Experimental Study and Artificial Neural Networks Simulation of Activated Carbon Synthesis in Fluidized Bed Reactor

Abstract

In this work, thermal activation of pistachio shell was studied in a fluidized bed reactor. The effects of operating conditions on the pore development within the char particles were studied experimentally. The results showed that activation temperature, residence time, oxidizing gas type and concentration have main effects on the Iodine adsorption capacity of the product. The highest surface area was obtained using steam activation at temperature 850°C for 45 min. The synthesis process was also simulated using artificial neural networks (ANNs) to estimate the Iodine number of the product. The present work applied a Tan-sigmoid transfer function in three layers in the feed forward neural network with back propagation algorithm. The results of the network are in good agreement with the experimental data with a maximum relative deviation of 0.015%.