Prediction of adsorption efficiency for the removal of nickel (II) ions by zeolite using artificial neural network (ANN) approach

Fresenius Environmental Bulletin

Volumn 20, Issue 12, 2011, Pages 3158-3165

  Turp, Sinan M ^a   Eren, Beytullah ^a   Ateş, Asude ^a  

^a SAKARYA UNIVERSITY   (Turkey)

Author keywords

Adsorption; Modeling; Neural network; Nickel (ii) ions; Zeolite

Indexed keywords

ADSORPTION; ALGORITHM; AQUEOUS SOLUTION; ARTIFICIAL NEURAL NETWORK; CONCENTRATION (COMPOSITION); ERROR ANALYSIS; NICKEL; NUMERICAL MODEL; POLLUTANT REMOVAL; ZEOLITE;

EID: 84856241457     PISSN: 10184619     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (33)

1. Khopkar, S.M. (ed.) (1999) Environmental Pollution Analysis. New Age International Publishers, New Delhi, India.
2. Ouki, S.K. and Neufeld, R.D. (1997) Use of activated carbon for the recovery of chromium from the electroplating industry. Journal of Chemical Technology and Biotechnology (70), 3-8. (Pubitemid 27412228)
3. Patterson, J.W. (1997) Industrial Wastewater treatment technology, Science Publishers, New York.
4. Baileys, S.E, Olin T.J, Bricka, R.M, Adrian D.D. (1999) Are view of potentially low -cost sorbents for heavy metals, Water Research, 33(11),2469-79. (Pubitemid 29322408)
5. Sonune, A.and Ghate, R.,(2004) Developments in wastewater treatment methods, Desalination (167), 55-63.
6. Metcalf and Eddy, "Wastewater Engineering: Treatment and Reuse, 4th Ed.
7. Malkoc, E. and Nuhoglu, Y., (31 July 2006) Removal of Ni(II) ions from aqueous solutions using waste of tea Factory: Adsorption on a fixed-bed column, Journal of Hazardous Materials, Volume 135, Issues 1-3, Pages 328-336. (Pubitemid 44218755)
8. Arslanoglu, F. N., Kar, F., Arslan, N., (November 2005) Adsorption of dark coloured compounds from peach pulp by using powdered-activated carbon, Journal of Food Engineering, Volume 71, Issue 2, Pages 156-163. (Pubitemid 40753026)
9. Schlegel, M., Manceau, A., Chateigner, D., and Charlet, L., (1999) Sorption of metal ions on clay minerals: I. Polarized EXAFS evidence for the adsorption of Co on the edges of hectorite particles, Journal of Colloid Interface Science (215), pp. 140-158. (Pubitemid 29394546)
10. Prasad, M., Saxena, S., Amritphale, S.S. and Chandra, N. (2000) Kinetics and isotherms for aqueous lead adsorption by natural minerals, Industrial and Engineering Chemistry Research (39), pp. 3034-3037, (Pubitemid 30646670)
11. Prasad, M., Saxena S., and Amritphale, S.S., (2002) Adsorption models for sorption of lead and zinc on francolite mineral, Industrial and Engineering Chemistry Research, (41), pp. 105-111. (Pubitemid 34052824)
12. Kaoser, S., Barrington, S., Elektorowicz M. and Wang, Li. (2005) Effect of Pb and Cd on Cu adsorption by sandbentonite liners, Canadian Journal of Civil Engineering (32), pp. 241-249.
13. Gupta, V.K., (1998) Equilibrium uptake, sorption dynamics, process development and column operations for the removal of copper and nickel from aqueous solution and wastewater using activated slag, a low-cost adsorbent, Industrial and Engineering Chemistry Research (37), pp. 192-202.
14. Wang, J.M., Teng, X.J., Wang H., and Ban, H. (2004) Characterizing the metal adsorption capability of a class f coal fly ash, Environmental Science and Technology (38), pp. 6710-6715. (Pubitemid 39658109)
15. Gupta, V.K., Gupta, M. and Sharma, S. (2001) Process development for the removal of lead and chromium from aqueous solutions using red mud-an aluminium industry waste, Water Research (35), pp. 1125-1133.
16. Mahvi, A.H., Naghipour, D., Vaezi, F. and Nazmara, S. (2005) Teawaste as an adsorbent for heavy metal removal from industrial wastewaters, American Journal of Applied Science (2), pp. 372-375.
17. Dogan, E., Ates, A., Yilmaz, E. C., Eren, B. (2008) Application of Artificial Neural Networks to Estimate Wastewater Treatment Plant Inlet Biochemical Oxygen Demand, Environmental Progress, 27 (4), 439-446.
18. Mjalli, F.S., Al-Asheh, S., Alfadala, H.E. (2007) Use of artificial neural network black-box modeling for the prediction of wastewater treatment plants performance, Journal of Environmental Management, 83 (3), 329-338. (Pubitemid 46238366)
19. Zhu, J., Zurcher, J., Rao, M., Meng, M. Q-H. (1998) An online wastewater quality predication system based on a timedelay neural network, Engineering Applications of Artificial Intelligence, 11 (6), 747-758. (Pubitemid 128409037)
20. Gontarski, C.A., Rodrigues, P.R., Mori, M., Prenem, L.F. (2000), Simulation of an industrial wastewater treatment plant using artificial neural networks Computers & Chemical Engineering, 24 (2-7), 1719-1723.
21. Pai, T.Y., Tsai, Y.P., Lo, H.M., Tsai, C.H., Lin C.Y. (2007) Grey and neural network prediction of suspended solids and chemical oxygen demand in hospital wastewater treatment plant effluent, Computers & Chemical Engineering, 31 (10), 1272-1281. (Pubitemid 47077483)
22. Sahoo, G.B., Ray, C. (2006) Predicting flux decline in crossflow membranes using artificial neural networks and genetic algorithms, Journal of Membrane Science, 283 (1-2), 147-157. (Pubitemid 44293121)
23. Chen H., Kim, A.S. (2006) Prediction of permeate flux decline in crossflow membrane filtration of colloidal suspension: a radial basis function neural network approach, Desalination, 192 (1-3), 415-428.
24. Shetty, G. R., Shankararaman Chellam, (1 June 2003) Predicting membrane fouling during municipal drinking water nanofiltration using artificial neural networks, Journal of Membrane Science (217), Issues 1-2,69-86.
25. Guadix, A., Zapata., J.E., M. Almecija, C., Guadix, E.M. (2010) Predicting the flux decline in milk cross-flow ceramic ultrafiltration by artificial neural networks, Desalination, 250 (3), 1118-1120.
26. Libotean D., Giralt, J., Giralt F., Rallo, R., Wolfe, T., Cohen, Y. (2009) Neural network approach for modeling the performance of reverse osmosis membrane desalting, Journal of Membrane Science, 326 (2), 408-419.
27. Prakash, N., Manikandan, S.A., Govindarajan, L., Vijayagopal, V. (2008) Prediction of biosorption efficiency for the removal of copper (II) using artificial neural networks, Journal of Hazardous Materials, 152 (3), 1268-1275. (Pubitemid 351380685)
28. Fagundes-Klen, M.R., Ferri, P., Martins, T.D., Tavares, C.R.G., Silva, E.A. (2007) Equilibrium study of the binary mixture of cadmium-zinc ions biosorption by the Sargassum filipendula species using adsorption isotherms models and neural network, Biochemical Engineering Journal, 34 (2), 136-146. (Pubitemid 46441915)
29. Yetilmezsoy, K. and Demirel, S. (2008) Artificial neural network (ANN) approach for modeling of Pb(II) adsorption from aqueous solution by Antep pistachio (Pistacia Vera L.) shells, Journal of Hazardous Materials, 153 (3), 1288-1300. (Pubitemid 351458609)
30. 2+ removal from wastewater using electrodialysis, Chemical Engineering and Processing: Process Intensification, 48 (8), 1371-1381.
31. Kashaninejad, M., Dehghani, A.A., Kashiri, M. (2009) Modeling of wheat soaking using two artificial neural networks (MLP and RBF), Journal of Food Engineering, 91(4), 602-607.
32. Singh, K.P., Basant, A., Malik, A., Jain, G. (2009) Artificial neural network modeling of the river water quality-A case study. Ecological Modelling, 220, (6), 888-895.
33. Sutçu, H. (2007) Removal of Pb(II) and Ni(II) ions From Aqueous Solution By Peat, Fresenius Environmental Bulletin, Volume 16 - No: 12a.