Recyclability of elastomer toughened recycled poly(ethylene terephthalate): The effect of grinding-extrusion-injection moulding on the mechanical and morphological properties of the blend.

Reprocessing potential of recycled poly(ethylene-terephthalate) (RPET)/ethylene-butyl-acrylate-glycidyl methacrylate (EBA-GMA) blends was investigated. PET flakes from food packaging were compounded with 0, 5, 10, 15 and 20 % EBA-GMA. Injection moulded specimens were produced, and some of the specimens were grinded, and reproduced to simulate real reprocessing. It was revealed by scanning electron microscopy that the distribution and particle size of the elastomer did not change notably after recycling. Noticeable degradation of the polymer matrix was observable after every processing step. Such deterioration of PET resulted in higher crystallinity and rigid amorphous fraction, as found by differential scanning calorimetry, which ultimately led to higher storage modulus, while the notched impact strength and elongation at break decreased. Nevertheless, the mechanical performance of the reprocessed RPET/EBA-GMA blends still significantly outperforms that of the neat PET recyclate. The degree of chain breakage was found to be the primary factor determining the recyclability of RPET/EBA-GMA blends.

Thermal, thermomechanical and structural properties of recycled polyethylene terephthalate (rPET)/waste marble dust composites.

The main objective of this work is to review the capability of using waste marble dust (MD) particles as reinforcing materials in recycled polymeric composites to achieve environmentally friendly materials. In the present study, polymer composites were fabricated from recycled polyethylene terephthalate (rPET) and MD and then analyzed for their structural and thermal properties. Preparation of rPET-based composites containing 0-20 wt% MD was carried out through extrusion and injection molding. For their characterization Fourier transform infrared spectroscopy (FTIR), differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), and dynamic mechanical analysis (DMA) were applied. The DSC analysis revealed a nucleating effect of MD on rPET, which was manifested in a higher crystallization temperature (196.7 °C ⇒ 204.4 °C); however, the marble particles were also found to hamper chain mobility, thereby decreasing the crystallinity ratio (23.7 % ⇒ 19.2 %) of rPET and altering its crystalline structure. According to the TGA measurements, a slight increase occurred in the thermal stability of rPET, its major decomposition temperature increased from 446 °C to 451 °C when 20 wt% MD was incorporated into it. DMA showed an improved stiffness in the entire investigated temperature range for MD-filled composites versus neat rPET. Additionally, several factors were derived from the DMA data, including the effectiveness factor, degree of entanglement, and reinforcing efficiency factor which all suggested a decent interaction between the components indicating a proper reinforcing ability of marble powder. However, above 5 wt% MD content the reinforcing efficiency deteriorated due to the agglomeration of filler particles, which was also supported by scanning electron microscopic images.

Comparing the Performance of Raman and Near-Infrared Imaging in the Prediction of the In Vitro Dissolution Profile of Extended-Release Tablets Based on Artificial Neural Networks.

In this work, the performance of two fast chemical imaging techniques, Raman and near-infrared (NIR) imaging is compared by utilizing these methods to predict the rate of drug release from sustained-release tablets. Sustained release is provided by adding hydroxypropyl methylcellulose (HPMC), as its concentration and particle size determine the dissolution rate of the drug. The chemical images were processed using classical least squares; afterwards, a convolutional neural network was applied to extract information regarding the particle size of HPMC. The chemical images were reduced to an average HPMC concentration and a predicted particle size value; these were used as inputs in an artificial neural network with a single hidden layer to predict the dissolution profile of the tablets. Both NIR and Raman imaging yielded accurate predictions. As the instrumentation of NIR imaging allows faster measurements than Raman imaging, this technique is a better candidate for implementing a real-time technique. The introduction of chemical imaging in the routine quality control of pharmaceutical products would profoundly change quality assurance in the pharmaceutical industry.

Convolutional neural network-based evaluation of chemical maps obtained by fast Raman imaging for prediction of tablet dissolution profiles.

In this work, the capabilities of a state-of-the-art fast Raman imaging apparatus are exploited to gain information about the concentration and particle size of hydroxypropyl methylcellulose (HPMC) in sustained release tablets. The extracted information is utilized to predict the in vitro dissolution profile of the tablets. For the first time, convolutional neural networks (CNNs) are used for the processing of the chemical images of HPMC distribution and to directly predict the dissolution profile based on the image. This new method is compared to wavelet analysis, which gives a quantification of the texture of HPMC distribution, carrying information regarding both concentration and particle size. A total of 112 training and 32 validation tablets were used, when a CNN was used to characterize the particle size of HPMC, the dissolution profile of the validation tablets was predicted with an average f2 similarity value of 62.95. Direct prediction based on the image had an f2 value of 54.2, this demonstrates that the CNN is capable of recognizing the patterns in the data on its own. The presented methods can facilitate a better understanding of the manufacturing processes, as detailed information becomes available with fast measurements.

Development of Flame-Retarded Nanocomposites from Recycled PET Bottles for the Electronics Industry.

Recycled polyethylene-terephthalate (rPET) nanocomposites of reduced flammability were prepared by combining aluminum-alkylphosphinate (AlPi) flame retardant (FR) and natural montmorillonite (MMT), in order to demonstrate that durable, technical products can be produced from recycled materials. During the development of the material, by varying the FR content, the ratio and the type of MMTs, rheological, morphological, mechanical and flammability properties of the nanocomposites were comprehensively investigated. Related to the differences between the dispersion and nucleation effect of MMT and organo-modified MMT (oMMT) in rPET matrix, analyzed by Scanning Electron Microscopy (SEM), Energy Dispersive X-Ray Spectroscopy (EDS) and Differential Scanning Calorimetry (DSC), mechanical properties of the nanocomposites changed differently. The flexural strength and modulus were increased more significantly by adding untreated MMT than by the oMMT, however the impact strength was decreased by both types of nanofillers. The use of different type of MMTs resulted in contradictory flammability test result; time-to-ignition (TTI) during cone calorimeter tests decreased when oMMT was added to the rPET, however MMT addition resulted in an increase of the TTI also when combined with 4% FR. The limiting oxygen index (LOI) of the oMMT containing composites decreased independently from the FR content, however, the MMT increased it noticeably. V0 classification according to the UL-94 standard was achieved with as low as 4% FR and 1% MMT content. The applicability of the upgraded recycled material was proved by a pilot experiment, where large-scale electronic parts were produced by injection molding and characterized with respect to the commercially available counterparts.

Alternative polymer separation technology by centrifugal force in a melted state.

In order to upgrade polymer waste during recycling, separation should take place at high purity. The present research was aimed to develop a novel, alternative separation opportunity, where the polymer fractions were separated by centrifugal force in melted state. The efficiency of the constructed separation equipment was verified by two immiscible plastics (polyethylene terephthalate, PET; low density polyethylene, LDPE), which have a high difference of density, and of which large quantities can also be found in the municipal solid waste. The results show that the developed equipment is suitable not only for separating dry blended mixtures of PET/LDPE into pure components again, but also for separating prefabricated polymer blends. By this process it becomes possible to recover pure polymer substances from multi-component products during the recycling process. The adequacy of results was verified by differential scanning calorimetry (DSC) measurement as well as optical microscopy and Raman spectroscopy.