Pore Characterization and FTIR Spectras of Yellow Squash Particles and Adaptive Neuro-Fuzzy Inference System Modelling of the Breakthrough Curves of Reactive Blue 21 Dyestuff in a Fixed-Bed Column

OĞUZ E., Utku M.

ENVIRONMENTAL PROGRESS & SUSTAINABLE ENERGY, cilt.38, 2019 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 38
  • Basım Tarihi: 2019
  • Doi Numarası: 10.1002/ep.12943
  • Dergi Adı: ENVIRONMENTAL PROGRESS & SUSTAINABLE ENERGY
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Anahtar Kelimeler: fixed bed, yellow squash, RB21, BET surface area, zeta potential, ANFIS, CR-L DYE, AQUEOUS-SOLUTION, NETWORK ANN, WASTE-WATER, ADSORPTION, REMOVAL, OPTIMIZATION, EQUILIBRIUM, PARAMETERS, BEHAVIOR
  • Atatürk Üniversitesi Adresli: Evet

Özet

The breakthrough curves of Reactive Blue 21 were investigated in a fixed-bed column using shells of Yellow Squash. The effects of experimental conditions on the shape of the Reactive Blue 21 breakthrough curves were investigated. Besides, the mechanism of Reactive Blue 21 uptake was explained based on the results of Fourier Transform Infrared Spectroscopy. The electrophoretic mobilities of the particles were measured to obtain information about the biosorption mechanism. Surface area and total pore volume of the particles were obtained as 1.06 m(2)/g and 0.0014 cm(3)/g, respectively. The adaptive neuro-fuzzy inference system model has been applied for the prediction of Reactive Blue 21 breakthrough curves. The highest observed and predicted bed capacities were obtained as 17.565 and 17.606 mg/g. The coefficient of determination and mean squared error for the data set of the model were determined as 0.999 and 0.000085, respectively. (c) 2018 American Institute of Chemical Engineers Environ Prog, 38: S110-S117, 2019