getview_vol2_no.3_march_2012

Committee of the Global Engineers & Technologists Review Chief Editor

Ahmad Mujahid Ahmad Zaidi, MALAYSIA Managing Editor Mohd Zulkifli Ibrahim, MALAYSIA

Editorial Board

Dr. Arsen Adamyan Yerevan State University ARMENIA

Assoc. Prof. Dr. Gasham Zeynalov Khazar University AZERBAIJAN

Assistant Prof. Dr. Tatjana Konjić University of Tuzla Bosnia and Herzegovina BOSNIA and HERZEGOVINA

Assistant Prof. Dr. Muriel de Oliveira Gavira State University of Campinas (UNICAMP) BRAZIL

Assoc. Prof. Dr. Plamen Mateev Sofia University of St. Kliment Ohridsky BULGARIA

Dr. Zainab Fatimah Syed The University of Calgary CANADA

Assistant Prof. Dr. Jennifer Percival University of Ontario Institute of Technology CANADA

Prof. Dr. Sc. Igor Kuzle University of Zagreb CROATIA

Assoc. Prof. Dr. Milan Hutyra VŠB - Technical University of Ostrava CZECH

Prof. Dr. Mohamed Abas Kotb Arab Academy for Science, Technology and Maritime Transport EGYPT

Prof. Dr. Laurent Vercouter INSA de Rouen FRANCE

Prof. Dr. Ravindra S. Goonetilleke The Hong Kong University of Science and Technology HONG KONG

Prof. Dr. Qeethara Kadhim Abdulrahman Al-Shayea Al-Zaytoonah University of Jordan JORDAN

Prof. Yousef S.H. Najjar Jordan University of Science and Technology JORDAN

Assoc. Prof. Dr. Al-Tahat D. Mohammad University of Jordan JORDAN

Assoc. Prof. Dr. John Ndichu Nder Jomo Kenyatta University of Agriculture and Technology- (JKUAT) KENYA

Prof. Dr. Megat Mohamad Hamdan Megat Ahmad The National Defence University of Malaysia MALAYSIA

Prof. Dr. Rachid Touzani Université Mohammed 1er MOROCCO

Prof. Dr. José Luis López-Bonilla Instituto Politécnico Nacional MEXICO

Assoc. Prof. Dr. Ramsés Rodríguez-Rocha IPN Avenida Juan de Dios Batiz MEXICO

Dr. Bharat Raj Pahari Tribhuvan University

NEPAL Prof. Dr. Abdullah Saand Quaid-e-Awam University College of Eng. Sc. & Tech.

PAKISTAN

Prof. Dr. Naji Qatanani An-Najah National University

PALESTINE

Prof. Dr. Anita Grozdanov University Ss Cyril and Methodius REPUBLIC OF MACEDONIA

Prof. Dr. Vladimir A. Katić University of Novi Sad SERBIA

Prof. Dr. Aleksandar M. Jovović Belgrade University SERBIA

Prof. Dr. A.K.W. Jayawardane University of Moratuwa SRI LANKA

Prof. Dr. Gunnar Bolmsjö University West SWEDEN

Prof. Dr. Peng S. Wei National Sun Yat-sen University at Kaohsiung. TAIWAN

Prof. Dr. Ing. Alfonse M. Dubi University of Dar es Salaam TANZANIA

Assoc. Prof. Chotchai Charoenngam Asian Institut of Tecnology THAILAND

Prof. Dr. Hüseyin Çimenoğlu Instanbul Technical University (İTÜ) TURKEY

Assistant Prof. Dr. Zeynep Eren Ataturk University TURKEY

Dr. Mahmoud Chizari The University of Manchester UNITED KINGDOM Prof. Dr. David Hui University of New Orleans

USA

Prof. Dr. Pham Hung Viet Hanoi University of Science VIETNAM

Prof. Dr. Raphael Muzondiwa Jingura Chinhoyi University of Technology ZIMBABWE

Dear the Seeker of Truth and Knowledge, As we entered 2012, we’re surely hopes with a few wishes for a significant improvement as where a few signs for 2012 will be better. Although a new year is filled and always brings new challenges, and we know that will be the case in 2012, but a new year is coloured also with opportunities. We hopes that whatever challenges face us as individuals, a state or a nation, we will greet them with grace and determination to move forward and make things better. A bright and shiny new year always brings the promise that this time we can succeed on a higher level of our optimism and enthusiasm for life. As also the Global Engineers and Technologist Review; a forum for the publication and dissemination of original work which contributes to the understanding of multi-disciplinary underpinning in the fields of engineering, technology, chemistry, environmental sciences, management and economics, physics, mathematics and statistics, computer and information sciences, geology and biology, by now has been in 2nd year. Although the GETview is still young and always keeping her path and existence as a peer-reviewed journal - open access journal, close partnerships with others in the academic community, including libraries, universities, scholarly societies, faculty, and students through collaborative efforts for high-quality research platforms, however, will play an important role of this community combination to improve and sustain high-quality journal publication in where the GETview take to stand for it. Therefore, the GETview always look forward to receive the scholarly and original contributions giving insight into case study, practices and fundamental in multi-disciplinary form the core of the journal contents. The GETview will always striving for to play a key role in the broad dissemination of high-quality journals Happy New Year! Assoc. Prof. Ahmad Mujahid Ahmad Zaidi, PhD Chief Editor The Global Engineers and Technologists Review

©PUBLISHED 2012 Global Engineers and Technologists Review GETview ISSN: 2231-9700 (ONLINE) Volume 2 Number 3 March 2012 All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, electronic, mechanical photocopying, recording or otherwise, without the prior permission of the Publisher. Printed and Published in Malaysia

Vol.2, No.3, 2012 1. WATER QUALITY INDEX OF WATER BODIES ALONG FARIDPUR-BARISAL

ROAD IN BANGLADESH RUMMAN MOWLA CHOWDHURY, SARDAR YAFEE MUNTASIR and M. MONOWAR HOSSAIN 9. SYNTESIS AND FABRICATION OF AN EFFECTUAL DYE SENSITIZED SOLAR CELL MATHISUTAN MURUGIAH, JAMIL HASHIM, UMAR NIRMAL and YUHAZRI, M.Y. 16. A SIMULATED ANNEALING ALGORITHM AND BRANCH-AND-BOUND FOR

DETERMINING FOR MAXIMAL PLANAR OF GRAPH NIK FARJAM, B. and YUNUSI, M. 20. INFLUENCE OF TREATED METAL OXIDE FOR SUSTAINABLE ENERGY

CONVERSION ANIKA ZAFIAH, M.R., NUR MUNIRAH, A. and ABDULLAH, M.F.L. 26. SOLID FUEL FROM EMPTY FRUIT BUNCH FIBER AND WASTE PAPERS PART 3: ASH CONTENT FROM COMBUSTION TEST YUHAZRI, M.Y., HAERYIP SIHOMBING, YAHAYA, S.H., SAID, M.R., UMAR NIRMAL, SAIJOD LAU and PHONGSAKORN PRAK TOM © 2012 GETview Limited. All right reserved

CONTENTS

ISSN 2231-9700 (online)

GLOBAL ENGINEERS & TECHNOLOGISTS REVIEW www.getview.org

G.L.O.B.A.L E.N.G.I.N.E.E.R.S. .& .-.T.E.C.H.N.O.L.O.G.I.S.T.S R.E.V.I.E.W 1

RUMMAN MOWLA CHOWDHURY1, SARDAR YAFEE MUNTASIR2 and M. MONOWAR HOSSAIN3

1, 3 Institute of Water Modelling Dhaka, BANGLADESH

[email protected]

2 Department of Civil Engineering Stamford University Bangladesh

51, Siddeswari Road, Dhaka – 1217, BANGLADESH 2 [email protected]

3 Department of Water Resources Engineering

Bangladesh University of Engineering and Technology Dhaka-1000, BANGLADESH

[email protected]

1.0 INTRODUCTION Water is a unique resource because it is essential for all life and it constantly cycles between the land and the atmosphere. The same water that is used for crop and animal production can also be shared with the public and the aquatic and terrestrial ecosystems (Cooper et al., 1998). Water resources are of great environmental issues and studied by a wide range of specialists including hydrologists, engineers, ecologists, geologists and geo morphologists (Kumar and Dua, 2009). It has become an important issue for them as it affects not only human uses but also plant and animal life. For healthy living, potable safe water is absolutely essential. It is a basic need of all human being to get the adequate supply of safe and fresh drinking water. One of the most effective ways to communicate water quality is Water Quality Index (WQI), where the water quality is assessed on the basis of calculated water quality indices. Quality of water is defined in terms of its physical, chemical, and biological parameters. However, the quality is difficult to evaluate from a large number of samples, each containing concentrations for many parameters (Almeida, 2007). Horton (1965) proposed the first WQI, a great deal of consideration has been given to the development of index methods. A water quality index provides a single number that expresses overall water quality at a certain location on several water quality parameters and turns complex water quality data into information that is understandable and useable by the general people. WQI is a mathematical instrument used to transform large quantities of water quality data into a single number which represents the water quality level while eliminating the subjective assessments of water quality and biases of individual water quality experts. Basically a WQI attempts to provide a mechanism for presenting a cumulatively derived, numerical expression defining a certain level of water quality (Miller et al., 1986). Comparison can be made through the

ABSTRACT

Water quality parameters of 34 different water stations along the Faridpur-Barishal road in Bangladesh were collected to determine water quality index (WQI). Six most important parameters - pH, total dissolved solids, dissolves oxygen, biochemical oxygen demand, electrical conductivity and temperature difference were considered for WQI. The WQI was assessed using a weighted arithmetic index method and National Sanitation Foundation method. According to the arithmetic mean method WQI values vary between 19 and 96, wherein NSF Method WQI values vary between 55 and 91. In weighted arithmetic index method highest favourable value gives a low statistical value to the index whereas lowest favourable value gives a low statistical value to the index in NSF method. The values of the WQI showed that the water of the maximum stations are poor and very poor in condition, few of them can be referred to as good, and among all water stations only one of the stations Id(p-7) contains excellent water quality parameter for human consumption and other uses. The results revealed that although WQI of most of the water bodies are beyond acceptable limit but could be used for domestic and household purpose after purification. Keywords: Water Quality Index, Pre-Monsoon, Dissolved Oxygen, Biochemical Oxygen Demand, Total Dissolved Solids.

WATER QUALITY INDEX OF WATER BODIES ALONG FARIDPUR-BARISAL ROAD IN BANGLADESH

Global Engineers & Technologists Review, Vol.2 No.3 (2012)

© 2012 GETview Limited. All rights reserved 2

WQI among the water bodies and a general analysis of water quality on different levels can be made. A water quality index is a means to summarize large amounts of water quality data into simple terms (e.g., poor, good etc.) for reporting to management and the public in a consistent manner. Importance of water bodies along the roadside is evident in terms of water quality, biodiversity conservation and use for aquaculture, as maximum of the water bodies of Bangladesh are expected to be productive. So utilization of the existing resources is very much vital. In the way to improving the condition of these water resources, its proper management is very much necessary and for doing this all information on the resources namely physico-graphic, chemical and biological characteristic of these water resources must be collected. The objective of this paper is to determine the WQI of 34 water bodies along Faridpur-Barishal road. Drinking water contamination and variation of drinking water quality in pre-monsoon is the basis of calculated values of WQI as concentrations of different water quality parameters tend to be at its worse condition during pre-monsoon season. Based on the WQI an assessment was made whether these water bodies are acceptable for domestic use and even for drinking purpose. Local people living along this road are completely dependent on these water bodies as there is no proper water supply made to meet their needs. For this reason, this analysis is extremely necessary so that people living in these areas can mark out the best water source available. Also if they need more water badly they can also determine which water bodies can used after proper treatment is done. Similar type of studies have been done in India by Chauhan and Singh, (2010), where WQI values were determined in several stations along Ganges River so that quality of water can be seen along the river. Also several studies have been performed to determine water qualities along streams (Abrahão et al., 2010) where effluents come from industries. But this study has its individual significance as WQI values of 34 stations were taken along a road’s length of a specific region in Bangladesh. Although in some places a confined research may be done like determining WQI of local ponds, but along roadside water bodies this type of study is not available. 2.0 STUDY AREA AND METHODOLOGY The present study was conducted along the priority road which is of 128 km in length, touching 4 districts namely - Barishal, Madaripur, Gopalngonj and Faridpur. The parameters - water temperature, pH, dissolved oxygen, total dissolved solids (TDS) and electrical conductivity (EC) of 34 different locations along Faridpur-Barishal road during pre monsoon (March until April in 2011) was collected and analyzed immediately at the sampling site using standard equipment. The study area is shown on a satellite image with 34 sampling stations in Figure 1. Sampling stations were numbered arbitrarily for convenience of records. Sampling date, place and time were recorded on the sampling bottles. For BOD measurement, a 500ml bottle was used for collection of water samples and the oxygen was fixed at the sampling site before being carried to the laboratory for further analysis.

Figure 1: Index map of study area The examination and analysis of the water bodies including laboratory analysis was done as per the standard methods of USEPA, (2004) and (Trivedi and Goel, 1986). The calculation of WQI was made using weighted arithmetic index method (Brown et al., 1972) and National Sanitation Foundation method. Finally assessment of surface water quality based on water quality index was done. Table 1 shows the details of analysis methods and necessary equipments used in the study.



Table 1: Details of physic-chemical parameters, analysis methods and the equipments 3.0 WQI COMPUTATION EQUATIONS The calculation of WQI, selection of parameters has great value. The water quality index will widen if too many parameters are used. Importance of various parameters depends on the intended use of water. Four parameters which is pH, TDS, δT, DO were used to calculate WQI by national sanitation foundation method. Five physico-chemical parameters namely pH, TDS, EC, DO, BOD were used to calculate wqi by the weighted arithmetic index method. Several steps of weighted arithmetic index method are given (brown et al., 1972) in the following steps:

3.1 Calculation of Sub Index of Quality Rating (qn) Let there be n water quality parameters where the quality rating or sub index (qn) corresponding to the nth parameter is a number reflecting the relative value of this parameter in the polluted water with respect to its standard permissible value. The value of qn is calculated using the following expression. qn = 100[(Vn - Vio) / (Sn - Vio)] (1) Where,

qn = quality rating for the nth water quality parameter. Vn = estimated value of the nth parameter at a given sampling station. Sn = standard permissible value of nth parameter Vio = ideal value of nth parameter in pure water. All the ideal values (Vio) are taken as zero for drinking water except for pH = 7.0 and dissolved oxygen=14.6mg/L. (Tripaty and Sahu, 2005).

3.2 Calculation of Quality Rating for pH For pH the ideal value is 7.0 (for natural water) and a permissible value is 8.5 (for polluted water). Therefore, the quality rating for pH is calculated from the following relation: qpH = 100 [(VpH -7.0)/(8.5 -7.0)] (2) Where,

VpH = observed value of pH during the study period. 3.3 Calculation of Quality Rating for Dissolved Oxygen The ideal value (VDO) for dissolved oxygen is 14.6 mg/L and standard permitted value for drinking water is 5 mg/L. Therefore, quality rating is calculated from following relation: qDO = 100 [(VDO - 14.6)/(5 – 14.6)] (3) Where,

VDO = measured value of dissolved oxygen 3.4 Calculation of Unit Weight (Wn) Calculation of unit weight (Wn) for various water quality parameters are inversely proportional to the recommended standards for the corresponding parameters. Wn = K/Sn (4) Where,

Wn = unit weight for nth parameters

Serial Number Temperature Methodology Equipments 1 Temperature Visible Centigrade Thermometer 2 Salinity Visible Sensaso-CL 410,HACH,USA 3 pH Visible Sensaso-CL 410,HACH,USA 4 Transparency Visible Secchi Disk 5 Dissolved Oxygen Visible Dissolved Oxygen Meter, (Model-YK22 DO),USA6 BOD Laboratory Dissolved Oxygen Meter, (Model-YK22 DO),USA7 Conductivity Visible Conductivity Meter, (Model-CD4302,USA) 8 TDS Visible Sensaso-CL 410,HACH,USA



Sn = standard value for nth parameters K = constant for proportionality

3.5 Calculation of WQI WQI is calculated from the following equation: n n WQI =∑ qn Wn / ∑ Wn (5) n=1 n-1 3.6 Calculation of WQI by NSF method The NSF water quality index was developed by the National Sanitation Foundation (NSF) in 1970. An equation of NSF water quality index was found by using weighted factor of individual parameter and sub-index of each water quality parameter based on their respective testing values which can be found by water quality index calculator or water quality index curve of respective parameters. The water quality index of individual parameter was calculated from water quality index calculator used by Environmental Engineering and Earth Sciences, Center of Environmental Quality, Wilkes University (Islam et al., 2011). WQI = 0.17IDO + 0.11IpH + 0.10I ΔT + 0.07ITDS (6)

4.0 RESULTS OF SUB-WATER QUALITY INDEX Sub water quality index of five parameters for the former method (Brown arithmetic mean method) are given in Table 2 and Sub water quality index of four parameters by the NSF method are given in Table 3. Table 2: Sub water quality Index of the physico-chemical parameters according to Brown Method.

Station Sub water quality

Index (PH)

Sub water quality Index (TDS)

Sub water quality Index (EC)

Sub water quality Index (BOD)

Sub water quality Index (DO) P-1 5.125 0.334 0.087 7.687 36.433P-2 4.371 0.264 0.070 9.224 38.035P-3 4.974 0.278 0.073 4.612 26.824P-4 -25.925 0.122 0.032 18.449 26.024P-5 16.429 0.116 0.031 3.843 28.025P-6 10.701 0.073 0.020 4.612 46.843P-7 21.252 0.056 0.015 9.993 29.627P-8 20.800 0.104 0.028 16.911 27.625P-9 15.073 0.117 0.031 15.374 40.437K-1 3.768 0.142 0.038 15.374 45.241R-1 11.757 0.079 0.020 21.524 32.830R-2 15.073 0.078 0.021 26.904 30.428P-10 17.936 0.116 0.031 3.843 41.237BP-1 8.441 0.118 0.031 3.843 44.440P-11 22.458 0.098 0.026 18.449 41.638P-12 33.612 0.124 0.033 23.830 38.035K-2 20.197 0.132 0.035 4.612 26.024P-13 4.522 0.171 0.045 3.843 32.429K-3 0.301 0.148 0.039 29.979 45.641K-4 5.426 0.137 0.036 20.755 36.433K-5 9.044 0.165 0.044 26.136 42.038R-3 12.209 0.123 0.031 16.143 34.431K-6 7.536 0.159 0.042 26.136 50.446K-7 8.139 0.151 0.040 12.299 46.042R-4 7.536 0.083 0.022 23.830 41.638R-5 9.044 0.126 0.033 5.381 52.047P-14 26.678 0.113 0.030 7.687 34.431R-6 6.029 0.086 0.022 12.299 45.641B-1 -3.165 0.589 0.151 5.381 52.047B-2 1.507 0.410 0.107 6.150 48.444P-15 4.522 0.115 0.040 9.224 46.042R-7 20.046 0.229 0.060 17.680 35.232P-16 0.000 0.361 0.094 9.224 45.641P-17 18.087 0.119 0.034 9.993 32.830



4.1 pH pH is one of the most important factors that serves as an index for the pollution. The experimental water bodies were found to be approximately neutral or slightly alkaline. The highest value of pH was 9.23 at P-12 and lowest was 5.28 at P-4. The lowest mean value of pH was 7.67 ± 0.05. A pH between 6.7 and 8.4 is suitable, while pH below 5.0 and above 8.3 is detrimental. In the present investigation pH values were within the ICMR standards (7.0 - 8.5) (Tripaty and Sahu, 2005). Maximum Sub water quality index for pH was found 36 at P-12 station and Minimum was found as -36 at station P-4 according to Brown’s method. The maximum and minimum values are 35 (P-4) and 95 (P-1) respectively. Table 3: Sub water quality Index of the physico-chemical parameters according to NSF Method.

4.2 Total Dissolved Solids The TDS level found to fluctuate from 73.1 mg/l to 766 mg/l within the water bodies. The TDS content was maximum in B-1 and minimum in P-7 with average of 219.61 ± 1.79 mg/l. The amounts of total solids are influenced by the activity of the plankton and organic materials. Slightly high value of TDS were recorded at only one sampling stations and other values were less than the WHO limit. Water containing more than 500 mg/L of TDS is not considered desirable for drinking water supply. Maximum Sub water quality index for TDS is found close to 1 (Brown Method) at B-1 station. Minimum Sub water quality index for TDS was found almost 0 at rest of the 33 stations (Brown Method). Maximum Sub water quality index for TDS is found 86 (Station P-7) and minimum Sub water quality index for TDS was found as 20(Station B-1, 2). (NSF method) 4.3 Dissolved Oxygen The value of DO varied from 1.6 mg/l to 8.1mg/l. The maximum DO value (8.1mg/l) was recorded in K-2 and minimum value (1.6mg/l) was recorded in B-1. The mean value of DO was 4.90 ± 0.16mg/l. Concentrations below 5 mg/L may adversely affect the performance and survival of biological communities and below 2 mg/L may lead to fish mortality. Water without adequate DO may be considered wastewater. Maximum Sub water quality index for DO was found 52 at B-1 and minimum sub water quality index for DO was found 26 at P-4 (Brown Method). Maximum Sub water quality index for

Station Sub water quality Index (PH)

Sub water quality Index(TDS)

Sub water quality Index (ΔT)

Sub water quality Index(DO) P-1 93 42 84 78 P-2 92 54 84 66 P-3 93 52 89 99 P-4 35 78 91 99 P-5 81 79 87 99 P-6 91 84 88 25 P-7 69 86 77 98 P-8 70 80 70 99 P-9 84 79 85 53 K-1 92 75 85 33 R-1 90 83 81 84 R-2 84 83 89 93 P-10 77 79 74 53 BP-1 92 79 82 33 P-11 67 81 79 53 P-12 41 77 73 68 K-2 72 76 84 99 P-13 93 70 82 88 K-3 88 74 87 30 K-4 93 75 89 75 K-5 92 71 83 46 R-3 90 78 89 87 K-6 93 72 85 15 K-7 92 73 81 27 R-4 93 83 84 45 R-5 92 77 85 11 P-14 57 79 73 87 R-6 93 82 86 30 B-1 83 20 77 11 B-2 90 20 84 20 P-15 93 79 87 30 R-7 72 60 74 87 P-16 88 36 68 30 P-17 77 78 83 88



DO was found 99 at (P-3, 4, 5 and K-2) and minimum sub water quality index for DO was found 11 at B-1, R-5. 4.4 Biochemical Oxygen Demand BOD varied between 0.5 mg/l to 3.9 mg/l among the different sampling stations. The minimum values were found in P-5, P-10, BP-1 and P-13. The Maximum value was recorded in K-3. The mean value of BOD was 1.76±0.14 mg/l. Maximum Sub water quality index for BOD was found 30 at K-3. Minimum Sub water quality index for DO was found 4 at P-5 (Brown Method). 4.5 Electrical Conductivity Conductivity is measured in terms of conductivity per unit length, and meters typically use the unit micro Siemens /cm. The values of water conductivity (2ms) varied from 154 μs /cm to 1544 μs/cm among the water bodies. The value of conductivity was recorded lowest in R-1 and maximum in B-1. The mean value was 452.67±2.51μs/cm. The mean value was 365.17μs/cm. Sub water quality index for Electrical Conductivity is almost 0 at all stations (Brown Method). 4.6 Temperature Difference Surface water temperature varied between 26.3˚C and 33.3˚C and water temperature varied between 23.8˚C and 34.2˚C.Maximum difference in temperature was 5.6˚C and minimum was 0.5˚C, 2.43˚C was the average difference. Maximum Sub water quality index of temperature difference is 91 at station number P-5, and the minimum was at P-17 and the value was 68.

5.0 ASSESSMENT OF WATER QUALITY WQI has been classified into 5 classes. Table 4 and Table 5 represent the 5 classes of water quality based on WQI of two methods respectively. Table 4: Status of water quality based on Arithmetic WQI method (Brown et al., 1972)

Water quality index Status 0-25 Excellent26-50 Good51-75 Poor 76-100 Very poorAbove 100 Unsuitable for drinking and propagation of fish culture Table 5: Status of water quality based on National Sanitation Foundation WQI

Water quality index Status0-25 Very Bad26-50 Bad51-75 Medium76-100 GoodAbove 100 Excellent The observed range of water quality index along the road in pre monsoon is 19 to 96 by the arithmetic mean method. Maximum WQI was 96 at station P-12 and minimum is 19 at station P-4. Only one single station’s water quality can be expressed as excellent (P-4). Water quality of station P-1, P-3, P-5 and P-13 can be called as good water. P-2, P-6, P-7, P-8, P-9, P-10, P-14, P-16, P-17, K-1, K-2, K-7, R-1, R-2, R-3, R-4, R-5, R-6, R-7, B-1, B-2, BP-1 have been classified as poor water. Rest of the stations P-11, P-12, K-3, K-5, K-6 have been classified as containing very poor water, but all of them can be used for domestic purpose by taking proper disinfection procedure. Stations with WQI values more than 90 can be classified as unsuitable for both domestic and aquaculture purposes. 1 of the stations turned out to be unsuitable as WQI value is more than 90. According to the NSF, WQI varied between 55 and 91. As the lowest value indicates the best value most of the water stations fall within medium to good water quality range. Among the stations P-5, 9, 10, 11, 12, 15, 16, R-4, 5, 6 BP-1, K-3, 5, 6, 7 have been classified as medium water. And rest of the stations water has been classified as good water. There is a little difference in categorization of the stations according to the two methods as the parameters selected for the methods are different and this is because of the unavailability of the parameters. One point is noticeable that according to the arithmetic mean method by brown WQI ranges from 51-75 has been classified as poor where according to NSF WQI this range has been classified as medium. So it will be better to count acceptable range between 0-50 for Browns method and 75- to more than 100 for the NSF method. Table.3 shows the WQI values of the 34 stations measured in pre monsoon period. Station P-1, 3, 4, 5,



13 can be classified as the best stations among all. Table 6 represents WQI value of the 34 stations by two methods. Table 7 represents the maximum, minimum and average value of different parameters. Standard and ideal values of different water quality parameters have been shown in Table 8. Guidelines are recommended by World Health Organization (WHO) and Indian Council of Medical Research (ICMR). Table 6: Location wise calculated values of Water Quality Index for pre monsoon period

Table 7: Maximum, minimum and average values of diffrent water quality parameters

Table 8: Drinking water standards and unit weight

Station* Station name

Water quality index

(weighted arithmetic

index)

Water quality index

(National Sanitation

Foundation WQI) P-1 Right(Education Board pond1, Barisal) 50 81P-2 Right(Education Board pond2, Barisal) 52 78P-3 Left(Roads and Highways pond, Barishal) 37 90P-4 Right(Forest Office pond) 19 77P-5 Right(Opposite of Ansar VDP pond) 48 91P-6 Left(opposite of Madrasha) 62 71P-7 Right(Tri-road More) 61 87P-8 Right(pond) 65 84P-9 Right(Andipur pond, Purbopansha, Babuganj, Barisal 71 73K-1 Rajguber khal, babuganj, Barisal 65 68R-1 Duarika (Sugandha) River, Mohiuddin Jahangir bridge, Babuganj, Barisal 66 81R-2 Shikerpur river, Babuganj, Barisal(M.A. Jalil bridge) 73 84P-10 Left(Kaler dighi, Dakhin Shikerpur, Ujirpur, Barishal) 63 74BP-1 Left(Batazor khal), Gournodi, Barisal 57 72P-11 Right(Shamsul Howlader pond), Batazor, Giurnodi Barishal 83 68 P-12 Left(Mahilara A.N. High School pond), Gournodi, Barishal 96 64K-2 Ashukathi khal, Gournodi, Barishal 51 88P-13 Right(Gournodi Busstand pond), Gournodi, Barisal 41 88K-3 Southern Khal, Koltokshal, Gournodi, Barishal 76 63K-4 Bhurghata Khal, Kalkini, Maderpur 63 80K-5 Kornapara khal, Kalkini, Maderipur 77 68R-3 Mostofapur River, Maderipur 63 85K-6 Srinerdi khal, Maderipur 84 60K-7 Kamerer khal, Rajore, Faridpur 67 67R-4 Kumer nodi(river), Moksudpur, Tekerhat, Gopalgonj 73 70R-5 Kumer nodi, Dignagar, Moksudpur, Gopalgonj 67 65P-14 Sagor Mollah pond, Dignagar, Moksudpur, Gopalgonj 69 79R-6 Kumer nodi, Bhanga bazar, Bhanga, Faridpur 64 70B-1 Bhanga beel, Bhanga,Faridpur 55 77B-2 Nurpur Beel, opposite to bhanga beel, Bhanga, Faridpur 57 55P-15 Sagordi river, Bhanga, Faridpur 60 71R-7 Hasan shaheb pond, Shontoshi, Nagorkanda, Faridpur 73 76P-16 Kumer nodi, Bakunda, Faridpur 55 61P-17 Polishfari pond, Goalchamot, Faridpur 61 84Groups Maximum Minimum Average pH 9.23 5.28 7.67 DO(mg/l) 8.1 1.6 4.89 BOD(mg/l) 3.9 .5 1.73 Conductivity(2ms) 1544 154 448.22 TDS 766 73.1 215.635 Air Temperature 33.3 26.8 29.5 Water Temperature 34.2 23.8 27.43

Parameter Recommending Agency Standard value (S) Ideal value 1/S Assigned weightage factor pH ICMR 8.5 7 0.117647 0.226087822TDS WHO 500 0 0.002 0.003843493EC WHO 1400 0 0.000714 0.001372676DO WHO 5 14.6 0.2 0.384349297BOD ICMR 5 0 0.2 0.384349297K 0.52036 1



4.0 CONCLUSION WQI have some margins as it may not carry enough information about the actual situation of the water bodies. Also many other uses of water quality data cannot be met with an index. Despite of having such problem WQI are more recompense than its drawback. WQI of the stations along the Faridpur –Barishal road for the pre monsoon season was found fairly high according to the Brown method, as concentration of water quality parameters are maximum during pre monsoon and due to the same reason according to NSF method the values were low. In accordance with Brown method it is found from the calculation that parameter which shows the highest favorable value gives a low statistical value to the index and compliant with NSF method the favorable value has descending order. BOD, DO was found to be the most important parameter as it contributes the most for the WQI calculation among the five parameters for the former method. Out of the 34 stations almost 5 stations were found suitable for domestic and aquaculture purpose. So if proper treatment is done then all the 34 water bodies could become useful and could help people in rural areas during time of crisis. The study result is expected to provide valuable information in connection with the use of water bodies by the local people of the study region. REFERENCES [1] Abrahão, R., Carvalho, M., Da Silva Jr., W., Machado, T., Gadelha, C. and Hernandez. M. (2010): Use of Index Analysis to Evaluate the Water Quality of a Stream Receiving Industrial Effluents. WaterSA, Vol.33, No.4, pp.459-466. [2] Almeida, C.A. (2007): Influence of Urbanization and Tourist Activities on the Water Quality of the Potrero De Los Funes River (San Luis – Argentina). Environmental Monitoring and Assessment, Vol.133, No.1-3, pp.459-465. [3] Brown, R.M., McCleiland, N.J., Deininger, R.A. and O’Connor, M.F. (1972): A Water Quality Index - Crossing the Psychological Barrier (Jenkis, S.H., ed.) Proc. Int. Conf. on Water Poll. Res., Jerusalem, Vol.6, pp.787-797. [4] Chauhan, A. and Singh, S. (2010): Evaluation of Ganga Water for Drinking Purpose by Water Quality Index at Rishikesh, Uttarakhand, India. Report and Opinion, Vol.2, No.9, pp.53-61. [5] Cooper, J., Rediske, R., Northup, M., Thogerson, M. and Van Denend, J. (1998): Agricultural Water Quality Index. Scientific Technical Reports. paper 11. [6] Horton, R.K. (1965): An Index Number for Rating Water Quality. Journal of Water Pollution Control

Federation, Vol.37, No.3, pp.300-306. [7] Islam, S., Rasul, M.T., Alam, M.J.B. and Haque, M.A. (2011): Evaluation of Water Quality of the Titas River Using NSF Water Quality Index. Journal of Scientific Research, Vol.3, No.1, pp.151-159. [8] Kumar, A. and Dua, A. (2009): Water Quality Index for Assessment of Water Quality of River Ravi at Madhopur, India. Global Journal of Environmental Sciences, Vol.8, No.1, pp.49-57. [9] Miller, W.W, Young, H.M., Mahannah, C.N. and Garret, J.R. (1986): Identification of Water Quality Differences in Nevada through Index Application. Journal of Environmental Quality, Vol.15, pp.265-272. [10] Tripaty, J.K. and Sahu, K.C. (2005): Seasonal Hydrochemistry of Groundwater in the Barrier Spit System of the Chilika Lagoon, India. Journal of Environmental Hydrology, Vol.13, pp.1-9. [11] Trivedi, R.K. and Goel, P.K. (1986): Chemical and biological method for water pollution studies. Environmental Publications, Karad (Maharashtra), India. p.248. [12] USEPA. (2004): National Wadeable Stream Assessment: Water Chemistry Laboratory Manual. EPA841-B-04-008. U.S. Environmental Protection Agency, Office of Water and Office of Research and Development, Washington, DC.



MATHISUTAN MURUGIAH1, JAMIL HASHIM2, UMAR NIRMAL3 and YUHAZRI4, M.Y.

1, 2, 3 Faculty of Engineering and Technology Multimedia University

Jalan Ayer Keroh Lama, 75450, Melaka, MALAYSIA [email protected]

[email protected] [email protected]

4 Faculty of Manufacturing Engineering Universiti Teknikal Malaysia Melaka

Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, MALAYSIA [email protected]

1.0 INTRODUCTION The development of finding clean alternatives to power generation is crucial due to the raising global demand for green energy sources as an alternative to depleted fossil fuels (El-Badri, 2010). Photovoltaic or solar energy is an emerging alternative that has a potential of clean solution to this issue. Moving toward the latest technology, earlier studies were deployed in developing solar cell technology using crystalline. Crystalline materials were thought to have a prospect as an alternative source of energy but it was costly. The idea of thin film materials was later discovered and soon it has captured the attention of many solar cell developers (Olivia, 1998). Dye sensitized solar cell (DSSC) was such an attempt of using thin film materials in solar cell. It was first developed by O’Regan and Gratzel (Lanlan et al., 2010) and later it has attracted more interests due to its low cost and simple fabrication process. This was followed by rigorous studies to improve the cost of solar cell development. Further progress was made with the invention of DSSC using titanium dioxide (TiO2) thin film, thus, generating a new technology for converting light energy into electrical energy (Lanlan et al., 2010). It has been recorded that DSSC using TiO2 as a thin film substance showed up to 7.1 % in efficiency (i.e. solar cell output efficiency) under solar illumination with dye photo physics and electrolyte redox chemistry (Yeji et al., 2010). Currently, TiO2 material is widely adopted as the best alternative material in producing electrode for the DSSC. DSSC device comprises a large band gap semiconductor nanocrystalline electrode. The band gaps of the bulk TiO2 are 3.0eV for rutile phase and 3.2eV for anatase phase. The porous TiO2 film has achieved energy conversion efficiency of about 11.1% (Yeji et al., 2010) and (Tsokos, 2008). In regard to this and due to its high refractive index, TiO2 have been widely used in painting, coatings, plastics and optical industries (Stucky and Bartl, 2010) and (Reijnders, 2009). Beside TiO2, investigations on amorphous silica (SiO2) nanoparticles (particles< 100 nm) have been carried out in determining its performance and level of energy efficiency. However, in considering its environmental effects, research on this material has been aborted as the material is hazardous to mankind (Reijnders, 2009). Further research was conducted to develop another alternative

ABSTRACT

This paper is the result of an experimental study on using zinc oxide (ZnO) as an alternative material to titanium oxide (TiO2) in the fabrication of dye sensitized solar cell (DSSC). The zinc oxide thin film was prepared using sol-gel route technique. ZnO powder was annealed separately at 250ºC and 500ºC. ZnO powder annealed at 500 ºC was found to be more effective compared to the one annealed at 250ºC. Higher temperature annealing condition has given significant result in producing higher grade ZnO with reduced impurity and increased absorption intensity. Scanning Electron Microscope (SEM), X-ray Diffraction (XRD), Particle Size Analyzer and Energy Dispersive X-ray Spectrometry (EDS) were used to study the microstructure of the material. Fabrication of DSSC was carried out using ZnO porous, natural dye, graphite, sulphuric acid and ITO glasses. Tests were conducted using natural sunlight and the results revealed that the DSSC produced has an efficiency of 25.0%., very comparable with results from other studies. Thus, an effectual DSSC has been achieved. Keywords: Indium Tin Oxide, ITO glass, Zinc Oxide, Dye-Sensitized Solar Cell, DSSC.

SYNTHESIS AND FABRICATION OF AN EFFECTUAL DYE SENSITIZED SOLAR CELL



material for DSSC fabrication using zinc oxide (ZnO) nanoparticles. Findings from the research show that ZnO has the potential to be an alternative electrode material because of its wide band gap (i.e. 3.37eV) which is comparable to TiO2 material. Moreover, ZnO with flat band potential, higher than TiO2, is very much beneficial for enhancing the cell’s open circuit photo voltage at 60Mv of excitation binding energy (Pawar et al., 2009). ZnO is also known for its electrical and optical properties, low cost, non-toxicity, and relatively low deposition temperature (Shen et al., 2010) making it a promising alternative. In lieu to the above, the current work initiates to explore on the possibility to develop an alternative material for fabrication a low cost DSSC. Zinc acetate dehydrate was used as a starting or precursor material to producing zinc oxide. This was followed with the study on thin film application. There are several techniques available to produce thin film for the solar cell such as magnetron sputtering, pulsed laser deposition, spray pyrolysis, thermal evaporation and sol-gel route (Musil et al., 2005), (Bao et al., 2005), (Nakaruk et al., 2010), (Shah et al., 2009), (Rani et al., 2008), (Micheal et al., 1982), (Fouad et al., 2006), (Hench and West, 1990). In this work, the study has focused on synthesized zinc oxide powder by using sol-gel route technique. This technique was chosen since it is cheap, processing can be done at low operating temperature while offering high uniformity and easy controlled reaction (Brinker and Scherer, 1990). Microstructure analysis was carried out for two different heat treated samples (i.e. ZnO treated at 250ºC and 500ºC) to determine the annealing condition of the samples. These samples were further analyzed using particle size analyzer, X-RAY Diffractometer (XRD) XPERT-PRO with Cu-Kα radiation (λ=1.54060) and Energy Dispersive X-Ray Spectrometry (EDS). Energy Dispersive X-Ray Spectrometry (EDS) was conducted using a scanning electron microscope (SEM) machine, EVO 50 ZEISS-7636. Dye is normally used to excite the photon junction semiconductor mechanism. The most efficient sensitizer dye that has been used for the fabrication of DSSC is ruthenium polypyridyl complex (Grätzel, 2003). Other sensitizer dyes widely used are N719 ethanol dye (Lanlan et al., 2010) and Eosin-Y dye (Rani et al., 2008). Recent researches have shown that natural dyes can be used as a sensitizer replacing the ruthenium complex (Grätzel, 2003) and (Nazeeruddin et al., 2011). This includes leaves and flowers with colour pigment detectable in red-to-blue spectrums. Good examples of source of natural dye are dragon fruit (Hylocereus costaricensis) and raspberries (Riyaz and Nafarizal, 2010). Therefore, for the current work, dragon fruit was used in extracting the natural dye due to its high availability factor in Malaysia. 2.0 MATERIALS AND METHODS

2.1 Preparation of Zinc Oxide Powder The zinc oxide porous solution was prepared by dissolving zinc acetate dehydrate, Zn(CH3COO)22H2O in an acetic acid solution at room temperature (28 ± 5oC). A milky solution was formed and by using sol-gel route technique, clear solution was obtained by magnetic stirring. The prepared solution was found to be stable and colourless without turbidity. The heating was done at 90 ± 5°C until the solution evaporated leaving white particles in the beaker. During this period of time, white ZnO precipitates were slowly formed by settling down at the bottom of the beaker. The heating process was continued (90 ± 5°C) until formation of particles in gel-like paste was observed. The gel-like paste was then annealed in the oven at 90 ± 5°C for approximately 8 hours to form ZnO porous. This sample was then divided into two and given further annealing treatment at two different temperatures; i.e. 250ºC and 500ºC. A detailed elucidation of the structure and composition was carried out using various characterization techniques. Surface morphology and the particle size of the ZnO substance were analyzed through SEM (model: EVO 50 ZEISS-7636) and particle size analyzer. Before taking the SEM images, the samples were coated with a thin layer of gold using ion sputtering (model: JEOL, JFC-1600). All observing conditions were performed at room temperature of 28 ± 5 oC and at humidity level of 80 ± 10 %. X-ray diffraction (XRD) of the samples was obtained using a XPERT-PRO with Cu-Kα radiation (λ=1.54060). Quantitative analysis of elements was done by energy-dispersive X-ray (EDX) measurements. 2.2 Preparation of ZnO Electrodes and Counter Electrode ZnO powder was chunked into small particles followed by 15ml addition of ethanol. The mixture (i.e. ZnO powder and ethanol) was mixed uniformly until it produced a well uniform ZnO paste. The paste was carefully deposited onto a 2 x 2 cm2 indium tin oxide (ITO) glass to form the electrode, Figure 1(a). By means of using a hot place, the ZnO electrode was heated up to 150 ± 5°C for approximately 15 minutes. This was done to harden the ZnO paste on the ITO glass while indirectly enhancing the bonding characteristics (i.e. ZnO paste against the ITO glass). For the purpose of preparing the natural dye, pieces of fresh dragon fruit flesh with weight approximately 50 grams is mixed into 50 ml distilled water at room temperature of 28 ± 5oC, Figure 1(b). The mixture is further blended using an electric blender (model: Braun AG, type 4-172) for 10 minutes until a homogenous colour (i.e. dark pink) is seen by the naked eye. When this is achieved, the harden ZnO electrode is dipped into the dye solution for 24 hours, Figure 1(c).



For the purpose of preparing the counter electrode, graphite is deposited on the conducting surface of another virgin ITO glass, Figure 1(d). This was followed by treating both the opposite surfaces of the electrode and counter electrode with sulphuric acid. The two sides of ITO glasses that had been treated with sulphuric acid were then sandwiched securely together, Figure 1(e). The whole DSSC is left to dry at room temperature at 28 ± 5oC for about one hour before it was evaluated. (a) (b) (c) (d) (e)

Figure 1: Preparation of the Dye Sensitized Solar Cell, (a) ZnO electrode preparation, (b) Fresh dragon fruit, (c) ZnO electrode coated with dragon fruit dye, (d) Counter electrode preparation, (e) Prepared DSSC. 3.0 RESULTS AND DISCUSSION

3.1 Particle Size Analyzer Particle size analysis test was conducted on two samples of ZnO treated at different temperatures of 250ºC and 500ºC. The results of the particle size and its distribution are presented in Figure 2. From Figure 2(a) & Figure (b), ZnO sample at 250ºC shows the average size of the particle was between 100µm to 500µm. For the ZnO sample at 500ºC, the average size of particle was between 2µm to 20µm. From the result, it shows that ZnO sample annealed at 500ºC gave far finer particle than the one annealed at 250ºC. Consequently, the 500ºC annealed samples with smaller particle size gave large surface area of contact and large absorptive character compared to ZnO sample annealed at 250ºC. Based on this observation, ZnO annealed at 500ºC was selected for further fabrication of dye sensitized solar cell. (a) (b)

Figure 2: Particle size distribution of ZnO at different temperatures, (a) 250ºC, (b) 500ºC. 3.2 Scanning Electron Microscope analysis Based on the images obtained by SEM, the ZnO particles were thin flakes of very fine particles that were agglomerated jointly. This was due to the formation of carbonates or carboxylate ions from the acetic acid or other hydroxyl ions. This finding was similar to other findings as reported by Rani et al., (2008). The ZnO powder which was annealed at 250ºC [c.f. Figure 3(a)] shows the morphology was rougher as compared to ZnO annealed at 500ºC, Figure 3(d). At higher magnifications, the amount of synthesising reaction that occurs for both samples can be seen clearly [c.f. Figure 3(b), Figure 3(c), Figure 3(e) and Figure 3(f)]. Upon SEM anaylsis, it was found that ZnO powder sample annealed at 500ºC had smaller particle size and the reaction growth was more symmetrical as compared to ZnO sample at 250ºC. The uniformity in particle size and finer surface area makes ZnO annealed at 500ºC [c.f. Figure 3(f)] in better advantage compared to sample annealed at 250ºC [c.f. Figure 3(c)].

ITO glass

ZnO paste

Graphite



(a) (b) (c) (d) (e) (f)

Figure 3: SEM images of ZnO at different temperatures and magnifications, (a) ZnO at 250ºC, 20X, (b) ZnO at 250ºC, 3000X, (c) ZnO at 250ºC, 5000X, (d) ZnO at 500ºC, 20X, (e) ZnO at 500ºC, 3000X, (f) ZnO at 500ºC, 5000X.

3.3 XRD Pattern Analysis From Figure 4(a) ZnO sample annealed at 250ºC gave a non uniform diffraction pattern compared to ZnO powder annealed at 500ºC. However, ZnO at 250ºC did not exhibit any true character. Part of it was transformed back to the zinc acetate. This is due to the insufficient annealing heat which was not high enough to fully oxidize the sample, and the sudden exposure to the environment had caused the intermolecular structure to return to its initial condition. ZnO oxide powder annealed at 500ºC gave a more promising result as shown in the X-RAY diffraction, Figure 4(b). From the figure, it shows that the intensity of absorption of ZnO sample annealed at 500ºC lies between position 30º to 40º on a hexagonal plane at º2Theta measurement. Therefore, ZnO sample at 500ºC was selected as a thin film material to fabricate the DSSC. (a) (b)

Figure 4: XRD patterns of ZnO powder at different temperatures, (a) 250ºC, (b) 500ºC. 3.4 Energy Dispersive X-Ray Spectrometry Analysis From the results obtained in Figure 5(a) and Figure 5(b), it was found that there was carbon impurity in both samples. For ZnO sample at 250ºC, the weight by percentage of carbon impurity was about 16.49% while the atomic weight was about 33.07%. For ZnO sample at 500ºC, the weight by for carbon impurity was about 5.82% and atomic weight was about 17.43% which is significantly lower than 250ºC ZnO sample. This shows that the amount of the impurities can be reduced when the sample is heat treated at a higher temperature. The above results also show that the 500ºC ZnO sample has a higher atomic percentage of Zn and O composition in the sample as compared to ZnO sample at 250ºC. In other words, ZnO sample at 500ºC gives better quality amount of ZnO which is vital in producing an effective thin porous film of ZnO for DSSC. Thus, this is the main reason ZnO sample at 500ºC was selected as the substrate for producing a thin porous film of DSSC.

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(a) (b)

Figure 5: EDS spectrums of ZnO at different temperatures, (a) 250ºC, (b) 500ºC. 3.5 I-V Curve Analysis The testing for the DSSC was carried out to determine the voltage and current generated by the solar cell. Theoretically, short circuit current (Isc) and open circuit voltage (Voc) represents the maximum photocurrent and photovoltage of the fabricated DSSC. The maximum power of a solar cell can be found using Equation 1. Pmax = Imax x Vmax (1) The fill factor (FF) of a solar cell is expressed using Equation 2. FF = Pmax / (Isc x Voc) (2) Thus, the efficiency of the solar cell is the measurement of the electrical power generated by DSSC divided by the solar power distributed on the surfaces of DSSC. Taking the solar power (i.e. natural sunlight intensity) per unit area square to be 1mW/mm2 and the surface size of the DSSC to be 20 x 20 mm2, the nett solar power in mili Watts is expressed in Equation 3. Psolar nett = 1mW/mm2 x 20mm x 20mm = 400mW (3) Correspondingly, the measurements of voltage and current were taken at every 5 minutes of time interval for a total duration of 30 minutes where the DSSC was subjected to direct sunlight (i.e. DSSC was placed 90 degrees below the sun light). From Figure 6, theoretically, it can be said that the transient photocurrents generated are almost consistent per unit time. The transient current decreased proportionately with increase in its resistance. The instantaneous current was at maximum with zero internal resistance and decayed when the internal load resistance becomes very large.

Figure 6: Theoretical graph of I-V curve showing Isc, Voc, Imax & Vmax for determining Pmax and FF By merging all the values into a single graph as per Figure 7, the graph shows that the current and voltage of DSSC are found to be consistent with varied times. The efficiency (η) of the fabricated DSSC is expressed in Equation 4. η = Pmax / Psolar nett (4) Making Pmax as the subject in Equation 2 and substituting it in Equation 4 the following is obtained: η = (FF x Isc x Voc) / Psolar nett (5)

Element Weight % Atomic%C 16.49 33.07 O 31.80 47.87 Zn 51.71 19.05 Total 100.00 100.00

Element Weight % Atomic%C 5.82 17.43 O 18.13 40.75 Zn 76.04 41.82 Total 100.00 100.00



Knowing the values of Imax and Vmax from Figure 6, Pmax is computed using Equation 6 which is as follow: Pmax = Imax x Vmax = 1mA x 100mV = 100mW (6) In regard to this, values of Isc and Voc are determined from Figure 6 and the field factor is computed using Equation 2 where: FF = (1mA x 100mV) / (1.3mA x 275mV) = 0.28 (2’) Lastly, with Isc = 1.3mA, Voc = 275mV, FF = 0.28 and Psolar nett = 400mW, the efficiency of the fabricated DSSC is computed using Equation 5 where η = 25%. Figure 7: I–V curves for the fabricated DSSC using two ITO glasses with one electrode coated with graphite and the other coated with ZnO powder annealed at 500ºC and treated with natural dragon fruit dye

4.0 CONCLUSION This work has successfully established the cost effective method of producing an effectual dye sensitized solar cell using ZnO and natural dye. The synthesis of ZnO was carried out using sol- gel route technique in producing zinc acetate dehydrates that was successfully transformed into ZnO material. The DSSC produced had an efficiency of about 25%, a positive result as compared to other findings. This clearly shows that the ZnO material has the ability to be an alternative material to TiO2 in fabricating a low cost DSSC. ZnO powder annealed at 500 ºC was found to be more effective compared to one annealed at 250ºC. Higher temperature annealing condition gave significant outcome in producing higher grade of ZnO with reduced impurity and increased absorption intensity. The result shows that ZnO and natural dye have a promising application in the fabrication of dye sensitized solar cell. REFERENCES [1] El-Badri, A.S. (2010): World Oil Outlook. Yearly report of Organization of The Petroleum Exporting Countries, pp.1-281. [2] Bao, Q., Chen, C., Wang, D., Ji, Q., Lei, T. (2005): Pulsed Laser Deposition and its Current Research Status in Preparing Hydroxyapatite Thin Films. Applied Surface Science, Vol.252, Iss.5, pp.1538-1544. [3] Brinker, C.J. and Scherer, G.W. (1990): Sol-Gel Science: The Physics and Chemistry of Sol-Gel Processing. Academic Press. [4] Fouad, O.A., Ismail, A.A., Zaki, Z.I., Mohamed, R.M. (2006): Zinc Oxide Thin Films Prepared by Thermal Evaporation Deposition and Its Photocatalytic Activity. Appl. Catal. B: Environ, Vol.62, p.144. [5] Grätzel, M. (2003): Dye-Sensitized Solar Cells. Journal of Photochemistry and Photobiology C: Photochemistry

Reviews, Vol.4, Iss.2, pp.145-153. [6] Hench, L.L. and West, J.K. (1990): The Sol-Gel Process. Chemical Reviews, Vol.90, No.1, pp.33–72. [7] Lanlan, L., Renjie, L., Ke, F. and Tianyou, P. (2010): Effects of Annealing Conditions on the Photoelectrochemical Properties of Dye-Sensitized Solar Cells Made With ZnO Nanoparticles. Solar Energy, Vol.84, No.5, pp.845-853.



[8] Micheal, R.S. and Waltham M. (1982): Method to Synthesize and Produce Thin Films by Spray Pyrolysis. U.S. patent 4336285. [9] Musil, J., Baroch, P., Vlček, J., Nam, K.H. and Han, J.G. (2005): Reactive Magnetron Sputtering of Thin Films: Present Status and Trends. Thin Solid Films, Vol.475, Iss.1, pp.208-218. [10] Nakaruk, A., Ragazzon, D. and Sorrell, C.C. (2010): Anatase Thin Films by Ultrasonic Spray Pyrolysis. Journal of Analytical and Applied Pyrolysis, Vol.88, Iss.1, pp.98-101. [11] Nazeeruddin, M.K., Baranoff, E., Grätzel, M. (2011): Dye-Sensitized Solar Cells: A Brief Overview. Solar Energy, Vol.85, Iss.6, pp.1172-1178. [12] Olivia, M. (1998): Fundamentals of Photovoltaic Materials. Technical report by National Solar Power Research Institute, pp.1-8. [13] Pawar, B., Dukhohama, G., Mane, R., Ganesh, T., Anilghule, S.R., Jadhava, K.D. and Sung-Hwanhan. (2009): Preparation of Transparent and Conducting Boron-Doped Zno Electrode for Its Application in Dye-Sensitized Solar Cells. Solar Energy Materials & Solar Cells, Vol.93, pp.524-527. [14] Rani, S., Suri, P., Shishodia, P.K. and Mehra, R.M. (2008): Synthesis of Nanocrystalline ZnO Powder Via Sol–Gel Route For Dye-Sensitized Solar Cells. Solar Energy Materials and Solar Cells, Vol.92, Iss.12, pp.1639-1645. [15] Reijnders, L. (2009): The Release of TiO2 and SiO2 Nanoparticles from Nanocomposites. Polymer Degradation and Stability, Vol.94, No.5, pp.873-876. [16] Riyaz, A.M.A. and Nafarizal, N. (2010): Fabrication and Analysis of Dye-Sensitized Solar Cell Using Natural Dye Extracted From Dragon Fruit. Issue on Electrical and Electronic Engineering, Vol.2, Iss.3. [17] Shah, N.M., Panchal, C.J., Kheraj, V.A., Ray, J.R. and Desai, M.S. (2009): Growth, Structural and Optical Properties of Copper Indium Diselenide Thin Films Deposited by Thermal Evaporation Method. Solar Energy, Vol.83, Iss.5, pp.753-760. [18] Shen, L., Ma, Z.Q., Shen, C.F., He, B. and Xu, F. (2010): Studies on Fabrication and Characterization of a ZnO/p-Si-based Solar Cell. Superlattices and Microstructures, Vol.48, No.4, pp.426-433. [19] Stucky, G.D. and Bartl, M.H. (2010): Mesostructured Thin Film Oxides. Chapter 8 of Thin Film Metal-Oxides: Fundamentals and Applications in Electronics and Energy, Springer, pp.255-279. [20] Tsokos, K.A. (2008): Physics for the IB Diploma, 5th edition, Cambridge, Cambridge University Press, pp.800-835. [21] Yeji, L., Jinho, C. and Misook, K. (2010): Comparison of the Photovoltaic Efficiency on DSSC for Nanometer Sized TiO2 using a Conventional Sol–gel and Solvothermal Methods. Journal of Industrial and Engineering Chemistry, Vol.16, Iss.4, pp.609-614.



NIK FARJAM1, B. and YUNUSI2, M.

1, 2 Department of Mathematics Tajik National University

Dushanbe, 40, Rudaki Ave, TAJIKISTAN [email protected]

[email protected]

1.0 INTRODUCTION A graph is usually visualized by representing each vertex through a point in the plane, and by representing each through a curve in the plane, connecting the points corresponding to the end vertices of the edge. Such a representation is called a during of the graph if no two vertices are represented bye the same point, if the curve representing on edge not include any other points, representing a vertex (except its end points), and if two distinct edge have at most one common point. A drawing of a graph is plane it no two distance edge intersect part form their end points. A graph is planar if it admits a plane drawing. In electronic circuits, components are joined by means of conducting strips. These may not cross, since this would lead to undesirable signals. In this case, an insulated wire must be used. For layers without crossings, which are then pasted together? The good is to use a few layers are possible. In this application it would be desirable to know the thickness of a hyper graph whose nodes are cell to be paced and whose hyper edges correspond to the nets connecting the cells. If the thickness problems could be should for graphs, it would be a useful engineering tool in the layout of electronic circuits. 2.0 THEORETICAL BOUNDS Theorem (2.1) by Harary (1991). let G'= (V, E') be a maximum planer sub graph of a graph G= (V, E) them |E'|≤ 3|V|-6. Theorem (2.2) by Harary (1991). let G'= (V, E') be a maximum planer sub graph of a graph G= (V, E) which does not contain any triangles then |E'|≤ 2|V|-4. Theorem (2.3) by Cimikowski (1994). let m<9 then G is planer. Theorem (2.4) by Cimikowski (1994). if G is planar and n≥4 then it has at least four vertices of degree<6 The problem of determining a maximal planar sub graph is NP-complete. Theorem (3.5) by Clia and Goldmacher (1977), Yannakakis (1978) and Sylslo (1978) MPS is NP-complete. Theorem (2.6) by Kotzig (1955) the maximum planar sub graph of Qn contains 2n+1 -4 edges.

ABSTRACT

Maximum planar sub graph (MPS) has important application in facility layout and automated graph drawing. MPS is NP-complete. This paper presenting simulated annealing algorithms and branch – and bound algorithms for finding a mps of a no planar of graph Keywords: MPS, Simulated Annealing, Branch-and-Bound.

A SIMULATED ANNEALING ALGORITHM AND BRANCH - AND -BOUND FOR DETERMINING FOR MAXIMAL PLANAR OF GRAPH



3.0 ALGORITHM FOR MPS In 3.1 the performance ratio RA (p) of an approximation algorithm A for a maximization problem P is the minimum ratio of obtained solutions to the cost of optimal solution: min [A(G)]/[OPT(G)], if OPT(G) ≠0 RA = 1, if OPT(G) = 0 Since a spanning tree contain n-1 edges, and a maximum planer sub graph could contain at most edges (by theorem (2, 1) the performance ratio of this method is 1/3. Lim n-1 = 1 n⟶ ∞ 3n – 6 3 And since a maximal planar sub graph of any graph G can have more than 2n-4 (if G is triangle-free), and any spanning tree of G, which is bipartite, has n-1 edges the performance ratio of this method is 1/2. (By Theorem (2.2)) Lim n-1 = 1 n⟶ ∞ 2n – 4 2 3.1 GRE for MPS A greedy algorithm to search a maximal planar sub graph is to apply a planarity testing algorithm and to add a many edges as possible to a planar sub graph. See algorithm (3.1) (GRE) for a detailed description of this edge adding method GRE (G= (V, E), G'= (V', E')) (i) E"=E\E'; (ii) while there is an edge (u, v) is E" (ii) do E' ⟵ E' ⋃ {(U, V)}, E" ⟵ E"\ {(U, V)} (iv) if (V, E') is not planar (v) then E' ⟵ E' \ {(U, V)}; (vi) return (V, E').

4.0 SIMULATED ANNEALING, SA SA algorithm imitated the cooling process of material in a heat bath. SA was originally proposed by Kirkpatrick et al., (1983) based on some idea given by Metropolis et al., (1953). The search begins with initial temperature t0 and ends when temperature is decreased to frozen temperature t1, where 0≤ t1≤ t0. The equilibrium detection rate r tells when an equilibrium state is achieved, and temperature current temperature by the cooling ratio α, where 0<α<1. To determine good parameters for a given problem is often a hard task, and it needs experimental analysis. There are also adaptive techniques for SA. (Van Laarhoven and Aarts, 1987). The temperature of the SA algorithm gives the probability of choosing solutions that makes the current solution worse. If there are many bad solutions in a neighborhood of a "better" solution, and these bad solutions are accepted too often, the algorithm does not converge to good solution. For, ore details concerning SA algorithm, see (Van Laarhoven and Aarts, 1987), (Metropolis et al., 1953) and the references given there; Select a cooling ratio α and an initial temperature t0; Select a frozen temperature tl and an equilibrium detection r; Select an initial solution; set t← t0 and e← 0; (i) while t ≥ tl do (ii) while e ≤r do (iii) e ← e+1 (iv) randomly select a solution S∊N (S0) (v) δ ← cost (s) – cost (s0) (vi) generate a random integer i ;o ≤ i ≤ 1; (vii) if i ≤ e -δ/t then (viii) s0← s



(iix) t← α t; (ix) e← e; (x) return s0 ; Now we introduce a SA algorithm for determining MPS. The algorithm gets as input a graph G= (V, E) and a planar sub graph G'= (V, E') of G.SA maintains two sets of edges. The first set, E1, is initialized as E'. The second set, E2, is initialized as E/E'. The first set maintains the edges of a maximum planer sub graph and the second set always contains the remaining edges of the input graph. In what follows, we say shortly that a set of edges is planar, if the graph induced by this edge set is planar. After initialization, local optimization guided by SA scheme is applied to increase the size of E1 in the following way. An edge e2 from E2 is chosen randomly. First SA tries to move e2 to E2 without violating the planarity of E1 (this increase the size of E1) if this is not possible, SA randomly chooses and edge e1. From E1 and tries two swap this edge with e2. If the planarity of E1 is violated, SA checks if it is acceptable (according to the rules of SA) to move e1 to E2 (this decreases the size of E1). To check that is it allowed to move an edge E1 to E2, we make a random test. A random real i; 0 ≤ i ≤ 1, is generated if i ≤ e -1/t, where t is the current temperature, holds then a move that decreases the size of E1 is accepted. Since an n- vertex planar graph has at most 3n-6 edges (by theorem (2.2)) we have added a test to recognize optimal solutions in the while-loops of SA. 4.1 SA for MPS Select Cooling α and initial temperature t.; select frozen ratio α temperature t1 and equilibrium detection rate t; find an planar sub graph G'= (V, E') of G and set E, = E' (i) E2 = E\E1, t = t and e = 0 (ii) while t ≥ t1 and (|E1| < 3|V| - 6) do (iii) while e ≤ r and (|E1| < 3|V| - 6) do (iv) e = e +1 (v) randomly select an edge e2 from E2; (vi) if E1 ⋃ {e2} is planar then (vii) set E1= E1 ⋃ {e2} and E2 = E2 \ {e2}; else (viii) randomly select an edge e1 from E1; (iix) if (E1\{e1} ⋃ {e2}) is planar then (ix) set E1 = E1 \ {e1} and E1 = E1 ⋃ {e2}; (x) set E2 = E2 \ {e2} and E2 = E2 ⋃ {e1}; else (xi) generate a random real number i, 0≤ I ≤ 1; (xii) if i≤ e -1/t then (xiii)set E1 = E1 \ {e1} and E2 = E2 ⋃ {e1}; end; (xiv) t = ∝ t; (xiiv)16. e = 0; end; (xiv) return (V, E1); end

5.0 BRANCH-AND-BOUND One method to solve a discrete and finite optimization problem is to generate all possible solution and then choose the best one of them. For NP-complete problem this exhaustive search method fails since the number of solutions is exponential in the size of the input. For example, given a graph G= (V, E), there exist 2|E| different sub graph containing all |V| vertices. If the problem in question asks a sub graph of the given graph with some specific property, it is possible that all sub graphs need to be checked before the right one is found. Only small instance can be solved in this way. Branch-and-bound is a method that can be used in the exhaustive search by recognizing partial solutions that can not lead to an optimal solution. For example, suppose that we know that the optimal solution for a maximization problem is at least K (we have found a solution with cost K). If during the generation of the other solution candidates we recognize that the current solution can not be augmented to any solution with cost ≥ K, we can stop generating these solution candidates and continue searching from more promising solution. The efficiency of the branch- and- bound techniques depended highly on the problem in question and the order in which the solution candidates are found. If the lower bound for the optimal solution is bad, there are little possibilities to reject any solutions. The worst case during time of branch-and-bound is still exponentially but often it decreases the computation time remarkably (Kotzig, 1955).



5.1 Branch-and-Bound for MPS Since a planar graph can have no more than 3n-6 edges, and since any graph with fewer than 9 edges is trivially planar, it suffices to generate and test only sub graph satisfying 3n-9 these size constraints and hence at most is number. Secondly, since a non-planar graph may have less than 3n-6 edges, say, 3n-k where one need test at most sub graphs, which is still exponentially large.

4.0 CONCLUSION In this paper presenting two algorithms have concerning the maximal planar sub graph (MOPS) in particular branch-and-bound algorithm for solving the maximum planer sub graph problem have been presented techniques for reducing the number of sub graphs processed during the search have been described. REFERENCES [1] Cimikowski, R.J. (1994): Branch-and-Bound Techniques for the Maximum Planar Sub Graph Problem.

International journal of computer mathematics, Vol.53, pp.135-147. [2] Clia, P. and Goldmacher, R. (1977): On the Deletion of Non Planar Edges of Graph. In proceeding 10th southesstrn conference on combinatorics, graph theory, and computing, pp.727-738. [3] Harary, F. (1991): Graph Theory. Addison Wesley Longman Publishing Co. [4] Kirkpatrik, S., Gelatt, C.D. and Vecchi, M.P. (1983): Optimization by Simulated Annealing. science, Vol.220, No.4598, pp.671- 680. [5] Kotzig, A. (1955): On Certain Decompositions of Graphs. Matematicko-fyzikalny casopis, Vol.5, pp.144-151. [6] Metropolis. N., Rosenbluth, A.W., Rosenbluth, M.N., Teller, A.H. and Teller. E. (1953): Equation of State Calculation by Fast Computing Machines. Journal of chemical physics, Vol.21, pp.1087-109. [7] Sylslo, M.M. (1978): Outer Planar Graph: Characterization, Testing, Coding and Counting. Bulletin de L'Academine polonaise des sciences, Vol.26, No.8, pp.675-684. [8] Van Laarhoven, P.J. and Aarts, E.H. (1987): Simulated Annealing: Theory and Application. 1st Edition, Springer Publishing. [9] Yannakakis. M. (1978): Node-End Edge-Deletion NP-Complete Problems. In proceeding of the 10th Annual ACM symposium on theory of computing. pp.253-264.



ANIKA ZAFIAH1, M.R., NUR MUNIRAH2, A. and ABDULLAH3, M.F.L.

1, 2 Department of Materials and Design Engineering Faculty of Mechanical and Manufacturing Engineering

3 Department of Communication Engineering Faculty of Electrical and Electronic Engineering

Universiti Tun Hussein Onn Malaysia 86400, Parit Raja, Batu Pahat, Johor, MALAYSIA

[email protected]

1.0 INTRODUCTION The quality of human life depends to a large degree on the availability of energy. This is threatened unless renewable energy resources can be developed in the near future. Fortunately, the supply of energy from the sun to the earth is gigantic, i.e., 3 X 1024 J/year or about 104 times more than what mankind consumes currently. In other words, covering only 0.1% of the earth’s surface with solar cells with an efficiency of 10% would satisfy our current needs (Gratzel, 2005). The first generation of solar cell most highly represented in commercial production. It is relatively expensive to produce and very pure silicon is needed, and due to the energy-requiring process, the price is high compared to the power output (Lund et al., 2008). Therefore, a basic dye solar cell is proposed for sustainable energy conversion of visible light into electricity. A metal oxide (band gap < 3eV) (Hoffmann et al., 1994) and (Sumandeep, 2007) is thought to promote the internal trapping of light by scattering (redirecting) the light reflected from the metallic electrode in the active layer and also to improve the transport of charge carriers through the active layer (Banwell, 1983) based on the sensitization of wide band gap semiconductors (Gratzel, 2003). In order to develop the dye solar cell for mass production, the performance of the cell is very crucial and it is mainly depends on the dye used as sensitizer. The absorption spectrum of the dye and the anchorage of the dye to the surface of metal oxide are important parameters in determining the efficiency of the cell. The sensitization of wide band gap semiconductors using natural pigments is usually ascribed to anthocyanins, found in fruits, flowers and leaves of plants which have advantages over chlorophyll as dye solar cell sensitizer (Hao et al., 2006), (Martinez et al., 2011), (Calogero et al., 2010). Meanwhile, for better dye absorption into the thin film, manipulating the physical and chemical properties of metal oxide can leads to higher solar cell performance. Jin and Suslick (2010) summarized that ultrasonic approached has more advantages over conventional methods in the synthesis of nanostructured materials such as metals, alloys, oxides (Mandzy et al., 2005), sulfides, carbides, carbons, polymers, and even biomaterials. The versatility of the ultrasonic process where perform in a solvent form more uniform size distribution, contribute to higher surface area, faster reaction time, and improved phase purity. This paper discussed the technique of preparing dye solar cell using engineering grade metal oxide of Titanium Dioxide, TiO2 (>99% purity) with undergo ultrasonic process and

ABSTRACT

The large-scale use of photovoltaic devices for electricity generation is prohibitively expensive at present: generation from existing commercial devices costs about ten times more than conventional methods. This paper presents a thin-film solar cell (TFSC), also called a thin-film photovoltaic cell (TFPV), is a solar cell that is made by depositing one or more thin film of photovoltaic material on a substrate. There are four types of TFSC: Amorphous silicon (a-Si), cadmium telluride (CdTe), copper indium gallium selenide (CIS or CIGS) and dye-sensitized solar cell (DSSC). DSSC of natural dyes from local fruits which consist of the carbonyl and hydroxyl groups of anthocynin molecule influences the performance of photosensitized effect due to high interaction on the surface of filler. Metal oxide; MO1 and treated metal oxide; MO2 using ultrasonic is to break the particle agglomeration from micro down to nano scale. The microstructure of metal oxide were observed using Field Emission Scanning Electron Microscope (FESEM) and the electrical characteristic of MO1 with open circuit, Voc=0.69790 V, short circuit, Isc=0.22 mA, fill factor, FF=77.9106 gives 0.031% efficiency and MO2, with Voc=0.74228 V, Isc=0.36 mA, FF=57.0124 gives 0.039% were reported. Therefore, this ultrasonic treatment is reliable to be used for further application. Keywords: Photovoltaic, Dye-Sensitized, Silicon, Semiconductor, Photoelectrons, Anthocynin.

INFLUENCE OF TREATED METAL OXIDE FOR SUSTAINABLE ENERGY CONVERSION



natural dyes extracted from a local fruits as sensitizer to develop a single cell of dye solar cell with increasingly higher voltage and more efficient. 2.0 THEORY AND METHODS

2.1 Operation of Dye Solar Cell The architecture of an example of dye solar cell (DSC) is shown in Figure 1. The DSC consists of a dye-covered, nanoporous metal oxide usually TiO2 layer and an electrolyte encapsulated between two glass plates. The front and counter substrates are coated with a transparent conducting oxide (TCO), then fluorine doped tin oxide (SnO2:F), FTO which is most commonly used. The FTO at the counter electrode is coated with few atomic layers of platinum (Pt), in order to catalyze the redox reaction with the electrolyte. The front electrode is coated with a nanocrystalline metal oxide layer with average particle sizes of 5 to 200 nm. Three modification of TiO2 exist: rutile, anatase and brookit. In the DSC preferably only the anatase modification is used. On the surface of the metal oxide, a monolayer of dye molecules is adsorbed. The huge nanoporous surface allows for adsorption of a sufficiently large number of dye molecules for efficient light harvesting. In dye solar cell, an incoming photon from the sunlight boosts an electron from natural dye and courses the electrons to be at the excited state. Those excited electrons are injected into the conduction band of the metal oxide electrode, resulting in oxidation of the sensitizer. Then, the injected electrons in the conduction band of metal oxide are transported by diffusion along the metal oxide particle network towards the external conducting glass made of indium-tin oxide and consequently reach the carbon black counter electrode through the external load. Finally, the oxidized sensitizer (dye*) accepts electrons from the I– ion redox electrolyte, regenerating the ground state (dye), and I– is oxidized to I3– state. The oxidized redox mediator, I3–, diffuses toward the counter electrode where it is re-reduced to I– ions (Lee et al., 2009).

Figure 1: Architecture of a dye solar cell. The metal oxide and the electrolyte are located between two glass plates, coated with transparent conducting oxide (TCO). The metal oxide thin film is covered with a monolayer of dye and the counter electrode is coated with carbon black (Sastrawan, 2006) 2.2 Dye Solar Cell Assembled and Characterization The extraction of dye from the plant material was carried out in lab scale quantity comprised of soaking, dried, cleaned and pulverized plant material followed by a second step of heating up dyestuff at certain temperature. The solution was further filtered to obtain the dyestuff. This process was adopted from Lee et al., (2009) and Agarwal and Ghaziabad (2009). Engineering grade; 99% purity of TiO2 was grinded in a mortar and pestle with few drops of surfactant resultant uniform and lump free paste namely MO1. The metal oxide mixture was placed uniformly over a slide in a rapid motion. The MO1 slide was sintered over a hot plate until transitioned from white to a brownish colour has been observed. Once the film has cooled, the slide was placed in a Petri dish filled with sensitizing dye for a few minutes. Meanwhile for the treated metal oxide, MO2, the ultrasonic process was carried out using clamp-on tubular reactor with tube diameter of 60 mm and length of 580 mm at certain frequency (trial frequency at 18.520 kHz) as in Table 1. The MO2 electrode preparation method goes the same as MO1. Then, counter electrode were prepared using carbon black.

Table 1: Condition process for clamp-on tubular reactor Freq (kHz) Sweeping(kHz) Power (%) MaxCurrent (A) PWMPeriod (s) PWMRatio (%) FSWM Range (kHz) FSWM Ratio (%) FSWMPeriod (s) 18.520 0 50 2 0.010 100 0.500 50 0.010 The cells were assembled by sandwiching the glass together. Then 2 to 3 drops of an electrolyte is place between the two electrodes for capillary action. The sandwiching of the electrodes is offset so that each one has a small exposed portion. An alligator clamp was attached on the expose portion as shown in Figure 2. The negative clamp goes to the metal oxide/sensitizer plate and the positive clamp goes to the



carbon black plate. The assembled dye solar was observed based on ultrasonic treated TiO2 and its electrical properties performance. The assembled dye solar, surface morphology of the TiO2thin film was observed using Field Emission Scanning Electron Microscope (FESEM), surface profiler and Atomic Force Microscope (AFM). The assembled solar cell was tested upon 1 Sun of light illumination using Solar Simulator for I-V characteristic to calculate the cell efficiency. Figure 2: Single cell of assembled dye solar cell (Tholvanen, 2003)

3.0 RESULTS AND DISCUSSION FESEM images of TiO2 revealed both micro and nanoscale surface morphology. Figure 3(i) and Figure 4(i) shows an average gross view of TiO2 thin film surface -sponge like, while, Figure 3(ii) and Figure 4(ii) displays a clear view of the TiO2 which gives a range between 100 – 300 nm of particle size. Figure 3: Metal oxide morphology with magnification for untreated TiO2, (i) 2000, (ii) 10000, (iii) 25000, (iv) 50000, (v) 75000 & (vi) 100000

Figure 4: Metal oxide morphology with magnification for treated TiO2, (i) 2000, (ii) 10000, (iii) 25000, (iv) 50000, (v) 75000 & (vi) 100000



Figure 4 shows denser and smoother structure as compared to Figure 3. Smaller particle size or less large particle agglomerates known to contribute a slightly higher in surface area, thus faster reaction time, and improved phase purity, creating ‘sponge like’ high porosity structure. Therefore, more dye sensitizer will be absorbed to the metal oxide film and enhanced the performance of photovoltaic solar cell. The grain boundaries of surface area thin film equivalent to 25 µm2 for untreated and treated TiO2 with ultrasonic revealed more uniform size distribution, contributed to higher surface area, faster reaction time, and improved phase purity. According to Ahmad et al., (2010), when the grain size becomes larger, electron movement from particles to other particles improves. Figure 5 also shows the surface morphology of both films (untreated and treated with ultrasonic) in a 3D form by using Atomic Force Microscope, AFM. The difference between the highest peaks to the lower one represent by the color range shows for both films. It is observed that there is large gap in between those higher and lower particles for treated metal oxide with ultrasonic coated film that has smaller particle size with large surface area to volume ratio and this is where the detrapping and trapping of electrons in metal oxide film takes place. As the porosity of a film gets smaller and deeper, the electron diffusion gets slower and simultaneously jeopardize the photovoltaic performance. Figure 5: 3D surface structure of metal oxide film in range 25 µm2 However, the optimum particle size shall be examined and should not be reduced indefinitely due to the influences of the metal oxide porosity layer. As the particle size decreases, the pores also get smaller. The electrolyte has to be able to penetrate the pores and be present where there is absorbed dye. In addition, larger particles scatter light more effectively, and this has been found to have a positive effect on the performance of the cell (Kalyanasundaram and Gratzel, 1988). In spite of light scattering, the particle size also influenced the surface roughness of a film as shown in Figure 5. The thin film of untreated TiO2 gives 0.37 µm particle size with 11.4970 µm thick [Figure 6(a)] while [Figure 6(b)] with 0.15 µm gives 6.2984 µm as its thickness. Noted that the treated thin film of TiO2 with reduce in particle size causes reduction in thickness, simultaneously creating more multiple layers up to 42 layers. Meanwhile, the untreated with larger particle size and higher thickness gives only 31 layers. Hence, the photovoltaic solar cell resembles photosynthesis in plants more effectively, by its multiple layers.

(a) (b) Figure 6: Thickness and surface roughness of (a) untreated (width=1567.8 μm, height=-11.497μm, TIR=35.649μm), (b) treated (width=654.72 μm, height=-6.2984 μm, TIR=8.9482μm) TiO2 thin film by Surface Profiler The solar cell performance is determined by its overall conversion efficiency (η) and incident photon to conversion efficiency (IPCE). Three parameters (Isc, Voc, and FF) are usually used to characterize solar cell outputs. The short-circuit current, Isc, is obtained when the current flows freely through an external circuit that has no load or resistance. Voc corresponds to the energy difference between the Fermi level of the semiconductor and the level of the electrolyte redox couple. The fill factor (FF) can be calculated from the maximum power point, which is a quantitative measure of the device’s quality defined by the square of the I-V curve as shown in Figure 7. For cells of reasonable efficiency, FF has a value in the range of 0.7 to 0.85. Based on the graph, the fill



factor and the efficiency of the cells were calculated. The electrical parameters of prepared dye solar cell were summarized in Table 2. Figure 7: Graph of I-V characteristic prepared cells, untreated metal oxide with ultrasonic process; MO1 and treated metal oxide with ultrasonic process; MO2

Table 2: The electrical parameters of prepared dye solar cell

Due to imperfect sealant (using only clipper to assemble both electrode and counter electrode) and the cell being exposed in a period of time under the light beam before the first data been recorded, it is revealed that the photovoltaic solar cell in this research using a liquid electrolyte has high efficiency, but suffer from low thermal and chemical stability. The liquid electrolyte will evaporate when the cell is imperfectly sealed and the permeation of water or oxygen molecules and their reaction with electrolytes slow down the overall cell’s performance (Hanhong et al, 2009). Based on electrical characteristic of prepared cells, it is possible to conduct a preliminary test upon normal sunlight or outdoor test and have a clear view how the dye solar cell actually perform. In addition, the energy in sunlight includes several kinds of radiation and each kind has a different wavelength. The radiations are Ultraviolet (UV) radiation, to the visible light spectrum as shown in Figure 8, to infrared radiation. The wavelengths radiation range is from less than 290 nanometers for UVC (a very short, high-energy wavelength) to 3000 nanometers (a very long, low-energy wavelength) (Kartini, 2004). In other words, there are many factor could influence the dye solar cell performance under normal sunlight. Figure 8: Amounts of UV light in living environments (Mori, 2005)

4.0 CONCLUSION The assembled dye solar cell comprises of three layer structure of engineering grade (>99% purity) metal oxide as photoelectrode, natural dye as sensitizer, liquid electrolyte as the electron donor and carbon black as counter electrode. First encouraging results on this new generation of energy conversion solar cell have been presented and successfully design. Respective dye solar cell, untreated metal oxide with ultrasonic process; MO1 with Voc=0.69790 V, Isc=0.22 mA, FF=77.9106 gives 0.031% efficiency and treated metal oxide with ultrasonic process; MO2 with Voc=0.74228 V, Isc=0.36 mA, FF=57.0124 gives 0.039% efficiency. The ultrasonic process of MO2 enhanced the efficiency of the solar cell. Thus, further study of design and fabrication methods of a single cell energy conversion could be utilized to improve the efficiency of the output parameter.

Voc (V) Isc (A) Jsc (mA/cm2) Imax (A) Vmax (V) Pmax (mW) FF Efficiency (η%) MO1 0.6979 0.00022 0.05584179 0.00024 0.49576 0.121454 77.9106 0.0310 MO2 0.74228 0.00036 0.09038500 0.00030 0.51515 0.15300 57.0124 0.0390



REFERENCES [1] Agarwal, K. and Ghaziabad, K. (2009): Euro.Patent.App. EP0754734A1. [2] Ahmad, M.K., Halid, M.L.M., Rasheid, N.A., Ahmed, A.Z., Abdullah, S. and Rusop, M. (2010): Effect of Annealing Temperatures on Surface Morphology and Electrical Properties of Titanium Dioxide Thin Films Prepared by Sol Gel Method. Journal of Sustainable Energy& Environment, Vol.1, pp.17-20. [3] Banwell, C.N. (1983): Fundamentals of Molecular Spectroscopy. 3rd edition. McGraw Hill Book Co Ltd. [4] Calogero, G., Marco, G.D., Cazzanti, S., Caramori, S., Argazzi, R., Carlo, A.D. and Bignozzi, C.A. (2010): Efficient Dye-Sensitized Solar Cells Using Red Turnip and Purple Wild Sicilian Prickly Pear Fruits, Int. J. Mol. Sci., Vol.11, pp.254-267. [5] Gratzel, M. (2005): Solar Energy Conversion by Dye-Sensitized Photovoltaic Cells. Inorg. Chem., Vol.44, pp.6841-6851. [6] Gratzel, M. (2003): Dye Sensitized Solar Cells. J. Photochem. Photobiol. C4, p.145. [7] Hanhong, C., Ziqing, D.L., Yicheng, D. and Aurelien, P. (2009): Dye-Sensitized Solar Cells Combining ZnO Nanotip Arrays and Nonliquid Gel Electrolytes. Journal of Electronic Materials, Vol.38, No.8, pp.1612-1664. [8] Hao, S., Wu, J., Huang, Y. and Lin, J. (2006): Natural Dyes as Photosensitizers for Dye-Sensitized Solar Cell. Sol. Ener. Vol.80, pp.209-214. [9] Hoffmann, M.R., Martin, S.T., Choi, W. and Bahnemann, D.W. (1994): Environmental Applications of Semiconductor Photocatalysis, Chem. Rev., Vol.95, pp.69-96. [10] Jin, H.B. and Suslick, K.S. (2010): Applications of Ultrasonic to the Synthesis of Nanostructured Materials. Adv. Mater., Vol.22, pp.1039-1059. [11] Kalyanasundaram, K. and Gratzel, M. (1988): Application of Functionalized of Transition Metal Complexes in Photonic and Optoelectronic Devices. Coordination Chemistry Reviews, Vol.77, pp.347-414. [12] Kartini, I. (2004): Synthesis and Characterisation of Mesostructured Titania for Photoelectrochemical Solar Cells. PhD Thesis at the University of Queensland. [13] Lee, K.E., Charbonneau, C., Guobin, S., George, P.D. and Raynald, G. (2009): Nanocrystalline TiO2 Thin Film Electrodes for Dye-Sensitized Solar Cell Applications. Jom, Vol.61, Iss.4, pp.52-57. [14] Lund, H., Nilsen, R., Salomatova, O., Skare, D. and Riisem, E. (2008): Solar Cells, retrieved on August 2010 from http://org.ntnu.no/solarcells/pages/generations.php [15] Mandzy, N., Grulke, E. and Druffel, T. (2005): Breakege of TiO2 Agglomerates in Electrostatically Stabilized Aqueous Dispersions. Powder Technology, Vol.160, pp.121-126. [16] Martinez, A.R.H., Miriam, E., Susana, V., Fracisco, Q. and Rogelio, R. (2011): New Dye-Sensitized Solar Cells Obtained from Extracted Bracts of Bougainvillea Glabra and Spectabilis Betalain Pigments by Different Purification Processes. Int. J. Mol. Sci., Vol.12, pp.5565-5576. [17] Mori, K. (2005): Photo-Functionalized Materials Using Nanoparticles: Photocatalysis, KONA, Vol.23, pp.205-214. [18] Sastrawan, R. (2006): Photovoltaic Modules of Dye Solar Cells. PhD Thesis at Albert-Ludwigs University. [19] Sumandeep, K. (2007): Light Induced Oxidative Degradation Studies of Organic Dyes and Their Intermediates. PhD Thesis at Thapar University. [20] Tholvanen, A. (2003): Characterization and Manufacturing Technique of Dye-Sensitized Solar Cell. Master Thesis at Helsinki University of Technology.



YUHAZRI1, M.Y., HAERYIP SIHOMBING2, YAHAYA3, S.H., SAID4, M.R., UMAR NIRMAL5, SAIJOD LAU6 and PHONGSAKORN PRAK TOM7

1, 2, 3 Faculty of Manufacturing Engineering 4 Faculty of Mechanical Engineering Universiti Teknikal Malaysia Melaka

Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, MALAYSIA [email protected] 2iphaery@ utem.edu.my

5, 6 Faculty of Engineering and Technology

Multimedia University Jalan Ayer Keroh Lama, 75450, Melaka, MALAYSIA

[email protected] [email protected]

7 Nuclear Power Division Malaysia Nuclear Agency

Bangi, 43000, Kajang, MALAYSIA [email protected]

1.0 INTRODUCTION Producing energy from renewable biomass is only one of the various ways of responding to the challenges of the energy crisis. Since the oil crisis in 1970’s the use of biomass as a source of energy is a topic of growing interest and debate as agreed by Gómez-Loscos (2012), Tong and Li (2012), Arias (2011), Vaclav (2010), Fernando (2009), Kaygusuz and Keles (2008). Corley and Tinker (2008) in their book discuss in detail about oil palm in Malaysia. In 2004, Malaysia had about 3.87 million hectares of land under oil palm cultivation. Currently, more than 80 percent of the oil palm produced is used for food applications like cooking oil, frying oil and many others. Oil palm is a perennial crop. It has an economic life span of about 25 years. Traditionally, oil palm is grown for its oil example like palm oil, palm kernel oil, and palm kernel cake as the community products. Besides palm oil and palm kernel, oil palm industry generates large quantity of biomass residue which is side products as stated before like fronds, trunks, EFB, palm oil mill effluent, palm fibre and shell that have not been fully commercially exploited. Through concerted research and development efforts by many research organizations including Malaysian Oil Palm Board, this co – products from palm oil industry have been found to be good resources for many application such as palm oil fuel ash a biomass residue (Brown et al., 2011), oil palm as a viable concrete pozzalanic material (Foo and Hameed, 2009), Oil palm ash as partial replacement of cement for solidification/stabilization of nickel hydroxide sludge (Chun et al., 2008), oil palm ash in concrete (Tangchirapat et al., 2007).There are many competitive uses of these materials. One of them is to utilize them as a fuel for

ABSTRACT

This research discussed on the results obtained for each sample that have been conducted to the solid fuel briquettes made of empty fruit bunch fiber and waste papers from view of ash content during combustion test. The results shows tremendous amount of ash content can be generated from these biomass compositions. Percentage of ash content in every composition is important to know how much ash produced every burning process because this is really related to environmental issues (human and equipment, i.e hygiene). Hence, the possibility result in this research is the development of solid fuel briquette by mixing the empty fruit bunch with a waste paper can be one sources of fuel energy. From the combustion analysis shows sample briquette of S/N 5 was found to be the best ratio as the amount of ash produced at the end of combustion process is the least compared to others researcher with a value of 1.11 percent. Keywords: Empty Fruit Bunch Fiber, Waste Papers, Ash Content.

SOLID FUEL FROM EMPTY FRUIT BUNCH FIBER AND WASTE PAPERS PART 3: ASH CONTENT FROM COMBUSTION TEST



energy production but in term of biodiesel fuel. In fact, Malaysian government has identified biomass as fifth fuel resource to compliment the petroleum, gas, coal, and hydro as energy resources, while palm biomass has been identified as a single most important energy source as stated by Sumiani (2006). On the other hands, the main sources of biomass in Malaysia are domestic wastes, agricultural wastes, effluent sludge and wood chips (Yuhazri et al., 2011) and (Yuhazri et al., 2010). Biomass energy systems can be based on a wide range of feedstock like food and garden wastes (Romeela and Ackmez, 2012), solid wastes and sewage sludge (Despina et al., 2012), cellulosic ethanol (Gonzalez, 2011), coal and cattle biomass (Carlin et al., 2011) and many more. They use many different conversion technologies to produce solid, liquid, and gaseous fuels. These can then be used to provide heat, electricity and fuels to power vehicles; using burners, boilers, generators, internal combustion engines, turbine or fuel cells. Power can be generated by co – firing a small portion of biomass on existing power plant, burning biomass in conventional steam boilers, biomass gasification and anaerobic digestion. Converting palm biomass into a uniform and solid fuel through briquetting process appears to be an attractive solution in upgrading its properties and add value as reported by (Sławomir, 2012), (De et al., 2012), (Nasrin et al., 2011), (Chuen-Shii, 2009). Biomass briquette is the process of converting low bulk density biomass into high density and energy concentrated fuel briquettes. Biomass briquette plant is of various sizes which converts biomass into a solid fuel. Briquettes are ready substitute of coal or wood in industrial boiler and brick kiln for thermal application. Biomass briquettes are non conventional source of energy, renewable in nature, eco – friendly, non polluting and economical. Process of converting biomass into solid fuel is non polluting process. It involves drying, cutting, grinding, and pressing with or without the aid of a binder. Malaysia has involved in palm oil industry over the last four decades and since then it has generated vast quantities of palm biomass, mainly from milling and crushing palm kernel. Empty fruit bunch is the main solid waste from oil palm obtained from milling process. This biomass can be used as an alternative energy for combustion purposes especially in industry. Unfortunately, due to its poor physical properties EFB is not normally utilized as fuel. However, it can be use in optimise by upgrading and treating its properties. The method that can be used is the briquetting technique. Briquetting is the alternative method in upgrading biomass into a useful solid fuel that can be done through various technologies. In this research, EFB material will be mixed up with the recycled papers and it will be turned into solid briquette through the briquetting process. The used of recycle papers in this research is to utilized the abundant papers into something useful, thus helps in reducing the number of municipal wastes generated every year. Papers are selected as a material to be used compared to the other types of recycled wastes such as glass and plastic because it is known to be a good material for a combustion ignition. As for plastics, it may be compatible to papers to be used as ignition material in combustion, but it will spread a toxic gas while it is burn. The scope of this research is mainly focusing on the mixing of the empty fruit bunch, EFB and the recycled papers. All these palm oil mills is to be obtained, mixed up and to be develop as a fuel briquette at a certain ratio or percentage with the EFB as the major element. This fuel briquette is to be carried out with the performance tests and comparison tests in terms of its calorific values (Yuhazri et al., 2012a), gas emission (Yuhazri et al., 2012b), stability and durability, proximate, ultimate, immerse and crack, but in this paper (part 3) only discuss on ash content produced after combustion test. 2.0 MATERIALS AND METHODS Empty Fruit Bunch (EFB) supplied by Malaysian Palm Oil Board (MPOB) from one of plantation in Malaysia was used as reinforced material in this green composites fabrication. The EFB used in the composites was in a chopped strand form. The EFB type used was shown in the Figure 1(a) and the Table 1 is the basic properties of EFB used for the fabrication of the composites based on study done by (Nasrin et al., 2008). (a) (b)

Figure 1: (a) EFB in fibrous form, (b) Shredded paper in shredder machine.



Recycled papers are use as a matrix material in the solid fuel briquette fabrication. The reason to choose papers as recycled waste in this research is because due to the properties of papers which can provide good properties for combustion. Furthermore, it can act as a binder during the blending of papers and EFB during fabrication stage. The papers are obtained from waste papers of the paper shredder machine. This is because the crushing papers have a standard size and dimension after is shredded inside the crushing machine. The standard size and dimension helps to ensure that the blending of papers and EFB is uniform. Table 1: Properties of EFB as raw materials. (Nasrin et al., 2008) Raw Material Average size of Materials Calorific Value Moisture Content Ash Content kJ/kg % % Pulverized EFB <212µm 17000 12.0 2.41 EFB Fibre 3 cm 16641 16.0 4.70 EFB Fibre 2.5 mm 16641 14.0 4.60 The dimension of sample briquette produced during sample preparation is 40 mm in diameter and 73 mm in length with average weight about 67.64 grams. The ratio of briquette produced is presented in Table 2 and Figure 2 is actual specimens.

Table 2: Sample ratio and its serial number Ratio of EFB to Paper Serial Number

90:10 S/N 1 80:20 S/N 2 70:30 S/N 3 60:40 S/N 4 50:50 S/N 5 40:60 S/N 6 There are several steps involved in producing a single briquette according to its ratio. Firstly, the waste papers need to be immersed in water for 24 hours and then it is blended using a blender to mash up the waste papers. Then, the blended papers it weighed again to get the weight of mashed papers with water. After dividing the EFB and shredded papers according to their ratios, the EFB fiber is mixed up with the shredded paper. Then, the compacting step takes place by compacting the mixing of EFB and waste paper into a solid briquette by using hydraulic press machine and cylinder mold. The size of the mold is 100 mm in length and 40 mm in diameter. The mixing is compressed into the mold until it gets to the desired length which is 73 mm. The amount of pressure applied during compacting process is 3 bars. Finally, the solid briquette is placed inside a drying oven at temperature 100 °C for 24 hours to remove the water obtained during the compacting process. (a) (b) (c) (d) (e) (f)

Figure 2: Samples of solid briquettes in different ratios; (a) S/N 1, (b) S/N 2, (c) S/N 3 (d) S/N 4, (e) S/N 5 and (f) S/N 6.



3.0 RESULTS AND DISCUSSION From the combustion test, the amount of ash produced from the combustion of each briquette can be obtained. It can be done by taking the residue from the sample that has burnt completely and weighed it using a digital weight scale. The percentage of ash content produce for each briquette can be calculated. The percentage of ash content of solid briquette for each ratio is represented in a Table 3. Table 3: Ash content and percentage of ash for sample briquettes

Ratio of EFB to paper Mass of Briquette (g) Ash content (g) Percentage of Ash (%) S/N 1 135.28 4.8 3.55 S/N 2 135.28 2.0 1.48 S/N 3 135.28 6.0 4.44 S/N 4 135.28 2.1 1.55 S/N 5 135.28 1.5 1.11 S/N 6 135.28 2.4 1.77 The sample briquette S/N 5 produced the least amount of ash as a result of the combustion process test. This is followed by a sample briquette S/N 2 with percentage of ash content is 1.48 %. Sample briquette S/N 3 produced the largest amount of ash content which is 4.44 % and followed by sample briquette S/N 1 with percentage of 3.55 %. This value can be further represent by a graphical form in Figure 3.

Figure 3: Percentage of ash in briquettes. Figure 3 shows the gap between briquettes with the highest ash content with a briquette with the lowest ash content is 3.33 percent. A good and quality briquette in terms of combustion efficiency is the least amount of ash content produced after combustion process. This shown that the briquette is burning effectively causing the ash produced at the end of the combustion process is small. From the experiment, the higher amount of waste paper in the ratio, the smaller the amount of ash produced at the end of the combustion process. This is because, paper will get burnt easily and it will burn completely first leaving the EFB that sustained the burning of the briquettes. Briquettes with the largest amount of EFB will produce greater amount of ash at the end of the combustion process. This is proven by the experimental work conducted which shown that S/N 3 and S/N 1 produced the highest amount of ash content compared to others. Similar to the combustion analysis conducted by Nasrin et al., (2008), 100 % EFB briquette produced the highest amount of ash content compared to other briquettes tested. The authors also discussed on the comparison of the ash content produced by the EFB in two different conditions which one is in fibre form and the other one is in powder form. It is shown that EFB in fibre form will produce greater ash content compared to EFB in powder form at the end of combustion process. Obernberger and Thek (2004), also stated that in order to maintain a high operating comfort for end users in the residential heating sector, a high ash content must be avoided. This is due to the possibility of increasing danger of slag and deposit formation in the furnace as well as the rising of dust emission. High percentage of ash content implied that fiber could only burnt satisfactorily in a limited range of coal appliances for example step furnace. High ash content is likely to reduce the ignitability of fuel briquettes which in contrast to fuel property that should be combustible and easy to ignite. Mass losses over specific temperature ranges in a specific atmosphere provide a compositional analysis of that substance. Figure 4 illustrated the comparison of ash content on sample briquettes S/N 5 and S/N 6 with a sample briquette conducted by Nasrin et al., (2008) based on the same ratio.



Figure 4: Percentage of ash in sample briquettes Based on the Figure 4, it is proven that the ash content of the fuel briquette form S/N 5 and S/N 6 are relatively lower compared to the sample briquettes produced by the author at the same ratio. The author is conducting a sample briquette of EFB and sawdust at several ratios. The different between the ash content from S/N 5 with the author sample briquette of 50 (EFB):50(S) is 1.11 percent whereby the different in percentage of ash produced for sample briquette S/N 6 with sample briquette of 40(EFB):60(S) is 1.22 percent. This has clearly shown that the sample briquette S/N 5 and S/N 6 produced are better compared to the sample briquettes produced by the author. Another comparison can be made with the other researchers that have conducted the study on the same field which is production of solid briquettes by referring the Table 4. Table 4: Comparison of ash content (%)

No Authors Title of study Ash content (%) 1 Husain et al. (2002) Briquetting of palm fiber and shell. 5.8 2 Demirbas and Sahin (1997) Briquetting of waste paper and wheat straw 13.6 3 Yaman et al. (2000) Production of briquettes form olive refuse and paper mill waste 5.0 4 Nik Farah Nik Zulkifli (2006) Development of fuel briquettes from Oil Palm Trunk 1.8 Table 4 shows the percentage of ash content in fuel briquette for several researches on biomass briquettes. Based from the table, the least amount of ash obtained from the briquettes from those researchers is higher compared to the palm briquettes that have been studied now. The comparison for the ash content of the sample briquettes produced with the other researchers can be further represented by Figure 5. Figure 5: Comparison of briquette S/N 5 with other journal Referring to Figure 5, it is shown that sample briquette S/N 5 gives a better percentage of ash content compared to other briquettes from other researchers. The difference may be due to the mass and density of the briquettes produced which vary with the other researchers. Sample briquettes that gives the second best percentage of ash content is from the author 4 which studied on the development of fuel briquette form oil palm trunk (OPT). The different if ash content for this author and S/N 5 is 0.69 percent. The difference is smaller compared to the different of percentage of ash content of sample S/N 5 with author 2 which is 12.49 %. The reason for the large gap may be due to the compositional of the raw material used for the briquettes.

4.0 CONCLUSION The experiment carried out, it was generally found out that the characteristics of palm biomass briquettes produced from compaction of EFB and waste paper were satisfactory and compatible with the other researches that involved the palm briquettes. From combustion (heat released) analysis, it can be concluded that S/N 6



gives the best properties in terms of burning time of the briquette and sample S/N 4 is the best ratio as it released the highest value of heat released from the combustion process with a value of 162.77 kJ. As for the ash content, sample S/N 5 was found to be the best ratio as the amount of ash produced at the end of combustion process is the least compared to others with a value of 1.11 percent. In the nutshells it can be summarized that all samples briquettes have their own strength and weakness when they were subjected to different types of testing, but still all the briquettes were compatible with each others and it is suitable to be commercialized as a new solid fuel sources that can be utilized in many application such as camping, barbeque and for residence utilization energy. The blending of EFB fiber with waste paper can improve its physical, mechanical, and combustion properties. REFERENCES [1] Arias, N.C. (2011): Production of Biomass From Short Rotation Coppice for Energy Use: Comparison Between Sweden and Spain, Master thesis at Department of Energy and Technology, Faculty of Natural Resources and Agricultural Science, Swedish University of Agricultural Science. [2] Brown, O.R., Yusof, M.B.B.M., Salim, M.R.B. and Ahmed, K. (2011): Physico-chemical Properties of Palm Oil Fuel Ash As Composite Sorbent in Kaolin Clay Landfill Liner System. Clean Energy and Technology (CET),

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[20] Romeela, M. and Ackmez, M. (2012): Energy from Biomass in Mauritius: Overview of Research and Applications, (Waste to Energy). Springer London Publisher. ISBN: 978-1-4471-2306-4. [21] Sławomir, O. (2012): Analysis of Usability of Potato Pulp as Solid Fuel, Fuel Processing Technology, Vol.94, Iss.1, pp.67-74. [22] Sumiani, Y. (2006): Renewable Energy From Palm Oil – Innovation on Effective Utilization of Waste. Journal of Cleaner Production, Vol.14, Iss.1, pp.87-93. [23] Tangchirapat, W., Saeting, T., Jaturapitakkul, C., Kiattikomol, K. and Siripanichgorn, A. (2007): Use of Waste Ash From Palm Oil Industry In Concrete. Waste Management, vol.27, pp.81–88. [24] Tong, Z. and Feng, T. (2012): A Study On Energy Saving of LEED-NC Green Building Rating System From Point Analysis. Advanced Materials Research, Vols.374-377, pp.122-126. [25] Vaclav, S. (2010): Energy Myths and Realities: Bringing Science to the Energy Policy Debate. Government Institutes Publisher. [26] Yaman, S., Sahan, M.S., Haykiri, M.H., Sesen, K., Ku’’c,u’’kbayrak, S., (2000): Production Of Fuel Briquettes From Olive Refuse And Paper Mill Waste. Journal of Fuel Processing Technology. pp. 23-31. [27] Yuhazri, M.Y., Sihombing, H., Jeefferie, A.R., Ahmad Mujahid, A.Z., Balamurugan, A.G., Norazman, M.N. and Shohaimi, A. (2011): Optimazation of Coconut Fibers Toward Heat Insulator Applications. Global Engineers & Technologists Review, Vol.1, No.1, pp.35-40. [28] Yuhazri, M.Y., Kamarul, A.M., Haeryip Sihombing, Jeefferie, A.R., Haidir, M.M., Toibah, A.R. and Rahimah, A.H. (2010): The Potential of Agriculture Waste Material for Noise Insulator Application Toward Green Design and Material, International Journal of Civil & Environmental Engineering, Vol.10, No.5, pp.16-21. [29] Yuhazri, M.Y., Haeryip Sihombing, Umar, N., Saijod, L. and Phongsakorn, P.T. (2012a): Solid Fuel from Empty Fruit Bunch Fiber and Waste Papers Part 1: Heat Released from Combustion Test, Global Engineers and Technologists Review, Vol.2, No.1, pp.7-13. [30] Yuhazri, M.Y., Haeryip Sihombing, Yahaya, S.H., Said, M.R., Umar, N., Saijod, L. and Phongsakorn, P.T. (2012b): Solid Fuel from Empty Fruit Bunch Fiber and Waste Papers Part 2: Gas Emission from Combustion Test, Global Engineers and Technologists Review, Vol.2, No.2, pp.8-13.

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