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A Simple Method for the Reliable Prediction of Char Yield of Polymers
Author(s) -
Atabaki Fariborz,
Keshavarz Mohammad Hossein,
Noorollahy Bastam Naser
Publication year - 2017
Publication title -
zeitschrift für anorganische und allgemeine chemie
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.354
H-Index - 66
eISSN - 1521-3749
pISSN - 0044-2313
DOI - 10.1002/zaac.201700197
Subject(s) - char , polymer , additive function , yield (engineering) , ether , quantitative structure–activity relationship , root mean square , amide , chemistry , mathematics , computational chemistry , organic chemistry , thermodynamics , stereochemistry , pyrolysis , physics , mathematical analysis , quantum mechanics
Two simple models are introduced to predict the char yield of different polymers. The first model is based on the basis of the number of some atoms in the repeat units that may contain chemical groups/moieties such as methyl, phenyl, carbonyl, ether, amide, and ester. The second model uses some molecular fragments beside elemental composition to derive more reliable correlation. In contrast to available Quantitative Structure – Property Relationships (QSPR) methodology, there is no need to use complex molecular descriptors, computer codes and expert users. Two models were constructed on the basis of the measured char yield of 111 polymers and compared with the predicted results of group additivity method. The root mean square (RMS) deviations of the first and second models are 12.6 and 7.2, which are lower than those predicted by two group additivity methods, i.e. 16.3. The new models were tested for 11 new synthesized polymers, where the RMS values are lower than those obtained by group additivity method.