Polymer rheology profoundly influences the intricate dynamics of material extrusion in fused filament fabrication (FFF). This numerical study, which uses the Giesekus model fed with a full rheometric experimental dataset, meticulously examines the molten flow patterns inside the printing nozzle in FFF. Our findings reveal new insight into the interplay between elastic stresses and complex flow patterns, highlighting their substantial role in forming upstream vortices. The parametric map α-λ from the Giesekus model allowed us to sort the materials and connect the polymer rheology with the FFF nozzle flow dynamics. The identification of elastic instabilities, the characterization of flow types, and the correlation between fluid rheology and pressure drop variations mark significant advancements in understanding FFF processes. These insights pave the way for tailored nozzle designs, promising enhanced efficiency and reliability in FFF-based additive manufacturing.

Fused Filament Fabrication is an additive manufacturing technique in which molten thermoplastic polymers are extruded through a nozzle. Therefore, the interplay between the viscoelastic nature of the polymer melt, temperature, printing conditions and nozzle shape may lead to inconsistent extrusion. To improve the extrusion control and optimize the print-head performance, a better understanding of the flow process of the polymer melt both in the nozzle and the liquefier is needed. However, several challenges need to be overcome due to the complexity of gathering experimental data on the melt pressure in the nozzle and the lack of numerical models able to capture the full rheology of the molten polymer. This research introduces an innovative approach for monitoring the pressure within a material extrusion 3D printer's nozzle. This method involves utilizing a pin in direct contact with the molten material, which then transmits the applied force from the material to an externally mounted load cell. The setup provides reliable, repeatable pressure data in steady-state conditions for two nozzle geometries and at different extrusion flows and temperatures. Moreover, the Giesekus model enabled capturing the viscoelastic rheometric features of the melt, and the numerical predictions have been compared with the experimental data. Results show that the numerical model accurately describes the flow conditions in the nozzle and allows the estimation of the behavior of the melt in the liquefier zone, the area of the print-head where the filament is molten. It could be concluded that the backflow, which is the backward flow of the molten polymer in the gap between the filament and the liquefier towards the cold end, caused significant non-linearities in the total pressure drop measured in the feeders, which were related to normal forces induced by shear in that region.

The optimal design seeks the best possible solution(s) for a mechanical structure, device, or system, satisfying a series of requirements and leading to the best performance. In this work, optimized nozzle shapes have been designed for a wide range of polymer melts to be used in extrusion-based additive manufacturing, which aims to minimize pressure drop and allow greater flow control at large extrusion velocities. This is achieved with a twofold approach, combining a global optimization algorithm with computational fluid dynamics for optimizing a contraction geometry for viscoelastic fluids and validating these geometries experimentally. In the optimization process, variable coordinates for the nozzle's contraction section are defined, the objective function is selected, and the optimization algorithm is guided within manufacturing constraints. Comparisons of flow-type and streamline plots reveal that the nozzle shape significantly influences flow patterns. Depending on the rheological properties, the optimized solution either promotes shear or extensional flow, enhancing the material flow rate. Finally, experimental validation of the nozzle performance assessed the actual printing flow, the extrusion force and the overall print control. It is shown that optimizing the nozzle can significantly reduce backflow-related pressure drop, positively impacting total pressure drop (up to 41 %) and reducing backflow effects. This work has real-world implications for the additive manufacturing industry, offering opportunities for increased printing speeds, enhanced productivity.

Material extrusion is an additive manufacturing process in which material is selectively dispensed through a nozzle. In this work, we are focused on fused filament fabrication (FFF) and we intend to analyze the melt flow patterns generated by a commercial version of polycarbonate, modeled by means of a viscoelastic model (Giesekus) based on rheological properties experimentally determined under viscometric flows. The axisymmetric flow through the same longitudinal section nozzle geometry used in the work of Mendes et al. (2019) has been numerically simulated in steady state at a constant temperature using OpenFOAM® (O. Ltd, 2019) and rheoTool (Pimenta and Alves, 2016). The results show that although the extensional flow type is predominant in the fluid domain, the shear-induced normal stress differences are relevant, and even dominating, not only at the exit of the die but also in the tapered region of the nozzle. Shear-induced normal stress differences are responsible for the excess pressure drop, and also for the equilibrium height (H^∗) in the backflow region, where the polymer melt flows upwards, between the solid filament that enters into the print-core and the liquefier wall.

Hypothesis: Our ability to dictate the colloid geometry is intimately related to self-assembly. The synthesis of anisotropic colloidal particles is currently dominated by wet chemistry and lithographic techniques. The wet chemical synthesis offers limited particle geometries at bulk quantities. Lithographic techniques, on the other hand, provide precise control over the particle shape, although at lower yields. In this respect, two-photon polymerization (2PP)¹ has attracted growing attention due to its ability to automatically fabricate complex micro/nano structures with high resolution. Experiments: We manufacture precisely designed colloids with sizes ranging from 1 µm to 10 µm with 2PP and optimize the process parameters for each dimension. Moreover, we study the shape dependent Brownian motion of these particles with video microscopy and estimate their diffusion coefficients. Findings: We observe that increasing the geometrical anisotropy leads to a pronounced deviation from the analytically predicted diffusion coefficient for disks with a given aspect ratio. The deviation is attributed to stronger hydrodynamic coupling with increasing anisotropy. We demonstrate, for the first time, 2PP manufacturing of colloids with tailored geometry. This study opens synthesis of colloidal building blocks to a broader audience with limited access to cleanrooms or wet-chemistry know-how.

Micro-patterned diamond has been investigated for numerous applications, such as biomimetic surfaces, electrodes for cell stimulation and energy storage, photonic structures, imprint lithography, and others. Controlled patterning of diamond substrates and moulds typically requires lithography-based top-down processing, which is costly and complex. In this work, we introduce an alternative, cleanroom-free approach consisting of the bottom-up growth of nanocrystalline diamond (NCD) micropillar arrays by chemical vapour deposition (CVD) using a commercial porous Si membrane as a template. Conformal pillars of ~4.7 μm in height and ~2.2 μm in width were achieved after a maximum growth time of 9 h by hot-filament CVD (2% CH ₄ in H ₂ , 725 °C at 10 mbar). In order to demonstrate one of many possible applications, micropillar arrays grown for 6 h, with ~2 μm in height, were evaluated as moulds for imprint lithography by replication onto hard cyclic olefin copolymer (COC) and onto soft polydimethylsiloxane (PDMS) elastomer. The results showed preserved mechanical integrity of the diamond moulds after replication, as well as full pattern transfer onto the two polymers, with matching dimensions between the grown pillars and the replicated holes. Prior surface treatment of the diamond mould was not required for releasing the PDMS replica, whereas the functionalisation of the diamond surface with a perfluorododecyltrichlorosilane (FDDTS) anti-stiction layer was necessary for the successful release of the COC replica from the mould. In summary, this paper presents an alternative and facile route for the fabrication of diamond micropillar arrays and functional micro-textured surfaces.

The concept and synthesis approach for planar Compliant Fluidic Control Structures (CFCSs), monolithic flexible continua with embedded functional pores, is presented in this manuscript. Such structures are envisioned to find application in biomedicine as tunable microfluidic devices for drug/nutrient delivery. The functional pores enlarge and/or contract upon deformation of the compliant structure in response to external stimuli, facilitating the regulated control of fluid/nutrient/drug transport. A thickness design variable based topology optimization problem is formulated to generate effective designs of these structures. An objective based on hydraulic diameter(s) is conceptualized, and it is extremized using a gradient based optimizer. Both geometrical and material nonlinearities are considered. The nonlinear behaviour of employed hyperelastic material is modeled via the Arruda-Boyce constitutive material model. Large-displacement finite element analysis is performed using the updated Lagrangian formulation in plane-stress setting. The proposed synthesis approach is applied to various CFCSs for a variety of fluidic control functionalities. The optimized designs of various CFCSs with single and/or multiple functional pores are fabricated via a Polydimethylsiloxane (PDMS) soft lithography process, using a high precision 3D printed mold and their performances are compared with the numerical predictions.

The controlled patterning of polymeric surfaces at the micro- and nanoscale offers potential in the technological development of small-scale devices, particularly within the fields of photovoltaics, micro-optics and lab- and organ-on-chip, where the topological arrangement of the surface can influence a system's power generation, optical properties or biological function - such as, in the latter case, biomimicking surfaces or topological control of cellular differentiation.One of the most promising approaches in reducing manufacturing costs and complexity is by exploitation of the self-assembling properties of colloidal particles. Self-assembly techniques can be used to produce colloidal crystals onto surfaces, which can act as replicative masks, as has previously been demonstrated with colloidal lithography, or templates in mold-replication methods with resolutions dependent on particle size. Within this context, a particular emerging interest is focused on the use of self-assembled colloidal crystal surfaces in polymer replication methods such as soft lithography, hot and soft embossing and nano-imprint lithography, offering low-cost and high-resolution alternatives to conventional lithographic techniques.However, there are still challenges to overcome for this surface patterning approach to reach a manufacturing reliability and process robustness comparable to competitive technologies already available in the market, as self-assembly processes are not always 100% effective in organizing colloids within a structural pattern onto the surface. Defects often occur during template fabrication. Furthermore, issues often arise mainly at the interface between colloidal crystals and other surfaces and substrates. Particularly when utilized in high-temperature pattern replication processes, poor adhesion of colloidal particles onto the substrate results in degradation of the patterning template. These effects can render difficulties in creating stable structures with little defect that are well controlled such that a large variety of shapes can be reproduced reliably.This review presents an overview of available self-assembly methods for the creation of colloidal crystals, organized by the type of forces governing the self-assembly process: fluidic, physical, external fields, and chemical. The main focus lies on the use of spherical particles, which are favorable due to their high commercial availability and ease of synthesis. However, also shape-anisotropic particle self-assembly will be introduced, since it has recently been gaining research momentum, offering a greater flexibility in terms of patterning. Finally, an overview is provided of recent research on the fabrication of polymer nano- and microstructures by making use of colloidal self-assembled templates.

The patterning of conductive polymers is a major challenge in the implementation of these materials in several research and industrial applications, spanning from photovoltaics to biosensors. Within this context, we have developed a reliable technique to pattern a thin layer of the conductive polymer poly(3,4-ethylenedioxythiophene) (PEDOT) by means of a low cost and high throughput soft embossing process. We were able to reproduce a functional conductive pattern with a minimum dimension of 1 μm and to fabricate electrically decoupled electrodes. Moreover, the conductivity of the PEDOT films has been characterized, finding that a post-processing treatment with Ethylene Glycol allows an increase in conductivity and a decrease in water solubility of the PEDOT film. Finally, cyclic voltammetry demonstrates that the post-treatment also ensures the electrochemical activity of the film. Our technology offers a facile solution for the patterning of organic conductors with resolution in the micro scale, and can be the basis for the realization and development of polymeric microdevices with electrical and electrochemical functionalities.