Martensitic transformation sensitivity–driven processing roadmap for laser powder bed fusion of NiTi shape memory alloys: Paradigm shift from defect elimination to precise performance control

Abstract

Laser powder bed fusion (LPBF) fabricated NiTi shape memory alloys (SMAs) fabricated to comparably high density using different processing parameters can exhibit significant differences in martensitic transformation temperature (MTT) (differing by > 50 °C), altering their functional performance and making precise performance control challenging. Herein, we establish a simple but generalisable law, E_L/v (where E_L and v denote linear energy density and scan velocity, respectively), which governs densification and martensitic transformation behaviours in LPBF-processed Ni-rich NiTi SMAs. MTT sensitivity was introduced as a process evaluation metric, shifting the paradigm from conventional defect-centric frameworks toward performance-oriented optimisation. A parameter-dependent and universal vaporisation model is established by systematically decoupling the roles of energy input in MTT. Results demonstrate that Ni loss and MTT sensitivity depend on E_L/v rather than on E_L, with ∼0.67 at.% Ni loss per kJ·s·m⁻² and a linear increase in the martensite start (M_S) temperature of ∼83 K. Microstructural analyses confirm that E_L/v governs melt pool overlap, mode stability and microstructural and transformational homogeneity. It is revealed that the amount of input energy density (e.g. E_L) dictates melt pool geometry and densification, while the manner of input energy density (e.g. normalised input energy density rate, E_L/v) governs melt pool dynamics, elemental vaporisation and microstructure evolution. This dual-criterion rationalises the M_S temperature variability observed under identical energy densities and enables predictive control of transformation features, residual stress and precipitation. The proposed framework delivers NiTi components with superior tensile elongation (∼22 %), surpassing that of most LPBF-processed Ni-rich counterparts. Moreover, its universality is validated in 304L stainless steel and CuAlMn SMA, underscoring its applicability beyond NiTi SMAs. This study offers mechanistic insights into processing–melt pool dynamics–structure–property interactions and offers a universal roadmap for LPBF parameter design, advancing process optimisation beyond defect mitigation and enabling precise performance control through melt pool management.