
obtained indicated that these parameters were dependent on different ratios of TiO 2 . According
to the thermogravimetric curves it is shown that the activation energy at high of higher conversion
increases with increasing the percentage of TiO 2 particles and epoxy resin. The SEM analysis suggests
that TiO 2 particles are uniformly distributed within the material, besides the mechanical property
of materials are found to the addition of TiO 2 .
ª 2011 University of Bahrain. Production and hosting by Elsevier B.V. All rights reserved.
* Corresponding author at: Université de Mascara, Faculté des
Sciences et Technologie, Département des Sciences et Techniques, BP:
763, Route de Mamounia, Mascara 29000, Algeria. Tel.: +213 553 883
884.
E-mail address: laarej_merad@yahoo.com (L. Merad).
1815-3852 ª 2011 University of Bahrain. Production and hosting by
Elsevier B.V. All rights reserved.
Peer review under responsibility of University of Bahrain.
doi:10.1016/j.jaubas.2011.12.002
Production and hosting by Elsevier
1. Introduction
Epoxy/TiO 2. was prepared by a solution mixture method, in
which epoxy resin and nano-TiO 2 powder were mixed (Hung
et al., 2006). Epoxy resins are widely used in most industrial
applications, such as preparation of composites. The kinetics
of epoxy resin cure has been widely investigated in the literature
under conventional thermal processing conditions
(Navabpour et al., 2006).
Resin transfer moulding (RTM) is rapidly gaining acceptance
as one of the most promising manufacturing routes for
composite structures such as the aerospace and automotive
industries. However, relatively limited information is available

38 L. Merad et al.
on the chemistry and cure characteristics of the types of thermosetting
resins used in such applications (Karkanas et al., 1996).
The aim of this study is to describe the kinetic investigation
of a curing thermoset resin system. A lot of experimental techniques
are suitable for following the rates and extents of cure
reactions in thermosets. Among them thermal gravimetric
analysis may be considered as one of the most interesting
techniques for macrokinetic analysis of cure reactions and a
detailed investigation of thermal decomposition of epoxy
resins containing a commercial TiO 2 PC500 from Millennium
at different percentages of 1%, 2%, 5% and 10%, for
evaluating the thermal stability and to determine the thermal
decomposition kinetic parameter (activation energy) and to
measure the mechanical property (hardness).
2. Experimental
2.1. Reagents
The materials used in this work were of a commercially
available grade of the diglycidyl ether of bisphenol A
((4-(2,3-epoxypropoxy)phenyl)propane) abbreviated as
DGEBA. It was used under its commercial presentation
(Dow Chemical Company; DER 332). The cure agent was
4,4 0 -DiaminoDiphenylSulfone (DDS).
Titanium dioxide TiO 2 -PC500 from Millenium Inorganic
Chemicals (anatase > 99%, Surface area 250 m 2 ), crystallite
mean size = (5–10 nm) was used as received.
2.2. Apparatus
2.2.1. DSC
Dynamic scans were performed using a heat-flux DSC (Mettler
Toledo TC11) under nitrogen purge. The instrument was calibrated
with indium.
2.2.2. SEM
The scanning electron microscopic (SEM) studies were performed
on a Hitachi S800-FE operated at 30 kV.
2.3. Methods
2.3.1. DSC
Samples of the mixture of epoxy resin and curing agent were
introduced in a furnace maintained at the temperature chosen
for the experiment (100, 135 and 150 °C). They were successively
removed and after different times they were elapsed (typically
between 1 and 6 h with a step of 1 h) and submitted to a
DSC analysis with a heating rate of 10 °C min 1 from 30 to
350 °C. These scans allowed determining the heat of reaction
DH residual generated by the curing of the remaining epoxy resin
not polymerized in the furnace.
A scan performed directly on a sample of the mixture epoxy
resin/curing agent without heat treatment was allowed to
determine the heat of reaction DH total generated by the complete
polymerization process.
2.3.2. TGA
2.3.2.1. Sample preparation. The epoxy samples were prepared
by the following three steps:
1. Heating the epoxy resin in an oven at 40 °C.
2. Adding the TiO 2 at different percentage 1%, 2%, 5% and
10%.
3. Heating samples at 135 °C for 6 h.
The thermal property of Epoxy resin/TiO 2 sample was investigated
by TG/DTG under N 2 environment. The analyses were
carried out using heating rates of 5.0, 10.0, 20.0 and
30.0 °C min 1 for each experiment with approximately
20.0 mg up to 850 °C.
3. Kinetic methods
3.1. Thermal analysis
The DSC plots were also fitted using the equation described by
Karkanas et al. (1996). The reaction rates for this work are calculated
from the DSC using the following equations:
2.2.3. TGA
The thermogravimetry analysis (TGA) was carried out on a
SETARAM 92-12 apparatus under an N 2 atmosphere.
a ¼ DH t
DH Tot
da
dt ¼ 1dDH t
DH tot dt
ð1Þ
ð2Þ
Figure 1 Chemical structures and cure reaction of DGEBA by DDS (Farquharson et al., 2007).

Kinetic study of the RTM6/TiO 2 by DSC/TGA for improved hardness of resin 39
Table 1 Total heat of reaction of RTM6 resin at different
heating rates.
Heating rate (°C min 1 ) 1 2 5 10 20 30
DH total (J g 1 ) 439.29 435.32 437.00 434.05 432.89 439.57
where DH t is the partial area under DSC trace up to time t and
DH tot is the total enthalpy of reaction measured as the area under
the heat flow against time for DSC.
The DSC plots were also fitted using the equation described
by Karkanas et al. (1996) and Puglia et al. (2003).
@a
@t ¼ðk 1 þ k 2 a m Þð1 aÞ n ð3Þ
@a
@t ¼ k 1ð1 aÞ n 1
þ k 2 a m ð1 aÞ n 2
ð4Þ
where k 1 and k 2 are the rate constants, m and n are the reaction
orders.
In the non-isothermal experiments carried out with a
thermobalance, the sample mass is measured as function of
temperature (see Fig. 1).
The calculation of kinetic data is based on the kinetic Eq.
(5):
@a
@t ¼ kan
where a is the amount of sample undergoing reaction, n is the
reaction order, and k is the specific rate constant. The temperature
dependence of k is expressed by Arrhenius Eq. (6):
k ¼ A exp
E a
RT
where A is the Arrhenius constant, E a is the activation energy,
and R is the gas constant.
The activation energy can be determined by Kissinger’s
method without a precise knowledge of the reaction mechanism,
using the following Eq. (7).
b
ln ¼ ln AR h i
1 E
þ ln nð1 aÞn ð7Þ
E
T 2 max
RT max
ð6Þ
where T max is the temperature corresponding to the inflection
point of the thermodegradation curves which correspond to
the maximum reaction rate, a max is the conversion at T max
and n is the reaction order. Taking into account the Kissinger’s
approximation which states that:
f 0 ða max Þ¼nð1 a max Þ n 1 ffi const ð8Þ
The activation energy can determined from a plot of
lnðb=T 2 max Þ against 1/T max.
4. Results and discussion
Table 1 shows the enthalpy of cure for DSC curing for isothermal
temperature after curing using DSC.
Fig. 2 shows the plots of conversion and reaction rate for
the isothermal curing of RTM6 cured using DSC. The conversions
and reaction rates were obtained using the DSC curves
and Eqs. (2) and (3).
The curves of reaction rate on time were fitted to the kinetics
Eq. (4). The equation was modified to account for the diffusion
effect, which occurs when the resin is transformed from the
rubbery to glassy state (Navabpour et al., 2006).
The time interval to reach that maximum value is different
for each cure temperature and shifts to longer times for lower
cure temperatures.
All the above observations lead to the conclusion that the
cure of the specific epoxy-amine system follows a complex
reaction mechanism, with autocatalytic phenomena occurring
during the early stages of the cure.
The reaction schemes for epoxies are relatively well established
and mainly involve primary and secondary amino group
addition to the epoxy group, for normal curing conditions.
Under extreme conditions of high cure temperatures, etherification
may also occur. These reactions may be catalysed by
any impurities present in the resin, or by the hydroxyl and
tertiary amine products formed, resulting in autocatalysis
(Shoichiro et al., 2005).
Table 2 summarizes the parameters obtained from fitting
the experimental data to the Eqs. (4) and (5). Values of preexponential
factor and activation energy were calculated from
Figure 2 (a) Fractional conversion for isothermal Cure at 100 °C for different time of reticulation. (b) Reaction rates for dynamic cure at
different times of cure for RTM6 at 100 °C.

40 L. Merad et al.
Table 2
Parameters obtained from fitting the isothermal curing results using DSC.
Cure temperature (°C) k 1 (10 5 s 1 ) k 2 (10 3 s 1 ) m n n 1 n 2
Eq. (4)
@a
@t ¼ðk 1 þ k 2 a m Þð1 aÞ n
100 2.21 0.53 0.95 0.59 – –
135 3.52 0.92 1.09 0.66 – –
150 4.30 1.35 1.11 0.79 – –
@a
Eq. (5)
@t ¼ k 1ð1 aÞ n1 þ k 2 a m ð1 aÞ n2
100 2.15 0.51 0.95 – 0.52 0.66
135 3.43 0.89 1.07 – 0.58 0.73
150 4.11 1.28 1.05 – 0.71 0.86
the temperature dependence of k 1 and k 2 using the Arrhenius
equation. Values of E 1 and E 2 for the conventionally cured
samples are in agreement with those obtained by Karkanas
and Partridge. The values of A 1 and A 2 were, however, much
smaller than the values obtained by them. As in their analysis
they did not correct the kinetics models for diffusion control,
the fits to the experimental data were not as good as in this
work, and this might explain the observed differences in
pre-exponential factors (see Fig. 3).
A 1 ¼ 22420 s 1 ; E 1 ¼ 71:l kJ mol 1
ð4Þ
A 2 ¼ 10256 s 1 ; E 2 ¼ 55:65 kJ mol 1
A 1 ¼ 25820 s 1 ; E 1 ¼ 73:6 kJ mol 1
A 2 ¼ 25460 s 1 ; E 2 ¼ 61:84 kJ mol 1
4.1. SEM
For appreciation dispersion of Nanoparticles TiO 2 .
As shown in Figs. 4 and 5 of SEM, the epoxy resin has a
smooth and flat surface in without TiO 2 , with addition of
percentage of TiO 2 it is observed that a relatively little amount
of TiO 2 particles are attached to the surface of resin with a
good dispersion.
The SEM analysis suggests that TiO 2 particles are uniformly
distributed within the materials.
The non-isothermal kinetic study of weight loss during a
thermal decomposition process of epoxy resin containing
ð5Þ
TiO 2 at 1%, 2%, 5% and 10%. Two different methods, all
based on Arrhenius kinetic theory, were used for the kinetic
analysis of the TG/DTG data: one based on differential
method and other based on integral method. In all of these
methods, calculations were performed to estimate the kinetic
parameter activation energy.
For obtaining the kinetic information, such as the activation
energy, the TGA study has been conducted with the
variation of the heating rates.
Fig. 6(a) shows the TGA thermograms of epoxy resin
containing different percentage of TiO 2 1%, 2%, 5% and
10% at a constant heating rate 10 °C min 1 .
Fig. 6(b) shows the TGA thermograms of epoxy resin
containing a 1% of TiO 2 , corresponding to dynamic experiments
carried out at different heating rates (5, 10, 20, and
30 °C min 1 ).
The corresponding differential (DTG) curves of this sample
are shown in Figs. 7 and 8. The thermal decomposition process
in two steps degradation, probably corresponding to epoxy
resin two step corresponding to the degradation of ether group
structures in the polymer matrix (Santos et al., 2002; Shoichiro
et al., 2005; Hansmann et al., 2003).
The non-isothermal kinetic study of weight loss during a
thermal decomposition process of RTM6/TiO 2 samples is
extremely complex because of the presence of two components
and their consecutive reactions. Two different methods, all
based on Arrhenius kinetic theory, were used for the analysis
of TG/DTG data, one on integral method and the other based
on approximation method. In all these methods, calculations
Figure 3 (a) Reaction rates for dynamic cure at different times of cure for RTM6 at 135 °C. (b) Reaction rates for dynamic cure at
different times of cure for RTM6 at 150 °C.

Kinetic study of the RTM6/TiO 2 by DSC/TGA for improved hardness of resin 41
Figure 4 (a) SEM image of RTM6 + 1% TiO 2 , (b) SEM image of RTM6 + 2% TiO 2 .
Figure 5 (a) SEM image of RTM6 + 5% TiO 2 , (b) SEM image of RTM6 + 10% TiO 2 .
Figure 6 (a) TGA thermograms of RTM6 with TiO 2 constant heating rate of 10 °C min 1 , (b) TGA thermograms of RTM6 with 1% at
a of TiO 2 at different heating rates.
were performed to estimate the kinetic parameter as activation
energy (Ng et al., 1999).
Using the Kissinger Eq. (11), lines of lnðb=T 2 maxÞ versus 1/
T max for each stage of the thermal degradation were plotted
for all samples. Fig. 9(a) shows the representative plots for
each stage of the thermal degradation of epoxy resin at 1%
of TiO 2 . The calculated decomposition activation energies
for epoxy step of all samples are listed in Table 2. The
activation energies for epoxy resins contain a different percentage
of TiO 2 as compared to them.
The all steps mainly involve the degradation of carbonyl
groups in the resin matrix. However, the activation energies
at higher conversions increase with increasing the percentage
of TiO 2 .
Another procedure for calculating the activation energy is
taking the Flynn–Wall–Ozawa equation. At given value of
the conversion, the activation energy can be obtained from a
logarithmic plot of heating rates as a function of the reciprocal
of temperature, since the slope of such a line is given by 0.4567
E/R. For the present work, the conversion values of 50% and
98% were used. The fitting lines of different samples at the
selected conversion values are shown in Fig. 9. All of the
calculated activation energies are listed in Table 3. The activation
energy at different conversions increases with increasing
the percentage of TiO 2 (Lu et al., 2004).
The experiment realized with different heating rates indicates
the same mechanisms with variation kinetic parameter
values. The kinetic parameter obtained by integral and
approximation methods presented good correlation. In
general, the values obtained by the Kissinger method were high
for the first step than the values obtained by the
Flynn–Wall–Ozawa method and for the second step the values
obtained by Kissinger were small than the values obtained by
the Flynn–Wall–Ozawa method. In the present study, the two

42 L. Merad et al.
Figure 7 (a) TGA thermograms of RTM6 with 2% of TiO 2 at different heating rates, (b) TGA thermograms of RTM6 with 5% of TiO 2
at different heating rates.
of a viscous flow. The blends undergo melting and noncross-linked
reagents leave the samples. Maybe the rate of their
escape inversely depends on the viscosity. Of course, catalytic
reactions with a diffusion control are possible as well. The
diffusion coefficient is inversely proportional to the viscosity.
When nano-TiO 2 particles are dispersed in epoxy resin, the
interaction between larger surface areas of particles and substrate
will help reduce the activity of substrate bond. This
interaction improves the hardness of materials such as the
mechanical property of the epoxy resin/TiO 2 . It can be seen
from Fig. 10 that when the concentration of nanosized TiO 2
powder increases, the hardness of materials will be improved
(see Tables 4 and 5).
5. Conclusions
Figure 8 DTG curve of a sample at a constant heating rate of
10 °C min 1 .
methods show good agreement when used to determine the
decomposition activation energies at certain conversion values.
The activation energy for the first step of the decomposition
is very low (about 25 kJ/mol or 6 kcal/mol). It is too low for
the overwhelming majority of high-temperature reactions. It
seems that such energy could be attributed to activation energy
A combination of nth order and autocatalytic reaction kinetics
was applied to fit data from dynamic and isothermal DSC
scans of a commercial RTM resin. A unique set of kinetic
parameters was obtained for the dynamic case, suggesting a
constant reaction mechanism throughout the range of the
heating rates used. In the isothermal case, the kinetic parameters
required to achieve a good fit were different from those
found in the dynamic runs; in particular, the reaction orders
had to be allowed to vary with cure temperature. The thermal
Figure 9 (a) Plot of lnðb=T 2 max Þ versus 1/T max of RTM6 with 1% of TiO 2 for calculating the activation (b) Plots of logb versus 1/T of
RTM6 with 1% of TiO 2 for calculating the activation energies by Kissinger method Flynn–Wall–Ozawa.

Kinetic study of the RTM6/TiO 2 by DSC/TGA for improved hardness of resin 43
Table 3
Calculated decomposition activation energies for every stage of all samples by Kissinger method.
Samples First step Second step
Temperature range (°C) D m (%) T (°C) Temperature range (°C) D m (%) T (°C)
RTM6 + 1%TiO 2 280–500 63.44 410.10 500–834.12 26.42 650.11
RTM6 + 2%TiO 2 280–500 65.43 415.78 500–834.12 28.67 654.67
RTM6 + 5%TiO 2 280–500 68.45 425.76 500–834.12 30.45 699.98
RTM6 + 10%TiO 2 280–500 74.76 435.56 500–834.12 33.56 673.45
loss rates were altered by the TiO 2 nanocharges. The kinetic
parameters obtained by approximation and integral methods
were satisfactory and present good correlation.
This experiment attempts to process materials, using epoxy
resin and nanosized TiO 2 powder, the hardness will increase
with the increase of concentration of TiO 2 .
References
Figure 10
TiO 2 .
Hardness of epoxy/TiO 2 on different concentration of
stability of epoxy resin containing nanocharges TiO 2 was evaluated
by thermogravimetric curves and activation energy obtained
from thermogravimetric data. The results obtained
indicated that the activation energies at higher conversions increase
with increasing the percentage of TiO 2 . The degradation
activation energies, decomposition temperatures and weight
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Table 4
Calculated decomposition activation energies for every stage of all samples by Kissinger method.
Samples Region Conversion a T max (K) (b =10°C.min 1 ) Activation Energy E a (kJ/mol) Correlation coefficient r
1% TiO 2 1 Step 0.00–0.50 0.00–0.50 673 21 0.995
Step 0.50–0.98 0.50–0.98 953 155 0.998
2% TiO 2 1 Step 0.00–0.50 0.00–0.50 675.67 23 0.998
2 Step 0.50–0.98 0.50–0.98 960.34 157 0.997
5% TiO 2 1 Step 0.00–0.50 0.00–0.50 678.56 25 0.993
2 Step 0.50–0.98 0.50–0.98 967.78 161 0.995
10% TiO 2 1 Step 0.00–0.50 0.00–0.50 683.56 29 0.996
2 Step 0.50–0.98 0.50–0.98 971.56 168 0.998
Table 5
Calculated decomposition activation energies for every stage of all samples by Flynn–Wall–Ozawa method.
Samples Region Conversion Activation Energy
E a (kJ/mol)
1% TiO 2 1 Step 0.00–0.50 0.00–0.50 29 0.995
2 Step 0.50–0.98 0.50–0.98 146 0.998
2% TiO 2 1 Step 0.00–0.50 0.00–0.50 25 0.998
2 Step 0.50–0.98 0.50–0.98 153 0.997
5% TiO 2 1 Step 0.00–0.50 0.00–0.50 28 0.993
2 Step 0.50–0.98 0.50–0.98 159 0.995
10% TiO 2 1 Step 0.00–0.50 0.00–0.50 31 0.996
2 Step 0.50–0.98 0.50–0.98 170 0.998
Correlation
coefficient r

44 L. Merad et al.
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Journal of the Association of Arab Universities for Basic and Applied Sciences (2012) 11, 45-49
تنقية وقود الديزل الحيوي باستخدام الكاربون المنشط المحضر من بقايا الشاي المستنفذ
عبدالرحمن باسل فاضل،‏
محمد مجبل ذياب،‏
عبدالقادر يوسف عبدالقادر
قسم
الكيمياء،‏ كليه
جامعة العلوم،‏
الموصل،‏ الموصل،‏
العراق
الملخص:‏
تضمنت
الدراسة الحالية
تحضير
تفاعل انتقال االسترة المحفز بالقاعدة.‏
استرات
النتائج
المثيل(‏
المستحصلة
هالم السليكا.‏
الناتجة وذلك
أظهرت
المثيل وخواص احتراقية
وقود الديزل الحيوي
باستخدام
‏)استرات المثيل(‏
بعد فصل الناتج العرضي
الكربون
مع نموذج الديزل الحيوي المنقى
النتائج
أفضل
أن
المستنفذ و استخدامه لنفس الغرض
تنقية الديزل الحيوي باستخدام
مقارنة بطرق التنقية
مرة أخرى.‏
من زيت القلي المستنفذ
‏)الكليسيرول(‏
تم تنقية
المنشط المحضر من بقايا الشاي المستنفذ.‏
باستخدام طريقة الغسل بالماء،‏
األخرى
وأظهرت
الكربون
المستخدمة.‏
النتائج
أعطى المنشط
من خالل
الديزل الحيوي)‏
قورنت ولقد
وطريقة التنقية باستخدام
حصيلة من استرات
كما تم إعادة تنشيط الكربون المنشط
أيضاً‏ أن الكربون
المنشط
المستنفذ المعاد
تشيطه هو األخر قد أعطى حصيلة أعلى وخواص احتراقية أفضل مقارنة بطرق التنقية األخرى المستخدمة.‏
A.Fadhil et al.

Journal of the Association of Arab Universities for Basic and Applied Sciences (2012) 11, 45–49
University of Bahrain
Journal of the Association of Arab Universities for
Basic and Applied Sciences
www.elsevier.com/locate/jaaubas
www.sciencedirect.com
ORIGINAL ARTICLE
Purification of biodiesel using activated carbons
produced from spent tea waste
Abdelrahman B. Fadhil *, Mohammed M. Dheyab, Abdul-Qader Y. Abdul-Qader
Department of Chemistry, College of Science, Mosul University, Mosul, Iraq
Available online 30 January 2012
KEYWORDS
Biodiesel;
Waste cooking oil;
Spent tea waste;
Activated carbons;
Fuel properties
Abstract Waste cooking oil was converted into biodiesel through base catalyzed transesterification.
After separating the glycerol, the crude methyl esters were purified using activated carbons
produced from spent tea waste. Yield and fuel properties of the produced biodiesels were compared
with those purified by using silica gel and conventional method namely water washing method. The
study revealed that using activated carbons for the purification of biodiesel resulted in higher yield
and better fuel properties compared to those purified using silica gel and water washing method.
Furthermore, the spent activated carbon was regenerated and reused for the same purpose. However,
the results showed that the yield and fuel properties of those purified using the regenerated
activated carbon were also better than those purified using silica gel and water washing method.
ª 2012 University of Bahrain. Production and hosting by Elsevier B.V. All rights reserved.
1. Introduction
* Corresponding author.
E-mail address: abdelrahmanbasil@yahoo.com (A.B. Fadhil).
1815-3852 ª 2012 University of Bahrain. Production and hosting by
Elsevier B.V. All rights reserved.
Peer review under responsibility of University of Bahrain.
doi:10.1016/j.jaubas.2011.12.001
Production and hosting by Elsevier
The production of biodiesel from edible oils competes with the
use of land for food production. Moreover, the price of edible
plant and vegetable oils is usually higher than petro diesel.
Thus, finding a cheaper feedstock such as waste cooking oil
for biodiesel production reduces the cost of biodiesel production
since the feedstock costs constitutes approximately 70–
95% of the overall cost of biodiesel production. Hence, the
use of waste cooking oils and non-edible oils should be given
higher priority over the edible oils as biodiesel feedstock
(Chhetri et al., 2008; Canakci, 2007). The purity level of the
biodiesel has strong influence on its fuel properties. Especially,
the amount of glycerides and triglycerides present in the fuel
can cause serious problems in application. Another factor that
must be taken into account is that the fuel must be almost free
of water, alcohol, glycerin and catalyst; thus, the ester layer
has to be treated. Therefore, the refining step of the products
obtained by transesterification is very important (Karaosmanoglu
et al., 1996; Predojevic, 2008).
In this study, the production of biodiesel from waste cooking
oil through base catalyzed transesterification was investigated.
After separating the glycerol, the crude methyl esters
were purified using activated carbons produced from spent
tea waste. The results were compared with those purified by
using silica gel and water washing methods. Properties of the
produced fuels were measured and compared with those purified
using other methods. Furthermore, the spent activated

46 A.B. Fadhil et al.
carbon was regenerated and reused again for the same
purpose.
2. Materials and methods
2.1. Preparation of carbon adsorbents
Tea is the second drink after water in Iraq. Therefore, large
amounts of tea are consumed, accumulated and discarded.
Such biowaste could be an attractive precursor for activated
carbon (AC) preparation. Spent tea waste (STW) was collected
from local coffee shops within the city of Mosul, north of Iraq.
STW was washed thoroughly with tap water and by distillated
water several times, then it was dried in an oven at 50 °C for
5 h. The dried STW was sieved using a 20–40 mesh sieve,
and the particles of 30–40 mesh were used as a precursor for
activated carbon (AC) production. Two types of activated carbons
were prepared from STW as follows:
For batches, 20 g of the dried STW was placed into a quartz
tube, and the tube was in turn placed into an electrical tubular
furnace. The furnace was heated gradually until a temperature
of 600 °C was reached. The activation was conducted at this
temperature for 120 min, to produce thermally activated carbon
(AC TH ). The second type was prepared through placing
20 g of the dried STW into a stainless steel tube which was
placed into an electrical tubular furnace. The sample was
heated gradually in a flow of steam until a temperature of
600 °C was attained. The activation was performed at this temperature
for 120 min to produce (AC ST ). The yield of the produced
carbons was calculated as following:
Yield% ¼ W ACproduced
W STWused
100
Silica gel was thermally activated at 105 °C for 5 h and was
kept in a sealed container to be used later.
2.2. Assessment of the produced carbon adsorbents
Surface area of the prepared activated carbons (ACs) was
determined by their adsorptive capacity of iodine, referred to
as iodine adsorption number (IAN). The quantity of iodine adsorbed
per gram of the activated carbon was determined by
titration against the standard solution of sodium thiosulphate
according to ASTM (1999). Adsorption capacity for the prepared
carbons was determined through their adsorption of
methylene blue (MB) from its aqueous solution. Surface properties
of the produced carbons such as PH, total acidity and
oxygen surface groups were determined. The surface functional
groups of the activated carbons were analyzed by a Fourier
transform infrared (FTIR) spectroscope.
2.3. Preparation of the raw oil
Waste cooking oil (WCO) was collected from local restaurants
within the city of Mosul, north of Iraq and used as a feedstock
for biodiesel production. At first, 500 g of the oil was mixed
with freshly activated MgSO 4 , and left overnight to eliminate
any water content. Then the oil was filtered by using cloth filter
to remove any solid impurities and MgSO 4 particles, and was
kept in a sealed container to be used later. Mean molecular
weight of the oil was determined according to the formula presented
by (Zhu et al., 2006):
MW ¼ 56:1 1000 3=ðSV AVÞ ð2Þ
where, SV is the saponification value and AV is the acid value.
2.4. Transesterification of waste cooking oil
Five hundred grams of the oil was poured into a 250 mL three
necked round bottomed flask equipped with a mechanical stirrer,
and a condenser, and placed in water bath. Freshly prepared
catalyst solution (KOH = 0.75% w/w of oil dissolved
in methanol in a ratio of 6:1 MeOH–oil) was introduced into
the reactor. The mixture was refluxed for 1 h at (60 °C) with
continuous stirring. After the reaction was over, the mixture
was transferred into a separating funnel and left to settle for
24 h. Two layers were obtained, the upper was the methyl esters
(ME) and the lower was the glycerol. Glycerol layer was
discarded, and the methyl ester layer was distillated under vacuum
to recover excess methanol. Finally, the methyl ester layer
was kept for purification and assessment.
2.5. Chemicals
Methanol (reagent grade), acetone, glacial acetic acid, iodine,
potassium iodide, sodium thiosulfate, starch, diethyl ether, isopropyl
alcohol, silica gel and formic acid were purchased from
BDH. Potassium and sodium hydroxide, and magnesium sulfate
were supplied from Merck, whereas chloroform, n-hexane
and hydrochloric acid were supplied from Fluka. Chemicals
were used without any further purification.
2.6. Purification of biodiesel over activated carbons
A chromatography column of (15 cm height and 1 cm i.d) was
packed with glass wool, then a bed (2 g = 5 cm) of activated
carbon was introduced into the column. Next, crude methyl esters
were transferred into the column and allowed to pass
through the adsorbent bed with a flow rate of (15 drop/min).
Percentage yield was calculated on a weight basis with respect
to the methyl ester introduced into the column (Predojevic,
2008). Silica gel was also used for the same purpose. Purification
using (water washing) method was also adopted.
Table 1
Physicochemical properties of the raw oil.
Property Test procedure Value
Density @ 16 °C g/ml (D) ASTM D4052-91 0.9233
Kine.Viscosity@ 40 °Cmm 2 /s(KV) ASTM D445 26.50
Flash point °C (T F ) ASTM D93 244
Pour point °C (PP) ASTM D2500 9
Cloud point °C (CP) ASTM D2500 1
Acid value mg KOH/g (AV) ASTM D664 2.82
Iodine number mg I 2 /100 oil(IN) Paquot, 1979 110
Refractive index @ 20 °C (RI) D1747-09 1.470
Conradson carbon residue% (CCR) ASTM D4530 0.35
Sapon. value mg KOH/g oil (SV) ASTM D5555-95 201
Calculated cetane index (CCI) Krisnangkura, 1986 49.15
Higher heating value (HHV) Demirbas, 2008 39.27

Purification of biodiesel using activated carbons produced from spent tea waste 47
Table 2
Characteristics of the prepared carbon adsorbents.
Sample Yield % IAN mg I 2 /g MB mg/g PH Acidity m mol g 1 Basicity m mol g 1
AC ST 27 767 39.30 9 1.57 3.55
AC TH 41 688 43.0 8 1.53 3.15
SG – 478 – – –
2.7. Properties assessment of the purified biodiesels
Properties of the parent oil were measured according to the
ASTM standards listed in Table 1. Iodine number (IN) was
measured according to the Hanus method (Paquot, 1979).
Higher heating value (HHV) was determined depending on
equations proposed by Demirbas (Demirbas, 2008). The calculated
cetane index (CCI) is based on Krisnagkura equation
(Krisnangkura, 1986):
CCI ¼ 46:3 þð5458=SVÞ ð0:225INÞ ð3Þ
Where, SV is the saponification value and IN is the iodine
number.
2.8. Regeneration of spent activated carbon
Spent activated carbon (AC ST ) used for the purification of
crude methyl esters was regenerated to be reused for the purpose
explained in (Section 2.6). Then, the yield and fuel properties
of the purified methyl esters were determined and
compared with those purified by the authentic (AC ST ), silica
gel and water washing method.
3. Results and discussion
3.1. Properties of the feed stock
Each value of the measured properties was the result of at least
two trials, only the mean was recorded. The average molecular
weight obtained for WCO is 821. It is well known that base
catalyzed transesterification (BCTE) is not suitable for oils of
high free fatty acid content (>1%), for it leads to catalyst
deactivation and soap formation. As a result, yield decreases
(Sharma et al., 2008). However, reviewing the literature indicates
little works about the production of BD from oils of high
fatty acid content using BCTE (Phan and Phan, 2008; Araujo
et al., 2011).
3.2. Characterization of the adsorbents
Yield, total acidity, PH, oxygen surface groups and iodine and
methylene blue adsorption numbers of the produced biochars
were determined and presented in Table 2. Yield of the produced
carbons was specified as the ratio of the weight of final
activated carbons to that of initial raw materials used for the
preparation. It can be seen from Table 2 that yield AC ST
was lower than that produced through one step pyrolysis. This
is because steam accelerates further removal of the volatiles
from the structure of the feedstock. As a result, the yield decreases.
Iodine adsorption number was used as a function of
surface area of the produced carbons. Each 1.0 mg of iodine
adsorbed equals to 1.0 m 2 of the activated carbon internal surface
area (Egwaikhide et al., 2007). Iodine adsorption numbers
of the adsorbents are listed in Table 2. It can be seen from this
table that AC ST had higher surface area compared to AC TH .
This is because steam activation helps to increase the porous
structure through further removal of volatiles. Consequently,
the surface area increases. The adsorption of methylene blue
is attributed to its meso porosity. MB values of the produced
carbons were much lower than those of the IAN. This means
that the produced carbons have micro porous structures. The
values of PH showed that both AC ST and AC TH had a basic
surface, but the surface of AC ST was more basic. This was also
confirmed through the titration against a (0.06 M) solution of
HCl. The most important oxygen groups specified by FTIR
spectroscope for the produced AC are presented in Table 3.
3.3. Purification of biodiesel using the produced activated
carbons
The main purpose of this study was to use the produced activated
carbons for biodiesel purification, and comparing its results
with those purified by using silica gel and water washing
methods. Yields of the produced BD fuels were specified by the
weight percentage of the purified BD relative to the original
weight of the crude methyl esters introduced into the column.
It can be seen from Tables 4 that using ACs for purification of
the crude methyl esters results in higher yields compared to
using SG and water washing methods. In comparison to SG,
activated carbon has higher surface area. Besides, it is well
known that the adsorption takes place through physical or
chemical interactions between the adsorbate and the adsorbent
surface. Furthermore, the oxygen groups that exist on the surface
of the adsorbent play an important role in the adsorption.
As for the SG, it is well known that the only groups that exist
in SG are silanol groups, while many oxygen groups can be
found on the surface of activated carbon. This is why, purification
using ACs is better. With regard to water washing method,
excessive amounts of water are added with gentle shaking
to remove impurities such as glycerol, unreacted methanol and
base (catalyst). Consequently; part of the esters is lost in the
form of emulsion and soaps decreasing the yield. One of the
disadvantages of this method is that it produces large amounts
Table 3 Fundamental IR absorption bands of the produced
carbons.
Band cm 1 Possible assignment
3425–3435 OH groups in aliphatic and phenolic structures
2925 Represents aliphatic CH, CH 2 and CH 3 stretching
modes
1726 C‚O in ketones, aldehydes or carboxyl
1599 VC‚O
1450 C–O Stretching vibrations, C–O–C, O–H bending
modes in carboxylic acids, carboxyl, lactones, esters,
and ethers.
874 O–O stretching
716 C‚O stretching

48 A.B. Fadhil et al.
Table 4
ACs.
Property
Yields and properties of biodiesel purified using the
WCO
AC ST AC TH SG Washing by DW
Yield% 97 95.50 93 88
Density @ 16 °C g/ml 0.8755 0.8766 0.8800 0.8920
KV @ 40 °Cmm 2 /sec 2.63 2.73 3.22 3.40
AV mg KOH/g oil 0.092 0.144 0.247 0.301
RI @ 20 °C 1.445 1.446 1.448 1.457
(PP) °C 8 8 7 6
T F °C 169 169 172 175
HHV MJ/KG 40.66 40.71 40.93 41.11
of highly polluting wastewater. It also increases the size and
cost of the separation equipment, resulting in yield loss, and
causes an environmental disposal problem (Saleh et al.,
2010). Pighinelli et al. (2011) prepared ethyl ester from sunflower
oil. They used three methods for purifying the produced
ethyl esters including acidified water (5% of phosphoric acid),
silica gel and distillation. The yields of the produced ethyl esters
obtained by using these purification methods were
(84.4%, 84.6% and 92.3%), respectively. Predojevic (2008)
prepared biodiesels from waste cooking. He used three different
methods for the purification of the produced methyl esters
including water washing method, washing by acidified water
(5% H 3 PO 4 ) and silica gel. He found that purification by the
acidified water and silica gel methods resulted in higher yield
(92%) compared to the water washing method (89%). Therefore,
one can say, that our handling was better than those applied
by the aforementioned studies; it resulted in higher yields.
For BD to be used as a fuel in diesel engines, it should meet
some specifications according to the ASTM standards or
European standards. Thus, after the purification of the produced
methyl esters by the suggested method, some essential
properties were measured, and compared to those obtained
by other methods. These properties were measured according
to the ASTM standards as can be seen in Table 1; fuel properties
of the produced fuels are given in Table 4.
One of the most important properties of biodiesel is viscosity.
This property should be low. Poor atomization of the fuel
spray and less accurate operation of the fuel injectors is associated
with high viscosity (Demirbas, 2009). It is obvious from
Table 4 that the viscosity of the methyl esters purified using the
ACs was lower than that purified by SG and water washing
method. This means that the ACs is an effective adsorbent in
removing impurities, such as glycerol and soaps which accompany
the biodiesel during its production, compared to SG and
water washing. The values were between (2.63 and 3.40 mm 2 /
sec). These values were much lower than those recommended
by the ASTM and the European standards. Density is another
important property of biodiesel. As in the case of the viscosity
values, the density of the methyl esters purified using ACs were
also lower than that purified using SG and water washing
method. The values ranged from (0.8755 to 0.8920 g/mL).
The acid value can be used as a guide in quality control of
fuels. Acid value for the produced methyl esters was lower
than that of the parent oil. Methyl esters purified using ACs
had lower acid values than those purified by using SG and
water washing method. Lower acid values of the methyl esters
purified using ACs reflects the high refining degree compared
to the methyl esters purified using SG and water washing
method. The values ranged from (0.092 to 0.301 mg KOH/
g). Refractive index (RI) values of the fuels were lower than
that of the parent oil and ranged between (1.445 and 1.457).
The flash point is the lowest temperature at which a fuel will
ignite when exposed to an ignition source (Ghobadian
et al.,2008). Flash point values of the methyl esters purified
using the ACs were lower than those purified using SG and
water washing method. This is because purification using
ACs leads to further elimination of impurities such as unreacted
triglycerides, glycerol and the catalyst, as well as higher
ester content of these samples is behind this phenomenon. The
pour point values ranged from ( 6to 8). Such values could
be a good indicator of the fact that BD fuels prepared in this
study are suitable for use in cold weather conditions prevailing
in Northern Iraq in winter. The HHV values ranged from
(40.66 to 41.11) million joules/Kg).
3.4. Regeneration of spent activated carbon
Some authors used adsorbents such as Magnesol, SG and ion
exchangers for BD purification. Borrios and Skelton (2008)
used Magnesol and ion exchanger resin for BD purification.
Predojevic (2008) used SG for BD purification. He found that
purification using SG resulted in higher yield and better fuel
properties in comparison to water washing method. However,
the problem with these adsorbents is that they cannot be recycled.
Besides, it is hard to dispose of their wastes particularly at
a larger scale (Saleh et al., 2010). One of the attractive characteristics
of activated carbon is that it can be regenerated therefore
spent activated carbon was regenerated and denoted as
(AC SR ). Yield and fuel properties of BD purified using (AC SR )
are listed in Table 4. It was found that the yield and the fuel
properties especially the acid value, kinematic viscosity and
flash point of BD purified using the AC SR were lower than
Table 5 Yield and properties of the biodiesel purified using AC SR .
Property
WCO
AC SR AC ST SG Washing by DW
Yield% 94 97 93 88
Density @ 16 °C g/ml 0.8865 0.8755 0.8800 0.8920
KV @ 40 °Cmm 2 /sec 3.10 2.63 3.22 3.40
AV mg KOH/g oil 0.195 0.092 0.247 0.301
RI @ 20 °C 1.449 1.445 1.448 1.457
(PP) °C 7 8 7 6
T F °C 171 169 172 175
HHV MJ/KG 40.89 40.66 40.93 41.11

Purification of biodiesel using activated carbons produced from spent tea waste 49
those purified using the AC S as can be seen from Table 5. This
can be attributed to the reduction of the active sites available
for the adsorption. However, in comparison to methyl esters
purified using SG and water washing method; purification
using AC SR resulted in higher yield and better fuel properties.
Thus, it can be said that AC or AC SR is a good adsorbent for
the purification of biodiesel in comparison to the SG or water
washing method.
4. Conclusions
Activated carbons prepared from spent tea waste used for the
purification of crude biodiesel produced from waste cooking
oil through base catalyzed transesterification. For comparison,
silica gel and water washing were also used for the same purpose.
The study showed that in general, using activated carbons
for biodiesel purification resulted in higher yields and
better fuel properties compared to the above mentioned methods.
Moreover, the fuel properties met the specified limits
according to the ASTM standards. Furthermore, spent activated
carbon was regenerated and reused for the same purpose.
The results indicated that regenerated activated carbon
was effective to produce a biodiesel fuel of higher yield and
better fuel properties compared to the other methods.
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Journal of the Association of Arab Universities for Basic and Applied Sciences (2012) 11, 50-55
حيوية بكتيريا اللبن والتقيم الحسي في الزبادي الحيوي بالقرفة او الثوم والمحضره من
حليب االبل والبقر
أمل شوري و أحمد بابا
30605
قسم الكمياء الحيوية ،
معهد علوم
الحياة،‏
كلية العلوم،‏
جامعة مااليا
كواللمبور،‏
ماليزيا
الملخص:‏
أجريت الدراسة الحالية للتحقق من تأثير الخالصة المائية المحضرة من الثوم
)Allium sativum(
)Cinnamomum verum(
على حيوية بكتيريا اللبن
والقرفة
Lactobacillus spp. (
)Streptococcus thermophilus
12 ثالجة لمدة
للزبادي.‏ تراوحت أعداد
يوم تحت درجة حرارة
4
Lactobacillus spp.
عدم وجود الخالصة المائية للثوم أو القرفة من
و
في الزبادي المحضر من حليب البقر واإلبل خالل فترة حفظه في
درجات مئوية.‏ كما تم خالل هذه الدراسة تقييم الخصائص الحسية
في الزبادي الطازج المحضر من حليب البقر في وجود أو
10 6 X 2.4
إلى
cfu/ml 10 6 X 2.1
في اليوم األول من
البدء في الدراسة.‏ ولم تتغير هذه القيمة بشكل معنوي طوال فترة التخزين المبرد التي استمرت لمدة
أما بالنسبة ألعداد
للثوم والقرفة فقد كانت
12
Lactobacillus spp.
cfu/ml 10 6 X 13.2
البكتيريا بشكل معنوي،‏ بعد إضافة الخالصة المائية للقرفة والثوم ، إلى
يوم.‏
في الزبادي المحضر من حليب اإلبل بدون الخالصة المائية
في اليوم األول من البدء في الدراسة،‏ وازدادت أعداد
و
10 6 X 26.9 10 6 X 19.2
cfu/ml
على التوالي.‏
الخالصة المائية.‏ أما بالنسبة ألعداد بكتيريا
في حين أن أعداد هذه البكتيريا انخفضت بشكل خطي في التخزين المبرد بدون
Streptococcus thermophilus
في الزبادي المحضر من
حليب البقر أو حليب اإلبل،‏ سواء بوجود أو في عدم وجود الخالصة المائية،‏ فقد تراوحت من
1.4
cfu/ml 21 8 X 6.3
مع تزايد األعداد في اليوم
24
إلى
من التخزين المبرد.‏ وفيما يتعلق بالخصائص الحسية
فلم توجد اختالفات في الطعم مثل الحموضة أو المرارة أو الحالوة بين كال المجموعتين من الزبادي.‏ إال أن
وجود الخالصة المائية للثوم في زبادي حليب البقر خفضت بشكل معنوي جودة الرائحة إلى
مقارنة بزبادي حليب اإلبل
2.3±0.7
.)5.5±1.0(
A.B. Shori, A.S. Baba

Journal of the Association of Arab Universities for Basic and Applied Sciences (2012) 11, 50–55
University of Bahrain
Journal of the Association of Arab Universities for
Basic and Applied Sciences
www.elsevier.com/locate/jaaubas
www.sciencedirect.com
ORIGINAL ARTICLE
Viability of lactic acid bacteria and sensory evaluation
in Cinnamomum verum and Allium sativum-bio-yogurts
made from camel and cow milk
Amal Bakr Shori *, Ahmad S. Baba
Biomolecular Research Group, Division of Biochemistry, Institute of Biological Sciences, Faculty of Science,
University of Malaya, 50603 Kuala Lumpur, Malaysia
Available online 15 December 2011
KEYWORDS
Yogurt;
S. thermophilus;
Lactobacillus spp;
Allium sativum;
Cinnamomum verum
Abstract The present study investigate the effect of herbal water extract prepared from Allium sativum
and Cinnamomum verum on the viability of lactic acid bacteria (Lactobacillus spp and Streptococcus
thermophilus) in cow- and camel-milk yogurts during 21 day refrigerated storage. The
organoleptic properties of fresh-yogurts were evaluated. Lactobacillus spp count for fresh cow
milk-yogurts (0 day) in both present and absent of C. verum and A. sativum was ranged from 1.4
·10 6 to 2.1 · 10 6 cfu/mL. These values were not significantly changed throughout the 21 days of
refrigerated storage. Lactobacillus spp count in fresh plain camel milk- yogurt was 13.2 · 10 6 cfu/
mL whereas fresh C. verum- and A. sativum-camel milk- yogurts had higher Lactobacillus spp
counts (19.2 · 10 6 and 26.9 · 10 6 cfu/mL respectively; p < 0.05). However, refrigerated storage
to 21 days resulted in linear decrease in Lactobacillus spp counts. Furthermore, S. thermophilus
counts in fresh cow- and camel- milk yogurts in either absent or present of C. verum or A. sativum
ranged from 2.4 to 3.6 · 10 8 cfu/mL and these values increased by day 14 of storage. In organoleptic
properties of yogurts no differences were observed in sourness, bitterness, and overall preference
scores between the two groups of yogurts. The present of A. sativum in cow milk-yogurt reduced
the aroma score to (2.3 ± 0.7, p < 0.05) compared to camel milk-yogurt (5.5 ± 1.0).
ª 2011 University of Bahrain. Production and hosting by Elsevier B.V. All rights reserved.
* Corresponding author.
E-mail address: shori_7506@hotmail.com (A.B. Shori).
1815-3852 ª 2011 University of Bahrain. Production and hosting by
Elsevier B.V. All rights reserved.
Peer review under responsibility of University of Bahrain.
doi:10.1016/j.jaubas.2011.11.001
Production and hosting by Elsevier
1. Introduction
Recently, the food biotechnology industry has developed a
number of commercial products containing a single probiotic
strain or bacterial associations of various complexities. Yogurt
has been known for its nutraceutical, therapeutic, and probiotic
effects (Gu¨ ler-Akın and Akın, 2007). Also, lactic acid bacteria
and its metabolites have shown to play an important role
in improving microbiological quality and shelf-life of many
fermented food products. Dairy products have long been consumed
by consumers and provide a good example of bio-preservation
(Zottola et al., 1994).

Viability of lactic acid bacteria and sensory evaluation in Cinnamomum verum and Allium sativum 51
Today LAB is a focus of intensive international research for
its pivotal role in most fermented foods. Basically, for its ability
to produce various anti-microbial compounds promoting probiotic
properties (Temmerman et al., 2002) that includes antitumoral
activity (De-Vuyst and Degeest, 1999; Østlie et al.,
2003), reduction of serum cholesterol (Desmazeaud,1996; Jackson
et al., 2002), alleviation of lactose intolerance (De Vrese
et al., 2001), stimulation of the immune system (Isolauri et al.,
2001), and stabilization of gut microflora (Gibson et al., 1997).
Furthermore, LAB strains synthesize short chain fatty acids,
vitamins, and exopolysaccharides (EPS) that are employed in
the manufacturing of fermented milk to improve its texture
and viscosity (Curk et al., 1996; Ruas-Madiedo et al., 2002).
The main technological properties of yogurt bacteria in milk fermentation
are acidification, texture enhancement, flavour production,
and the final level of lactic acid which is the main
product of the metabolic activity of starter cultures. However,
the acidification rate during yogurt production depends on the
strains and their associations (Beal et al., 1999).
Development of dairy products with new products and flavours
has potential health benefits thereby increasing sales and
consumers satisfaction. Traditional preparation of yogurt may
be beneficial by including other ingredients such as soya protein,
vegetables, sweet potato, pumpkin and plum (Joo et al., 2001;
Park et al., 2003) to enhance the flavour as well as the nutritional
quality (Shori and Baba, 2011). However, traditional medicinal
plants such as Allium sativum and Cinnamomum verum have
been proved to provide important therapeutic values. Besides,
it is highly aromatic and possesses anti-microbial activities (Harris
et al., 2001; Gende et al., 2008) that could affect the yogurts’
LAB counts and their organoleptic properties. Therefore, the
objective of the present research was to study the survival of
LAB in A. sativum and C. verum yogurts made from cow milk
and camel milk and comparison to their respective plain yogurts
during 21 day of refrigerated storage and evaluate the organoleptic
properties of these yogurts.
2. Materials and methods
2.1. Materials and chemicals
Commercial fresh and pasteurized full cream cow milk (Dutch
Lady, Malaysia) and camel milk (Al-Turath, Saudi Arabia)
were purchased from supermarket. Camel milk was frozen
and used to make yogurt within 2 weeks from the date of pasteurization.
The herbs used in the present study were C. verum
bark purchased from local store in Saudi Arabia and A. sativum
powder (McCormick, Malaysia). Further supplies incorporated
in present study were commercially available yogurt
bacteria mixture (Chris-Hansen, Denmark) and probiotic mixture
(Bio-Life, Malaysia) in which one capsule contained 5 billion
cfu of probiotic bacteria. The agars used in the present
study were M.R.S Agar, M17 Agar obtained from Oxoid
(Basingstoke, Hampshire, England). Additionally, lactose
monohyrate, C 12 H 22 O 11 ÆH 2 O was obtained from Systerm.
2.2. Water extraction of herbs
Ten grams of C. verum bark and A. sativum powder were
mixed thoroughly with 100 mL of distilled H 2 O. The mixture
was incubated overnight in a water bath at 70 °C (Julabo,
Model Sw-21c or Haake Model SWD 20) followed by centrifugation
(Eppendoft 5804 R; 10000 rpm) for 15 min at 4 °C. The
clear supernatants were harvested and used as C. verum and A.
sativum water extracts in the making of herbal yogurts (Behrad
et al., 2009).
2.3. Preparation of starter culture
Starter culture for making yogurt was prepared by pre-heating
of fresh and pasteurized full cream milk to 41 °C. A mixture
of yogurt bacteria consisting of Lactobacillus acidophilus
LA-5, Bifidobacterium bifidum Bb-12, Lactobacillus casei LC-
01 and Streptococcus thermophilus Th-4 in the ratio of 4:4:1:1
and a capsule of probiotic mix containing L. bulgaricus, L.
rhamnosus, B. infantis and B. longum in the ratio of 1:1:1:1
were mixed thoroughly with the preheated milk prior to an
overnight incubation at 41 °C. The yogurt formed was refrigerated
(4 °C) and used as starter culture within 7 days (Rashid
et al., 2007).
2.4. Preparation of yogurts
C. verum and A. sativum yogurts were prepared by mixing
10 mL of each herbal-water extract with 85 mL of pasteurized
full cream milk and 5 g of starter culture (Shah, 2003). The mixture
was mixed thoroughly followed by incubation at 41 °C. The
pH of the mixture was determined every 30 min until the pH of
yogurt reached 4.5 by using pH meter (Cyper Scan 510). At that
moment, the incubation was terminated by placing the yogurts
in ice-bath for 60 min. These yogurts were then placed in the
refrigerator for up to 21 days. Control yogurts were prepared
using the same procedures except 10 mL of distilled H 2 O was
used in place of herbal-water extract.
2.5. Microbial viable cell count (VCC) in yogurts
2.5.1. Buffered peptone water
Twenty grams of buffered peptone water was mixed with 1 L
distilled water, the mixture was distributed into final tubes followed
by autoclaved at 121 °C for 20 min. The pH of media at
25 °C was 7.2 ± 0.2.
2.5.2. Sample preparation
Yogurt samples (1 mL) were individually mixed with 9 mL of
0.15% sterile buffered peptone water. The mixtures were thoroughly
stirred and serial dilutions were prepared by using buffered
peptone water.
2.5.3. Enumeration of Lactobacillus spp using the pour plate
method
Lactobacillus spp was enumerated, particularly, as described
by Kailasapathy et al. (2008). MRS agar was prepared by mixing
MRS powder with water (62 g/1 L distilled H 2 O) and the
solution was autoclaved followed by cooling to 45 °C. The
melted MRS agar (15 mL) was then placed in a petri dish.
Appropriately diluted yogurt (1 mL) was then transferred in
the molten MRS agar. The mixture was evenly mixed by gently
tilting and swirling the dish. The plates were sealed with parafilm
and were left at room temperature to allow the agar to

52 A.B. Shori, A.S. Baba
solidify. Thereafter, the plates were inverted and placed in the
incubator (37 °C) for 48 h. Viable Lactobacillus spp count was
calculated (Sivakumar and Kalaiarasu, 2010) as follows:
CFU Number of colonies formed dilution factor of sample
=mL ¼
1mL of sample
*CFU: colony forming unit.
2.5.4. Enumeration of S. thermophilus using the spread count
method
S. thermophilus was enumerated using M17 agar (Rybka and
Kailasapathy, 1995). The M17 agar powder was mixed with
water (48.3 g in 950 mL distilled H 2 O) and the mixture was sterilized
by autoclaving. The molten M17 agar was allowed to cool
to 45 °C prior to the addition of sterilized lactose solution
(50 mL, 10% w/v). The mixture was dispensed (15 mL) in a petri
dish and the molten M17 agar was allowed to solidify at room
temperature. Appropriately diluted yogurt (0.1 mL) was placed
on the M17 agar and the sample was spread on the surface using
a sterile spreader. The plates were incubated in inverted position
at 37 °C for 48 h. Viable microbial count (S. thermophilus) was
calculated (Sivakumar and Kalaiarasu, 2010) as follows:
CFU Number of colonies formed dilution factor of sample
=mL ¼
0:1mL of sample
*CFU: colony forming unit.
2.6. Organoleptic properties
Organoleptic properties on yogurt were running after 1 day of
refrigerated storage. Twelve participants were randomly selected
and identified themselves as students and departmental
staff. Their age range between 20 and 35 years and were engaged
as untrained panels for the sensory evaluation. Each panel was
presented with two groups of yogurt (cow-milk and camel-milk
yogurts) each group contains three coded yogurt samples
(10 mL for each). The first group contained
plain-cow-milk yogurt, A. sativum-cow-milk yogurt, and C. verum-cow-milk
yogurt. The second group contained plain-camelmilk
yogurt, A. sativum-camel-milk yogurt, and C. verum-camelmilk
yogurt. The evaluation was scored on 1–10 point hedonic
scale (1–2 = extremely poor, 3–4 = poor, 5–6 = fair, 7–
8 = good, 9–10 = excellent) according to taste (sour, sweet,
and bitter), aroma and overall preference.
3.1.1. Bacteria counts of Lactobacillus spp
Lactobacillus spp counts were 1.4 · 10 6 , 2.1 · 10 6 , and
1.7 · 10 6 cfu/mL for fresh plain-, C. verum- and A. sativumcow-milk
yogurts, respectively (Fig. 1). Lactobacillus spp
counts increased to about 2.3 · 10 6 cfu/mL for all three yogurts
by day 7 of storage with significant effect (p < 0.05) seen
in plain-cow-milk yogurt. Lactobacillus spp counts in all three
yogurts were almost similar during the 14 days of storage but
the viable cell counts reduced gradually to 1.4 · 10 6 cfu/mL for
plain- and A. sativum-cow-milk yogurts and 1.7 · 10 6 cfu/mL
for C. verum-cow-milk yogurt by day 21 of storage.
In contrast, Lactobacillus spp counts in fresh camel-milk
yogurts were about tenfold higher than in fresh cow-milk yogurts
(Figs. 1 and 2). The viable cell count in plain-camel-milk
yogurt was 13.2 · 10 6 cfu/mL; however, the addition of C. verum
and A. sativum increased (p < 0.05) the counts to
19.2 · 10 6 and 26.9 · 10 6 cfu/mL, respectively. There were
small decreases in Lactobacillus spp counts in yogurts
(p < 0.05, for plain-camel-milk yogurt) after 7 days refrigerated
storage. However, pronounced reduction in Lactobacillus
spp counts occurred in plain- and A. sativum-camel-milk
yogurts over the 14 days with lowest count being 1.3 · 10 6
and 1.7 · 10 6 cfu/mL, respectively, on day 21 of storage. Lactobacillus
spp counts in C. verum-camel-milk yogurts reduced
slowly during this period resulting in highest counts
(4.3 · 10 6 cfu/mL) amongst the three types of camel-milk yogurts
on day 21 of storage.
3.1.2. Bacteria counts of Streptococcus thermophilus
S. thermophilus counts in fresh cow- and camel-milk yogurts
ranged 2.0–3.0 · 10 8 cfu/mL (Figs. 3 and 4). The viable cell
counts increased with refrigerated storage to similar values
for all plain-, A. sativum- and C. verum-cow-milk yogurts
and reached the highest counts 4.30 · 10 8 , 4.90 · 10 8 and
5.30 · 10 8 cfu/mL, respectively, by day 14 of storage; followed
by a small reduction to 3.7 · 10 8 , 4.50 · 10 8 and 4.70 · 10 8 cfu/
mL, respectively, by day 21 of storage. In comparison, the
viable cell counts in camel-milk yogurts increased almost
twofold higher by day 14 of storage (9.5 · 10 8 , 11.7 · 10 8
and 9.9 · 10 8 cfu/mL) for plain-, A. sativum- and C. verum-camel-milk
yogurts, respectively. Extension of storage to day 21
resulted in a decrease in viable S. thermophilus counts to
7.0 · 10 8 cfu/mL for both plain- and C. verum-camel-milk yogurts
but not for A. sativum camel-milk yogurt which was
2.7. Statistical analysis
The experiment was designed according to a 2 · 3 factorial design.
All experiments were performed in three batches (n = 3) and the
average was taken. Data were expressed as mean ± standard error
using one-way ANOVA by SPSSÒ version 17.0. Means were
compared using Duncan’s multiple range tests, and statistical significance
was standard by ANOVA at p < 0.05.
3. Results
3.1. Survival of lactic acid bacteria into plain and herbal yogurts
Figure 1 Changes in bacterial counts of Lactobacillus spp
(10 6 cfu/mL) during 21 day refrigerated storage (4 °C). C.
verum-cow-milk yogurt, A. sativum-cow-milk yogurt versus
control plain-cow-milk yogurt. Values are presented as
mean ± SEM (n = 3). For C. verum-cow-milk yogurt (0 day)
ANOVA showed a significant effect at 5% level.

Viability of lactic acid bacteria and sensory evaluation in Cinnamomum verum and Allium sativum 53
Figure 2 Changes in bacterial counts of Lactobacillus spp
(10 6 cfu/mL) during 21 day refrigerated storage (4 °C). C.
verum-camel-milk yogurt, A. sativum-camel-milk yogurt versus
control plain-camel-milk yogurt. Values are presented as
mean ± SEM (n = 3). For both cow- and camel-milk yogurts in
the presence of C. verum and A. sativum ANOVA showed a
significant effect at 5% level during all periods of storage.
12.5 · 10 8 cfu/mL. The addition of A. sativum- and C. verum in
cow-milk yogurts showed no significant effect on the survival
rate of S. thermophilus compared to their control (plain yogurt).
However, the addition of A. sativum in camel-milk yogurts
showed increased (p < 0.05) in S. thermophilus counts
on 7 and 21 days compared to its control while, there was no
effect on S. thermophilus counts in the presence of C. verum.
3.2. Organoleptic properties of stored yogurts
The sensory evaluations of cow- and camel-milk yogurts were
shown in Table 1. No differences were observed in sourness,
bitterness, and overall preference scores between the two
groups of yogurts, both in the absence and presence of A. sativum
or C. verum. The plain yogurt sweetness score was greater
for cow-milk yogurt than the camel-milk yogurt. However, the
presence of A. sativum and C. verum effects on sweetness was
reduced in cow-milk yogurt, but increased in camel-milk yogurt.
The aroma score was slightly greater in cow-milk yogurt
(6.1 ± 1.8) than in camel-milk yogurt (5.4 ± 1.4). The
presence of A. sativum reduced aroma score in cow-milk
Figure 3 Changes in bacteria counts of Streptococcus thermophilus
(10 8 cfu/mL) during 21 day refrigerated storage (4 °C). C.
verum-cow-milk yogurt, A. sativum-cow-milk yogurt versus
control plain-cow-milk yogurt. Values are presented as
mean ± SEM (n = 3). For all treated yogurt ANOVA showed
no significant effect at 5% level.
Figure 4 Changes in bacteria counts of Streptococcus thermophilus
(10 8 cfu/mL) during 21 day refrigerated storage (4 °C). C.
verum-camel milk yogurt A. sativum-camel-milk yogurt versus
control plain-camel-milk yogurt. Values are presented as
mean ± SEM (n = 3). For A. sativum-camel-milk yogurt at 7
and 21 days ANOVA showed a significant effect at 5% level.
yogurt (2.3 ± 0.7, p < 0.05) contrary to camel-milk yogurt
(5.5 ± 1.0).
4. Discussion
In this present study, the viable counts of Lactobacillus spp
for both types of yogurts confirmed to reduce during refrigerated
storage (by day 14 for cow-milk yogurts and day 7
for camel-milk yogurts). This result was in agreement with
previous study that found refrigerated storage decreased
the viable counts of Lactobacillus spp significantly by the
14th day of refrigerated storage (Shah and Ravula, 2001;
Haynes and Playne, 2002; Kailasapathy and Sultana, 2003;
Laniewska-Trokenheim et al., 2010). Additionally, the reduction
of Lactobacillus spp counts could be associated with the
post-acidification of yogurt which causes a further reduction
in pH values (Shah, 2000; Omer and Eltinay, 2009; Eissa
et al., 2010). However, in this present study, the pH of
cow-milk yogurts reduced at faster rates than camel-milk yogurts
during refrigerated storage (data not shown). Thus, the
more rapid reduction of Lactobacillus spp counts in all camel-milk
yogurts than cow-milk yogurts (Figs. 1 and 2)
could be attributed to the higher antibacterial properties of
camel milk than cow milk (El Agamy et al., 1992).
Conversely, the increase in the viability of S. thermophilus
in both cow-milk and camel-milk yogurts throughout the first
14 days of refrigerated storage was in agreement with other
previous studies (Birollo et al., 2000). To the best knowledge
of the researchers, this is the first simultaneous report on the
survival of both Lactobacillus spp and S. thermophilus during
refrigerated storage which showed higher survival percentage
of these bacteria in cow-milk than in camel-milk yogurts. Furthermore,
the significant drop in the viable cell counts of S.
thermophilus by day 21 of storage in both cow-milk and camel-milk
yogurts may be attributed to the accumulation of organic
acids (Østlie et al., 2003). However, the sustained
survival of S. thermophilus in A. sativum-camel-milk yogurt
indicated a positive effect of its addition into camel milk during
yogurt preparation. The reason is not clear. Thus, further
studies are required.
Viable LAB was higher in camel-milk than in cow-milk yogurts
and this may be partly explained by the higher free amino

54 A.B. Shori, A.S. Baba
Table 1
Mean taste panel scores for herbal yogurts versus control (plain yogurt) made from cow and camel milk.
P-cow-milk Y a,b,c AS-cow-milk Y a,b,c CV-cow-milk Y a,b,c P-camel-milk Y a,b,c AS-camel-milk Y a,b,c CV-camel-milk Y a,b,c
Sourness 5.83 ± 1.95 6.42 ± 1.73 5.67 ± 1.72 6.42 ± 1.93 5.92 ± 1.68 5.67 ± 1.15
Sweetness 4.83 ± 1.19 3.42 ± 1.16 3.58 ± 1.83 3.83 ± 1.75 4.92 ± 1.38 4.83 ± 1.27
Bitterness 2.92 ± 1.51 3.08 ± 1.88 2.42 ± 1.24 2.42 ± 1.31 2.17 ± 1.27 2.83 ± 1.64
Aroma 6.08 ± 1.83 2.33 ± 0.65 6.33 ± 1.50 5.42 ± 1.44 5.50 ± 1.00 5.75 ± 1.48
Overall preference 6.50 ± 1.45 5.08 ± 1.24 5.92 ± 1.56 6.17 ± 1.64 5.75 ± 1.71 6.00 ± 1.21
a P = plain, AS = A. sativum, CV=C. verum and Y = yogurt.
b First group (AS-cow-milk Y, CV-cow-milk Y versus P-cow-milk Y), second group (AS-camel-milk Y, CV-camel-milk Y versus P-camel-milk
Y).
c Values are presented as mean ± SEM, n = 12. Significant for aroma at AS-cow-milk Y.
acids in camel milk than in cow milk (Mehaia and Al-Kanhal,
1992), and higher milk protein proteolysis by L. delbrueckii spp
bulgaricus in camel milk than in cow milk (Abu-Tarboush,
1996). Both factors contribute to apparent higher digestibility
of camel milk than cow milk which readily supported growth
and metabolism of LAB during fermentation and refrigerated
storage. Therefore, the higher ‘mortality’ of Lactobacillus spp
in camel-milk yogurts during refrigerated storage may not
affect its functional values because the viable cell counts of
LAB on the 3rd week of storage in camel-milk yogurts were
still higher than those in the 2nd week of storage for cow-milk
yogurts.
Furthermore, in this present study, the decrease in the aroma
score for A. sativum-camel-milk yogurt could be explained
via study conducted by Hansanugrum and Barringer (2010)
which found that milk proved effective in the deodorization
of AMS (allyl methyl sulphide) latter identified as responsible
for the ‘garlic odour’ (Block, 2010). Moreover, the significant
higher aroma score for A. sativum-camel-milk yogurt than A.
sativm-cow-milk yogurt suggested that camel milk was more
effective in the deodorization of AMS than cow milk.
5. Conclusion
A. sativum and C. verum enhanced Lactobacillus spp counts
more in camel-milk yogurts than in cow-milk yogurts with respect
to growth during fermentation except they could not sustain
Lactobacillus spp survival in camel-milk yogurts during
refrigerated storage. However, these herbs did not affect S.
thermophilus counts in camel- and cow-milk yogurts both during
fermentation and refrigerated storage. The addition of A.
sativum and C. verum did not affect the organoleptic properties
of cow- and camel-milk yogurts although A. sativum may reduce
the aroma score in the former but not in the latter.
Acknowledgement
We acknowledge the financial support of University of Malaya
Research Grant (RG023-090BIO).
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