Kinetic analysis of the thermal degradation of an intumescent fire retardant coated green biocomposite

This study focuses on the thermal degradation behaviour of a newly developed fire retardant coated Green BioComposite (GBC) and its kinetic analyses under inert and oxidative atmosphere. An intumescent fire retarding system comprised of Ammonium PolyPhosphate-Tris (2-HydroxyEthyl) IsoCyanurate (APP-THEIC) and Boric Acid (BA) is used to improve fire retardancy of GBC. Multiples formulations having different proportions of APPTHEIC and boric acid are developed to study the heat shielding effect and morphology of the material. The fire retardant coated GBC is characterised using Thermo Gravimetric Analysis (TGA) and Scanning Electron Microscopy (SEM). TGA showed similar thermal decomposition profile for fire retardant coated specimens except for E/20APP-THEIC/10BA showing reduced decomposition rate after 650 ???C and higher amount of residual char as compared to other coatings. However, SEM images revealed better morphology for E/29APP-THEIC/1BA, which indicates improved thermal insulation to the underlying substrate. The evaluation of the degradation of such materials are quite expensive at industrial scale since the heating rates are extremely high and it was not possible to evaluate the thermal decomposition behaviour of the Intumescent Fire Retardant (IFR) coated GBC directly by TGA at very high heating rates. Therefore, it is imperative to develop predictive models for kinetics of degradation of such materials. In this research study, the controlled and IFR coated GBC has been thermally decomposed at three different heating rates and a predictive model for its kinetics of degradation has been determined. Kinetics Neo software package developed by Netzsch Company is used to establish a kinetic model for the decomposition of controlled and IFR coated green biocomposite. The decomposition mechanism and degradation products of the controlled (uncoated) and IFR coated GBC allowed for the interpretation of the kinetic decomposition models.