The content and distribution of nitrogen (N) are critical determinants of the mechanical properties, corrosion resistance, and hydrogen embrittlement resistance of austenitic stainless steels. However, a limited understanding of gas-liquid-solid N transport and compositional evolution during the additive manufacturing of these steels restricts their engineering application. The extreme local temperatures in Laser Powder Bed Fusion (PBF-LB/M) create a dynamic competition between N evaporation loss and absorption from the shielding gas, further complicating this evolution. A key challenge lies in the direct experimental observation of N, a light element, during its dynamic transport within the melt pool and its final distribution in the solidified microstructure. To address this, we developed a multi-physics model integrating "absorption–convection–evaporation–solidification redistribution", which provides a coupled framework describing the evolution of N. Furthermore, via sophisticated Electron Probe Microanalyzer (EPMA) experiments incorporating background noise correction and tracer element (Mn) correlation analysis, we overcame the characterization barriers for N. Results indicate distinct N distribution channels shaped by Marangoni convection and subsequently locked in by rapid solidification, providing direct visual evidence of the melt pool flow's dominant role in shaping the final compositional distribution. Excellent agreement between model and experiment demonstrates that: (1) N transport features spatiotemporally separated competitive processes; (2) Significant non-equilibrium solute trapping (effective partition coefficient k' > 0.9) occurs at the rapid solidification front; and (3) A net N loss is ubiquitous, with high energy input causing the most severe depletion and poorest homogeneity, while low energy input simultaneously mitigates N loss and enhances compositional uniformity. This work elucidates the mechanistic origins of N evolution in PBF-LB/M, establishes a validated predictive framework for process–composition control, and provides a generalizable characterization strategy for tracking light-element transport in metallurgical melt pools.
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