Yıl 2016, Cilt 20 , Sayı 3, Sayfalar 433 - 440 2016-12-01

Bakır biyosorpsiyon işlemine Yapay Sinir Ağı (ANN) yaklaşımı
Artificial Neural Network (ANN) approach to copper biosorption process

Deniz Bingöl [1] , Erdal Kılıç [2] , Merve Hercan [3]


Bu makale, çörek otu kullanılarak bakır biyosorpsiyon işleminin değerlendirilmesi için yapay sinir ağı (ANN) modelinin kullanımını göstermektedir. Deneysel değişkenler (sıcaklık, biyosorbent kütlesi, başlangıç bakır derişimi, başlangıç pH’ı) çıkış olarak, herhangi bir zamanda adsorplanan bakır miktarını tahmin etmek için kurulan sinir ağında girdi olarak kullanılmıştır. Ağ tahmini ve ilgili deneysel veriler arasındaki yüksek R2-değerleri, eğitim ve test veri setleri için sırasıyla 0,89 ve 0,93, yapay nöron ağını kullanarak biyosorpsiyon işleminin modellemede yeterli bir yöntem olduğunu kanıtlamaktadır. Gibbs serbest enerji (ΔG°), entalpi (AH°) ve sorpsiyonun entropi değişimi (ΔS°) gibi termodinamik parametreler de değerlendirildi. Biyosorpsiyon işleminin gerçekte kendiliğinden, istemli ve ekzotermik olduğu bulunmuştur. Bakır iyonunun denge sorpsiyonu, Langmuir denklemine göre belirlenmiştir ve 293 K’de 16,13 mg/g olarak bulunmuştur. Model sonuçları ve deneysel veriler arasındaki karşılalaştırma çörek otu kullanılarak bakırın giderilebileceğini göstermektedir.

This paper demonstrates use of artificial neural network (ANN) model for the evaluation of copper biosorption process using black cumin. The experimental variables (temperature, biosorbent mass, initial copper concentration, initial pH) were used as the input to the constructed neural network to predict the adsorbed amounts of copper at any time as the output. The high R2-values, 0.89 and 0.93 for training and testing data sets, respectively; between the network prediction and the corresponding experimental data prove that modeling the biosorption process using artificial neuron network is a satisfactory method. Thermodynamic parameters such as Gibbs free energy (ΔG°), the enthalpy (Δ) and the entropy change of sorption (Δ) were also evaluated. It was found that the biosorption process was spontaneous, favorable and exothermic in nature. The equilibrium sorption of copper ions was determined from the Langmuir equation and found to be 16.13 mg/g at 293 K. A comparison between the model results and experimental data showed that the ANN model is able to predict the removal of copper using black cumin.

  • REFERENCES
  • http://water.epa.gov/drink/contaminants/basicinformation/copper.cfm
  • A. Özer, G. Gürbüz, A. Çalimli, B. K. Körbahti. (2009, February). Biosorption of copper(II) ions on Enteromorpha prolifera: Application of response surface methodology (RSM). Chem. Eng. J. 146, pp. 377–387. Available: http://www.sciencedirect.com/science/article/pii/S1385894708003719
  • P. King, P. Srinivas, Y. P. Kumar, V. S. R. K. Prasad. (2006, August). Sorption of copper(II) ion from aqueous solution by Tectona grandis l.f. (teak leaves powder). J. Hazard. Mater. B136, 560–566. Available: http://www.sciencedirect.com/science/article/pii/S0304389405008423
  • Y. P. Kumar, P. King, V. S. R. K. Prasad. (2006, September). Equilibrium and kinetic studies for the biosorption system of copper(II) ion from aqueous solution using Tectona grandis L.f. leaves powder. J. Hazard. Mater. B137,1211–1217.
  • Available: http://www.sciencedirect.com/science/article/pii/S0304389406003475
  • Y. P. Kumar, P. King, V. S. R. K. Prasad. (2006, September). Removal of copper from aqueous solution using Ulva fasciata sp.-A marine green algae. J. Hazard. Mater. B137, 367–373. Available: http://www.sciencedirect.com/science/article/pii/S0304389406001452
  • C. Cojocaru, M. Diaconu, I. Cretescu, J. Savic, V. Vasic. (2009, March). Biosorption of copper(II) ions from aqua solutions using dried yeast biomass. Colloids and Surfaces A: Physicochem. Eng. Aspects 335, 181–188. Available: http://www.sciencedirect.com/science/article/pii/S0927775708007607
  • H. Chen, G. Dai, J. Zhao, A. Zhong, J. Wu, H. Yan. (2010, May). Removal of copper(II) ions by a biosorbent-Cinnamomum camphora leaves powder. J. Hazard. Mater. 177, 228–236. Available: http://www.sciencedirect.com/science/article/pii/S0304389409019931
  • A. Çelekli, M. Yavuzatmaca, H. Bozkurt. (2010, January). An eco-friendly process: Predictive modelling of copper adsorption from aqueous solution on Spirulina platensis. J. Hazard. Mater. 173, 123–129. Available: http://www.sciencedirect.com/science/article/pii/S0304389409013375
  • A. N. Kosasih, J. Febrianto, J. Sunarso, Y. H. Ju, N. Indraswati, S. Ismadji. (2010, August). Sequestering of Cu(II) from aqueous solution using cassava peel (Manihot esculenta). J. Hazard. Mater. 180, 366–374. Available: http://www.sciencedirect.com/science/article/pii/S0304389410004863
  • W. M. Ibrahim. (2011, September). Biosorption of heavy metal ions from aqueous solution by red macroalgae. J. Hazard. Mater. 192, 1827–1835.
  • Available: http://www.sciencedirect.com/science/article/pii/S0304389411008879
  • B. Kiran, K. Thanasekaran. (2011, September). Copper biosorption on Lyngbya putealis: Application of response surface methodology (RSM). Int. Biodeter. Biodegr. 65, 840–845. Available: http://www.sciencedirect.com/science/article/pii/S0964830511001296
  • P. S. Kumar, S. Ramalingam, V. Sathyaselvabala, S. D. Kirupha, S. Sivanesan. (2011, January). Removal of copper(II) ions from aqueous solution by adsorption using cashew nut shell. Desalination 266, 63–71. Available: http://www.sciencedirect.com/science/article/pii/S0011916410005680
  • S. Lu, S. W. Gibb. (2008, April). Copper removal from wastewater using spent-grain as biosorbent. Biores. Tech. 99, 1509–1517.
  • Available: http://www.sciencedirect.com/science/article/pii/S0960852407003653
  • K. S. Tong, M. J. Kassim, A. Azraa. (2011, May). Adsorption of copper ion from its aqueous solution by a novel biosorbent Uncaria gambir: Equilibrium, kinetics, and thermodynamic studies. Chem. Eng. J. 170, 145–153. Available: http://www.sciencedirect.com/science/article/pii/S1385894711003494
  • S. M. El-Said, M. B. S. Alamri, S. El-Barak Ali-Bin, O. Alsogair. (2009, April). Adsorptive removal of Arsenite as (III) and Arsenate as (V) heavy metals from waste water using Nigella sativa L. Asian J. Sci. Res. 2, 96–104. Available: http://scialert.net/qredirect.php?doi=ajsr.2009.96.104&linkid=pdf
  • D. Bingöl, M. Hercan, S. Elevli, E. Kılıç. (2012, May). Comparison of the results of response surface methodology and artificial neural network for the biosorption of lead using black cumin. Biores. Tech. 112, 11–115. Available: http://www.sciencedirect.com/science/article/pii/S0960852412003355
  • K. H. Chu. (2003, January). Prediction of two-metal biosorption equilibria using a neural network. Eur. J. Miner. Process Environ. Protect. 3(1), 119–127. Available: http://ejmpep.com/chu.pdf
  • K. Yetilmezsoy, S. Demirel. (2008, September). Artificial neural network (ANN) approach for modeling of Pb(II) adsorption from aqueous solution by Antep pistachio (Pistacia Vera L.) shells. J. Hazard. Mater. 153, 1288–1300.
  • Available: http://www.yildiz.edu.tr/~yetilmez/1st%20page%20Jour.%20Article11.pdf
  • K. V. Kumar, K. Porkodi. (2009, May). Modelling the solid–liquid adsorption processes using artificial neural networks rained by pseudo second order kinetics. Chem. Eng. J. 148, 20–25. Available: http://www.sciencedirect.com/science/article/pii/S1385894708004361
  • A. Çelekli, F. Geyik. (2011, May). Artificial neural networks (ANN) approach for modeling of removal of Lanaset Red G on Chara contraria. Biores. Tech. 102, 5634–5638. Available: http://www.sciencedirect.com/science/article/pii/S0960852411002379
  • B. Das, N. K. Mondal. (2011, December). Calcareous Soil as a New Adsorbent to remove lead from aqueous solution: Equilibrium, kinetic and thermodynamic study. UJERT 1(4), 515–530. Available: http://www.environmentaljournal.org/1-4/ujert-1-4-13.pdf
  • A. R. Khataee, G. Dehghan, M. Zarei, A. Ebadi, M. Pourhassan. (2011, February). Neural network modeling of biotreatment of triphenylmethane dye solution by a gren macroalgae. Chem. Eng. Res. Des. 89, 172–178. Available: http://www.sciencedirect.com/science/article/pii/S0263876210001711
  • S. D. Balkin, D. K. J. Lin. (2000, May). A neural network approach to response surface methodology. Commun. Statist.-Theory Meth., 29, 2215–2227.
  • Available: http://www.tandfonline.com/doi/abs/10.1080/03610920008832604
  • S. Haykin. (1999). Neural networks: a comprehensive foundation, Second Edition, Prentice Hall International, Inc.Available: http://dl.acm.org/citation.cfm?id=521706
  • A. Ghaffar. (2008, January). Removal of lead(II) ions from aqueous solution under different physicochemical conditions using various sorbents. AJSE 33(1a), 55–61.
  • Available: https://ajse.kfupm.edu.sa/articles/331A_P.6.pdf
  • A.R. Khataee, M. B. Kasiri, (2010, October). Artificial neural networks modeling of contaminated water treatment processes by homogeneous and heterogeneous nanocatalysis. J. Mol. Catal A: Chem. 331, 86–100. Available: http://www.sciencedirect.com/science/article/pii/S1381116910003468
Konular Mühendislik
Yayımlanma Tarihi Aralık 2016
Bölüm Araştırma Makalesi
Yazarlar

Yazar: Deniz Bingöl

Yazar: Erdal Kılıç

Yazar: Merve Hercan

Tarihler

Başvuru Tarihi : 23 Ocak 2016
Kabul Tarihi : 14 Haziran 2016
Yayımlanma Tarihi : 1 Aralık 2016

Bibtex @araştırma makalesi { saufenbilder270003, journal = {Sakarya University Journal of Science}, issn = {1301-4048}, eissn = {2147-835X}, address = {}, publisher = {Sakarya Üniversitesi}, year = {2016}, volume = {20}, pages = {433 - 440}, doi = {10.16984/saufenbilder.25723}, title = {Artificial Neural Network (ANN) approach to copper biosorption process}, key = {cite}, author = {Bingöl, Deniz and Kılıç, Erdal and Hercan, Merve} }
APA Bingöl, D , Kılıç, E , Hercan, M . (2016). Artificial Neural Network (ANN) approach to copper biosorption process. Sakarya University Journal of Science , 20 (3) , 433-440 . DOI: 10.16984/saufenbilder.25723
MLA Bingöl, D , Kılıç, E , Hercan, M . "Artificial Neural Network (ANN) approach to copper biosorption process". Sakarya University Journal of Science 20 (2016 ): 433-440 <http://www.saujs.sakarya.edu.tr/tr/issue/25594/270003>
Chicago Bingöl, D , Kılıç, E , Hercan, M . "Artificial Neural Network (ANN) approach to copper biosorption process". Sakarya University Journal of Science 20 (2016 ): 433-440
RIS TY - JOUR T1 - Artificial Neural Network (ANN) approach to copper biosorption process AU - Deniz Bingöl , Erdal Kılıç , Merve Hercan Y1 - 2016 PY - 2016 N1 - doi: 10.16984/saufenbilder.25723 DO - 10.16984/saufenbilder.25723 T2 - Sakarya University Journal of Science JF - Journal JO - JOR SP - 433 EP - 440 VL - 20 IS - 3 SN - 1301-4048-2147-835X M3 - doi: 10.16984/saufenbilder.25723 UR - https://doi.org/10.16984/saufenbilder.25723 Y2 - 2016 ER -
EndNote %0 Sakarya Üniversitesi Fen Bilimleri Enstitüsü Dergisi Artificial Neural Network (ANN) approach to copper biosorption process %A Deniz Bingöl , Erdal Kılıç , Merve Hercan %T Artificial Neural Network (ANN) approach to copper biosorption process %D 2016 %J Sakarya University Journal of Science %P 1301-4048-2147-835X %V 20 %N 3 %R doi: 10.16984/saufenbilder.25723 %U 10.16984/saufenbilder.25723
ISNAD Bingöl, Deniz , Kılıç, Erdal , Hercan, Merve . "Artificial Neural Network (ANN) approach to copper biosorption process". Sakarya University Journal of Science 20 / 3 (Aralık 2016): 433-440 . https://doi.org/10.16984/saufenbilder.25723
AMA Bingöl D , Kılıç E , Hercan M . Artificial Neural Network (ANN) approach to copper biosorption process. SAUJS. 2016; 20(3): 433-440.
Vancouver Bingöl D , Kılıç E , Hercan M . Artificial Neural Network (ANN) approach to copper biosorption process. Sakarya University Journal of Science. 2016; 20(3): 440-433.