A survey on basic influencing factors of solidified grain morphology during electron beam melting

[Display omitted] •Steady-state solidification criterion based on temperature gradient (G) and solidification rate (R) was not as accurate as expected.•Melt flow increases the instability and uncertainty of the solidification parameters.•Limited controllability of G and R makes it challenging to control the solidification structure.•A small molten pool under low-power conditions is conducive to stronger melt convection.•Strong convection allows the stray grain to grow in competition with the columnar crystal. Structure-function integration relies on the flexibility of in-situ solidification microstructure control of additive manufacturing (AM)-built metallic components. Thus, the basic factors influencing the solidified grain morphology must be further investigated, as the mechanisms of grain morphology evolution under the supernormal metallurgical conditions of high energy beam irradiation have not been sufficiently clarified. In this study, experimental and simulated single-track melting of Co-Cr-Mo alloy with electron beam were performed to probe the basic influencing factors of solidified grain morphology. With the aid of numerical modeling and data analysis, the importance of each variable to the grain morphology and correlation between variables, including process parameters, solidification parameters, and fluid velocity to the grain morphology, were revealed. Under unsteady solidification of the dynamic moving molten pool, prediction of the solidification criterion based on the fundamental solidification parameters was not as accurate as expected. The processability and thermophysical properties of the material jointly determined the limitations of controlling the solidification parameters only by the power and scan speed. Furthermore, the effect of melt flow on the grain morphology was discussed. The study results may inspire efficient methods for AM-solidified crystalline control through simpler and operable process optimization.