Artificial Neural Network Modelling for the Removal of Fe (III) from Aqueous Solutions Using Chitosan Magnetite Nano Composites (CMNs)

Abstract

Journal of Advanced Chemical EngineeringJ o ur nal of A d v a n ce d Che m ic a l E ng ineer in g AbstractA two-layer Artificial Neural Network (ANN) model was engendered to soothsay the deliberation efficacy of Fe (II) particles from fluid arrangement utilizing chitosan magnetite nano composites (CMNs). The sorbet stock arrangement was yare by dissolving a pre-computed amount of FeCl 3 in twofold refined water to give last fixation 100 mgl −1 . The stock arrangement was debilitated to get standard arrangements with fixation in the scope of 5-30 mgl −1 and their last pH was transmuted in accordance with 4.5. Fifty millilitres of FeCl 3 arrangement of fancied focus was put in a 125 ml Erlenmeyer flagon containing 0.02 g of CMN sorbent. A period of 3 hours was discovered adequate to accomplish the balance. The ANN model was intended to suspect sorption efficacy of CMNs for target metal particle by amalgamating back spread (BP) with guideline segment examination. A sigmoid axon was utilized as exchange capacity for information and yield layer. The Levenberg-Marquardt calculation (LMA) was connected, giving a base estimation of mean squared mistake (MSE) for preparing and cross approbation at the 6th place of decimal.

Magnetic Bagasse Pith as an Efficient Adsorbent for Toxic Dyestuffs (Preparation, Characterization, and Application)

“…A heterogeneous surface characteristic is observed with various particles shape and size. The presence of fibrous (high aspect ratio) particles in pith image is another notable aspect; this may be due to the known limitation of sieve to hold fibrous particles that pass sieve longitudinally [12].…”