Pyrolysis model development for a polymeric material containing multiple flame retardants: Relationship between heat release rate and material composition

This work details an approach to the development of a model of polymeric material fire behavior and its relation to flame retardant content. This approach employs a new controlled atmosphere pyrolysis apparatus to measure mass loss rate, back surface temperature, and sample shape profile evolution for 0.07-m-diameter disk-shaped samples exposed to well-defined radiant heating. Interpretation of these measurements using a thermal decomposition reaction mechanism, derived from thermal analysis experiments, and a numerical pyrolysis model, ThermaKin, yields properties that define heat and mass transport in the pyrolyzing solids. In the current study, this approach was extended to the analysis of flame retardant materials and applied to a set of materials comprised of glass-fiber-reinforced polybutylene terephthalate blended with aluminum diethyl phosphinate and melamine polyphosphate. Additionally, this work found evidence of so-called “wick” effect through which the molten polymer, when blended with glass fiber, was observed to be transported from regions of higher concentration to regions of lower concentration. Incorporation of the wick effect into the pyrolysis model was required to correctly capture the pyrolysis dynamics. The resulting pyrolysis model was found to be capable of predicting mass loss rate data as a function of material composition and external radiative heat fluxes ranging from 30 to 60 kW m−2 with an average error of 15%. Using heats of complete combustion of gaseous decomposition products determined in an earlier work, idealized cone calorimetry simulations were conducted to show that, when the gas-phase combustion inhibition effect is excluded, aluminum diethyl phosphinate has a relatively minor impact on the heat release rate, while the impact of melamine polyphosphate is significant. This work demonstrates, for the first time, that it is possible to establish a quantitative relation between the burning rate and material composition and thus, enables intelligent design of flame retardant materials tailored for specific applications.