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Reliable simulation of polymers on an atomistic length scale requires a realistic representation of the cured material. A molecular modelling method for the curing of epoxy systems is presented, which is developed with respect to efficiency while maintaining a well equilibrated system. The main criterion for bond formation is the distance between reactive groups and no specific reaction probability is prescribed. The molecular modelling is studied for three different mixing ratios with respect to the curing evolution of reactive Groups and the final curing stage. For the first time, the evolution of reactive groups during the curing process predicted by the molecular modelling is validated with near-infrared spectroscopy data, showing a good agreement between simulation results and experimental measurements. With the proposed method, deeper insights into the curing mechanism of epoxy systems can be gained and it allows us to provide reliable input data for molecular Dynamics simulations of material properties.
Annually vast amounts of plastics are produced world-wide. However, recycling and waste management is still insufficient resulting in large quantities of plastics being released into the environment. Degradation by sunlight, mechanical and biological factors lead to the breakdown of this waste into little fragments. By convention particles smaller than 5 mm are referred to as microplastics (MP). The occurrence of MP has been reported by researchers virtually all around the globe. Gaining knowledge on MP is currently a time-consuming process because analysis mainly relies on micro-infrared and micro-Raman methods. Prior to that the particles need to undergo purification and enrichment. Thus, only small numbers and volumes of samples can be investigated. Here we tested NIR spectroscopy combined with a multivariate data analysis as a means of speeding up the process of MP analysis.
Experiments were performed using the most abundant polymers polyethylene, polypropylene, polyethylene terephthalate and polystyrene. MP samples were obtained by adding the cryomilled and sieved (<125 µm) particles to approximately 1 g of standard soil at 0,5–10 mass%. Spectra were recorded with a fiber optic reflection probe connected to a FT-NIR spectrometer. 5–10 spectra recorded of each sample were used for the calibration of chemometric models (partial least squares regression, PLSR). “Unknown” test samples were then used to test the model’s capability to predict the type and amount of polymer.
In samples containing 1–5 % of the polymers the prediction yielded the highest degree of agreement with the gravimetric reference values. At low polymer loads some false positive results in the identification were observed. Large amounts of polymers limited the prediction capability by a nonlinear behaviour of the absorption. Further testing was done with real world samples such as compost and washing machine filters. Even though the calibration did not account for these highly complex sample compositions, satisfactory results could be achieved.
Epoxy resins are one of the first choices for structural adhesives and are widely used in combination with fibers as fiber reinforced plastics (FRP). The mechanical properties are the result of the complex chemical network structure that is generated by the thermally catalyzed cross linking reaction. Numerical simulations on the atomistic length scale are appropriate tools to understand and improve the mechanical properties and its mechanisms of epoxy resins. This leads to the necessity of a model generation procedure that covers the characteristic cross linking mechanisms of epoxy resins and is able to generate a realistic representation of the network structure. Research in the field of Molecular Dynamic based curing kinematics of polymers has led to cross linking procedures that are based on the main chemical curing reaction and can produce models, whose mechanical properties are in agreement with experimental values. Nevertheless an assessment of the realism of these cross linking procedures is difficult, since various complex aspects, such as the influence of the activator molecules or catalyzing chemical reactions may be important, but are hard to characterize. By using the method of in situ near-infrared spectroscopy (NIR) the time and temperature evolution of the reactive groups, epoxy and either amine or anhydrite curing groups, can be measured. It has been shown that this method is well suited for analyzing the curing process and to characterize the fully hardened epoxy resin. Thus NIR measurements of the cross linking kinetics of epoxy resins give a valuable insight in the curing process that can be used to calibrate and assess numerical approaches of the cross linking procedure. A modeling technique for the curing kinematics of epoxy resins is presented, that is able to realistically represent the cross linking mechanism and generate simulation models with characteristics in good agreement with experimentally analyzed cured epoxy resins. This is achieved by calibrating the cross linking parameters and is shown by a comparison of both, the cross linking procedure and the resulting network structure, with experimental results of NIR measurements. The modeling approach is incorporated in the Molecular Dynamic Finite Element Method (MDFEM) framework and implements a step by step molecular network build-up. This allows to perform MDFEM equilibrium iterations during the curing procedure in order to create realistic and well equilibrated simulation models. Furthermore MDFEM simulations of tensile tests are presented to evaluate the influence of the network structure on the elastic mechanical properties. These numerical tests also illustrate the need for accurate models when deriving material properties from atomistic length scale simulations.
Supernatants from a fermentation process of Pichia pastoris were investigated by Raman spectroscopy. Using partial least squares regression, the principal substrates glycerol and methanol could be predicted, however not the expressed protein. To gain further insight, a priori prepared calibration samples were studied by vibrational-, UV/Vis-, and fluorescence spectroscopy. For the quantification of glycerol and methanol, Raman spectroscopy was identified as the most sensitive technique, and superior to near-infrared spectroscopy, but not for protein contents below 1 g L–1. Both UV/Vis absorption and fluorescence spectroscopy are well suited for the quantification of protein, however, best results were obtained with UV/Vis absorption.