Chain-Growth Polymerization Using Monte Carlo Simulation: Termination by Combination

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Both the average and the distribution of molecular weights are major factors in understanding the properties of polymers. It is therefore expedient to apply different approaches to predict the progress of the polymerization process.

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Monte Carlo (MC) simulation is a powerful technique that gives the average molecular weight and molecular weight distribution without the need for solving complicated equations. MC simulation requires only a good understanding of the phenomena inside the reactor and simple programming using random number generators.

In this Demonstration, a basic polymerization process that involves both propagation and termination steps is simulated with the MC technique. The polymeric chain will continue growing until the generated random number falls in range of the termination step. Then the chain stops growing and its length is stored in a matrix. The stored data is later statistically analyzed to determine the number average molecular weight, the polydispersity index (PDI), and the chain length distribution.

As expected, the PDI value is close to 1.5 since the selected termination is by combination.

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Contributed by: Mamdouh Al-Harthi and Housam Binous  (November 2011)
Open content licensed under CC BY-NC-SA


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