Kinetics study and neural network modeling of degradation of Naphtol Blue Black by electro-Fenton process: effects of anions, metal ions, and organic compound

Auteurs :  Chafia Bouasla, Mohamed El-Hadi SAMAR, Hocine BENDJAMA
Année : 2014
Domaine : Génie Chimique
Type : Article de journal
Revue : Desalination and Water Treatment
Résumé en PDF :  (résumé en pdf)
Fulltext en PDF :  (.pdf)
Mots clés : degradation, Electro-Fenton, Naphtol Blue Black, Artificial neural network

Résumé : 

In the present work, the degradation of azo dye Naphtol Blue Black (NBB) in aqueous solution by electro-Fenton process was investigated. The results indicated that the degradation of NBB by electro-Fenton process followed the second-order reaction kinetics. The experimental results were also modeled by artificial neural network (ANN) with mean squared error of 10-5. This model was developed in Matlab using a feed forward back propagation network; multilayered perceptron. The input variables to the feed-forward neural network were as follows: initial Fe3+ concentration, initial pH, concentration of Na2SO4, temperature, applied current, and initial dye concentration. The degradation efficiency and rate constant were chosen as the experimental responses or output variables. The findings indicated that ANN provided reasonable predictive performance (R2 > 0.99). Effects of additives such as anions, metal ions, and organic compound on the efficiency and on the rate constant of NBB degradation were also studied under optimum conditions.