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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.
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.
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 order to determine the relevance of microplastic particles in various environmental media, comprehensive investigations are needed. However, no analytical method exists for fast identification and quantification. At present, optical spectroscopy methods like IR and RAMAN imaging are used. Due to their time consuming procedures and uncertain extrapolation, reliable monitoring is difficult. For analyzing polymers Py-GC-MS is a standard method. However, due to a limited sample amount of about 0.5 mg it is not suited for analysis of complex sample mixtures like environmental samples. Therefore, we developed a new thermoanalytical method as a first step for identifying microplastics in environmental samples. A sample amount of about 20 mg, which assures the homogeneity of the sample, is subjected to complete thermal decomposition. The specific degradation products of the respective polymer are adsorbed on a solid-Phase adsorber and subsequently analyzed by thermal Desorption gas chromatography mass spectrometry. For certain identification, the specific degradation products for the respective polymer were selected first. Afterwards real environmental samples from the aquatic (three different rivers) and the terrestrial (bio gas plant) systems were screened for microplastics. Mainly polypropylene (PP), polyethylene (PE) and polystyrene (PS) were identified for the samples from the bio gas plant and PE and PS from the rivers. However, this was only the first step and quantification measurements will follow.
Analysis of microplastic particles (MP) in environmental samples needs sophisticated techniques and is time intensive due to sample preparation and detection. An alternative to the most common (micro ) spectroscopic techniques, FTIR or Raman spectroscopy, are the thermoanalytical methods, where specific decomposition products can be analyzed as marker compounds for different kind of plastics types and mass contents. Thermal extraction desorption gas chromatography mass spectrometry (TED-GC-MS) allows the fast identification and quantification of MP in environmental samples without sample preparation. Whereas up to now only the analysis of thermoplastic polymers was realized, this is the first time that even the analysis of tire wear (TW) content in environmental samples is possible. Various marker compounds for TW were identified. They include characteristic decomposition products of elastomers, antioxidants and vulcanization agents. Advantages and drawbacks of these marker substances were evaluated. Environmental samples from street run off were exemplarily investigated and presented.
Due to the high molecular weights the analysis of polymers is difficult to carry out. Their dissolution is usually limited and the vapor pressure is very low. However, the degradation of a polymer leads usually to smaller compounds which then enable volatile analysis to aid in the characterization of the degradation or decomposition mechanism. The type and the amount of these smaller degradation products is characteristic for the momentary stage of the degradation process.
With thermal desorption coupled to gas chromatography with mass spectrometry (TDS-GC-MS) the polymers can be heated from ambient temperatures to approximately 300 °C. During the heating process small volatile products with a molecular mass up to 350 - 400 m/z were first cryogenic trapping, reheated under controlled conditions and finally separated through a chromatographic column and identified with mass spectrometry. For instance clear differences in the released volatile species of Polypropylene (PP) can be observed depending on the progress of accelerated aging.
In combination with a Thermogravimetric analyzer (TGA) the samples can be heated up to 1000 °C under inert as well oxidative atmosphere. This leads to a complete thermal-pyrolytic or thermo-oxidative degradation of the whole material and a release of degradation fragments over a range of Mw. These fragments enable conclusions for the underlying degradation or decomposition pathways. For coupling to GC-MS a solid-phase adsorption agent can be coupled to the exhaust of the TGA. This adsorption agent is usually a PDMS species that is capable to adsorb compounds with a wide range of polarities. After the thermal extraction the solid-phase adsorption agent will be analyzed by TDS-GC-MS. Therefore, it is possible to determine the species and amounts of the released complex thermal or thermo-oxidative degradation products in detail. This approach offers overall advantageous over existing volatile analytical methods.
Thus, it was possible to determine new thermal and thermo-oxidative degradation mechanism pathways of a well-known material like Polyamide 66 (PA 66). Further example is the unique analysis of small polymer particles, which can be identified and quantified in complex environmental samples. This is our current focus of R&D activities within the framework of the analysis of microplastics in the environment. In the present work we will present a new, automatized set up of this method.
n order to determine the relevance of microplastic particles in various environmental media, comprehensive investigations are needed. However, no analytical method exists for fast identification and quantification. At present, optical spectroscopy methods like IR and RAMAN imaging are used. Due to their time consuming procedures and uncertain extrapolation, reliable monitoring is difficult. For analyzing polymers Py-GC-MS is a standard method. However, due to a limited sample amount of about 0.5 mg it is not suited for analysis of complex sample mixtures like environmental samples. Therefore, we developed a new thermoanalytical method as a first step for identifying microplastics in environmental samples. A sample amount of about 20 mg, which assures the homogeneity of the sample, is subjected to complete thermal decomposition. The specific degradation products of the respective polymer are adsorbed on a solid-phase adsorber and subsequently analyzed by thermal desorption gas chromatography mass spectrometry. For certain identification, the specific degradation products for the respective polymer were selected first. Afterwards real environmental samples from the aquatic (three different rivers) and the terrestrial (bio gas plant) systems were screened for microplastics. Mainly polypropylene (PP), polyethylene (PE) and polystyrene (PS) were identified for the samples from the bio gas plant and PE and PS from the rivers. However, this was only the first step and quantification measurements will follow.
Der Fänger im Spülgas
(2015)