Chairman of the Editorial Board: Prof. N. BENHARRATS Editors-In-Chief: H.ADJELOUT M.BENHALILIBA Publishing secretary: N.BOUALLA A.S. BAQUHAIZEL Assistant - Editors : L. BENSAHLA TALET A.BENDRAOUA L.MAAMAR M.ADJDIR M.HADJEL Material Sciences Editors : A. SAYAD F. GRECU K. BENABDELI N. HANIF A. ABABOU S. FLAZI K. AITMOKHTAR A. MKOUASSI Z. SOUIDI A. MOULAY M. SADDIK M. BENYETTOU B. YAO O. IMINE M. KACEM M. SAHEB M. HAMANE B. MANSOUR A. NEMDILI D. HADDOUCHE B. IMINE N. F E R H A T L. MOUNI D. NEDJAR M. MEDDI M. GODRON A. ALI BACHA A. MANSRI A. BENMOUSSAT M. KADRI M. BENHALILIBA B. SAIDANI H. NASRI T. AYADAT R. GHOUL
Centre Régional des Métiers de l’Éducation et de la Formation (CRMEF, Fès) (Maroc). Bucharest University (Roumania). Université Mustapha Stambouli (Mascara-Algérie). Université Chouaib Doukkali (El Jadida-Maroc). Université Hassiba Ben Bouali (Chlef-Algérie). Université des Sciences et de la Technologie d’Oran M-B (Oran-Algérie). Université de la Rochelle (Rochelle -France). Institut National Polytechnique Félix Houphouët-Boigny (INP-HB) (Yamoussoukro-Côte d’Ivoire). Université Mustapha Stambouli (Mascara-Algérie). Station de recherche forestière (INRF) (Ain Skhouna-Saida). Université Chouaib Doukkali (El Jadida-Maroc). Université des Sciences et de la Technologie d’Oran M-B (Oran-Algérie). Université Félix Houphouet Boigny (Côte d’Ivoire). Université des Sciences et de la Technologie d’Oran M-B (Oran-Algérie). Université d’Oran 2 Mohamed Ben Ahmed (Oran-Algérie). Université Larbi Benm’hidi (Oum El Bouaghi-Algérie). Université des Sciences et de la Technologie d’Oran M-B (Oran-Algérie). Université d’Oran 2 Mohamed Ben Ahmed (Oran-Algérie). Université des Sciences et de la Technologie d’Oran M-B (Oran-Algérie). Université Abou Bekr Belkaîd (Tlemcen- Algérie). Université des Sciences et de la Technologie d’Oran M-B (Oran-Algérie). Centre National de Recherches Préhistoriques Anthropologiques et Historiques (CNRPAH, ex CRAPE) (Alger-Algérie). Université Mohand Oulhadj (Bouira-Algérie). Université des Sciences et de la Technologie d’Oran M-B (Oran-Algérie). École Nationale Supérieure d’Hydraulique (Blida-Algérie). Université Montpellier II (France). Université des Sciences et de la Technologie d’Oran M-B (Oran-Algérie). Université Abou-Bekr-Belkaid (Tlemcen-Algérie). Centre Universitaire de Tamenrasset (Algérie). Université (Guelma-Algérie). Université des Sciences et de la Technologie d’Oran M-B (Oran-Algérie). Université Abderahmane Mira (Bejaia-Algérie). Université Chadli Bendjedid (Tarf-Algérie). Université de Prince Mohammad Bin Fahd (Arabie Saoudite). Université des Sciences et de la Technologie d’Oran M-B (Oran-Algérie).
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Contents
Preparation and Characterizationof Dense Membranes Based Zeolitic Imidazolate Framework (ZIF-8) For Separation: Aromatic—Aliphatic Mixture ............................................................................................................. 3 Study of the Floristic Diversity in Bissa Forest, Chlef, Algeria .................... 11 Hysteresis Based On Artificial Intelligence Techniques of Six Sectors DTC with Voltage Zero for Induction Machine ..................................................... 20 Elimination of Heavy Metal by the Adsorption Process on Activated Carbon from Olive Pomace ........................................................................................ 32 Equilibrium and Isotherm Modeling of Toxic dye Adsorption onto Modified Apricot Stone.................................................................................................. 39 Electrical Characterization of A Novel Metal–Semiconductor Au/AlPc-H/pSi/Al Organic Diode ....................................................................................... 50
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Algerian Journal of Research and Technology
[email protected] http://www.univ-usto.dz/AJRT/ ISSN Print:2543-3954 A.J.R.T Volume 02 (N° 01) (2017) 03-10
PREPARATION AND CHARACTERIZATIONOF DENSE MEMBRANES BASED ZEOLITIC IMIDAZOLATE FRAMEWORK (ZIF-8) FOR SEPARATION: AROMATIC— ALIPHATIC MIXTURE A. Hamlila,L Aouintia*, A. Si Ahmedb,A.Tabbicheb, F.Z.. Zradnia a
LSPBE Laboratoire de synthèse organique physico chimie biomoleculaire et environement, USTO –MB, BP. 1505 Bir El Djir, 31000 Oran, Algeria. b
University of Science and Technology Mohamed Boudiaf (USTO-MB), Faculty of Chemisty, BP. 1505Bir El Djir, 31000 Oran, Algeria. *Corresponding author. Tel.: + 00 231 772693484; fax: + 00 213 41425763.
Abstract. Separation of organic–organic liquid mixtures using membranes has been investigated extensively over the past several decades due to its great significance in the chemical 2- industry, with aromatic-alkane and alkane-alkene systems among the most studied. The latter is one of the most difficult to separate using a membrane process, but promising results have already been obtained for the former. However, even for these highly studied systems, pervaporation (PV) has not yet been attempted as an economical and simple alternative to organic-organic separation technologies. These liquid-liquid separations are still carried out by energy-consuming processes, such as rectification,azeotropic distillation or liquid-liquid separation. To overcome this problem, we decided to investigate the potential of mixed matrix membranes based on a low-cost technical polymer. Polyvinyl chloride (PVC)-based mixed matrix membranes wereprepared with zeolitic imidazolate framework (ZIF-8) particles, and the composite membranes were studied for the separation of toluene-heptane mixtures. It was found that the PVC transport properties could be significantly modified both by the amount and by the type of ZIF-8 incorporated. Keywords.Membrane, composite, separation, Polyvinyl chloride,ZIF 8. INTRODUCTION Separation of the aromatic-aliphatic fractions of industrial cuts, such as ethane-ethylene or benzene-cyclohexane, is an important goal in the petrochemical industry. Unfortunately, because the physical properties of the saturated and unsaturated compounds are similar, the conventional industrially used separation methods, i.e., adsorption, distillation, and liquidliquid extraction, are not very efficient and can even be energy demanding because of the formation of azeotropes or the lack of significant volatility differences of the close boiling components (Aouinti et al.,2015a; Kelle et al., 1992). Metal–organic frameworks (MOFs) are a relatively new family of nanoporous materials which are produced from metal ions or clusters linked by organic molecules.(Li et al.,2009; Tianet
3
al.,2011)Many MOF-typematerials with diverse framework architectures and functional properties have been synthesised to date (Sumidaet al.,2011;Betard et al.,2011). Zeolitic imidazolate frameworks (ZIFs) are a sub-family of MOFs that have tuneable pore sizes and chemical functionality, coupled with exceptional chemical stability, and exhibit versatile structures analogous to that of inorganic zeolites (Hayashi et al.,2007).Particularly, several ZIFs have been successfully prepared as membranes and have demonstrated themolecular sieving effect needed for gas separation (Venna et al., 2010;Thomton et al., 2013). For example, ZIF-8 is made from linking of zinc(II) cations and 2-methylimidazole anions, giving a sodalite topology with a pore cavity of 11.6 A° and a theoretical pore aperture of 3.4 A°( Park et al., 2006). Recently, ZIFs gained attention as fillers for mixed matrix membranes because of their molecular sieving effect, facile synthesis and good compatibility with polymers.(Bae et al.,2010) synthesised ZIF-90 particles with sub-micrometer size and incorporated them into several polyimide polymers (Ultem polyetherimide Matrimid, and 6FDA-DAM). In this study, poly (vinyl chloride) (PVC), a low-cost polymer, was used as a highly selective hosting matrix. Improvement of its pervaporation properties was achieved by incorporating aromatic-selective inorganic fillers into the organic network. PVC is a glassy polymer (Tg = 82°C) with low transport properties for hydrocarbons. PVC was primarily chosen because of its medium polarity. The solubility parameter of PVC (PVC) is 19.2 MPa1/2, close to that of aromatics (e.g., Benzene = 18.8 Mpa1/2 and Toluene = 18.2 Mpa1/2) and significantly higher than the solubility parameters of aliphatic compounds, e.g., hexane = 14.9 Mpa1/2and heptane = 15.1 Mpa1/2 (Okamoto et al., 1999). This indicates that PVC will have a high affinity for aromatic structures and a relatively low affinity for nonpolar aliphatic structures (Allan et al., 1979; Neel et al.,1985). The aim of the present work is to develop a novel and high-performance mixed matrix membrane for the separation of organic molecules using PVC and ZIF-8. ZIF-8 particles were chosen for their higher affinity for toluene versus heptane. The structures and morphologies of the nanocomposite membranes were characterized. EXPERIMENTAL Reagents. The PVC, graciously provided by ENIP of Skikda (ALGERIA), has an average molecular mass of approximately 149.1 kg/mol. The IR characteristics of the PVC are in agreement with those previously reported. Synthesis of ZIF-8 The ZIF-8 nanocrystals were synthesised following the rapid room temperature synthesis method reported by (Cravillon et al.,2009). In a typical synthesis, a solution of 3 g (10 mmol) of Zn(NO3)2,6H2O in 100 mL of methanol and another solution of 6.6 g (80 mmol) of 2-methylimidazole in 100 mL of methanol were prepared and then mixed by vigorously stirring for 1 h at room temperature. After 1 h stirring, the resulting ZIF-8 nanocrystals were separated by centrifugation, washed three times with fresh solvent. Preparation of pure and nanocomposite membranes With thicknesses between (80.10-6 and 200.10-6 m) was performed from THF polymer solutions (12 wt%) by dispensing samples into 6x10-2-m-diameter molds at a stirring speed of 280 tr/min. For nanocomposite films, particular attention was given to proper dispersion of the inorganic particles in the polymer matrix in order to ensure good contact with the polymer phase. Hence, 4
a suspension of ZIF-8 in 7 ml of THF were stirred for 24 h and was slowly added to the polymer solution and then stirred for 24 h before casting into the glass molds. The membranes were allowed to dry slowly at room temperature, and composite films up to 40 wt% of ZIF-8 were prepared. The pure PVC films were colorless, whereas the composite films were white. Fourier transform infrared spectroscopy (FTIR) FTIR spectral measurements were performed using a Nicolet spectrophotometer scanning from 400 to 4000 cm−1. X-ray diffraction measurements (XRD) Have been performed using advanced diffractometer (PANalytical, XPERT-PRO) equipped with a CuKα radiation source (X = 0.154 nm). The diffraction data were collected in the range of 2 θ = 3–60°. Scanning electron microscopy (SEM) The membrane surface cross section images were recorded with SEM using a high-resolution Jeol JMS – 7001 F apparatus. Sorption measurements Sorption measurements of the PVC films was performed by immersion in pure liquids (toluene, n-heptane) at room temperature (25 ± 1 °C). The samples, weighing at least 5 x10-4 kg each, were submerged in the liquids until the sorption equilibrium was reached, approximately 24 h. Before each measurement, the samples were rapidly blotted, and theweight increase was recorded using a hermetically sealed flask. The measurements were repeated several times (relative error: ±3%). The degree of swelling (Sw) was calculated foreach sample using the following equation: Sw (%) = 100 x (Ww-Wd)/Wd
(1)
Where Ww and Wd are the weights of the membrane in the wet and dry states, respectively. RESULTS AND DISCUSSION Membrane characterizations Membrane morphology The SEM images of the homogeneous and composite membranes are shown in figure 1(a–c). A major difference in the microstructure. SEM pictures were obtained to determine whether the effect of the filler at the microscopic level could be seen (Fig.1). The PVC view can be considered as a reference for a fully dense cross section of the glassy polymer (Fig. 1a); with a magnification of 2000, the cross section appears neat and homogenous, and only some small defects can be seen. Conversely, all other pictures show heterogeneous surfaces. The micronsized cavities and pores are visible in the SEM images.
5
a
b
c
Fig. 1. SEM images of membrane cross-section a-PVC, b-c PVC membranes loaded with 10.20 wt% of ZIF-8 respectively X-ray diffraction of ZIF-8 and membranes It is well known that a stable dispersion at the nanometer scale level is essential to achieving high-quality coatings nanohybrids X-ray diffraction was used to determine whether ZIF-8 was well represented as individuals in nanohybrids are presented (Feng et al.1997). The diffraction patterns of 1-X-rays, PVC, ZIF-8, and PVC- ZIF-8- nanohybrids are shown in the figure 2. After the incorporation of ZIF-8 into the PVC matrix, the first two characteristic X-ray diffraction peaks of ZIF8 disappeared in the spectrum of the PVC-15% ZIF 8 membrane and the PVC-30% ZIF-8 membrane. Other new peaks with different intensities and reticular distances appeared - The formation of a crystalline phase for PVC-15% ZIF-8 - Good dispersion and good adhesion between ZIF8 nanoparticles and PVC. - Membranes are nanocomposites.
Fig.2. Membranes and ZIF-8 and PVC X-ray. The results of diffractometer XRD, there is provided two structures:
6
+
PVC
ZIF8 Structure of PVC-15% ZIF-8 membrane
PVC-15% ZIF8
ZIF8 Structure of PVC-30% ZIF-8 membrane
PVC-30% ZIF8
+
PVC
Fig.3.Possibilityof different intercalation structures between PVC and ZIF-8. Fourier transform infrared spectroscopy Infrared spectroscopy has been used to complement the structural information, thismethod allows to characterize the presence of chemical functions molecular interaction between PVC and ZIF-8 in the membranes is investigated by FTIR.
Fig.4. FTIR spectra of PVC, ZIF-8,PVC-15% ZIF8.membrane. Comparison of three bands of spectra gives the appearance of a new band at 3354.35. cm−1 is attributed to the formation of hydrogen bonding between the ZIF-8 and the PVC is the N-H bond for nanocomposite membranes. Sorption properties The mass transfer of homogenous polymeric membranes in pervaporation can be described by the well-accepted sorption–diffusion model. For a single component, the permeability P of a dense film can be expressed according to equation (2), where D is the diffusion coefficient of the permeant, and S is the sorption coefficient. P = S x D (2) However, in the pervaporation (PV) process, the permeability is rarely constant and can vary significantly with the concentration or the activity of the species of the partially vaporized 7
species. When a given species has a good affinity for the polymer, the degree of sorption increases exponentially manner with the increase of the species activity and can be modeled by the Flory–Huggins equation (Wijmans et al., 1998). Quantification of the sorption behavior characterizes the amplitude of the interactions between the small molecules and the PV film and makes it possible to predict the selectivity expected with a given binary mixture (Shriver et al., 1994). For mixed-matrix films, such as those prepared with ZIF-8 and PVC, it should be emphasized that the two matrices do not interact with the small molecules in a similar manner, and thus the sorption properties are not governed by the same laws. For the polymer matrix, the absorption interactions occur within the entire mass of the organic matrix. For ZIF-8, the absorption interactions are limited to specific fixed sites on the surface created by the inorganic matrix. One of the simplest models used to describe adsorption is the Langmuir model, which uses a perfectly planar surface and a single molecule adsorption per site (Lombaaardo et al.,1991). The adsorption capacity was also measured for a 1/1 mixture of toluene and n-heptane at 25 °C. The results obtained after a long period remained consistent, as shown in Fig.5; they correspondto an average value of the two pure values, i.e., Sw= 37wt%.
Toluene adsorption Heptane adsorption Toluene mixture 50 wt%
Adsorption( %)
42
35
28 0
50
100 150 Time (hours)
200
250
Fig.5. Adsorption characteristics of ZIF 8 measured in pure toluenevapor, pure n-heptane vapor and a 1/1 mixture of toluene/n-heptane vapor. This result clearly indicates that there is no adsorption competition between toluene and heptane and that the ZIF 8 selectivity remains the same. It was observed that ZIF-8had a strong affinity for toluene and exhibited a clear preferential sorption for toluene (1.2 times higher than that for heptane). The sorption properties of the composite PVC–ZIF 8 membranes were registered with a 50–50 wt% toluene/n-heptane mixture (Fig.6). Compared with the initial PVC swelling degrees,the results show a strong increase in the solvent sorption with the composite membranes, which significantly varies with the ZIF 8 content, as expected. To gain a better insight, the composition of the liquid sorbed at equilibrium was determined for the composite membrane having the higher ZIF 8 content, i.e., 40 wt% of ZIF 8, to obtain a reliable value and to check that the enhanced swelling degree was not just an artefact due to membrane defect (cracks) or to inadequate measurements.
8
Sweeling degree( %)
Série1; 30; 31 Série1; 40; 28 Série1; 20; 22
Série1; 15; 8,28 Série1; 0; 0,17
ZIF8 content(% wt)
Fig.6. Effect of ZIF8 content on the swelling degrees of the mixedmatrix membranes in the toluene/n-heptane mixture (50/50 wt%) at 25°C. Comparison of the degree swelling Sw (%) The comparison of our swelling results with previously reported data in the literature is not a straight forward task [Aouinti et al.,2015a , Aouinti et al.,2009b).A tentative comparison between the swelling results of the nanocomposite membranes prepared in this study and those reported in the literature (Aouinti et al.,2015c) was made and is listed in Table 1 . It can be observed that the PVC-20% ZIF 8 membrane prepared in this research showed good performances compared with the other composite membranes investigated for the removal of aromatic compounds from their mixtures TABLE 1.Comparison ofsorption for 50-50 wt % Feed Mixture. Membrane Material PVC PVC-20% Activated carbon PVC-20% Nanocor PVC-20%Magh H PVC-20% ZIF 8
T (°C) 20
Toluene-n-heptane
Degree swelling Sw (%) 0.2
Aouinti et al.,2015a
20
Toluene –n-heptane
10
Aouinti et al.,2015a
20 20 25
Toluene –n-heptane Toluene –n-heptane Tolu3ene –n-heptane
15 3 22
Aouinti et al.,2009b Aouinti et al.,2015c This study
Separation mixture
Ref
CONCLUSION In this study, several nanocomposite membranes were produced using PVC and ZIF-8 nanoparticles, a filler material with a higher affinity for toluene than for heptane. The sorptionstudies of the membranes revealed that the incorporation of filler significantly increases the extent of swelling of the nanocomposite PVC membranes. Acknowledgments The authors sincerely thank Pr. Hadjel for recording the SEM images. REFERENCES Allan F., Barton M., 1979.Solubility parameters, Chemical Reviews.” .75, pp 731-753. NeelJ., AptelP., ClementR., 1985.Basic aspects of pervaporation”, Desalination, .53, pp297326.
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Aouinti L., Roizard D., Hu G.H., Thomas F., Belbachir M., 2009b.Investigation of pervaporation hybrid polyvinylchloride membranes for the separation of toluene_n-heptane mixtures case of clays as filler, Desalination, 241, 174-18. AouintiL., Roizard D., Belbachir M., 2015a.PVC—Activated Carbon Based Matrices: A Promising Combination for Pervaporation Membranes Useful for Aromatic-Alkane Separations. Sep andPurif. Technol.147, 51-61. Aouinti L., Roizard D.,2015c. Pervaporation of Toluene—n-Heptane Mixtures with Hybrid PVC Membranes Containing Inorganic Particles, Journal of Earth Science and Engineering 5, 473-481. Bae T.H, Lee J.S, Qiu J.S, KorosW.J, Jones C.W., NairS., 2010. A high-performance gasseparation membrane containing submicrometer-sized metalorganic framework crystals.Angew. Chem., Int. Ed., 49, 9863–9866. Betard A., Fischer R.A., 2011. Metal organic framework thin film: from fundamentals to applications. Chem. Rev., 112, 1055–1083. Cravillon J., MunzerS., LohmeierS.J., FeldhoffA.,HuberK., WiebckeM., 2009. Rapid RoomTemperature Synthesis and Characterization of Nanocrystalsof aPrototypical Zeolitic Imidazolate FrameworkChem. Mater., 21, 1410–1412. Feng X., Huang R.Y.M.,1997. Liquid separation by membrane pervaporation: a review, Ind. Eng. Chem. Res.36, pp1048–1066. Hayashi H., Cote A.P., Furukawa H., O’Keeffe M., Yaghi. O. M., 2007. Zeolite A imidazolate framworks. Nat. Mater., 6, 501–506. Kelle G.F.,Marcinkowsky A.E, Verma S.K., Williamson K.D., 1992.Olefin Recovery andPurification via Silver Complexation. In Separation and Purification Technology, edited by Li, N. N., and Calo, J. M., New York: Marcel Dekker,pp 59-83. Li J.R., Kuppler J., Zhou Selective H.C., 2009. Gaz adsorption and separation in metal organic frame work. Chem. Soc. Rev., 2009, 38, 1477–1504. Lombaardo S.J.,BellA.T., 1991. A review of theoretical-models of adsorption, diffusion,desorption, and reaction of gases on metal-surfaces, Surf. Sci. Rep. Vol.1,pp3, 1–72. OkamotoK., Wang H., Fujiwara I.S.,TanakaK.,Kita H., 1999.Pervaporation of aromatic/nonaromatic hydrocarbon mixtures through crosslinked membranes of polyimide with pendant phosphonate ester groups” J. Membr. Sci. 157, 97–105. Park K.S., NiZ., Cote A.,Choi P., Huang R., Uribe-Romo F.J., Chae H.K., O’Keeffe M., Yaghi O., 2006. Exceptional chemical and thermal stability of zeolitic imidazolitic frameworks Sci. U. S. A., 2006, 103, 10186–10191. Sumida K., Rogow D.L., Mason J.A., McDonald T.M., Bloch E.D., Herm Z.R., Bae T.H., Long J.R., 2011. Carbon dioxide capture in metal organic-frameworks. Chem. Rev., 112, 724–781. Shriver D.F., AtkinsP.W., LangfordC.H., 1994.Inorganic Chemistry, Oxford University Press, Oxford, 2nd edition(Chapter 13). TanJ.C., Cheetham A.K., 2011. Mechanical properties of hybrid inorganic-organic framework matérials establishing fundamental structure- property relationships. Chem. Soc. Rev., 40, 1059–1080. Thornton A.W., Furman S.A., Nairn K.M., Hill B.P.,Hill M.R., 2013. Analytical representation of micropores for predicting gaz adsorption in porous materials. Microporous and mesoporous materials. 167, 188–197. VennaS.R, Carreon M.A, 2010. Highly permeable zeolithe imidazolate framework-8 membranes for CO2/CH4 separation J. Am. Chem. Soc. 132, 76–78. Wijmans J.G., BakerR.W., 1998.The solution-diffusion model: a review, J. Membr. Sci. 107, pp 1–21.
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Algerian Journal of Research and Technology
[email protected] http://www.univ-usto.dz/AJRT/ ISSN Print:2543-3954 A.J.R.T Volume 02 (N° 01) (2017) 11-19
STUDY OF THE FLORISTIC DIVERSITY IN BISSA FOREST, CHLEF, ALGERIA F. Senoucia*, A. Ababoub, M. chouiebc, N. Amrousb, N.H. Boukeffoussa Ghoulb Department of Biology, Faculty of Natural and Life Sciences, University of MostaganemAbd El Hamid Ibn Badis, Algeria. b Department of Biology, Faculty of Natural and Life Sciences, University of Chlef-Hassiba Ben Bouali, , Algeria. c Department of Agronomy, Faculty of Natural and Life Sciences University of MostaganemAbd El Hamid Ibn Badis, Algeria. *Corresponding author.
[email protected] a
Abstract.The exceptional biological richness of Mediterranean ecosystems was highlighted by many researchers. As part of the Mediterranean basin, northern Algeria is characterized by a high plant biodiversity, estimated to almost 3139 species. In this context, this study focused on the floristic diversity in the Bissa forest, a cork oak forest in the Northwest of Algeria. Throughout the seven cantons of Bissa forest, 122 plant species belonging to 43 families were identified and listed in a local floristic database. The most dominant families in terms of species percentage were the Asteraceae and Fabaceae. The highest biodiversity was shown respectively by the cantons of Ain Lemcen, Oued Rihane and Tizerouine, while the lowest biodiversity was observed in the cantons of Yahia Bouzekri and Sidi M'hamed Aberkane. Through the phytosociological analysis, three major vegetation units with different numbers of diagnostic species with fidelity thresholds ranging from 0.17 to 1 were distinguished. Furthermore, many differential species with a wide ecological spectrum were observed. Finally five species have been identified as generalists present in all cantons and adapting to all conditions of this forest. Keywords.Biodiversity, Phytosociology, Diversity indices, Phi coefficient, Similarity, Bissa forest. INTRODUCTION In ecology, ecosystems are often described by their floristic composition, which form under suitable environmental conditions the vegetal associations(McIntosh 1985). In this context, the vegetal association is a plant community characterized by definite floristic and sociological features (Braun-Blanquet 1932) and growing under a uniform habitat conditions (Flahault and Schroter, 1910), each plant community is recognized by a certain number of diagnostic species as defined by Westhoff and Van der Maarel (1978). According to Curtis (1959), the term diagnostic species is an important concept in vegetation classification; it is a plant of high fidelity to a particular community, whose presence serves as a criterion of recognition of that community. The relative constancy or abundance of these diagnostic species distinguishes one 11
association from another (Whittaker 1962). By their presence, abundance or potency, these species are considered to indicate certain site conditions (Gabriel and Talbot 1984). Patterns of vegetal association are assessed using floristic readings including a list of plants registered in a relatively uniform habitat (Mueller-Dombois and Ellenberg 1974); the floristic composition characterizing any habitat can be expressed by species richness (Fulbright, 2004), percent cover (Gimenez and Diaz, 2001) and fidelity measurements (Bruelheide 2000; Chytrý etal., 2002). North part of Algeria is characterized by a high plant diversity, estimated to almost 3139 species, among which 700 endemic species (Quezel and Santa 1962; 1963), under a constant anthropic and climatic pressure (Molinier 1971). Unfortunately, apart from the great work of Quezel and Santa (1962, 1963), this floristic richness remains poorly known and requires more consideration. The clear and precise knowledge and description of this natural richness is the key element that allows the preservation of this national wealth. In order to contribute to the description and the preservation of the Algerian flora, the aim of this study is the creation of local floristic database with the complete inventory of the flora, the identification of the floristic pattern in Bissa, one of the healthiest cork oak forests in Northwest Algeria. MATERIAL AND METHODS Study area Covering approximately 23 km2, the Bissa Forest is an ecological sanctuary located in a mountainous region 10 km from the Mediterranean and 45 km northeast of Chlef Wilaya, daira of Zeboudja, this forest belongs to the district of Zeboudja and Beni Haoua and is part of Oued Fodda province, extending between 36°25'30"- 36°28'41" of North latitude and 1°25'34"1°30'00" of East longitude (Fig. 1). The area is characterized by a very rugged relief, steep slopes and an average height of 700 meters the highest point stands over 1100 m. it is a typical Mediterranean area in terms of climate, distinguished by hot, dry summers and relatively rainy winters, with an annual dry period of 5 months and 74% of the annual precipitations are recorded during winter and autumn.
Fig 1. Location of Bissa forest.
Vegetation sampling 12
The floristic surveys were carried out over the spring between 2014 and 2016 all around the 7 cantons of Bissa forest (Hab Melouk, Ain Lemcen, Ain Laaouad, Oued Rihane, Tizerouine, Yahia Bouzekri and Sidi M'hamed Aberkane) and over a minimum area of 10×10m, using thepresence/absence method. Species identification was done based on Quezel and Santa (1962, 1963). Study of Biodiversity Shannon Index (H) To characterize the species diversity at the cantons level the Shannon (Shannon and Weaver, 1948) Index (H) was used. It’s calculated as follows: H = − ∑si=1 pi ln pi (1) Where: pi is the proportion (n/N) of individuals of one particular species found (n) divided by the total number of individuals found (N),ln is the natural log,Σ is the sum of the calculations, s is the number of species. Phytosociology Sokal and Sneath similarity index and UPGMA algorithm In order to classify the floristic surveys we combined the Sokal and Sneath binary index (Sokal and Sneath, 1963) to create a similarity matrix and the unweighted pair-group method with arithmetic mean (UPGMA) as agglomerative method based on the similarity matrix. The Sokal and Sneath index ranges between 0 and 1 and is defined as follows: S = a/(a + 2(b + c) ) (2) Where: a is the number of species common to the two quadrats,b is the number of species unique to the first quadrat, c is the number of species unique to the second quadrat. The coefficient of association To extract the main vegetation’s units from the floristic surveys classification, the ϕ-coefficient of association is a statistical measure of association ranging between 0 and 100%, that can be used as a measure of fidelity; it’s calculated as follows (Bruelheide 2000; Ababou et al., 2009; 2010; 2015): =
N.np −n.Np
(3)
√n.Np .(N−n).(N−Np )
Where: N is the total number of floristic surveys, Np is the number of floristic surveys in a particular group of sites obtained through Sokal and Sneath-UPGMA classification; n is the number of occurrences of the species in the all sites;np is the number of occurrences of the species in a particular group of sites. RESULTS AND DISCUSSION Biodiversity analysis 122 species distributed over 43 families were recorded throughout the 7 cantons of Bissa forest. Among the 43 families, the 8 most commonly represented were the Asteraceae, Fabaceae, Poaceae, Caryophyllaceae, Lamiaceae, Rosaceae, Geraniaceae and Rubiaceae. Indeed 54% of the total numbers of species belong to these families, while just the Asteraceae and Fabaceae alone accounted for 25% of the total number of the 122 species (Fig. 2). According to Shannon diversity index, the highest biodiversities were registered successively in the cantons Ain Lemcen, Oued Rihane and Tizerouine, while the lowest biodiversities were observed respectively in Yehia Bouzekri and Si M'hamed Aberkane cantons (Fig. 3). 13
The highest Eveness (EH) values of almost 1 confirmed that all inventoried species were equally distributed throughout the 7 cantons with no dominant species (Fig. 3). 0.82 0.82 1.64
0.82
2.46 0.82 0.82
0.82 2.46 0.82 0.82
9.02
2.46
0.82 0.82 2.46
1.64 0.82 6.56 15.57 2.46 0.82 0.82 0.82
0.82
3.28
4.92
4.92 4.10
1.64
0.82 1.64
0.82
6.56
3.28 1.64
3.28 0.82 0.82 0.82
0.82 0.82
Fagaceae Adoxaceae Anacardiaceae Apocynaceae Arecaceae Asteraceae Brassicaceae Caryophyllaceae Clusiaceae Crassulaceae Dioscoreaceae Euphorbiaceae Geraniaceae Lamiaceae Linaceae Myrtaceae Orchidaceae Plantaginaceae Primulaceae Rhamnaceae Thymelaeaceae
Smilacaceae Amaranthaceae Apiaceae Araceae Asparagaceae Boraginaceae Caprifoliaceae Cistaceae Convolvulaceae Cupressaceae Ericaceae Fabaceae Iridaceae Liliaceae Malvaceae Oleaceae Pinaceae Poaceae Ranunculaceae Rosaceae Urticaceae
Fig 2. Percentage of families recorded in Bissa forest. 30 25
Hab Melouk Ain Lemcen Tizerouine Yehia Bouzekri
Oued Rihane Aberkane Ain Laaouad
20 15 10 5
0 Shannon
Evenness
Margalef
Fig 3. Biodiversity indices in the different cantons of Bissa. In terms of specific richness (Margalef Index), the cantons of Ain Lemcen and Oued Rihane showed the highest specific richness, while the lowest specific richness was recorded in the cantons of Ain Laaouad, Si M'hamed Aberkane, and Yehia Bouzekri (Fig. 3). T-test revealed that the differences between the floristic diversities of the 7 cantons vary between non-significant to highly significant. The highest differences (P < 0.001, and P < 0.01) were observed between Yehia Bouzekri canton and all the remaining cantons and also between Si M'hamed Aberkane and Hab Melouk, Oued Rihane, Ain Lemcen, Tizerouine and Ain Laaouad cantons. Whereas, the remaining combinations were not significantly different (P> 0.05) such as those observed between Tizerouine canton and Hab Melouk, Oued Rihane, Ain Lemcen and Ain Laaouad cantons (Table 1).
14
TABLE 1. Shannon index and comparison between the biodiversity in the seven cantons of Bissa using the t-test.
Shannon(H) H.Melouk O.Rihane A.Lemcen M.Aberkane Tizerouine A.Laaouad Y.Bouzekri
H.Melouk O.Rihane 3.81 4.09 2.08 * * NS *** *** NS NS NS * *** ***
Test-t A.Lemcen M.Aberkane Tizerouine A.Laaouad 4.16 3.18 3.93 3.66 2.59 3.58 0.87 0.94 0.51 5.46 1.22 3.00 5.90 1.73 3.49 *** 4.38 2.69 NS *** 1.80 *** ** NS *** NS *** **
Y.Bouzekri 3.00 4.36 6.15 6.56 0.87 5.13 3.51
NS (p > 0.05), * (p < 0.05), ** (p < 0.01) and *** (p < 0.001). Phytosociological analysis The analysis of Bissa forest flora showed a high variability throughout the prospected area, some cantons were very rich and highly diversified such as Ain Lemecen and Oued Rihane, whereas other cantons such as Yehia Bouzkri and M’hammed Aberkane were poor with a limited diversity, to explore the constancy of this flora and the vegetation units that is influenced by specific ecological parameters for each canton, the application of the Sokal and Sneath similarity index combined to the UPGMA algorithm resulted in 3 groups of homogeneous cantons in term of flora (Fig. 4). In order to extract the main vegetation units related to the three groups of cantons, the ϕ-coefficient was applied. Following the application of the φ coefficient of fidelity throughout the 3 group of cantons, 3 vegetation units were extracted, each containing a certain number of diagnostic species strictly related to a different set of cantons. Through this coefficient, it was also possible to distinguish the existence of several differential species shared between two vegetation units. Finally, among the 122 species recorded in Bissa forest, 5 species were found to be generalist, distributed all over the study area, characterized by a wide ecological spectrum. Yehia Bouzekri Aberkane Ain Laaouad
Hab Melouk Oued Rihane Tizerouine Ain Lemcen
0.98
0.93
0.88 0.83 Sokal & Sneath Similarity
0.78
0.73
Fig 4. Dendrogram showing the classification of 7 cantons in Bissa forest based on the Sokal and Sneath Index and UPGMA. 15
Diagnostic species The three vegetation units extracted through the φ coefficient of fidelity were as follows: Vegetation unit A: Hypericum perforatum L. This vegetation unit was found to be specific to Ain Laaouad, Yehia Bouzekri, Hab Melouk and M’hammed Aberkane cantons. This unit is composed of 25 diagnostic species with relatively low degrees of fidelity ranging from 0.17 to 0.55, the highest fidelity values in this unit were shown by Hypericum perforatum (0.55) and Cistus ladaniferus (0.47), the list of diagnostic species in this vegetation unit were as follows: Hypericum perforatum (ϕ = 0.55) Filago exigua (ϕ = 0.35) Cistus ladanifeus (ϕ = 0.47) Galactites sp (ϕ = 0.35) Silene conica (ϕ = 0.42) Linum tenue (ϕ = 0.35) Anagallis monelli (ϕ = 0.35) Muscari comosum (ϕ = 0.35) Asparagus stipularis (ϕ = 0.35) Picris cupuligera (ϕ = 0.35) Avena bromoides (ϕ = 0.35) Pinus halepensis (ϕ = 0.35) Bromus madritensis (ϕ = 0.35) Plantago amplexicaulis (ϕ = 0.35) Centaurea pullata (ϕ = 0.35) Sanguisorba officinalis (ϕ = 0.35) Chenopodium murale (ϕ = 0.35) Satureja calamintha (ϕ = 0.35) Cistus salviifolius (ϕ = 0.35) Silene pseudovestita (ϕ = 0.35) Convolvulus althaeoides (ϕ = 0.35) Trifolium angustifolium (ϕ = 0.35) Daphne gnidium (ϕ = 0.35) Biscutella didyma (ϕ = 0.17) Filago minima (ϕ = 0.35) The relative weakness of the coefficient φ for most species of this unit indicates that these species also show some non-significant fidelity to other vegetation units. Vegetation Unit B: Crataegus monogyna Jacq. This vegetation unit was specific to the cantons of Ain Lemcen and Tizerouine. It is the richest of the three vegetation units with 38 diagnostic species, most of them showing a high degree of fidelity ranging from 0.30 to 1.00, the highest fidelity value (φ = 1.00) within this unit was shown by Crataegus monogyna, Cruciata glabra, Mentha Pulegium and Arenaria sepyllifolia meaning that these 4 species were strictly limited to the cantons of Ain Lemcen and Tizerouine, this unit included the following species: Crataegus monogyna (ϕ = 1.00) Leucanthemum paludosum (ϕ = 0.65) Cruciata glabra (ϕ = 1.00) Quercus canariensis (ϕ = 0.65) Mentha pulegium (ϕ = 1.00) Rhamnus alaternus (ϕ = 0.65) Arenaria sepyllifolia (ϕ = 1.00) Senecio vulgaris (ϕ = 0.65) Bellis annua (ϕ = 0.73) Spergularia marginata (ϕ = 0.65) Genista tricuspidata (ϕ = 0.73) Urtica pilulifera (ϕ = 0.65) Leucanthemum vulgare (ϕ = 0.73) Viburnum tinus (ϕ = 0.65) Rosa canina (ϕ = 0.73) Urginea maritima (ϕ = 0.40) Sherardia arvensis (ϕ = 0.73) Asparagus acutifolius (ϕ = 0.30) Tamus communis (ϕ = 0.73) Briza maxima (ϕ = 0.30) Bellis sylvestris (ϕ = 0.65) Crataegus laevigata (ϕ = 0.30) Erodium moschatum (ϕ = 0.65) Pardoglossum cheirifolium (ϕ = 0.30) Euphorbia segetalis (ϕ = 0.65) Hordeum murinum (ϕ = 0.30) Euphorbia cyparissias (ϕ = 0.65) Iris planifolia (ϕ = 0.30) Galactites duriaei (ϕ = 0.65) Nerium oleander (ϕ = 0.30) 16
Galium mollugo (ϕ = 0.65) Reichardia tingitana (ϕ = 0.30) Lavatera arborea (ϕ = 0.65) Rubus fruticosus (ϕ = 0.30) Lavandula dentata (ϕ = 0.65) Valerianella discoidea (ϕ = 0.30) Bellis major (ϕ = 0.65) Mercurialis ambigua (ϕ = 0.30) The high fidelity values (φ> 0.5) showed by the majority of the species indicated that the diagnostic species of this unit were rarely observed outside the cantons of Ain Lemcen and Tizerouine. Vegetation unit C : Myrtus communis L. This vegetation unit was composed of 30 diagnostic species, it showed also the largest number of most faithful diagnostic species, indeed among the 30 diagnostic species, 13 species showed a maximal φ coefficient (φ = 1.00) indicating that these species were strictly limited to this vegetation unit and therefore strictly related to the canton of Oued Rihane, whereas the low φ values (0.26 and 0.47) of the remaining species indicated that these species were non significantly shared by other vegetation units. The list of diagnostic species of this unit with their fidelity values was as follows: Myrtus communis (ϕ = 1.00) Astragalus lusitanicus (ϕ = 0.47) Anemone palmata (ϕ = 1.00) Phillyrea angustifolia (ϕ = 0.47) Anthemis maritima (ϕ = 1.00) Arisarum vulgare (ϕ = 0.47) Chamaerops humilis (ϕ = 1.00) Lonicera implexa (ϕ = 0.47) Euphorbia peplus (ϕ = 1.00) Lotus edulis (ϕ = 0.47) Herniaria hirsuta (ϕ = 1.00) Phagnalon saxatile (ϕ = 0.47) Lamium amplexicaule (ϕ = 1.00) Poa bulbosa (ϕ = 0.47) Linum strictum (ϕ = 1.00) Rubia tinctorum (ϕ = 0.47) Medicago rigidula (ϕ = 1.00) Rubus ulmifolius (ϕ = 0.47) Ornithogalum algeriense (ϕ = 1.00) Calicotome intermedia (ϕ = 0.35) Ruscus aculeatus (ϕ = 1.00) Daucus carota (ϕ = 0.35) Sedum acre (ϕ = 1.00) Lavandula stoechas (ϕ = 0.35) Stellaria media (ϕ = 1.00) Pistacia lentiscus (ϕ = 0.35) Trifolium campestre (ϕ = 0.65) Asphodelus microcarpus (ϕ = 0.26) Anacyclus radiatus (ϕ = 0.47) Olea europaea (ϕ = 0.26) Differential and generalist Species Among the remaining species, 24 species were identified as differentials (shared by two vegetation units) and 5 generalist species (distributed all around Bissa forest) (Table 2). Finally, among very few studies carried out in Chlef region, our study is similar to that carried out in the Beni-Haoua forest (Ababou et al., 2015), which improved understanding species distributions and occurrence in a southern Mediterranean forest. TABLE 2. Synoptic table of differential and generalist species in Bissa forest. Vegetation Unit Differential Species Cistus salviifolius Clematis cirrhosa Eryngium tricuspidatum
Unit A
Unit B φ Coefficient 0.42 0.30 0.30
17
Unit C 0.35 0.65 0.65
Eryngium campestre Galactites tomentosa Ophrys tenthredinifera Rubia peregrina Crepis vesicaria Geranium purpureum Geranium rotundifolium Hypochaeris laevigata Juniperus oxycedrus Plantago lagopus Ranunculus paludosus Smilax aspera Ampelodesmos mauritanicus Anagallis arvensis Bromus rubens Erodium moschatum Geranium malviflorum Phillyrea latifolia Cytisus villosus Nepeta multibracteata Schismus barbatus Arbutus unedo Cistus monspeliensis Erica arborea Quercus ilex Quercus suber
Generalist species -
0.30 0.30 0.30 0.30 0.73 0.73 0.73 0.55 0.55 0.55 0.55 0.55 0.40 0.40 0.40 0.40 0.40 0.40 0.26 0.26 0.26
0.65 0.65 0.65 0.65 0.47 0.47 0.47 0.35 0.35 0.35 0.35 0.35 0.26 0.26 0.26 0.26 0.26 0.26 0.17 0.17 0.17
-
-
CONCLUSION Through the seven cantons of Bissa, 122 species belonging to 43 families were listed in our floristic database. The Asteraceae and Fabaceae were the most important families in terms of species percentage. The highest biodiversity was shown by Ain Lemcen, Oued Rihane and Tizerouine cantons, while the lowest biodiversities were observed in the cantons Yahia Bouzekri and Sidi M'hamed Aberkane. The phytosociological analysis distinguished 3 major vegetation units with different numbers of diagnostic species according to the φ coefficient ranging from 0.17 to 1. Furthermore, many differential species with a lager ecological spectrum were observed. Finally five species have been identified as generalists present in all cantons and adapting to all conditions of Bissa forest. References Ababou A., Chouieb M., Khader M., Mederbal K., Saïdi D., Bentayeb Z., 2009. Multivariate analysis of vegetation in the salted lower-Cheliff plain, Algeria. B. Soc. Bot. Mex. 85: 59-69. Braun-Blanquet J., 1932. Plant sociology; the study of plant communities. Ed. McGraw-Hill, 476 p. 18
Ababou A., Chouieb M., Khader M., Mederbal K., Saïdi D., 2010. Using vegetation units as salinity predictors in the lower-Cheliff, Algeria. Turk. J. Bot. 34: 1-10. Ababou A., Chouieb M., Bouthiba A., Said, D., Mederbal, K., 2015. Floristic Diversity Patterns in the Beni-Haoua Forest (Chlef, Algeria) ecologia mediterranea – Vol. 41 (2) – 2015. Bruelheide H., 2000. A new measure of fidelity and its application to defining species groups. Journal of Vegetation Science, 11: 167-178. Chytry M., Tichy L., Holt J, Botta-Dukat Z., 2002. Determination of diagnostic species with statistical fi delity measures. Journal of Vegetation Science 13:79-90. Curtis J.T., 1959. The vegetation of Wisconsin. An ordination of plant communities. University of Wisconsin Press, Madison, Wisconsin. Fernandez-Gimenez M, Allen-Diaz B., 2001.Vegetation change along gradients from water sources in three grazed Mongolian ecosystems. Plant Ecology, 157:101-118. Flahault C., Schroter C., 1910. Report on the phytogeographic nomenclature. Proceedings of the 3rd International Botanical Congress, Brussels 1:131-164. Fulbright T.E., 2004. Disturbance effects on species richness of herbaceous plants in a semiarid habitat. Journal of Arid Environments 58: 119-133. Gabriel H.W., Talbot S.S., 1984. Glossary of landscape and vegetation ecology for Alaska. Alaska Technical Report 10. Bureau of Land Management, Washington, D.C. McIntosh R. P., 1985.The background of ecology, concept and theory. Cambridge, Cambridge University Press, 400 p. Molinier R., Vignes P., 1971. Ecology and biocenosis - living beings their environment their community environment.Ed. Delachaux and Niestle. Paris, France. Mueller-Dombois D., Ellenberg H., 1974. Aims and methods of vegetation ecology. New York: John Wiley. Quezel P., Santa S., 1962. New flora of Algeria and southern desert regions. Volume 1. ed. CNRS, Paris. Quezel P., Santa S., 1963. New flora of Algeria and southern desert regions. Volume 2. ed. CNRS, Paris. Shannon C. E., 1948. A Mathematical Theory of Communication. The Bell System Technical Journal 27: 379–423, 623–656. Sokal R.R., Sneath P.H.A., 1963. Principles of Numerical Taxonomy, Freeman, San Francisco, 359 p. Westhoff V., van der Maarel E., 1973. The Braun-Blanquet approach. In: Whittaker, R.H. (ed.) Handbook of vegetation science, part 5, Classification and ordination of communities, pp. 617726. Junk, The Hague. Whittaker R.H., 1962. Classification of natural communities. The Botanical Review 28:1-239.
19
Algerian Journal of Research and Technology
[email protected] http://www.univ-usto.dz/AJRT/ ISSN Print:2543-3954 A.J.R.T Volume 02 (N° 01) (2017) 20-31
HYSTERESIS BASED ON ARTIFICIAL INTELLIGENCE TECHNIQUES OF SIX SECTORS DTC WITH VOLTAGE ZERO FOR INDUCTION MACHINE Habib BENBOUHENNI Département de Génie Électrique, Ecole Nationale Polytechnique d’Oran Maurice Audin (ENPO-MA), BP : 1523 El M’nouer, Oran, Algeria. *Corresponding author. Tel.: + 213 663956329.
[email protected]. Abstract. In this paper, a novel structure of DTC with voltage zero based on intelligent hysteresis is proposed. This intelligent hysteresis is likely to be used for reduced of torque, flux ripples, and THD (Total Harmonic Distortion) of stator current. The proposed structure is analyzed and then compared with DTC conventional of the induction machine. Comparison depicts the proposed DTC control superiority over the conventional DTC control. In this proposed structure, the classical hysteresis of torque replace by the fuzzy controller, and hysteresis of flux replace by a neural controller. The control scheme is implemented using Matlab/Simulink. The simulation results are in good agreement which shows the effectiveness of the proposed DTC control. Keywords. DTC, Induction machine, Fuzzy controller, Neural controller, Classical hysteresis, Voltage zero, Intelligent hysteresis. INTRODUCTION Among all types of AC machine, the induction machine (IM) is most commonly used in industry. These machines are very economical, rugged and reliable and are available in the ranges of fractional horse power (FHP) to multi megawatt capacity (More et al., 2015). In normal reference frames, the torque and flux of an IM drive are coupled together and hence independent control becomes difficult (Surekha et al., 2015). The introduction of field oriented control (FOC) in the 1970s made a huge turn in the control of induction motor drive. FOC uses frame transformation to decouple the torque and flux components of the stator current (More et al., 2015). Therefore the performance of IM becomes similar to that of the dc motor. The implementation of this system, however, is complicated and is well known to be highly sensitive to parameter variations due to the feed forward structure of its control system (Allirani et al., 2012). A new control method called direct torque control (DTC) has been created. DTC is characterized by his simple implementation and robustness (Mouna et al., 2016). Figure1 shows a DTC of the induction machine. In DTC controlled IM drives, it is possible to control directly the stator flux linkage and the electromagnetic torque by the selection of an optimum inverter switching state. The selection of the switching state serves two functions: the flux and the torque 20
errors within their respective hysteresis bands and to obtain the fastest torque response and highest efficiency at every instant (Mahfouz, 2012). The disadvantages of conventional DTC include notable torque, flux and current pulsations and non-constant switching frequency operation. The advantages allotted to traditional techniques DTC (dynamic, robustness, facilitated implementation ….) nevertheless are counterbalanced by the use of a sampled hysteresis comparator; by principle, the comparator led functioning at variable frequency which increases the risks of mechanical excitation or acoustic resonances, and in addition, sampling at finished frequency results by an exceeding pseudo-random of the hysteresis band. These two factors contribute to making the contents harmonic of the various output signals not easily foreseeable (Boudana et al., 2012). This paper proposes new intelligent hysteresis controllers into DTC strategy of IM drive. Intelligent hysteresis improves the overall performance of DTC controlled system. The paper proposes a new hysteresis controllers based on fuzzy logic and neural networks. The fuzzy controller for flux hysteresis comparator and neural controller for torque hysteresis comparator. The proposed strategy is characterized by low inverter switching losses, leading to reduced torque ripples.
Fig. 1. Direct torque control scheme. INDUCTION MACHINE MODEL The model of IM in α, β reference can be written in the following from (Sebti, 2013; Mokhtari, 2016): x = A.X + B.U
(1)
Such as:
s ; U s s
i s
i X
Vs
Vs
21
(2)
r s 0
A
wr
w
R
1 1 wr . Ls .Ls.Tr .Ls wr 1 ; B 0 .Ls .Ls.Tr 1
0
0
0
Rs
0
0
0
0 1 . L s 0 1
(3)
With:
Tr
Lr ; Rr
1
M
2
Ls . Lr
; [
1
.T r
1 ]; T s .Ts
Ls Rs
In addition, the electromagnetic torque can be ex-pressed by: 3 Te p (s.is s.is ) 2 The mechanical equation of the motor can be expressed as:
(4)
.
J Te Tr fr.r
(5)
MODELING OF VSI Two level three phase inverter is used in this paper. Input of VSI is VDC and output of DTC stator voltage vector. Outputs are 𝑉 , 𝑉𝑏 , 𝑉𝑐 can be written as (Surekha et al., 2015; Boudjedaimi et al., 2008) :
Va
b c
V
V
1 1 2 SA Vdc SB 1 2 1 3 SC 1 1 2
(6)
CLASSICAL DTC WITH VOLTAGE ZERO In 1986 Takahashi and Noguchi proposed the basic concept of the DTC method (Surekha et al., 2015). DTC is a technique used in variable frequency drive for controlling the torque and finally the speed of three phase AC motor drive. It includes calculation of an estimate of the motor's magnetic flux and torque based on the measured voltage and current of the motor (Meha et al., 2014). The flux and torque are controlled by two comparators with hysteresis. The dynamics torque are generally faster than the flux then using a comparator hysteresis of several levels, is then justified to adjust the torque and minimize the switching frequency average (Mokhtari et al., 2016). From the measured Voltages and currents of Induction motor, it is easy to estimate the torque, flux and angle (Surekha et al., 2015; Nasir Uddin et al., 2012).
22
t (v s R s i s )dt s 0 t s (v s R s i s )dt 0 2 2 s s s
s arctg( Te
s ) s
3 ps i s s is 2
(7)
(8) (9)
(10)
A two levels classical voltage inverter can achieve seven separate positions in the phase corresponding to the eight sequences of the voltage inverter (Fig. 2) (Mokhtari et al., 2016).
Fig. 2. Different vectors of stator voltages provided by a two levels inverter, (100): (1: inverter switch is ON, 0: for OFF) I(D) F: increase (decrease) of flux magnitude, I(D) T: increase (decrease) of torque. Table 1 presents the conventional switching table CST and shows the sequences for each position.
TABLE 1. Switching table for classical DTC. N Cflx Ccpl 1 1 0 -1 0 1 0 -1
1
2
3
4
5
6
2 7 6 3 0 5
3 0 1 4 7 6
4 7 2 5 0 1
5 0 3 6 7 2
6 7 4 1 0 3
1 0 5 2 7 4
Figures 3 and 4 illustrate the torque and flux comparators, respectively.
23
Fig. 3. Torque hysteresis comparator.
Fig. 4. Flux hysteresis comparator. INTELLIGENT DTC WITH VOLTAGE ZERO Fuzzy set theory and fuzzy logic establish the rules of a nonlinear mapping. The use of fuzzy sets provides a basis for systematic ways for the application of uncertain and indefinite models. Fuzzy control is based on a logical system called fuzzy logic which is much closer in spirit to human thinking and natural language than classical logical systems (Mothur et al., 2007). Neural network (NN) is an interconnected group of artificial neurons that uses a mathematical model or computational model for information processing based on a connectionist approach to computation. In most cases, an ANN is an adaptive system that changes its structure based on external or internal information that flows through the network. Feed forward neural networks are capable of handling nonlinear functions and adapt themselves to variation of parameters due to external disturbances (Sudheer et al., 2016). The application of Fuzzy logic and artificial neural network attracts the attention of many scientists from all over the world (Boudana et al., 2012). The reason for this trend is the many advantages which the architectures of ANN have over traditional algorithmic methods. Among the advantages of ANN are the ease of training and generalization, simple architecture, the possibility of approximating non-linear functions, insensitivity to the distortion of the network, and inexact input data (Abbou et al., 2009). In this article, a neural controller is used to replace hysteresis controller of stator flux, and the fuzzy controller is used to replacing hysteresis controller of torque. In order to generate this intelligent hysteresis controller by Matlab/Simulink. The structure of the DTC control of induction machine using intelligent hysteresis controllers is illustrated below in figure 5.
24
Fig. 5. DTC control of IM using intelligent hysteresis controllers. Neural controller Also, in this section, we thought of replacing the hysteresis controller conventional of flux by a neural controller, with the objective of reduced the torque and flux ripples. We selected three linear feed-forward layers with one neuron in the input plus four neurons at the hidden layer, and one neuron in the output layer, with the activation tasks respectively of type “tansig” and “purelin”. The structure of the neural controller of stator flux is illustrated below in figure 6.
Input
Process Input 1
Layer 1
a{1}
Layer 2
a{1}
Process Output 1 Output
Fig. 6. Structure of neural controller.
p{1}
0
W
Delays 1
IW{1,1}
+
b
netsum
b{1}
Fig. 7. Layer 1.
25
tansig
a{1}
0
W
Delays 1
LW{2,1}
+
b
netsum
a{1}
purelin
a{2}
b{2}
Fig. 8. Layer 2. Fuzzy hysteresis controller In this paper, a Mamdani-type FLC is developed to adapt the torque hysteresis band in order to reduce the ripples in the machine-developed torque. In conventional DTC technique, the amplitude of the torque hysteresis band is fixed. However, in this proposed scheme, the FLC controls the upper and lower limits of the torque hysteresis band on the basis of its feedback inputs. The fuzzy systems are universal function approximators. The FLC is used as a nonlinear function approximator producing a suitable change in the bandwidth of the torque hysteresis controller in order to keep the torque ripples minimum (Idir et al., 2013). The block diagram for fuzzy logic based torque hysteresis controller is shown in figure 9. Te ref
Fuzzy Controller
+
-
Output
de/dt
Te* Fig. 9. Fuzzy logic control of torque hysteresis controller. The fuzzy controller design is based on intuition and simulation. For different values of machine speed and current, the values reducing torque and flux ripple were found. These values composed a training set which is used to extract the table rule U (e, ∆e) (Idir et al., 2013). The rules sets are shown in Table 2 (Abdelhafidh, 2014). TABLE 2. Fuzzy rules of torque hysteresis controller. e ∆e NL NM NP EZ PS PM PL
NL
NM
NP
EZ
PS
PM
PL
NL NL NL NL NM NP EZ
NL NL NL NM NP EZ PS
NL NL NM NP EZ PS PM
NL NM NP EZ PS PM PL
NM NP EZ PS PM PL PL
NP EZ PS PM PL PL PL
EZ PS PM PL PL PL PL
Figures 10 and 11 shows the membership functions of input and output variables respectively.
26
a) Error
b) Change in error Fig. 10. Input variables membership functions.
Fig. 11. Output variable membership function. SIMULATION RESULT The simulations of the DTC induction machine drive were carried out using the Matlab/Simulink simulation package. A 3-phase, 3 pole, induction motor with parameters of Rs=0.228Ω; Rr=0.332Ω; Ls=0.0084H; Lr=0.0082H; Lm=0.0078H; J=20 Kg.m2 are considered. The simulation results of intelligent DTC of IM are compared with classical DTC. For this end, the controls system was tested under deferent operating conditions such as sudden change of load torque.
27
Fig. 12. Performances of classical DTC for IM.
28
Fig. 13. Performances of classical DTC with intelligent hysteresis controllers. Figure 14 shows that the DTC with intelligent hysteresis controllers significantly reduces the ripple of the electromagnetic torque and stator flux compared to that of the classical DTC.
29
The dynamics of the components of the stator flux are not affected by the application of these load guidelines.
a) Classical DTC
b) Classical DTC with intelligent hysteresis controllers. Fig. 14. Zoom in the flux and torque.
CONCLUSION In this paper, the direct torque control of IM using intelligent hysteresis controllers is presented. This controller determinates the desired amplitude of torque hysteresis and flux hysteresis band. The intelligent DTC schemes improve considerably the drive performance in terms of reduced torque and flux pulsations. Therefore, intelligent DTC is an excellent solution for general purpose IM drives. REFERENCES Abdelhafidh M., 2014. Stratégies de commande DTC-SVM et DPC appliquées à une MADA utilisée pour la production d’énergie éolienne.
30
Abbou A., Mahmoudi H., 2009. Performance of a sensorless speed control for induction motor using DTFC strategy and intelligent techniques, Journal of Electrical Systems. 3-5, 64-81. Allirani S., Jagannathan V., 2012. Torque ripples minimization in DTC based induction motor drive using fuzzy logic technique, International Journal of Computer Applications. 40. Boudana D., Nezli L., Telmcani A., Mahmoudi M. O., Tadjine M., 2012. Robust DTC based on adaptive fuzzy control of double star synchronous machine drive with fixed switching frequency, Journal of Electrical Engineering. 63, 133-143. Boudjedaimi M., Wira P., Ouled Abdeslam D., Djennoune S., Urban, J. P., 2008. Commande d’un onduleur avec des approches neuromimétiques pour la compensation des courants harmoniques dans les réseaux électriques, International Conference on Electrical Engineering and its Applications. Idir A., Kidouche M., 2013. Direct torque control of three phase induction motor drive using fuzzy logic controllers for low torque ripple, Proceedings Engineering & Technology. 2, 7883. Mahfouz A. A., 2012. Itelligent DTC for PMSM drive using ANFIS technique, International Journal of Engineering Science and Technology. 4. Meha J., Sharma P., Dubey C., 2014. Comparative analysis of direct torque control and flux control of induction motor using P and PI controller, International Journal of Energing Technology and Advanced Engineering. 4. Mokhtari B., Benkhoris M. F., 2016. High ripples reduction in DTC of induction motor by using a new reduced switching table, Journal of Electrical Engineering. 67, 206-211. More S., Kulkarni A., 2015. Direct torque control of induction motor using fuzzy logic controller, Journal of Electrical and Electronics Engineering. 10, 53-61. Mothur H. D., Manjunath H. V., 2007. Study of dynamic performance of thermal units with asynchronous tielines using fuzzy based controller, Journal of Electrical Systems. 3, 124-130. Mouna E., Hamid C., El Afia A., 2016. An experimental comparison between conventional and new direct torque control stratégies of induction machine using DSPACE TMS 320F2812, Communications on Applied Electronics. 4. Nasir Uddin M., Hafeez M., 2012. FLC-Based DTC scheme to improve the dynamic performance of an IM drive, IEEE Transactions on Industry Applications. 48, 823-831. Sebti B., 2013. Commande par DTC d’un moteur asynchrone apport des réseaux de neurones. Sudheer H., Kadad SF., Sarvesh B., 2016. Improved fuzzy logic based DTC of induction machine for wide range of speed control using AI based controllers, Journal of Electrical Systems. 12, 301-314. Surekha V. M., Chandra Sekhar J. N., 2015. FLC-Based DTC schema for a new approach of Two-leg VSI fed induction motor, Journal of Engineering Research and Applications. 5, 7278.
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Algerian Journal of Research and Technology
[email protected] http://www.univ-usto.dz/AJRT/ ISSN Print:2543-3954 A.J.R.T Volume 02 (N° 01) (2017) 32-38
Elimination of Heavy Metal by the Adsorption Process on Activated Carbon from Olive Pomace A. Nait Merzoug1,2*, M.I. Bellazi1, O. Guellati2,3 (a) Laboratoire des Science et Techniques de l’eau et d’environnement, Université Mohamed Cherif Messadia de Souk Ahras, BP1553, 41000-Souk-Ahras, ALGERIA. (b) Université Mohamed Cherif Messadia de Souk Ahras, Fac. Sci, BP. 1553, 41000-SoukAhras, ALGERIA. (c) Laboratoire d’Etude et de Recherche des Etats Condensés (LEREC), Dép. de Physique, Université Badji-Mokhtar de Annaba, BP. 12, 23000 Annaba, ALGERIA. *Corresponding author. Tel.: + 05 55 14
[email protected]. Abstract.Waste water pollution by heavy metals remains one of the major problems to be solved throughout the world. Various conventional methods are used to remove heavy metals from existing wastewater. They are based on phenomena of chemical precipitation, ion exchange or adsorption, which is always the simplest and most effective technique. Our work has a dual environmental aspect; On the first hand a valorization of a natural byproduct in this case the olive-pomace collected in the region of Souk Ahras (East Algeria) and on the other hand the study of the adsorption of lead on this biomaterial. The activated carbon obtained after calcination and chemical activation has undergone a whole range of physicochemical analyzes such as: pH, moisture content, elementary analysis, surface area and infrared spectrometry. Indeed, the efficiency of our adsorbent is evaluated through the study of the various parameters that affects the adsorption phenomenon, namely: contact time, mass of the adsorbate, temperature, pH and initial concentration metal. The results obtained have shown a good efficiency of our support for the adsorption of metal ions in aqueous solution. Keywords. Adsorption; Olive pomace; Activated carbon, Biosorption, Heavy metal, Characterization. INTRODUCTION The pollution by heavy metals has received wide spread attention in the recent years (Li 2010, Salem 2014), due to the toxicological importance in the ecosystem (Wang 2011, Prado 2010). These heavy metals are not biodegradable and their presence in streams and lakes leads to bioaccumulation in living organism causing health problems in animals, plants and human being (Reddy 2010). Lead is one of the most harmful heavy metals which is present in water and in air. In water, lead is released in effluents from lead treatment and recovery industries, especially from battery manufacturing (Martin-Lara 2011, Drogana-Linda 2011). For drinking water, the maximum permissible limit of lead is 0.1 mg/l (Raji 1997, Tuabamme 2010), where the maximum concentration allowed for discharge into inland water is less than 1 mg/l. 32
Several methods such solvent extraction, ion exchange, precipitation and adsorption have been reported for the treatment of waste water contaminated with heavy metals (Gupta 2004, Ahmad 2006). Among these several physical and chemical methods, the adsorption onto activated carbon has been found to be superior to the other techniques because of its capability for adsorbing a broad range of different types of adsorbates efficiently and also its simplicity of design (Charbraborty 2005). However the commercial activated carbon is very expensive, so several works have been carried out to develop alternative non-conventional and low-cost adsorbents. In fact the olive-growing industry generates significant amounts of products which have been misused until today and represent a real source of pollution. These products offer activated carbon recycling opportunities. As a result, we have been interested in the valorization of olive pomace for activated carbon which can used as an adsorbent material. This which will allow us to achieve three objectives respectively the reduction of pollution, valorization and waste water treatment. MATERIALS AND METHODS Activated carbon preparation The olive pomaces used in this study was taken from olive stones at the region of Souk Ahras during the 2014-2015 year. The sample taken consists of pulp and core fragments. The samples were firstly washed with de-ionized water, dried and then ground into fine particles and sieved to a particle size of 160 µm. Secondly 300 g of samples was impregnated with concentrated potassium hydroxide (KOH) at the ratio 1:1 (wt%). After cooling to the ambient temperature the sample was washed with de-ionized water until pH 6-7, filtered with Whatman filter paper and dried in the oven at 105 °C for 6 hours. The samples were then carbonized in a muffle furnace at 600 °C for 2 hours and stored in tight bottle ready for use. Characterization of activated carbon The physiochemical parameters such us pH, moisture ash content and bulk density were made after the elaboration of the activated carbon. The first analysis was the elementary analysis to determine the composition of our activated carbon. The morphological analysis was characterized using FESEM (JEOL 6700-FEG microscope) in order to control the quality, structure and overall morphology of the adsorbent support. Fourier-Transform Infrared (FTIR) spectra of our activated carbon was recorded using a Bruker Vertex 77v spectrometer in the 400 to 4000 cm-1 range with 4 cm-1 resolution and with Opus software analysis system. Adsorbate preparation and adsorption study The reagents used were lead nitrate salt (Pb (NO3)2) and de-ionized water in order to prepare a stock solution of 1000 g/l. The reagents where of high grade. A Known weight of our activated carbon was added to 100 ml of adsorbate in flask and stirred at 500 rpm in a controlled temperature shaker at 298 °K. At predetermined time intervals, the samples were removed from the solution by filtration. The effect of pH on the lead ions adsorption onto the adsorbent was studied over a pH range of 2.0 to 12.0. The pH was adjusted by adding aqueous solutions of 0.1M HCl or 0.1M NaOH. The residual Pb2+ concentrations were determinate spectrophotomically using atomic absorption at 210 nm. The adsorption rate was calculated by the following equation: (𝐶 𝑉 − 𝐶 𝑉 ).100 𝑅 (%) = 0 0 𝐶 𝑉𝑒 𝑒 (1) 0 0
Where C0 and Ce are the initial and the equilibrium concentrations of sorbent and V is the solution volume. RESULTS AND DISCUSSIONS 33
Characteristics of activated carbon derived from olive pomace The physico-chemical characteristics of activated carbon are shown in table 1. TABLE 1. The physico-chemical characteristics of activated carbon derived from olive pomace. Activated carbon proprieties
pH
Moisture content (%) 10.4
6.02
Values
Ash content (%) 2.17
Bulk density ( g/cm3) 0.59
According to the obtained results we noted that the ash content is very low, which is an interesting characteristic for its use for the preparation of an activated carbon. The composition of the main elements of the activated carbon from the olive pomaces is shown in the Table 2. As shown, we can see that our adsorbent contains two major elements, namely carbon with 62.76 % and oxygen with 33.25 %, followed by aluminum and then silica. TABLE 2. Chemical composition of activated carbon. Element Percentage (%)
C 62.766
O 33.251
Al 2.516
Si 0.584
P /
Cl 0.274
Ca 0.207
Bi 0.403
The representative high magnification FESEM micrograph (Fig. 1) of the obtained activated carbon shows a homogeneous phase with cavities. These are the result from the treatment of the olive pomaces. We also noted the presence of macro and micro pores.
Fig. 1. High magnification FESEM micrograph of activated carbon. FTIR spectrum for the activated carbon from olive pomaces is shown in figure 2. It can be seen that there is a strong peak at 3400 cm-1 represents the O-H stretching, and a peak at 3031cm-1 and another at 2930 cm-1 which corresponding to =C-H stretching of aldehyde group and C-C stretching of aliphatic (CH2 and CH3). The peaks at 1700 cm-1, 1630 cm-1 and 15450 cm-1 were attributed respectively to the carbonyl (C=O) stretching of aldehyde group , C=C for alkene group and C=C for aromatic one. The peak at 1000 cm-1 can be assigned to the C-O stretching.
34
Also the peaks between 900 and 600 cm-1 can be related to the deformation δ C-H of aromatic groups.
Fig. 2. IR spectrum of activated carbon from Olive pomace. Influence of operation conditions in the adsorption process Effect of contact time on adsorption equilibrium The effect of contact time on lead ions sorption by activated carbon from olive pomaces is shown in figure 3. The results showed that a contact time of 200 mn assured attainment of equilibrium.
Fig. 3. Effect of contact time on the removal of ions lead on activated carbon. Metal uptake, us function of contact time, was noticed to occur in two phases. The first one was extremely rapid and this is probably due to the ions diffusion into the available sites of adsorption. However, the second phase was slow and the metal remove over a longer period until equilibrium was reached. Effect of initial pH Solution pH is a significant control parameter affecting the sorption processes; Batch experiments were conducted at different initial pH values ranging from 2 to 12. The results obtained are shown in figure 4. 35
Fig. 4. Effect of pH on the removal of lead ions. The results indicate a relatively little sorption at initial pH of 2 with only 21.5 % of lead ions removed. However, the increase of pH from 2 to 6 increases the percentage removal from 21.5 to 92.9 %. The fact that the amount of Pb2+ removal at low pH is considerably lower may be accounted by the competition between lead ions and H+ ions onto the active sites on sorbent surface. Also, the amount decreases when the pH >6 due to the formation of soluble hydroxyls complexes. Our results are in agreement with similar studies (Goyal 2008, Iqbal 2009, Panda 2008). Many studies have shown also, that the pH of aqueous solutions affects both of the solubility of metal ions and the fictional groups of adsorbent. As a result, the affinity of the adsorbent varies considerably for the metal ions. Effect of initial concentration of metal Dependency of the process of lead ions removal from different concentrations (0.5-2.5 10-4 M) by the activated carbon is illustrated in figure 5. The examination of the data reveals that the adsorption capacity increases as the value of the initial concentration increases to a maximum adsorption rate (92.1 %). An increase in the concentration leads to an increase in the ionic strength which leads to a reduction in the adsorption capacity of the activated carbon and this may entail a shielding of the negative charge of the adsorbent and consequently repulsion is produced between the adsorbent surface and these metallic cations.
36
Fig. 5. Effect of initial dye concentration on the removal of lead ions. Effect of adsorbent dose The effect of sorbent dose on the lead ions sorption kinetics by the activated carbon is illustrated in figure 6. As we can see, the percentage of removal increases with an increase in sorbent dose from 45.9 to 93.4 %. This can be attributed to increased surface area and the availability of more sorption sites.
Fig. 6. Effect of adsorbent amount on the removal of lead ions. CONCLUSION All the conclusion that can be drawn are: - The activation of olive pomace was successful and has favored the adsorption process of metallic ions; - The presence of functionalizes groups improve the efficiency of metal ions removal; - The output of metal removal by adsorption on our activated carbon is important; - The adsorption processes of ions metal is clearly influenced by the initial pH of the solutions. - The adsorption is also influenced by the adsorbent dose and the initial concentration of the concentration of the synthetic solution; Indeed, it is possible to use this agricultural waste as less expensive and very effective adsorbent for the removal of heavy metals after its activation.
37
References Ahmad A.A., 2006. Adsorption of direct dye on palm ash: Kinect and equilibrium modeling. J. of Hazardous Materials.094, 1-10. Chakraborty S., DasGupta S., Basu J.K., 2005. Adsorption study for the removal of basic dye: experimental and modeling. Chemosphere.58, 1079-1089. Gupta A.V., Ali I., 2004. Removal of lead and chromium from wastewater using bagasse flyash_sugar industry waste. J Colloid Interface Sci.271, 321-329. Goyal P., Sharma P., Srivastava S., Srivastava M., 2008. Saraca indica lead powder for decontamination of Pb: removal, recovery, adsorbent characterization and equilibrium modeling. J. Env. Sci. tech.5, 27-34. Iqbal M., Saeed A., Zafar S.I., 2009. FTIR spectrophotometry, kinetics and adsorption isotherms modeling, ion exchange and EDX analysis for understanding the mechanism of Cd2+ and Pb2+ by manga peel waste. Journal of hazardous mater.164, 161-171. Martín-LaraM.A., RodríguezI.L., BlázquezG.,CaleroM., 2011. Factorial experimental design for optimizing the removal conditions of lead ions from aqueous solutions by three wastes of the olive production. Desalination.278, 132-140. Mitic-Stojanovic D.L., Zarubica A., Purenovic M., Bojic D., Andjelkovic T., Bojic А.Lj., 2011. Biosorptive removal of Pb2+, Cd2+ and Zn 2+ from waste water by lagenaria vulgaris shell. WFC Org. za.3, 1-10. Panda G.C., Das S.K., Guha A.K ., 2008. Biosorption of cadmium and nickel by functinalized husk of lathyussativus. Colloid Surf. B 62, 173-179. Prado G.S.A., Moura A.O., Holanda S.M., Thiago O., Carvalho R., Andrade D.A.., Pescara C. I., Oliveira H.A.A., Okino Y.A.E., Pastore C.M.T., Douglas J.S., Zara L.F., 2010. Thermodynamic aspects of the Pb adsorption using Brazilian sawdust samples. Chemical engineering journal.160, 549 -555. Raji C., Anidudhun T.S., 1997. Chromium (IV) adsorption by sandust carbon: Kinetics and equilibrium. Indian journal of chemical technology.4, 228-236. Salem E.S., 2014. Biosorption of Pb2+ from natural waste using date pits: A green chemistry approach. Mod Chem Appl.2, 2-8. Wiwid Pranata P., Azlan K., Siti Najiah Mohd Y., Che Fauziah I., Azmi M., Norhayati H., Illyas Md I., 2014. Biosorption of Cu (II), Pb(II) and Zn(II) Ions from Aqueous Solutions Using Selected Waste Materials. Adsorption and Characterisation StudiesJournal of Encapsulation and Adsorption Sciences, 2014, 4, 25-35. Tuabamme J.T., Philomena K.I., 2010. Thermodynamic and kinetic behaviors lead (II) adsorption on activated carbon from Palmyra palm Nut. International Journal of applied Science and technology.3, 245-254. Xiao-ming L., Wei Z., Dong-bo W., Qi Y., Jian-bing C., Xiu Y., Ting-ting S., Guang-ming Z., 2010. Removal of Pb (II) from aqueous solutions by adsorption onto modified areca waste: kinetic and thermodynamic studies. Desalination.258, 148-153. Xue Song W., Zhi Peng L., Hua Hua M., Wen H., Hong Liang S., 2011. Kinetics of Pb (II) adsorption on black carbon derived from wheat residue. Chemical engineering journal. 166, 986-993.
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Algerian Journal of Research and Technology
[email protected] http://www.univ-usto.dz/AJRT/ ISSN Print:2543-3954 A.J.R.T Volume 02 (N° 01) (2017) 39-49
EQUILIBRIUM AND ISOTHERM MODELING OF TOXIC DYE ADSORPTION ONTO MODIFIED APRICOT STONE Moussa ABBAS (1)
* (1)
and Tounsia AKSIL (1)
Laboratory of Soft Technologies and Biodiversity, Faculty of Sciences,University M’hamed Bougara of Boumerdes, Boumerdes 35000, Algeria * (Corresponding author) E-mail:
[email protected] Tel.: +213 552408419; Fax: +213 21 24 80 08.
Abstract In the present study, adsorption of toxic dye Diret red 28 (acid benzidinediazo-bis-1naphtylamine - 4- sulfonique ) from aqueous solution was investigated using activated carbon synthesized with Phosphoric Acid activation. The synthesized adsorbent was analyzed using BET, FT-IR and SEM techniques. The BET analysis showed that the area provided by the synthesized activated carbon was 88.01 m2 g−1. The adsorption isotherms of Toxic dye onto ASAC are determined and correlated with common isotherms equations. The smaller RMSE values obtained for the Langmuir and Dubinin-R models indicate the better curves fitting, the monolayer adsorption capacity of toxic dye is found to be 32.85 mg.g-1 at temperature 25 oC and 23.42 mg.g-1 at temperature 65 oC at pH 13. The adsorption of toxic dye was carried out using a batch system and the effects of pH, contact time, adsorbent dosage, initial concentration and temperature on the adsorption capacity of synthesized adsorbent were investigated. Kinetics studies proved that for both metals, the kinetic data follows the pseudo second order kinetic model. In addition, the thermodynamics studies proved that the adsorption process of toxic dye could be considered spontaneous and endothermic.
Keywords: Apricot Stone, Direct Red 28, Kinetic, Isotherm, Adsorption, Thermodynamic 1. Introduction Dyes are colored compounds which are widely used in textiles, printing, rubber, cosmetics, plastics, leather industries to color their products results in generating a large amount of colored wastewater. Mainly dyes are classified into anionic, cationic, and non-ionic dyes. Among all the dyes using in industries, textile industries placed in the first position in using of dyes for coloration of fiber [1]. Dyes are chemical compounds which attach themselves to 39
fabrics or surface shells to impart color. Depolarization of waste water from textile and manufacturing industries is a major challenge for environmental managers [2] as dyes are water soluble and produce very bright colors in water with acidic properties. It has been projected that textile and manufacturing industries are using more than 10,000 commercially available (worldwide) dyes and the consumption of dyes in textile industry is more than 1000 tones/year and about 10-15% of these dyes are discharged into waste streams as effluents during the dyeing processes.
industrial wastewater [8]. The apricot stone used in the present study was prepared by chemical and physical activation this study was carried out with the aim to optimize conditions such as initial dye concentration, pH, particle size, contact time, adsorbent dosage, agitation speed and temperature. Besides this, the equilibrium adsorption data were fitted to various equations to obtain constants related to the adsorption phenomena. Equilibrium and kinetic analysis were conducted to determine the factors controlling the rate of adsorption, the optimization of various parameters in dye recovery and to find out the possibility of using this material as low-cost adsorbent for dye removal.
2. Experimental Analytical grade reagents are used in all experiments. Basic dye (C.I. Direct Red 28) (99 %) is purchased from Merck Company the chemical structure and Uv spectrum are represented in Figure 1. In this work, required activated carbon was prepared by a conventional method: carbonization and chemical activation with phosphoric acid as follows: Apricot stones obtained from Boumerdes region in Algeria, are air-dried, crushed and screened to obtain two fractions with geometrical mean sizes ranging from 63 to 2.5 mm. 100 g of the selected fraction are impregnated with concentrated H3PO4 and dried in air. Then, it is activated in a hot air oven at 250 °C . The carbonized material is washed with distilled water to remove the free acid until the pH reaches 6.8 and dried at 105 °C.
40
Figure 1: Chemical structure and Uv spectrum of Direct Red 28
2.1. Batch mode adsorption studies The effects of the experimental parameters such as the initial (C.I. Direct Red 28) concentration (40-100 mg.L-1), pH (2-14), adsorbent dosage (1-10 g.L-1), Agitation speed (1001200 rpm) and temperature (298-338 K) on the adsorptive removal of CR ions is studied in a batch mode of operation for a specific period of contact time (0-60 min). The (C.I. Direct Red 28) solutions are prepared by dissolving the accurate amount (C.I. Direct Red 28) (99 %) in distilled water, used as a stock solution and diluted to the required initial concentration. pH is adjusted with HCl or NaOH. The (C.I. Direct Red 28) content in the supernatant was measured spectrophotometrically on a Perkin Elmer UV-visible spectrophotometer model 550S at wavelength of 494 nm. The amount of (C.I. Direct Red 28) ions adsorbed by activated carbon qt (mg.g-1) is calculated by using the following equation (A1):
𝒒𝒕 =
(𝑪𝟎 − 𝑪𝒆 )∙𝑽 𝒎
(A1)
Where Co and Ct are the initial concentration and concentrations (mg.L-1) at any time respectively of the basic dye, V the volume of solution (L) and m the mass of the activated carbon (g).
2.2. Error functions Within recent decades, linear regression has been one of the most viable tool defining the best-fitting relationship quantifying the distribution of adsorbates, mathematically analyzing the adsorption systems and verifying the consistency and theoretical assumptions of an isotherm model. Due to the inherent bias resulting from the transformation which riding towards a diverse form of parameters estimation errors and fits distortion, several mathematically rigorous error functions (Root Mean Square Error (RMSE) equation (A2), the Sun of Error Squares (SSE) equation (A3) and Chi-Squares (X2) equation A(4) have lately drastically been addressed and confronted
41
𝐑𝐌𝐒𝐄 = √
𝐒𝐒𝐄 =
𝟏 𝐍
𝟏
∙ ∑𝐍𝟏(𝐪𝐞,𝐞𝐱𝐩 − 𝐪𝐞,𝐜𝐚𝐥 )𝟐
𝐍−𝟐
∞
∑ 𝐧=𝟏
𝐗 𝟐 = ∑𝐍𝟏
(𝐪𝐞𝐜𝐚𝐥 − 𝐪𝐞𝐞𝐱𝐩 )
𝟐
(𝐪𝐞,𝐞𝐱𝐩 −𝐪𝐞,𝐜𝐚𝐥 )𝟐
(A2)
(A3) (A4)
𝐪𝐞,𝐜𝐚𝐥
Where, qe(exp) (mg.g-1) is the experimental value of uptake, qe(cal) the calculated value of uptake using a model (mg.g-1), and N the number of observations in the experiment (the number of data points). The small the RMSE values, the better the curve fitting [9].
3. Results and Discussion 3.1. Characterization of the prepared ASAC The composition of native Apricot stone NAS and ASAC determined by X- fluorescence FX are summarized in Table 1. The FTIR spectra of the adsorbent display a number of absorption peaks, indicating that many functional groups are present in the adsorbent [10]. Table 1: Composition of NAS and ASAC
Oxides
NAS (%)
ASAC (%)
SiO2 Al2O3 Fe2O3 CaO MgO MnO Na2O K2O P2O5 TiO2 Cr2O3 SO3 ZnO CuO NiO P.E Total
0.963 0.413 0.092 0.303 0.138 0.001 0.079 0.120 0.056 0.009 0.001 0.063 0.001 0.008 0.002 97.58 99.83
0.326 0.075 0.025 0.264 0.096 0.003 0.049 0.118 0.698 0.004 0.003 0.037 0.001 0.009 0.002 98.32 100.03
P.E: Loss on Ignition
42
3.2. Effect of analytical parameters The effect of particle sizes on the acid dye adsorption by ASAC is examined. Significant variations in the uptake capacity and removal efficiency were observed at different particles sizes, indicating that the best performance is obtained with lower particle sizes (315-800 µm) is subsequently used in all adsorption experiments. The pH of the DR 28) solution plays an important role in the adsorption process. It is evident that the percentage of acid dye removal increases consistently with decreasing pH (Figure. 2). The surface charge of the adsorbent is positive when the medium pH is under the pH zpc value and negative for pH ions is favored. The pH(zpc) of ASAC is 7.05 and the surface charge of ASAC is negative at higher pH. As the pH decreases, the number of positively charged sites increases and favours the adsorption of CR ions by electrostatic attractions. The effect of the stirring speed on the CR dye adsorption capacity onto the prepared ASAC. The maximum uptake was obtained for a stirring speed of 300 rpm. Such moderate speed gives a good homogeneity for the mixture suspension. The adsorption capacity of CR increases with time and attains a maximum value after 40 min and thereafter, it reaches a constant value indicating that no more CR ions are further removed from the solution. The equilibrium time works out to be 40 min. Thus changing the initial concentration of acid dye from 50 to 100 mg.L-1, the adsorbed amount increases from 10.08 to 34.51 mg.g-1 (Figure. 3). This may be attributed to an increase in the driving force of the concentrations gradient with increasing the initial basic dye concentration in order to overcome the mass transfer resistance of CR ions between the aqueous and solid phases. For the first stage of batch adsorption experiments on ASAC.
Figure.2 : Effect of pH on the Direct Red 28 . adsorption onto ASAC
Figure .3 : Effect of contact time on the adsorption of Direct Red 28 onto ASAC
The effect of adsorbent dosage on the acid dye adsorption by ASAC is examined. Significant variations in the uptake capacity and removal efficiency are observed at different adsorbent 43
dosages (1 to 10 g.L-1) indicate that the best performance is obtained with an adsorbent dosage of 1 g.L-1. The optimum conditions are listed in Table 2. Table 2: Optimum parameters for the isotherm model Parameters
Optimum condition
Time (mn)
40
Agitation speed (rpm)
300
Adsorbent dosage (g/L)
1
Particle sizs (µm)
300-800
3.3. Adsorption isotherms models In general, an adsorption isotherm is an invaluable curve describing the phenomenon governing the retention or mobility of a substance from the aqueous porous media or aquatic environments to a solid-phase at a constant temperature and pH. Adsorption equilibrium is established when an adsorbate containing phase has been contacted with the adsorbent for sufficient time, with its adsorbate concentration in the bulk solution is in a dynamic balance with the interface concentration. Typically, the mathematical correlation, which constitutes an important role towards the modeling analysis, operational design and applicable practice of the adsorption systems, is usually depicted by graphically expressing the solid-phase against its residual concentration. Its physicochemical parameters together with the underlying thermodynamic assumptions provide an insight into the adsorption mechanism, surface properties as well as the degree of affinity of the adsorbents. Over the years, a wide variety of equilibrium isotherm models (Langmuir, Freundlich, Temkin, Elovich, Dubinin– Radushkevich) have been formulated in terms of three fundamental approaches.
3.3.1. Langmuir adsorption isotherm Langmuir adsorption isotherm, originally developed to describe gas–solid-phase adsorption onto activated carbon, has traditionally been used to quantify and contrast the performance of different bio-sorbents. In its formulation, this empirical model assumes monolayer adsorption, with adsorption can only occur at a finite (fixed) number of definite localized sites, that are identical and equivalent, with no lateral interaction and steric hindrance between the adsorbed molecules, even on adjacent sites. In its derivation, Langmuir isotherm refers to homogeneous adsorption, which each molecule possess constant enthalpies and sorption activation energy, with no transmigration of the adsorbate in the plane of the surface. Graphically (Figs.4a and 4b), it is characterized by a plateau, an equilibrium saturation point where once a molecule occupies a site, no further adsorption can take place. Moreover, Langmuir theory has related rapid decrease of the intermolecular attractive forces to the rise of distance.
44
Fgure 4: a) Adsorption Isotherm at 25 oC
b) Adsorption Isotherm at 65 oC
The assumptions of Langmuir equation include the followings: a) Maximum absorption occurs when the adsorbent surface is covered by a single molecular layer of soluble material. b) The absorption energy is fixed and identical at all the points. c) The molecules of adsorbed material cannot move in the adsorbent surface. The essential features of the Langmuir isotherm can be expressed in (B2).
Qe =
𝑸𝒎. 𝑲𝑳 ∙ 𝑪𝒆 𝟏 + 𝑲𝑳 ∙ 𝑪𝒆
Where C is the concentration of soluble material in the steady state mg/L. Qm is the maximum absorption capacity (mg/g) and KL is Langmuir equation constant (L/mg). Terms of dimensionless constant called separation factor which is defined by the following equation: 𝑹𝑳 =
𝟏
(B2)
𝟏+𝑲𝑳 ∙𝑪𝟎
Where KL is the Langmuir constant and Co the initial concentration of the adsorbate in solution. The values of RL indicates the type of isotherm: Irreversible : (RL = 0), Favourable : (0 < RL < 1) Linear : (RL = 1) Unfavourable : (RL > 1).
45
In this study, the RL values are less than 1, confirming that the adsorption process is favoured in both the cases as well as the applicability of Langmuir isotherm.
3.3.2. Dubinin–R adsorption isotherm - The Dubinin-Radushkevich isotherm Figure 5 can be used to describe adsorption on both homogenous and Heterogeneous surfaces [11] The Dubinin-R linear equation (B5) has the following form:
𝐋𝐧𝐪𝐞 = 𝐋𝐧𝐪𝐦 − 𝛃. 𝛆𝟐
(B5)
Where qm is the Dubinin-R monolayer capacity (mg.g-1) , β a constant related to sorption energy, and ε is the Polanyi potential which is related to the equilibrium concentration as follows equation (B6):
𝛆 = 𝐑𝐓𝐋𝐧 (𝟏 +
𝟏 𝐂𝐞
)
(B6)
Where R is the gas constant (8.314 J.mol-1 K-1) and T is the absolute temperature. The constant β gives the mean free energy E of adsorption per molecule of the adsorbate [12].
𝐄=
𝟏
(B7)
√𝟐 𝜷
The magnitude of E is useful estimating the mechanism of the adsorption reaction [13].
3.4. Adsorption kinetics Kinetic consideration is the first approach to be referred. Here by, adsorption equilibrium is defined being a state of dynamic equilibrium, with both adsorption and desorption rates are equal. The kinetic study is important for the adsorption process, it describes the uptake rate of adsorbate and controls the residual time of the whole adsorption process. Two kinetic models namely the pseudo first order and pseudo second-order are selected in this study to describe the adsorption. The pseudo first order equation [14] is given in equation (C1): 𝐊
𝟏 𝐥𝐨𝐠(𝐪𝐞 − 𝐪𝐭 ) = 𝐥𝐨𝐠𝐪𝐞 − 𝟐.𝟑𝟎𝟑 ∙𝐭
(C1)
The pseudo second order model [15, 16] is expressed by the equation (C2): 𝒕 𝒒𝒕
=
𝟏 𝐊 𝟐 ∙𝒒𝟐𝒆
+
𝟏 𝒒𝒆
∙𝒕
(C2)
Where qt (mg.g-1) is the amount of metal adsorbed on the adsorbent at various times t (min), K1 the rate constant of the pseudo-first order kinetic (min-1), K2 the rate constant of the pseudo-second order kinetic (g.mg-1 min-1). The determination coefficient and qe,cal of the pseudo-second order kinetic model are in good agreement with the experimental results (Table.3). Table. 3: Kinetic parameters for adsorption of CR ions onto ASAC Pseudo -First order Kinetic
46
Pseudo-Second order Kinetic
Co ( mg/L)
Qexp (mg/g)
K1 (mn-1)
50 80 100
9.990 18.44 34.84
0.0755 0.1146 0.1174
R2
Qcal ΔQ/Q (mg/g) (%)
0.9587 3.1438 0.7780 16.366 0.9364 23.662
217.7 12.66 47.24
Figure 5 : Thermodynamic parameters for the CR
K2 R2 (g/mg.mn)
0.0604 0.0157 0.0115
0.99962 0.99822 0.99918
Qcal (mg/g)
10.22 19.38 36.35
ΔQ/Q (%)
2.25 4.85 4.15
Figure 6 : Isotherm Modeling of D-R
The adsorption capacity of ASAC decrease (21.64 to 7.33 mg.g-1) with increasing temperature (295 to 323 K), indicating that the adsorption is disfavored at high temperature. Thermodynamic parameters are determined from the following equations (E1) and (E2) [17]. ΔG = - RT LnK
(E1)
ΔG = ΔH - TΔS
(E2)
The thermodynamic equilibrium constant K for the sorption was determined by Khan and Singh [18] by plotting qe/Ce versus Ce and extrapolating to zero qe, T is the absolute temperature in Kelvin and R is the universal gas constant (8.314 J.K-1mol-1). The ΔH and ΔS values obtained from the slope and intercept of Von’t Hoff plots of LnK versus 1/T (Figure. 6) and the ΔG values at various temperatures are summarized in Table .4.
47
In order to have an idea about the efficiency of the prepared ASAC, a comparison of basic dye adsorption of this work and other relevant studies is reported. The adsorption capacity of the adsorbent qmax is the parameter used for the comparison. One can conclude that the value of qmax is in good agreement with those of most previous works, suggesting that CR could be easily adsorbed on ASAC used in this work. This indicates that the apricot stone, very abundant in Algeria, is a cheap and effective adsorbent for the CR. Table.4 : Thermodynamic parameters for the Direct red 28 adsorption on ASAC T (K) 293
1/T (K-1) 0.003413
(Qe/Ce)= f(Ce ) R2 : 0.997 2
K
LnK
-3538.15 -3166.76
R : 0.997
0.2924
- 1.229
318
0.003145
R2: 0.994
0.3317
- 1.104
0.3733
- 0.985
0.003049
R : 0.996
ΔGo ( J/mol)
- 1.458
0.003247
328
ΔSo (J/K.mol)
0.2326
308
2
ΔHo (KJ/mol)
10.79254
24.759
-2919.18 -2671.58
4. Conclusion This study has shown that activated carbon prepared from apricot stone can be employed as effective adsorbent for the removal of CR from aqueous solution. The Dubinin-R and Langmuir isotherms model provided a better fit of the equilibrium adsorption data one. It gave a maximum adsorption capacity of 34.51 mg.g-1 at temperature 25 oC which decreased up to 23.08 mg.g-1 at 65 oC at 13. The pseudo-second order model proved the best description of the kinetic data. The negative value of ΔG and positive value of ΔH indicate that the adsorption of CR onto ASAC is spontaneous and endothermic over the studied range of temperatures. The positive value of ΔS state clearly that the randomness increased at the solid-solution interface during the CR adsorption onto ASAC, indicating that some structural exchange may occur among the active sites of the adsorbent and the ions. The adsorption of CR ions by ASAC follows a pseudo-second order kinetic model, which relies on the assumption that chemisorptions may be the rate-limiting step. In chemisorption, the CR ions are attached to the adsorbent surface by forming a chemical bond and tend to find sites that maximize their coordination number with the surface. This study in tiny batch gave rise to encouraging result, and we wish to achieve the adsorption tests in column mode under the conditions applicable to the treatment of industrial effluents and the present investigation showed that ASAC is a potentially useful adsorbent for the metals, acid and basic dyes. References [1] Reisch MS (Chemical & Engineering News 74 (1996). 10-12. [2] Ho YS, Chiang CC Adsorption 7 (2001) 139-147. [3] Kadolph S. The Delta Kappa Gamma Bulletin 75 (2008) 14. [4] Crini G Bioresour Technol 97 (2006). 1061-1085. [5] Forgacs E, Cserhati T, Oros G a review. Environ Int 30 (2004) 953-971.
48
[6] Muthukumar M, Selvakumar N Dye Pigment 62 (2004) 221-228. [7] Ong ST, Lee CK, Zainal Z l. Bioresour Technol 98 (2007)2792-2799. [8] Arami M, et al). Dyes and Pigments 73 (2007) 178-185. [9] M. Abbas et al; J. Ind. and Eng. Chem V 20 (2014) 745-751 [10] M. Abbas et al. Desalination and Water Treatment (2015) 1-12 [11] T. Shahwan, H.N. Erten, J. Radioanal. Nucl. Chem. V260 (2004) 43-48 [12] S.-H. Lin, R.-S. Juang, J. Hazard. Mater. V 92 (2002) 315-326 [13] A. Ozcan, E.M. Oncu, A.S. Ozcan, Colloids Surfaces A, Physico-Chem. Eng, Aspects V 277 (2006) 90-97 [14] S. Lagergren. K. Sven.Ventensskapsakad. Handlingar Band, V 24(1998)1-39. [15] Y.S Ho, G. Mc Kay Water Res. V 34, (3) (2000) 735-742. [16] Y.S. Ho, G. Mc Kay, Press Biochemistry, V 34, Issue 5 (1999) 451-465. [17] M. Abbas et al. Process Safaty and Environment Protection V 98 (2015) 424 – 436 [18] M. Ghaedj, F. Karimi, B. Barrazzch, R. Saraei, A. Danichfar, J. Ind. Eng. Chem. V19, 3 (2013) 756
49
Algerian Journal of Research and Technology
[email protected] http://www.univ-usto.dz/AJRT/ ISSN Print:2543-3954 A.J.R.T Volume 02 (N° 01) (2017) 50-57
ELECTRICAL CHARACTERIZATION OF A NOVEL METAL–SEMICONDUCTOR AU/ALPC-H/P-SI/AL ORGANIC DIODE 1I.
Missoum, 1M. Benhaliliba*, 2S. Ozcelik, 2T. Asar
1Physics 2Photonics
Faculty, USTO-MB University, BP1505 Oran, Algeria.
Application and Research Center Gazi University06500 Teknik okullar, Ankara, Turkey *Corresponding author.
[email protected]
Abstract. The Au/AlPc-H/p-Si/Al organic diodes based on Al-phthalocyanine diodes are fabricated by the spin coating process onto p-type silicon substrate. The Au/AlPc-H contact is thermally evaporated in vacuum at 10-6Torr. Here, we investigate the electronic parameters obtained from the current-voltage (I-V) characteristics achieved at room temperature under dark conditions within the -1V, +1V bias voltage range. The Cheung’s and Norde approximations are used for the calculation of the electronic magnitudes. The obtained values, such as ideality factor (n), barrier height (Φb) series resistance (RS), are approximately similar which approve the consistency of Cheung's and Norde methods. The I–V forward bias in log scale has been investigated to explore the dominated conduction mechanism. The AlPc Hydroxide/ p-Si contacts exhibit high rectification ratio (RR) in order of 2.73×104 and large ideality factor of 7.37. Keywords. AlPc Hydroxide; Organic diode; Spin-coating; Electrical parameters; Current-voltage measurement; Organic electronics. Introduction
50
Nowadays, the organic semiconductor materials are investigated by many researchers due to their different applications. In this ambitious filed, the metal-phthalocyanine semiconductors are used as diodes for optoelectronics [1], solar cells, liquid crystals, photovoltaic cell, gas sensors and optical data storage [2]. In order to fabricate organic diodes with such appropriate characteristics. Metal-phthalocyanine (M-Pc) where M=Zn, Cu, Al, Mg and Ni has been used as layers in the device fabrication [3- 6]. Organic diodes are fabricated by using several methods, which are mostly spin-coating and thermal evaporation. In this study, the AlPc-H material is deposited by spin-coating technique on p-Si substrates as well as the Au electrode is formed by thermal evaporation technique in low pressure vacuum as shown in figure 1. The current-voltage (I-V) characteristics of the fabricated ZnPc and AlPc-chloride organic diodes are measured and the electrical parameters such as ideality factor (n), barrier height (Φb), series resistance (RS) and rectification ratio (RR) are extracted and calculated for studying the microelectronic and the electronic behavior parameters of AlPc-H organic diode.
Experimental details The Au/AlPc-H/p-Si/Al organic diode is fabricated by spin coating system at 2000 rpm for 1 min and dried at 115 °C for 3 min; the process is repeated 2 times to get suitable films. The Au front contact is produced by thermal evaporation process in vacuum at pressure of 10– 6 T. The metallic (Au) contacts have a diameter of 1.5 mm. The current-voltage measurement of Au/AlPc-H/p-Si/Al organic diodes is performed from –3V to +3 V bias voltages by using Keithely 2400 source meter under dark conditions.
Results and discussion It is crucial to study the behavior of organic diode for that reason we plot I-V characteristics measurement. Figure 2 shows the I-V semilog plot of Au/AlPc-H/p-Si/Al organic diodes within (– 3V, + 3 V) voltage range under dark and room temperature conditions. Here, the I-V characteristics are investigated by means of the thermionic emission (TE) theory given as follow [7];
q (V IRs ) I I 0 exp nkT
(1)
The parameters I, V and I0 are the current, voltage and saturation current of organic diode respectively; the saturation current is given by [8]:
51
qΦ I 0 AA*T 2 exp b kT
(2)
A is the effective diode area, A* is Richardson constant which equal 32 A/K2cm2 [9] for the pSi, T is absolute temperature in Kelvin, q is the electron charge, n is ideality factor and b represents the barrier height that can calculate by using the following equation :
Φb
kT AA*T 2 ln q I 0
(3)
The I-V calculation of organic diode based on the TE theory shows that the plot of current versus voltage gives linear curve and the value of I0 can be extracted it from the y-axis intercept of this curve and injected in equation 3 to calculate b. The n represents the ideality factor which is greater than the unity and shows the deviation of the I-V characteristics of the diode from the ideal to non-ideal behavior which can be calculated by using the following equation [9]:
n
q dV kT d ln I
(4)
The constant K, T, q are Boltzmann constant, absolute temperature (300 K) and the electron charge respectively. The parameter n is equal to 1 in the ideal case. To explore the deviation from the ideal case we used the equation 4 to determine the ideality factor of Au/AlPc-H/pSi/Al fabricated diode from the slope of the linear part of the bias forward of lnI-V. The ideality factor n is very important parameter that decides the amount of contribution of tunneling on the recombination process and the change of performance of the device [10]. In order to calculate the series resistance, barrier height and ideality factor, we have used the functions of the method developed by Cheung and Cheung [11];
kT dV IR S n d (ln I ) q
(5)
and H(I) is given as follows; nkT I ln H ( I ) V * 2 q AA T
H ( I ) IR S nb
(6) (7)
The equation 5 of dV/dlnI versus current is represented in figure 3a. By using a linear fit of these curves, we can obtain the series resistance and ideality factor values from (nkT/q) + IR s plots. Series resistance takes the value of 3809 Ω and n of 7.35 for AlPc-H organic diode. From the equation 6, we calculate the barrier height and series resistance by using linear fit as 52
IR S n b as shown in figure 3b. The b takes the value of 0.14 eV and RS of 3839.16 Ω for AlPc-H organic diode. In order to compare and to emphasize the accuracy of the calculated values by Cheung method, we used the functions developed by Nordeas follows [12];
F V
V kT I (V ) ln q AA*T 2
(8)
Where γ is the first integer number greater than ideality factor of Au/AlPc-H/p-Si/Al;I and V are taken from the I-V characteristics in forward bias region. The barrier height of as-fabricated diode is defined as;
Φb F (V0 )
V0 kT q
(9)
Where F (V0) is the minimum value taken from the plot of F(V) vs. V curve as depicted in figure 4 and V0 is the corresponding value of voltage.
Fig. 1. The cross sectional of AlPc-H organic diode.
Besides, from the Norde method we calculated RS using the following equation;
Rs
kT n qI min
(10)
In this case, the Imin value is the minimum value of current corresponding to the value of V0. The calculated values of RS and b are determined from Norde method. The RS takes the value of 3657.57 Ω and b of 0.75 eV for AlPc-H organic diode. The values of ideality factor, series resistance and barrier height are calculated from Cheung method and are compared with those reported in literature as listed in table 1.
53
Fig. 2 The current-voltage characteristics plotting (semilog scale) of Au/AlPc-H/p-Si/Al diodes, in dark conditions.
Fig. 3 The plotting of dV/dlnI and H(I) as function of current of Au/AlPc-H/p- Si/Al organic diodes, in dark conditions.
54
Fig. 4 F(V) vs. Voltage of Au/AlPc-H/p-Si/Al organic diodes, in dark conditions.
TABLE 1. Comparison of microelectronic parameters of various organic diodes in dark conditions.
Organic diode
n
b(eV)
RS (Ω)
Reference
Au/AlPc-H/p-Si/Al
7.3
0.14
3.81×103
Currentstudy
Au/CoPc/p-Si/Al
1.3
0.90
314.5
[13]
Ag/CuPc/a-Si/p-Si/Ag
5.7
0.93
28.6
[14]
Ag/MgPc/p-Si
2.2
0.98
2.73×104
[15]
Table 1 displays the results of microelectronic parameters of some organic diodes based on Metalphthalocyanine (MPc where M= Al, Co, Cu and Mg) deposited on p-type Si substrates.
Fig. 5 The forward bias I–V characteristics of Au/AlPc-H/p-Si/Al organic diodes at room temperature.
55
We have noted that the deposited material has significant influence on the behavior of diode, the AlPc-H showed very high n of 7.35 and very small b of 0.14 eV compared to others diodes (CoPc, CuPc and MgPc). The high ideality factor suggests that the transport properties of the device could not be well defined by thermionic emission only; higher ideality factor could be due to presence of secondary mechanism at the interface [16] such as the recombination generation, image force effect and tunneling [7]. In order to survey the behavior deviation of the as-fabricated AlPc-H/p-Si organic diode, we determine the dominant transport charge mechanism by plotting the forward bias log I versus log V. This plot shows a power law behavior of the current I ∞ Vm+1 with different exponents (m+1), where (m+1) varies with the injection level and is also related to the distribution of trapping centers [9, 17, 18]; after that we distinct the linear regions and fit to calculate the (m +1) slopes as shown in figure 4. At low voltage (0.06 < log V < 0.14), the Au/AlPc-H/p-Si/Al organic diode is controlled by the trapped-charge-limited current (TCLC) in the band gap of the AlPc-H layer [16]. In intermediate voltages range, (0.16 < log V < 0.34) the dominant mechanism in the device is space charge limited current (SCLC) which is controlled by an exponential distribution of traps [19]. Obviously in the high voltages (0.36 < log V < 1.00) the slope decreases which means that most traps are filled (TFL) and the contribution of free charge carriers in the electric field becomes important [136-137]. As result, we can say that there is significant influence of recombination in the deviation of Au/AlPc-H/p-Si/Al organic diode from the ideal behavior.
Conclusion The Au/AlPc-H/p-Si/Al organic diode is fabricated by spin-coating and thermal evaporation techniques. The I-V characteristics are measured and used in the calculation of the electrical parameters by Cheung and Norde methods. The Au/AlPc-H/p-Si/Al revealed high RR value of 2.73×104 which proves that this structure is suitable candidate to be used as a good rectifier device. Here, the strong dependence of the microelectronic parameters on the deposited material is revealed. Besides, the AlPc-H showed three conduction mechanisms such as: TCLC, SCLC and TFL. The current study gives us more understanding of the Aluminum phthalocyanine hydroxide (AlPc-H) organic diode for the use in organic microelectronics applications.
Acknowledgment This work is a part of CNEPRU project under Ner B00L02UN310220130011supported by Oran University of Sciences and Technology www.univ-usto.dzand www.mesrs.dz. The first authors are grateful for the assistance of The Head of DUBTAM-Renewable 56
Energy Research Laboratory http://www.dicle.edu.tr/dubtam and the virtual library of SNDL https://www.sndl.cerist.dz. It is also included in ANVREDET project n° 18/DG/2016. www.anvredet.dz
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