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- Curing kinetics (2)
- Analysis (1)
- Automation (1)
- DSC (1)
- Degradation signatures (1)
- Differential scanning calorimetry (DSC) (1)
- Epoxy resin (1)
- Epoxy resins (1)
- In situ near-infrared (NIR) spectroscopy (1)
- Isothermal (1)
Organisationseinheit der BAM
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.
The TED-GC-MS analysis is a two-step method. A sample is first decomposed in a thermogravimetric analyzer (TGA) and the gaseous decomposition products are then trapped on a solid-phase adsorber. Subsequently, the solid-phase adsorber is analyzed with thermal desorption gas chromatography mass spectrometry (TDU-GC-MS). This method is ideally suited for the analysis of polymers and their degradation processes. Here, a new entirely automated System is introduced which enables high sample throughput and reproducible automated fractioned collection of decomposition products. Strengths and limitations of the system configuration are elaborated via three examples focused on practical challenges in materials analysis and identification: i) separate analysis of the components of a wood-plastic-composite material, ii) quantitative determination of weight concentration of the constituents of a polymer blend and iii) quantitative analysis of model samples of microplastics in suspended particulate matter.
Non-isothermal heating rate kinetics was applied to two epoxy resin systems. In situ near-infrared (NIR) measurements were taken with a heatable NIR cell which allowed the cure to be monitored by characteristic absorption bands. An autocatalyzed reaction of the nth order was shown to describe the epoxy conversion curves. Differential Scanning Calorimetry (DSC) was used as a complementary method. The kinetic models developed by both NIR and DSC are in good accordance with experimental epoxy conversion in the in situ NIR setup for single and multiple cure temperature ramps.
A linear calibration curve of the characteristic absorption bands of epoxy normalized to aromatic vibrations was introduced. The curing degree of structural epoxies that were cured according to an industrial temperature cure profile was determined by NIR using the calibration curve. The epoxy conversions of the structural components showed good agreement with the experimental in situ NIR. Several degrees of cure for structural specimens were evaluated by NIR and residual reaction enthalpy by DSC. We present the non-destructive NIR spectroscopy as an alternative to determine fast and non-destructive epoxy conversion, particularly suitable for high degrees of cure on structural components.
Durch den stetig steigenden Einsatz von Plastikprodukten sind unerwünschte Kunststofffunde in verschiedenen Umweltmatrices mittlerweile allgegenwärtig. Besonderes Interesse erfahren die Kunststoffpartikel von einer Größe kleiner 5 mm, sogenannte Mikroplastik (MP) Partikel. Es werden aktuell Risiken für Mensch und Umwelt diskutiert, die von diesen Partikeln ausgehen.
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.