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Glass fiber reinforced polyamide (PA) 6T/DT flame retarded with aluminum diethylphosphinate (AlPi) was tested to assess its flame retardant properties. Models for the decomposition of PA 6T/DT with and without AlPi are presented. Thermal decomposition was measured by performing TGA with Fourier transform infrared (FTIR) spectroscopy and FTIR spectroscopy in the condensed phase. Fire behavior was studied using a cone calorimeter and flammability was tested with UL 94 and the limiting oxygen index. AlPi works as an effective flame retardant for glass fiber reinforced PA 6T/DT materials, acting in the gas phase. Also observed was condensed-phase action, which occurs especially under oxidative conditions before the samples ignite.
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.
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.
In recent years, an increasing trend towards investigating and monitoring the contamination of the environment by microplastics (MP) (plastic pieces < 5 mm) has been observed worldwide. Nonetheless, a reliable methodology that would facilitate and automate the monitoring of MP is still lacking. With the goal of selecting practical and standardized methods, and considering the challenges in microplastics detection, we present here a critical evaluation of two vibrational spectroscopies, Raman and Fourier transform infrared (FTIR) spectroscopy, and two extraction methods: thermal extraction desorption gas chromatography mass spectrometry (TED-GC-MS) and liquid extraction with subsequent size exclusion chromatography (SEC) using a soil with known contents of PE, PP, PS and PET as reference material. The obtained results were compared in terms of measurement time, technique handling, detection limits and requirements for sample preparation. The results showed that in designing and selecting the right methodology, the scientific question that determines what needs to be understood is significant, and should be considered carefully prior to analysis. Depending on whether the object of interest is quantification of the MP particles in the sample, or merely a quick estimate of sample contamination with plastics, the appropriate method must be selected. To obtain overall information about MP in environmental samples, the combination of several parallel approaches should be considered.
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.
Near-infrared spectroscopy (NIR) turned out to be well suited for analyzing the degree of cure for epoxy systems. In contrast to dynamic scanning calorimetry (DSC), where the released heat of reaction determines the degree of epoxy conversion indirectly, NIR spectroscopy is able to determine the conversion directly by analyzing structural changes. Therefore, a new heatable NIR cell was equipped with an integrated thermocouple, which enables the real sample temperature to be controlled and monitored in situ during epoxy curing. Dynamic scans at different heating rates were used for kinetic modelling, to define kinetic parameters and to predict real curing processes. The kinetic models and their parameters were validated with an isothermal and a more complex multi-step curing scenario. Two available commercial epoxy systems based on DGEBA were used with an anhydride and with an amine hardener. NIR results were compared with DSC data. The simulated conversion predicted with a model fitted on the basis of NIR and DSC dynamic scans showed good agreement with the conversion measured in the isothermal curing validation test. Due to the proven reliability of NIR in measuring the reaction progress of curing, it can be considered a versatile measurement system for in situ monitoring of component production in the automotive, aerospace and wind energy sectors.
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 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.
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.