Nitinol (NiTi) shape memory alloys fabricated by Laser Powder Bed Fusion (L-PBF) Additive Manufacturing (AM) have attracted much attention in recent years, as compared with conventional manufacturing processes it allows to produce Nitinol parts with high design complexity. Avoidance of defects during L-PBF is crucial for the production of high quality Nitinol parts. In this study, analytical models predicting melt pool dimensions and defect formation criteria were synergistically used to develop processing maps demonstrating boundary conditions for the formation of such defects, as balling, keyhole-induced pores, and lack of fusion. Experimental validation has demonstrated that this method can provide an accurate estimation and guide manufacturability of defect-free Nitinol alloys. Moreover, the crack formation phenomena were experimentally analysed, which showed that a low linear energy density (E_l) should be chosen to avoid cracks in the optimized process windows. Based on model predictions and experimental calibrations, Nitinol samples with a relative density of more than 99% were successfully fabricated.

Laser powder bed fusion (L-PBF), categorized as additive manufacturing technique, has a capability to fabricate NiTi (Nitinol) shape memory alloys with tailorable functional properties and complex geometries. An important processing parameter, hatch distance (h), is often related to macroscale structural defects; however, its role on controlling the microstructure and functional properties is usually underestimated in L-PBF of NiTi. In this work, equiatomic NiTi (50.0 at% Ni) parts were fabricated with various hatch distances to tailor the microstructure and their shape memory characteristics. Contrary to what is observed in Ni-rich NiTi alloys, in this work, we demonstrate that phase transformation temperatures of L-PBF equiatomic NiTi do not decrease proportionally with hatch distance but rather relate to a critical hatch distance value. This critical value (120 μm) is derived from the synergistic effect of thermal stress and in situ reheating. Below this value, epitaxial grain growth and in situ recrystallization are enhanced, while above, irregular grains are formed and dislocations induced by thermal stresses decrease. However, the critical value found herein is characterized by high dislocation density and fine grain size, resulting in a superior thermal cyclic stability. The proposed finite element model is proven to be an effective tool to understand and predict the effect of hatch distance on grain morphology and dislocation density evolutions in L-PBF NiTi SMAs. In the present study, we provide a comprehensive understanding for in situ controlling L-PBF NiTi microstructure and functional characteristics, which contributes to designing 4-dimensional shape memory alloys.

A cellular automata (CA) model has been developed for solidification simulation considering the kinetic undercooling at the interface. The state-of-the-art model incorporates a decentered growth algorithm to suppress the grid anisotropy and a generalized height function method to calculate the curvature accurately. To develop a CA model which is independent of the mesh size, a new diffusion term is proposed to handle the diffusion between the interface cells and liquid cells. The developed CA model is employed to simulate the single-dendritic solidification of an Al–3Cu (wt pct) alloy. The simulated tip velocities agree with the prediction of the Kurz–Giovanola–Trivedi (KGT) model. Further studies show that the developed CA model converges to an equilibrium model with increasing kinetic mobility values. Moreover, it is found that the virtual liquid cell assumption which is commonly used in existing CA models may lead to a deviation in the mass balance. The mass balance error has been resolved by redistributing solutes from neighboring liquid cells in each time step. The developed CA model could be potentially used in solidification simulations with a high undercooling, which is common in welding and additive manufacturing.