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Abstract A critical issue in laser powder bed fusion (LPBF) additive manufacturing is the selective vaporization of alloying elements resulting in poor mechanical properties and corrosion resistance of parts. The process also alters the part’s chemical composition compared to the feedstock. Here we present a novel multi-physics modeling framework, integrating heat and fluid flow simulations, thermodynamic calculations, and evaporation modeling to estimate and control the composition change during LPBF of nickel-based superalloys. Experimental validation confirms the accuracy of our model. Moreover, we quantify the relative vulnerabilities of different nickel-based superalloys to composition change quantitatively and we examine the effect of remelting due to the layer-by-layer deposition during the LPBF process. Spatial variations in evaporative flux and compositions for each element were determined, providing valuable insights into the LPBF process and product attributes. The results of this study can be used to optimize the LPBF process parameters such as laser power, scanning speed, and powder layer thickness to ensure the production of high-quality components with desired chemical compositions.

Porosity defects are inherently present in Ti–6Al–4V (Ti6-4) parts produced using additive manufacturing (AM) methods like laser powder-bed fusion (LPBF). This work aims to investigate different laser-inherent porosity defects at various LPBF parameter settings and assess their impact on the fatigue behaviour of Ti6-4 implants processed by LPBF. The presence of LPBF-inherent porosity defects with different shapes and sizes was established using microstructural examination and X-ray micro-CT analysis. These mostly comprise lack-of-fusion porosity (LoFP), gas-entrapped porosity (GeP), and pores-induced microcracks. Volumetric porosity defects were seen to range from 1.9 × 104 to 9.52 × 105 μm3. The L-1 specimen exhibited the lowest defect, while the L-6 specimen displayed the largest number of defects. While LoFP defects predominate in L-6, there was a notable presence of GeP defects in the specimens processed using the factory default condition (L-D). Upon examination of the majority of specimens, GeP and LoFP coalesced to form clusters, leading to the formation of pores-induced microcracks. This ultimately leads to a decrease in fatigue performance. By maintaining the power at the default setting and increasing the scan speed by 8% of the default value, a specimen (L-1) with minimal porosity defects and superior fatigue performance is achieved. L-6 exhibits defects with significant dimensions and irregular form. Consequently, it displays inferior fatigue characteristics.

Abstract Porosity in directed energy deposition (DED) deteriorates mechanical performances of components, limiting safety-critical applications. However, how pores arise and evolve in DED remains unclear. Here, we reveal pore evolution mechanisms during DED using in situ X-ray imaging and multi-physics modelling. We quantify five mechanisms contributing to pore formation, migration, pushing, growth, removal and entrapment: (i) bubbles from gas atomised powder enter the melt pool, and then migrate circularly or laterally; (ii) small bubbles can escape from the pool surface, or coalesce into larger bubbles, or be entrapped by solidification fronts; (iii) larger coalesced bubbles can remain in the pool for long periods, pushed by the solid/liquid interface; (iv) Marangoni surface shear flow overcomes buoyancy, keeping larger bubbles from popping out; and (v) once large bubbles reach critical sizes they escape from the pool surface or are trapped in DED tracks. These mechanisms can guide the development of pore minimisation strategies.

Bulk metallic glasses (BMGs) are non-crystalline class of advanced materials and have found potential applications in the biomedical field. Although there are numerous conventional manufacturing approaches for processing BMGs, the most commonly used like copper-mould casting have some limitations. It is not easy to manage and control the critical cooling rate, especially when the fabrication of complex BMG geometries is involved. Other limitations of these techniques include the size constraints, non-flexibility, and the tooling and accessories are costly. The emergence of additive manufacturing (AM) has opened another promising manufacturing route for processing BMGs. AM processes, particularly laser powder-bed fusion (PBF-LB/M) builds parts layer-by-layer and successively fused the powder-melted feedstocks using prescribed computer-controlled laser scanner system, thereby forming a BMGs part upon sufficiently rapid cooling to ensure the glass forming-ability. PBF-LB/M overcomes the limitations of the pre-existing BMGs processing techniques by not only improving the part size, but also produces exceptionally complex structures and patient-specific implants. This review article aims to summarise and discuss the mechanism of BMGs formation through PBF-LB/M for biomedical applications and to highlight the current scientific and technological challenges as well as the future research perspectives towards overcoming the pore-mediated microcracks, partial crystallisation, brittleness and BMG size constraint.

Recent advances in modeling primary atomization in order to enable accurate practical-scale jet spray simulation are reviewed. Since the Eulerian⁻Lagrangian method is most widely used in academic studies and industrial applications, in which the continuous gas phase is treated in the Eulerian manner and droplets are calculated as Lagrangian point particles, the main focus is placed on improvement within this framework, especially focusing on primary atomization where modeling is the weakest. First, limitations of the conventional methods are described and then novel modeling proposals intended to tackle these issues are covered. These new modeling proposals include the Eulerian surface density approach, and the hybrid Eulerian surface/Lagrangian subgrid droplet generation approach. Compared to conventional simple yet sometimes non-physical models, recent models try to include more physical findings in primary atomization which have been obtained through experiments or direct numerical simulation (DNS). Model accuracy ranges from one that still needs some adjustment using experimental or DNS data to one which is totally self-closed so that no parameter tuning is necessary. These models have the potential to overcome the long-recognized bottleneck in primary atomization modeling and thus to improve the accuracy of whole spray simulation, and may greatly help to improve the spray design for higher combustion efficiency.