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For additive manufacturing (AM) through laser-based powder bed fusion of polymers (PBF-LB/P), accurate characterization of powder flowability is vital for achieving high-quality parts. However, accurately characterizing feedstock flowability presents challenges because of a lack of consensus on which tests to perform and the diverse forces and mechanisms involved. This study aims to undertake a thorough investigation into the flowability of eight feedstock materials for PBF-LB/P at different temperatures using various techniques.

For ambient temperature assessments, established metrics such as avalanche angle and Hausner ratio, along with the approximated flow function coefficient (FFC_app), are used. The study then focuses on the influence of elevated temperatures representative of in-process conditions. FFC_app and differential scanning calorimetry (DSC) are performed and analyzed, followed by a correlation analysis as a holistic approach to identify key aspects for flowability. Furthermore, two feedstock materials are compared with a previous study to connect the present findings to PBF-LB/P processing.

The study revealed intrinsic material properties such as mechanical softening near the melting point to become significant. This partially explains why certain powders with poor ambient temperature flowability are consistently demonstrated to produce high-quality parts. FFC_app and thermal characterization through DSC are identified as critical metrics for optimizing feedstock material characteristics across temperature ranges.

Previous studies emphasized specific characterizations of feedstock material at ambient temperature, presented a limited materials selection or focused on metrics such as shape factors. In contrast, this study addresses a partially understood aspect by examining the critical role of temperature in governing feedstock material flowability. It advocates for the inclusion of temperature variables in flowability analyses to closely resemble the PBF-LB/P process, which can be applied to material design, selection and process optimization.