Open Access

Thermoset materials characterization is often limited to solid state analytical techniques such as IR, NMR, DSC, TGA and mechanical testing. Alternatively, their off-gassing behavior can also be evaluated using GC based techniques such as TD-GC-MS, allowing this method to be applied to thermoset materials analyses such as identification, aging characterization, and formulation optimization. As an overview, common thermoset materials were evaluated by analyzing their gaseous degradation products via TGA-based pyrolysis and subsequent TD-GC-MS for the identification of representative volatile signatures. It is thereby possible to distinguish different classes of phenolic materials or cured epoxy resins, as well as their amine or anhydride curatives. Additionally, this method enabled quantification of a volatile fragment (bisphenol A, BPA) which is associated with oxidation of epoxy/amine thermoset materials. The amount of evolved BPA increased linearly with aging time and this trend exhibits linear Arrhenius behavior over the temperature range (80–125 °C) studied, in agreement with oxidation sensitivies based on oxygen consumption data. Further, TD-GC-MS was used to explore how off-gassing of residual anhydride curative from an epoxy/anhydride material depends on formulation stoichiometry. Even in formulations that theoretically contained enough epoxy to consume all anhydride (1:1 stoichiometry), an imperfect final cure state resulted in residual anhydride which could evolve from the material. For such materials, a slightly epoxy-rich formulation is required to ensure that the material contains no residual unreacted anhydride. Analysis of volatiles generated by thermal exposure is an attractive characterization approach enabling compositional analysis as well as complementary diagnostics for materials degradation.

In this work a novel iterative method for isothermal cure kinetic modelling of an epoxy resin system using differential scanning calorimetry (DSC) technique is presented. To reach the isothermal cure temperature, the sample has to be heated up from ambient temperature. This is commonly done with very high heat-up rates to minimise the time the sample reacts at temperatures other than the desired one. However, during heat up with high heating the amount of released energy rates cannot be measured directly because the shape of baseline is unknown. This means that the cure state at the beginning of the isothermal stage is unknown. For fast curing systems this unknown cure state causes significant inaccuracies in cure kinetics modelling. The presented iterative approach attempts to estimate the released enthalpy during heat-up of an isothermal run through an iterative numerical modelling of the heat-up phase. In each iteration the algorithm starts by estimating the enthalpy released during heat-up based on the recorded temperature profile and the calibrated model of the previous iteration. At the same time, it estimates the degree of cure at the end of the heat-up phase. Once the initial cure state is known the total heat of enthalpy can be recalculated for the current iteration. Subsequently the degree of cure and curing rate are re-evaluated with the newly estimated total enthalpy and used for determining the kinetics parameters. This is done by simultaneous fitting of the selected model to all experimental heat flow curves using a non-linear nonrestricted multivariable fitting method. The model with these new parameters is used again to estimate the released enthalpy and cure degree during the heat-up phase. The described loop is repeated until a predefined convergence criterion is satisfied. For modelling the reaction kinetics, the Kamal–Sourour equation accompanied with Rabinowitch approach to consider the diffusion effects is used. The diffusion reaction rate is modelled by the free volume model proposed by Huguenin and Klein. DiBenedetto model is applied to predict the Evolution of glass transition temperature against the degree of cure. In order to compensate the effect of the Initial values in the model’s calibration, the algorithm is implemented in a routine, which assesses the quality of the fitting and consequently selects the cure kinetics parameter. The described algorithm and the Routine are implemented in MATLAB. This paper demonstrates the application of this approach for using cure kinetics modelling to predict the degree of cure and the glass transition temperature. It supports the obtained results with validation tests using isothermal, dynamic and combined temperature profiles.

Using thermogravimetric analysis (TGA) with a solid-phase adsorber for thermal extraction, followed by subsequently analysing the adsorber with thermo-desorption gas chromatography mass spectrometry (TDS-GC–MS) enables measurement of polymer degradation under oxidizing atmosphere, and the identification of certain complex hydrocarbon degradation products by chromatographic separation and defined mass patterns. This technique, thermal-extraction desorption gas chromatography mass spectrometry (TED-GC–MS) was used to investigate the thermo-oxidative degradation of PA 66 and PA 66 doped with 2 wt% of metal oxide particles. In TGA pure PA 66 formed more residue under an oxidizing atmosphere than an inert one. In contrast to the measurements under inert atmosphere, several condensed aromatic species containing nitrogen could be identified in thermo-oxidative measurements. These degradation products were formed through condensation reactions of primary amides originating from imide hydrolysis. The formation of such highly condensed species also causes higher char formation. Four metal oxides have shown an impact on the thermo-oxidative degradation of PA 66: Fe2O3 on η-Al2O3 < pure Fe2O3 = Fe2O3 on γ-Al2O3 < pure ZnO. For ZnO even a char-stabilizing effect could be observed. A catalytic effect of these metal oxides causes more condensed cyclopentanone and pyridine derivates. Thus, more water is formed and released, resulting in increased hydrolysis of the imides and degradation at lower temperatures.