435362 Artificial Neural Network Modeling of Alpha-Alkene Polymerization with Zirconocene/MAO Catalyst

Monday, November 9, 2015
Exhibit Hall 1 (Salt Palace Convention Center)
Nikhil Prakash, Chemical Engineering Department, Sant Longowal Institute of Engineering & Technology (SLIET), Sangrur (Punjab), India

Polyolefins, the generic name for synthetic polymers based on ethylene, propylene, and α olefins, have become the world’s most common synthetic polymers. The development of new metallocene catalysts allows producing plastics with properties that can be accurately designed; copolymers with controlled molecular weight and monomer sequence distribution, polyolefins with isotactic, syndiotactic, stereoblock or hemiisotactic structures.[1]

A neural network (NN), in the case of artificial neurons called artificial neural network (ANN) is an interconnected group of artificial neurons that uses a mathematical or computational model for information processing based on a connectionistic approach to computation. In most cases an ANN is an adaptive system that changes its structure based on external or internal information that flows through the network. NNs are non-linear statistical data modeling tools. The use of neural networks (NNs) has become increasingly popular for applications where the mechanistic description of the interdependence of dependent and independent variables is either unknown or very complex.[2]

In this work, neural network approach is used to investigate the effect of reaction variables for slurry phase homopolymerization of propene with Me2Si(2-Me-Ind)2ZrCl2-MAO catalytic system. The experimental data were taken from Palza et al.[3] The effect of temperature, propylene concentration (pressure), cocatalyst-catalyst ratio, and catalyst concentration on catalyst productivity and molecular weight of the polymer has been studied using neural network approach in MATLAB® 7.0 software.[4]



[1] Bubeck R.A., Mater. Sc. and Eng. R: Reports, 39 :1, p. 1–28 (2002).

[2] Fernandes F. A. N. and Lona L. M.F., Brazilian Journal of Chemical Engineering, 22: 03, p. 401-418 (2005).

[3] Palza H., Velilla T. and Quijada R., Polymer-Plastics Technology and Engineering, 45:1, p. 85- 94.(2006).

[4] MATLAB®  version 7.0.1, 2004, computer software, The MathWorks, Inc., Natick, Massachusetts.

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