applying pareto design of gmdh-type neural network for solid-liquid equilibrium of binary systems (isotactic poly 1-butene (1)-organic solvents (2))

نویسندگان

hossein ghanadzadeh

allahyar daghbandan

mohammd akbarizadeh

چکیده

isotactic poly (1-butene), ipbu-1, was synthesized by using a metallocene catalyst. the thermodynamic phase behavior of polymer–organic solvents systems is very important in every polymer application.  in this paper, the solid–liquid equilibrium of ipbu-1 with different organic solvents (1-heptyne, cyclo octane) was studied by a mathematical model. by considering the experiments temperature-mole fraction results, phase diagram of the polymer solvent systems could be constructed. the temperature and activity coefficient based on mole fraction phase diagrams were predicted by using pareto genetic design of gmdh-type neural network. the results were very encouraging and congruent with the experimental data.

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عنوان ژورنال:
iranian journal of chemistry and chemical engineering (ijcce)

ناشر: iranian institute of research and development in chemical industries (irdci)-acecr

ISSN 1021-9986

دوره 33

شماره 1 2014

میزبانی شده توسط پلتفرم ابری doprax.com

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