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An alternative neural network approach to calculate the molecular weight distribution from dynamic rheological properties of i‐PP resins
Author(s) -
Giudici Reinaldo,
Scuracchio Carlos,
Bretas Rosario E. S.
Publication year - 2000
Publication title -
journal of applied polymer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.575
H-Index - 166
eISSN - 1097-4628
pISSN - 0021-8995
DOI - 10.1002/(sici)1097-4628(20000314)75:11<1416::aid-app14>3.0.co;2-x
Subject(s) - rheology , rheometer , superposition principle , polymer , materials science , tacticity , dynamic mechanical analysis , molar mass distribution , relaxation (psychology) , modulus , gel permeation chromatography , polypropylene , polymer science , range (aeronautics) , polymer chemistry , dynamic modulus , thermodynamics , composite material , polymerization , mathematics , physics , mathematical analysis , psychology , social psychology
The calculation of the molecular weight distribution (MWD) of a polymer from its rheological properties is an attractive method since rheological measurements are comparatively faster and cheaper than the classical gel permeation chromatography technique (GPC). The calculation, however, still has some drawbacks, such as the sensitivity of the mathematical solution involved (ill‐posed problem) and the limited frequency range covered by commercial rheometers, which can be especially critical for crystalline polymers, for which the time–temperature superposition is of limited worth. In this article, a new approach for evaluating the MWD from the storage modulus and the relaxation modulus curves is proposed. The method, based on the use of a neural network model, was employed to evaluate MWD from rheological data obtained with different isotactic polypropylene resins. The results show that this approach can be successfully used to compute MWD curves and should expand the range of application of the rheological technique. © 2000 John Wiley & Sons, Inc. J Appl Polym Sci 75: 1416–1423, 2000