جداسازی و پیش تغلیظ مقادیر ناچیز یون آهن با استفاده از مولکول نگاری پلیمری و کاربرد شبکه عصبی مصنوعی در پیشگویی بازده استخراج آن

نوع مقاله : مقاله علمی پژوهشی

نویسنده

چابهار- دانشگاه دریانوردی و علوم دریایی چابهار - دانشکده علوم دریائی - گروه شیمی دریا

کلیدواژه‌ها


عنوان مقاله [English]

Separation and pre-concentration of trace quantities of iron ions using molecularly imprinted polymer and its application of artificial neural networks for predicting the extraction yield

نویسنده [English]

  • hossein hashemi
چکیده [English]

In this study, a new modeling method based on three-layer artificial neural network (ANN) techniques has been employed to predict the extraction yield of iron from real samples by means of molecularly imprinted polymer. Input variables of the model were pH, absorption and desorption time, ligand amount and volume of solution while the output was extraction yield of iron ions. The mean squared error and correlation coefficient between the experimental data and the ANN predictions were determined as 0.0036 and 0.96428 for training, 0.0020 and 0.96232 for validation and 0.0004 and 0.9962 for testing data sets. The detection limit of the proposed method was 3.1 &mug. L-1. Dynamic linear range in the range of 200-1000 &mug. L-1 was obtained. The relative standard deviation was found to be below 8.8%. The method was applied to the recovery and determination of Fe in a few different real samples.

کلیدواژه‌ها [English]

  • Artificial Neural Network (ANN)
  • extraction iron
  • Molecularly imprinted polymer
  • Real samples
[1] F. A. Cotton, G. Wilkinson, 3 rd Ed, Wilery Interscience, (1988) 868.
[2] J. Kozak, J. Paluch, A. Węgrzecka, M. Kozak, M. Wieczorek, J. Kochana, P. Kościelniak, Talanta, 148 (2016) 626.
[3] S. Chen, N. Li, X. Zhang, D. Yang, H. Jiang, Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 138 (2015) 375.
[4] C. Pons, M. Miró, E. Becerra, J. M. Estela, V. Cerda, Talanta, 62 (2004) 887.
[5] L. Kozak, P. Niedzielski, K. Wachowiak, Microchemical Journal, 110 (2013) 54.
[6] M. Khajeh, M. Kaykhaii, M. Mirmoghaddam, H. Hashemi, Journal of Environmental Analytical Chemistry, 89 (2009) 981.
[7] M. Kaykhaii, M. Khajeh, S. H. Hashemi, Journal of Analytical Chemistry, 70 (2015) 1318.
[8] H. Hashemi, M. Khajeh, M. Kaykhaii, Analytical Methods, 5 (2013) 2778.
[9] ع. امیری، ع. رمضانی، م. جهانشاهی،  ع. ا. مقدمنیا، مجله علمی- پژوهشی شیمی کاربردی، شماره 38 (1395) ص 51.
[10] M. Khajeh, M. Kaykhaii, H. Hashemi, M. Mirmoghaddam, Polymer Science, 51 (2009) 344.
[11] S. H. Hashemi, M. Kaykhaii, M. Khajeh, Analytical Letters,48 (2015) 1815.
[12] M. Khajeh, M. Bohlooli, H. Hashemi, Journal of Macromolecular Science, 46 (2009) 526.
[13] M. Khayet, C. Cojocaru, Separation and Purification Technology, 86 (2012) 171.
[14] S. Mandal, P. V. Sivaprasad, S. Venugopal, K. P. N. Murthy, Applied Soft Computing, 9 (2009) 237.
[15] M. Khajeh, Y. Yamini, E. Ghasemi, J. Fasihi, M. Shamsipur, Analytica Chimica Acta, 581 (2007) 208.