Process optimization and scaling of molybdenum and tungsten in additive manufacturing techniques

Metal additive manufacturing processes pose a daunting challenge in defining optimal process parameters that yield porosity defect-free, dense parts. This is particularly true in refractory metals, where high melting temperatures limit process parameter windows. This present study investigates a dimensionless number analysis that has been derived through the Buckingham-PI theorem and demonstrates a robust correlation between process parameters and the density of the fabricated components. The introduction of this dimensionless number enables the initial estimation of process parameters without extensive modeling or experimentation. Additionally, a universal scaling law is proposed to enhance the translation of predicting process parameters for achieving an optimal density in as-built parts between different processing techniques. A combination of this proposed dimensionless number and scaling law offers process maps for tungsten and molybdenum with previously unknown process parameters. The universality of the proposed dimensionless number also demonstrates transferability, enabling the prediction of process parameters both for laser powder bed fusion and directed energy deposition systems.