Fused deposition modeling with polypropylene

This paper addresses the potential of polypropylene (PP) as a candidate for fused deposition modeling (FDM)-based 3D printing technique. The entire filament production chain is evaluated, starting with the PP pellets, filament production by extrusion and test samples printing. This strategy enables a true comparison between parts printed with parts manufactured by compression molding, using the same grade of raw material. Printed samples were mechanically characterized and the influence of filament orientation, layer thickness, infill degree and material was assessed. Regarding the latter, two grades of PP were evaluated: a glass-fiber reinforced and a neat, non-reinforced, one. The results showed the potential of the FDM to compete with conventional techniques, especially for the production of small series of parts/components; also, it was showed that this technique allows the production of parts with adequate mechanical performance and, therefore, does not need to be restricted to the production of mockups and prototypes.

Dispersion of fillers in viscoelastic polymer matrices using Eulerian-Lagrangian approaches

Understanding the behavior of c omplex composite materials using mixing procedures is fundamental in several industrial processes. For instance, polymer composites are usually manufactured using dispersion of fillers in polymer melt matrices. The success of the filler dispersion depends both on the complex flow patterns generated and on the polymer melt rheological behavior. Consequently, the availability of a numerical tool that allow to model both fluid and particle would be very useful to increase the process insight. Nowadays there ar e computational tools that allow modeling the behavior of filled systems, taking into account both the behavior of the fluid (Computational Rheology) and the particles (Discrete Element Method). One example is the DPMFoam solver of the OpenFOAM ® framework where the averaged volume fraction momentum and mass conservation equations are used to describe the fluid (continuous phase) rheology, and the Newton’s second law of motion is used to compute the particles (discrete phase) movement. In this work the refer red solver is extended to take into account the elasticity of the polymer melts for the continuous phase. The solver capabilities will be illustrated by studying the effect of the fluid rheology on the filler dispersion, taking into account different fluid types (generalized Newtonian or viscoelastic) and particles volume fraction and size. The results obtained are used to evaluate the relevance of considering the fluid complex rheology for the prediction of the composites morphology

Understanding the dispersion of fillers in polymer matrices

Understanding the mixing process of complex composite materials is fundamental in several industrial processes. For instance, the dispersion of fillers in polymer melt matrices is commonly employed to manufacture polymer composites, using a twin-screw extruder. The effectiveness of the filler dispersion depends not only on the complex flow patterns generated, but also on the polymer melt rheological behavior. Therefore, the availability of a numerical tool able to predict mixing, taking into account both fluid and particles phases would be very useful to increase the process insight, and thus provide useful guidelines for its optimization. In this work, a new Eulerian-Lagrangian numerical solver is developed OpenFOAM® computational library, and used to better understand the mechanisms determining the dispersion of fillers in polymer matrices. Particular attention will be given to the effect of the rheological model used to represent the fluid behavior, on the level of dispersion obtained. For the Eulerian phase the averaged volume fraction governing equations (conservation of mass and linear momentum) are used to describe the fluid behavior. In the case of the Lagrangian phase, Newton’s second law of motion is used to compute the particles trajectories and velocity. To study the effect of fluid behavior on the filler dispersion, several systems are modeled considering different fluid types (generalized Newtonian or viscoelastic) and particles volume fraction and size. The results obtained are used to correlate the fluid and particle characteristics on the effectiveness of mixing and morphology obtained.

Improvign mixing processes with the help of numerical tools

In several industrial applications, highly complex behaviour materials are used together with intricate mixing processes, which difficult the achievement of the desired properties for the produced materials. This is the case of the well-known dispersion of nano-sized fillers in a melt polymer matrix, used to improve the nanocomposite mechanical and/or electrical properties. This mixing is usually performed in twin-screw extruders, that promote complex flow patterns, and, since an in loco analysis of the material evolution and mixing is difficult to perform, numerical tools can be very useful to predict the evolution and behaviour of the material. This work presents a numerical based study to improve the understanding of mixing processes. Initial numerical studies were performed with generalized Newtonian fluids, but, due to the null relaxation time that characterize this type of fluids, the assumption of viscoelastic behavior was required. Therefore, the polymer melt was rheologically characterized, and, a six mode Phan-Thien-Tanner and Giesekus models were used to fit the rheological data. These viscoelastic rheological models were used to model the process. The conclusions obtained in this work provide additional and useful data to correlate the type and intensity of the deformation history promoted to the polymer nanocomposite and the quality of the mixing obtained.

Impact performance prediction of injection-molded talc-filled polypropylene through thermomechanical environment assessment

Due to the fact that different injection molding conditions tailor the mechanical response of the thermoplastic material, such effect must be considered earlier in the product development process. The existing approaches implemented in different commercial software solutions are very limited in their capabilities to estimate the influence of processing conditions on the mechanical properties. Thus, the accuracy of predictive simulations could be improved. In this study, we demonstrate how to establish straightforward processing-impact property relationships of talc-filled injection-molded polypropylene disc-shaped parts by assessing the thermomechanical environment (TME). To investigate the relationship between impact properties and the key operative variables (flow rate, melt and mold temperature, and holding pressure), the design of experiments approach was applied to systematically vary the TME of molded samples. The TME is characterized on computer flow simulation outputsanddefined bytwo thermomechanical indices (TMI): the cooling index (CI; associated to the core features) and the thermo-stress index (TSI; related to the skin features). The TMI methodology coupled to an integrated simulation program has been developed as a tool to predict the impact response. The dynamic impact properties (peak force, peak energy, and puncture energy) were evaluated using instrumented falling weight impact tests and were all found to be similarly affected by the imposed TME. The most important molding parameters affecting the impact properties were found to be the processing temperatures (melt andmold). CI revealed greater importance for the impact response than TSI. The developed integrative tool provided truthful predictions for the envisaged impact properties.

Phase morphology and crystallinity of poly(vinylidene fluoride)/poly(ethylene oxide) piezoelectric blend membranes

Polymer blends based on poly(vinylidene fluoride), PVDF and poly(ethylene oxide), PEO, with varying compositions have been prepared by solvent casting, the polymer blend films being obtained from solutions in dimethyl formamide at 70ºC. Under these conditions PVDF crystallizes from solution while PEO remains in the molten state. Then, PEO crystallizes from the melt confined by PVDF crystalls during cooling to room temperature. PVDF crystallized from DMF solutions adopt predominantly the electroactive β-phase (85%). Nevertheless when PEO is introduced in the polymer blend the β-phase content decreases slightly to 70%. The piezoelectric coefficient (d33) in pristine PVDF is -5 pC/N and decreases with increasing PEO content in the PVDF/PEO blends. Blend morphology, observed by electron and atomic force microscopy, shows the confinement of PEO between the already formed PVDF crystals. On the other hand the sample contraction when PEO is extracted from the blend with water (which is not a solvent for PVDF) allows proving the co-continuity of both phases in the blend. PEO crystallization kinetics have been characterized by DSC both in isothermal and cooling scans experiments showing important differences in crystalline fraction and crystallization rate with sample composition.

One-step in situ synthesis of polyamide microcapsules with inorganic payload and their transformation into responsive thermoplastic composite materials

Well-dispersed loads of finely powdered metals, metal oxides, several carbon allotropes or nanoclays are incorporated into highly porous polyamide 6 microcapsules in controllable amounts via an original one-step in situ fabrication technique. It is based on activated anionic polymerization (AAP) of ε-caprolactam in a hydrocarbon solvent performed in the presence of the respective micro- or nanosized loads. The forming microcapsules with typical diameters of 25-50 µm entrap up to 40 wt% of load. Their melt processing produces hybrid thermoplastic composites. Mechanical, electric conductivity and magnetic response measurements show that transforming of in situ loaded microcapsules into composites by melt processing (MP) is a facile and rapid method to fabricate materials with high mechanical resistance and electro-magnetic characteristics sufficient for many industrial applications. This novel concept requires low polymerization temperatures, no functionalization or compatibilization of the loads and it is easy to scale up at industrial production levels.

Assessing the application of polypropylene multifilament yarns in brain phantoms

The currently available clinical imaging methods do not provide highly detailed information about location and severity of axonal injury or the expected recovery time of patients with traumatic brain injury [1]. High-Definition Fiber Tractography (HDFT) is a novel imaging modality that allows visualizing and quantifying, directly, the degree of axons damage, predicting functional deficits due to traumatic axonal injury and loss of cortical projections. This imaging modality is based on diffusion technology [2]. The inexistence of a phantom able to mimic properly the human brain hinders the possibility of testing, calibrating and validating these medical imaging techniques. Most research done in this area fails in key points, such as the size limit reproduced of the brain fibers and the quick and easy reproducibility of phantoms [3]. For that reason, it is necessary to develop similar structures matching the micron scale of axon tubes. Flexible textiles can play an important role since they allow producing controlled packing densities and crossing structures that match closely the human crossing patterns of the brain. To build a brain phantom, several parameters must be taken into account in what concerns to the materials selection, like hydrophobicity, density and fiber diameter, since these factors influence directly the values of fractional anisotropy. Fiber cross-section shape is other important parameter. Earlier studies showed that synthetic fibrous materials are a good choice for building a brain phantom [4]. The present work is integrated in a broader project that aims to develop a brain phantom made by fibrous materials to validate and calibrate HDFT. Due to the similarity between thousands of hollow multifilaments in a fibrous arrangement, like a yarn, and the axons, low twist polypropylene multifilament yarns were selected for this development. In this sense, extruded hollow filaments were analysed in scanning electron microscope to characterize their main dimensions and shape. In order to approximate the dimensional scale to human axons, five types of polypropylene yarns with different linear density (denier) were used, aiming to understand the effect of linear density on the filament inner and outer areas. Moreover, in order to achieve the required dimensions, the polypropylene filaments cross-section was diminished in a drawing stage of a filament extrusion line. Subsequently, tensile tests were performed to characterize the mechanical behaviour of hollow filaments and to evaluate the differences between stretched and non-stretched filaments. In general, an increase of the linear density causes the increase in the size of the filament cross section. With the increase of structure orientation of filaments, induced by stretching, breaking tenacity increases and elongation at break decreases. The production of hollow fibers, with the required characteristics, is one of the key steps to create a brain phantom that properly mimics the human brain that may be used for the validation and calibration of HDFT, an imaging approach that is expected to contribute significantly to the areas of brain related research.

Impressão FDM de pares de materiais funcionais

Dissertação de mestrado integrado em Engenharia de Materiais

Targeting lactate transport suppresses in vivo breast tumour growth.

BACKGROUND Most cancers, including breast cancer, have high rates of glucose consumption, associated with lactate production, a process referred as "Warburg effect". Acidification of the tumour microenvironment by lactate extrusion, performed by lactate transporters (MCTs), is associated with higher cell proliferation, migration, invasion, angiogenesis and increased cell survival. Previously, we have described MCT1 up-regulation in breast carcinoma samples and demonstrated the importance of in vitro MCT inhibition. In this study, we performed siRNA knockdown of MCT1 and MCT4 in basal-like breast cancer cells in both normoxia and hypoxia conditions to validate the potential of lactate transport inhibition in breast cancer treatment. RESULTS The effect of MCT knockdown was evaluated on lactate efflux, proliferation, cell biomass, migration and invasion and induction of tumour xenografts in nude mice. MCT knockdown led to a decrease in in vitro tumour cell aggressiveness, with decreased lactate transport, cell proliferation, migration and invasion and, importantly, to an inhibition of in vivo tumour formation and growth. CONCLUSIONS This work supports MCTs as promising targets in cancer therapy, demonstrates the contribution of MCTs to cancer cell aggressiveness and, more importantly, shows, for the first time, the disruption of in vivo breast tumour growth by targeting lactate transport.

Modelação de governo electrónico para países emergentes: O caso de São Tomé e Príncipe

Tese de Doutoramento em Tecnologias e Sistemas de Informação