Abstract
Polyphosphonates and polyphosphates having good flame retardancy represent an important class of organophosphorus based polymer additives. In this analysis the flammability of 28 previously synthesized polyphosphoesters, modelled as dimmers, was explored using the multiple linear regression (MLR) and Partial Least Square (PLS) methodology. The statistical quality of the final MLR and PLS models was estimated using the following parameters: the squared correlation coefficient ( r t r a i n i n g 2= 0.917 and 0.976), the training root-mean-square errors (RMSEtr = 0.029 and 0.016) and the leave-seven-out cross-validation correlation coefficient ( q L 7 O 2= 0.748 and 0.881), respectively. External validation was checked for a test set of seven compounds using several criteria. The MLR models had somewhat inferior fitting results. The final MLR and PLS models can be used for the estimation of limiting oxygen index (LOI) values of new polyphosphoester structures. The presence of phosphonate groups and increasing molecular branching in an isomeric series favour the dimer flammability.
Highlights
An important feature of most commercial polymers is the flammability mechanism of polyphosphoesters[6] dimers.to be non-flammable or flame retardant[1]
The Multiple linear regression (MLR) and partial least squares (PLS) models developed for this series of dimer phosphoesters will be helpful to predict the limiting oxygen index (LOI) values of new untested compounds
Better statistical results and a more stable model to simulate polymer flammability were noticed in case of the RR dataset compared to the others, the presence of R chiral centre at the phosphorous atom being important for the dimer flammability
Summary
An important feature of most commercial polymers is the flammability mechanism of polyphosphoesters[6] dimers. To be non-flammable or flame retardant[1]. Other polymer This parallel approach gives the opportunity to compare the properties, like as: glass transition temperature, thermal quality of results supplied by the two methodologies. Decomposition temperature, etc., have been previously studied by quantitative structure-property relationships[2,3]
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