Journal of Interfaces, Thin Films, and Low dimensional systems

Artificial neural networks approach for modeling of Cr(VI) adsorption from aqueous solution by MR, MAC, MS

Document Type : Original Article

Authors

1 Chemistry department, Faculty of Arts and Sciences, Suleyman Demirel University

2 Chemistry Department, Faculty of Arst and Sciences, Suleyman Demirel University

3 Süleyman Demirel University, Graduate School of Applied and Natural Sciences, Department of Chemistry

Abstract

The adsorption ability of Dowex Optipore L493 resin modified with Aliquat 336 (MR), activated carbon modified with Aliquat 336 (MAC) and sawdust modified with Aliquat 336 (MS) for removal of Cr(VI) from aqueous solution in batch system was investigated. The effects of operational parameters such as adsorbent dosage, initial concentration of Cr(VI) ions, pH, temperature and contact time were studied. An artificial neural network (ANN) model was developed to predict the efficiency of Cr(VI) ions removal. The results revealed that the Langmuir isotherm fitted better than the Freundlich isotherm. The rate of adsorption was shown the best fit with the pseudo-second order model. Thermodynamic parameters showed that the adsorption of Cr(VI) adsorption was feasible, spontaneous and exothermic. The comparison of the removal efficiencies of Cr(VI) using ANN model and experimental results showed that ANN model can estimate the behavior of the Cr(VI) removal process under different conditions.

Keywords

Main Subjects

Article Title [Persian]

رهیافت شبکه عصبی مصنوعی برای مدلسازی جذب Cr(VI) از محلول آبی با MR, MAC, MS

Authors [Persian]

  • فطیه گوده 1
  • هاکان آکتاش 2
  • الیف آتالای 3

1

2

3

Abstract [Persian]

در این تحقیق توان جذب رزین دوکس اپتیپور493Lکه توسط  نمک آمونیوم 336  (MR) اصلاح شده است، توان جذب کربن فعال که با نمک آمونیوم 336 (MAC) اصلاح شده است و توان جذب خاک اره که توسط  نمک آمونیوم 336 (MS) اصلاه شده است را برای حذف Cr(VI)از محلول  آبی در یک سیستم مرکب مورد مطالعه قرار می دهیم. اثرات پارامترهای عملیاتی مانند دوز جاذب، غلظت اولیه یون های Cr (VI)، pH، دما و زمان تماس مورد مطالعه قرار گرفته است. مدل شبکه عصبی مصنوعی (ANN) برای پیش بینی کارایی حذف یونCr (VI)توسعه داده شده است. نتایج نشان می دهد که ایزوترم لانگمویر بهتر از ایزوترم فرویندلیش است. آهنگ جذب بهترین حالت را در مدل مرتبه شبه دوم نشان می دهد. پارامترهای ترمودینامیکی نشان می دهند که جذب Cr (VI)امکان پذیر، خود به خودی و گرمازا است. مقایسه کارایی حذف کروم (VI) با استفاده از مدل شبکه عصبی مصنوعی و نتایج تجربی نشان می دهد که مدل شبکه عصبی مصنوعی می تواند رفتار فرایند حذف Cr (VI)را در شرایط مختلف برآورد کند.

Keywords [Persian]

  • شبکه عصبی مصنوعی
  • کروم
  • جذب
  • لانگمویر
  • فرویندلیش
  • مدل شبه مرتبه دوم
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Journal of Interfaces, Thin Films, and Low dimensional systems
Volume 1, Issue 2 - Serial Number 2
March 2018
Pages 81-91