Simulations of the material deposition in extrusion-based additive manufacturing Prediction of the strand cross-section as function of the processing parameters Negative linear relationship between the printing force and the printing speed Abstract We propose a numerical model to simulate the extrusion of a strand of semi-molten material on a moving substrate, within the computation fluid dynamics paradigm. According to the literature, the deposition flow of the strands has an impact on the inter-layer bond formation in extrusion-based additive manufacturing, as well as the surface roughness of the fabricated part. Under the assumptions of an isothermal Newtonian fluid and a creeping laminar flow, the deposition flow is controlled by two parameters: the gap distance between the extrusion nozzle and the substrate, and the velocity ratio of the substrate to the average velocity of the flow inside the nozzle. The numerical simulation fully resolves the deposition flow and provides the cross-section of the printed strand. For the first time, we have quantified the effect of the gap distance and the velocity ratio on the size and the shape of the strand. The cross-section of the strand ranges from being almost cylindrical (for a fast printing and with a large gap) to a flat cuboid with rounded edges (for a slow printing and with a small gap), which substantially differs from the idealized cross-section typically assumed in the literature. Finally, we found that the printing force applied by the extruded material on the substrate has a negative linear relationship with the velocity ratio, for a constant gap.

We investigate experimentally and numerically the influence of the processing conditions on the cross-section of a strand printed by material extrusion additive manufacturing. The parts manufactured by this method generally suffer from a poor surface finish and a low dimensional accuracy, coming from the lack of control over the shape of the printed strands. Using optical microscopy, we have measured the cross-sections of the extruded strands, for different layer heights and printing speeds. Depending on the processing conditions, the cross-section of the strand can vary from being almost circular to an elongated rectangular shape with rounded edges. For the first time, we have compared the measurements of strands' cross-sections to the numerical results of a three-dimensional computational fluid dynamics model of the deposition flow. The proposed numerical model shows good agreement with the experimental results and is able to capture the changes of the strand morphology observed for the different processing conditions.

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A computational fluid dynamics model is used to predict the mesostructure formed by the successive deposition of parallel strands in material extrusion additive manufacturing. The numerical model simulates the extrusion of the material onto the substrate. The model takes into account the effect of the presence of the previously extruded material on the shape of the subsequently deposited strands. The simulated mesostructures are compared to optical micrographs of the mesostructures of 3D-printed samples, and the predictions agree well with the experiments. In addition, the influence of the layer thickness, the strand-to-strand distance, and the deposition configuration (with aligned or skewed layers) on the formation of the mesostructure is investigated. The simulations provide detailed information about the porosity, the inter-and intra-layer bond line densities, and the surface roughness of the mesostructures, which potentially can be used in a model-based slicing software.

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Soft and electrically active materials are currently being utilized for intelligent systems, including electronic skin, cybernetics, soft robotics, and wearable devices. However, fabricating materials that fulfill the complex requirements of such advanced applications remains a challenge. These attributes include electronic, adhesive, self-healing, flexible, moldable, printable, and strong mechanical properties. Inspired by the recent interest in transforming monofunctional materials into multifunctional ones through nanoreinforcement and mussel-inspired chemistry, we have designed a simple two-step methodology based on halloysite nanotube (HNT) and polydopamine (PDA) to address the grand challenges in the field. In brief, HNTs were coated with PDA and embedded within a poly(vinyl alcohol) (PVA)-based polymeric matrix in combination with ferric ions (Fe 3+ ). The final composite displayed a 3-fold increase in electrical conductivity, a 20-fold increase in mechanical stiffness, and a 7-fold increase in energy dissipation in comparison to their nonfunctional counterparts, which arose from a combination of nanotube alignment and mussel-inspired chemistry. Moreover, the developed composite could elongate up to 30000% of its original length, maintain its electrical properties after 600% strain, self-heal within seconds (both electrically and mechanically), and display strain-sensitivity. Finally, it was 3D-printable and thus amenable for engineering of customized wearable electronics.

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