Additive manufacturing (AM) has revolutionized the production of intricate 3D designs, emphasizing sustainable and customized solutions. The prevailing trend prioritizes sustainable devices that optimize the use of raw materials. Among such innovations, the additive manufacturing of prostheses incorporating strain sensors using NiTi shape memory alloys (SMAs) stands out, particularly in hip prostheses. SMAs, renowned for their superelasticity, showcase a consistent relationship between deformation and electrical resistivity. This unique property allows precise movement assessment throughout the lifecycle of a prosthesis. Our research highlights the significance of integrating strain sensors in the AM process of prostheses. While the assembly and testing of the prosthesis and sensor coupling were prototypical and necessitated further development for practical application tests, there is evidence indicating that the device holds significant potential for monitoring the lifespan of the prosthesis and predicting undesired failures in advance. Hence, the correlation between amplitude variation and electrical resistivity in the NiTi wire is emphasized, indicating its potential as a strain gauge for detecting dislocation in prosthetic implants. Moreover, it underscores the necessity for supplementary analysis, with a specific focus on investigating the high-cycle fatigue behavior, to acquire comprehensive insights into the NiTi wire performance as a sensor over extended periods of use.

Additive manufacturing (AM) technologies are revolutionising the production of complex and customised components. Despite these geometric innovations, the microstructure of these ‘new’ materials has posed a major obstacle to the widespread adoption of these technologies in novel applications. However, understanding the microstructural evolution during mechanical loading is necessary to elucidate the mechanisms and implications of using AM 3D objects in critical applications. This study uses in-situ synchrotron X-ray diffraction (XRD) during tensile testing to clarify the deformation mechanisms and microstructural transformations in additively manufactured 17 − 4 PH stainless steel (AISI 630). Controlled tensile loading was applied to the tensile specimens, enabling the simultaneous capture of XRD, thereby providing real-time insights into material response. The analysis highlighted the structural evolution and phase transformations occurring during deformation, providing a deeper understanding of the underlying mechanisms that influence the unique mechanical properties resulting from Laser Powder Bed Fusion (LPBF). The results demonstrate a clear correlation between microstructural attributes and mechanical performance, contributing to optimising the design vs. properties.

Indirect additive manufacturing techniques like Material Extrusion (MEX) are rising in industrial application due to the freedom of design usually attributed to additive processing, as well as accessibility and a real contribution to sustainability. This study highlights the role of µ-tomography as a core of non-destructive techniques to optimize shaping and sintering parameters. Moreover, brings forth the possibility of continuous improvement and quality control without disposable specimens. Therefore, this study aims to optimize the manufacture of metallic specimens (AISI 316L), for similar feedstock (binder/additive), by using µ-tomography to analyse the filament, the strand, and the 3Dobject (green and sintered). Optimization the different MEX steps relies on setting key process variables and understanding their impact on defects using µ-tomography. This methodology allows the evaluation of 3Dobjects quality by non-destructive techniques.

Additive Manufacturing is an essential process for novel geometries. However, complex parts demand a new perspective in defects control and support for the modelling of mechanical behaviour to assess the applicability of the 3D object to the conditions of the application. Therefore, non-destructive testing is essential for the evaluation of the role of stochastic defects (size, shape, and homogeneous distribution) on the mechanical properties of AM 3D objects. In this study, a wide evaluation of μCT (micro-computed tomography) for two metallic additive manufacturing processes – material extrusion (indirect) and selective laser melting (direct) – is performed. The results are analysed concerning physical properties changes that occur in additive manufacturing per defect origin type. Comparison of mechanical properties with the results of modelling, having in mind the defect characteristics, led to conclude that μCT is a powerful tool for AM parameter optimisation and the improvement of process sustainability.

Metal additive manufacturing (AM) has been evolving in response to industrial and social challenges. However, new materials are hindered in these technologies due to the complexity of direct additive manufacturing technologies, particularly selective laser melting (SLM). Stainless steel (SS) 316L, due to its very low carbon content, has been used as a standard powder in SLM, highlighting the role of alloying elements present in steels. However, reliable research on the chemical impact of carbon content in steel alloys has been rarely conducted, despite being the most prevalent element in steel. Considering the temperatures involved in the SLM process, the laser–powder interaction can lead to a significant carbon decrease, whatever the processing atmosphere. In the present study, four stainless steels with increasing carbon content—AISI 316L, 630 (17-4PH), 420 and 440C—were processed under the same SLM parameters. In addition to roughness and surface topography, the relationship with the microstructure (including grain size and orientation), defects and mechanical properties (hardness and tensile strength) were established, highlighting the role of carbon. It was shown that the production by SLM of stainless steels with similar packing densities and different carbon contents does not oblige the changing of processing parameters. Moreover, alterations in material response in stainless steels produced under the same volumetric energy density mainly result from microstructural evolution during the process.

Shape Memory Alloys (SMAs) can play an essential role in developing novel active sensors for self-healing, including aeronautical systems. However, the NiTi SMAs available in the market are almost limited to wires, small sheets, and coatings. This restriction is mainly due to the difficulty in processing NiTi through conventional processes. Thus, the objective of this study is to evaluate the potential of one of the most promising routes for NiTi additive manufacturing—material extrusion (MEX). Optimizing the different steps during processing is mandatory to avoid brittle secondary phases formation, such as Ni3Ti. The prime NiTi powder is prealloyed, but it also contains NiTi2 and Ni as secondary phases. The present study highlights the role of Ni and NiTi2, with the later having a melting temperature (Tm = 984 °C) lower than the NiTi sintering temperature, thus allowing a welcome liquid phase sintering (LPS). Nevertheless, the reaction of the liquid phase with the Ni phase could contribute to the formation of brittle intermetallic compounds, particularly around NiTi and NiTi2 phases, affecting the final structural properties of the 3D object. The addition of TiH2 to the virgin prealloyed NiTi powder was also studied and revealed the non-formation of Ni3Ti for a specific composition. The balancing addition of extra Ni revealed priority in the Ni3Ti appearance, emphasizing the role of Ni. Feedstocks extruded (filaments) and green strands (layers), before and after debinding & sintering, were used as homothetic of 3D objects for evaluation of defects (microtomography), microstructures, and mechanical properties. The composition of prealloyed powder with 5 wt.% TiH2 addition after sintering showed a homogeneous matrix with the NiTi2 second phase uniformly dispersed.

Additive manufacturing (AM) of metallic powder particles has been establishing itself as sustainable, whatever the technology selected. Material Extrusion (MEX) integrates the ongoing effort to improve AM sustainability, in which low-cost equipment is associated with a decrease of powder waste during manufacturing. MEX has been gaining increasing interest for building 3D functional/structural metallic parts because it incorporates the consolidated knowledge from powder injection moulding/extrusion feedstocks into the AM scope—filament extrusion layer-by-layer. Moreover, MEX as an indirect process can overcome some of the technical limitations of direct AM processes (laser/electron-beam-based) regarding energy-matter interactions. The present study reveals an optimal methodology to produce MEX filament feedstocks (metallic powder, binder and additives), having in mind to attain the highest metallic powder content. Nevertheless, the main challenges are also to achieve high extrudability and a suitable ratio between stiffness and flexibility. The metallic powder volume content (vol.%) in the feedstocks was evaluated by the critical powder volume concentration (CPVC). Subsequently, the rheology of the feedstocks was established by means of the mixing torque value, which is related to the filament extrudability performance.

Material extrusion (MEX) of metallic powder-based filaments has shown great potential as an additive manufacturing (AM) technology. MEX provides an easy solution as an alternative to direct additive manufacturing technologies (e.g., Selective Laser Melting, Electron Beam Melting, Direct Energy Deposition) for problematic metallic powders such as copper, essential due to its reflectivity and thermal conductivity. MEX, an indirect AM technology, consists of five steps-optimisation of mixing of metal powder, binder, and additives (feedstock); filament production; shaping from strands; debinding; sintering. The great challenge in MEX is, undoubtedly, filament manufacturing for optimal green density, and consequently the best sintered properties. The filament, to be extrudable, must accomplish at optimal powder volume concentration (CPVC) with good rheological performance, flexibility, and stiffness. In this study, a feedstock composition (similar binder, additives, and CPVC; 61 vol. %) of copper powder with three different particle powder characteristics was selected in order to highlight their role in the final product. The quality of the filaments, strands, and 3D objects was analysed by micro-CT, highlighting the influence of the different powder characteristics on the homogeneity and defects of the greens; sintered quality was also analysed regarding microstructure and hardness. The filament based on particles powder with D50 close to 11 µm, and straight distribution of particles size showed the best homogeneity and the lowest defects.

Selective Laser Melting (SLM) is an effective process for creating small parts with intricate geometries. Even though this process is largely studied, still the surface roughness and feasibility of different materials presents a major limitation for the applicability on some precision industries. Four different key metallic materials (SS 316L, TS H13, SS 420 and Copper), are optimized in SLM process in order to attain the best surface quality, without need of complementary finishing operations. By other hand there is a need to adjust the final dimensions to the design. Cube, semi-sphere, quadrangular pyramid geometries, with different dimensions are selected to evaluate the best parameters to attain a net shape. Infinite Focus Microscopy (IFM) shown that, for each geometry, there is an optimal adjust of parameters to the different geometries/dimensions to achieve the best surface quality and dimensional adjustments possible. Also, the different reductions in area between the STL file and the resulting parts, obliges the design to compensate this dimensional discrepancy, with this being highly dependent on the material used and the phases transformation that occur mid-process. A standard 316L austenitic stainless steel, with no mid-process phase change, was used as comparison. This study is a significant contribute to adjust the experimental conditions to the modelling. Selective Laser Melting (SLM); Stainless Steel; SS 316L; SS 420; Tool Steel; TS H13; Copper; Surface quality; Geometries; Infinite Focus Microscopy; Dimensional Accuracy; Phase Transformation