Optimization of photocatalytic degradation of red solophenyl direct dye in TiO2 aqueous suspension by application of full factorial experimental design

2014 ◽  
Author(s):  
Akila Benaissa ◽  
Mohammed Bouhelassa
Keyword(s):  
Experimental Design ◽  
Photocatalytic Degradation ◽  
Aqueous Suspension ◽  
Factorial Experimental Design ◽  
Direct Dye ◽  
Full Factorial Experimental Design ◽  
Full Factorial

scholarly journals The Design and Implementation of Adsorptive Removal of Cu(II) from Leachate Using ANFIS

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Nurdan Gamze Turan ◽  
Okan Ozgonenel
Keyword(s):  
Experimental Design ◽  
Contact Time ◽  
Fixed Bed ◽  
Experimental System ◽  
Factorial Experimental Design ◽  
Adsorbent Dosage ◽  
Initial Ph ◽  
Full Factorial Experimental Design ◽  
Full Factorial ◽  
Aqueous Leachate

Clinoptilolite was investigated for the removal of Cu(II) ions from industrial leachate. Adaptive neural fuzzy interface system (ANFIS) was used for modeling the batch experimental system and predicting the optimal input values, that is, initial pH, adsorbent dosage, and contact time. Experiments were studied under laboratory batch and fixed bed conditions. The outcomes of suggested ANFIS modeling were then compared to a full factorial experimental design (23), which was utilized to assess the effect of three factors on the adsorption of Cu(II) ions in aqueous leachate of industrial waste. It was observed that the optimized parameters are almost close to each other. The highest removal efficiency was found as about 93.65% at pH 6, adsorbent dosage 11.4 g/L, and contact time 33 min for batch conditions of 23experimental design and about 90.43% at pH 5, adsorbent dosage 15 g/L and contact time 35 min for batch conditions of ANFIS. The results show that clinoptilolite is an efficient sorbent and ANFIS, which is easy to implement and is able to model the batch experimental system.

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