Abstract
This study uses the Molecular Operating Environment software (MOE) to generate models to calculate the char yield of polybenzoxazines (PBz). A series of benzoxazine (Bz) monomers were constructed to which a variety of parameters relating to the structure (e.g., water accessible surface, negative van der Waals surface area and hydrophobic volume, etc.) were obtained and a quantitative structure property relationships (QSPR) model was generated. The model was used to generate data for new Bz monomers with desired properties and a comparison was made of predictions based on the QSPR model with the experimental data. This study shows the quality of predictive models and confirms how useful computational screening is prior to synthesis.
Highlights
Thermoset polymers have an established history in civil aviation, in applications involving decorative panels, secondary composite structures and adhesives typically around 90% of the interior furnishings of a typical civil airliner will contain thermoset composites [1]
The development of structural materials with improved thermal stability and fire resistance is key in this area to retard the spread of fire, and modern legislation is leading to the removal of halogenated flame retardants [2]
The training data set that was used in this research was compiled from various papers in the Handbook of Benzoxazine Resins [3]
Summary
Thermoset polymers have an established history in civil aviation, in applications involving decorative panels, secondary composite structures and adhesives typically around 90% of the interior furnishings of a typical civil airliner will contain thermoset composites [1]. In previous work [8] we have examined the thermal modelling of PBZs polymers is a growing area and was reviewed a special edition of theofJournal of stability of cured and investigated the influence of particleinsize and the structure the bisphenyl. We seek tointerested relate theinstructure of the monomer of particular polymer to the physical, the potential to predict structure–property relationships and have hadmechanical some success inproperties using quantitative structure polymer property relationships (QSPR) towards the prediction of e.g., has and thermal of the derived using mathematical methods. This technique glass transition temperature or Katrizky degree of cure [15]. The percentage error and difference error between the two values was calculated and a conclusion was made based on the comparison values
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