Removal of Cu2+ from aqueous solution by adsorption in a fixed bed column and Neural Network Modelling

OĞUZ E., ERSOY M.

CHEMICAL ENGINEERING JOURNAL, cilt.164, sa.1, ss.56-62, 2010 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 164 Sayı: 1
  • Basım Tarihi: 2010
  • Doi Numarası: 10.1016/j.cej.2010.08.016
  • Dergi Adı: CHEMICAL ENGINEERING JOURNAL
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.56-62
  • Anahtar Kelimeler: Fixed bed column, Copper ions, Sunflower, Neural Network, Adsorbent capacity, ACTIVATED CARBON, RATE CONSTANTS, CONE BIOMASS, BIOSORPTION, COPPER(II), BATCH, OZONATION, LEAD(II), DYES
  • Atatürk Üniversitesi Adresli: Evet

Özet

Adsorption potential of shells of Sunflower to remove Cu2+ ions from aqueous solution was investigated using a fixed-bed adsorption column. The effects of inlet Cu-o(2+) concentration (20-60 mg/L), feed flow rate (9-21 mL/min) and bed height (5-15 cm), initial solution pH (3-5.6) and particle size (0.25-0.5, 0.5-1 and 1-2 mm) on the breakthrough characteristics of the adsorption system were investigated. The adsorption capacities of the adsorbent at different particle sizes (0.25-0.5, 0.5-1, 1-2 mm) were determined as 17.26, 7.36 and 5.48 mg/g, respectively. The highest experimental and theoretical bed capacities were obtained to be 25.95 and 26.22 mg/g at inlet Cu-o(2+) concentration of 60 mg/L, bed height of 5 cm and flow rate of 5 mL/min, pH of 5.6 and particle size of 0.25-0.5 mm. A relationship between the predicted and observed data was conducted. The ANN model yielded determination coefficient of 0.986 and root mean square error of 0.018. The results indicated that Sunflower waste is a suitable adsorbent for the removal of Cu2+ ions from aqueous solution. (C) 2010 Elsevier B.V. All rights reserved.