3D Printing parameter optimisation combined with heat treatment for achieving high density and enhanced performance in refractory high-entropy alloys

In this study, a Ti1.5Nb1Ta0.5Zr1Mo0.5 (TNTZM) high-entropy alloy was fabricated using laser powder bed fusion (LPBF). By integrating 63 sets of parameter trials with machine learning (ML) models, an optimised process window was identified, achieving a density of up to 99.9%. The combination of rela...

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Bibliographic Details
Main Authors: Deyu Jiang, Miao Luo, Changxi Liu, Yashuo Zhang, Lai-Chang Zhang, Kuaishe Wang, Wen Wang, Lechun Xie, Liqiang Wang, Weijie Lu, Di Zhang
Format: Article
Language:English
Published: Taylor & Francis Group 2025-12-01
Series:Virtual and Physical Prototyping
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Online Access:https://www.tandfonline.com/doi/10.1080/17452759.2025.2524524
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Summary:In this study, a Ti1.5Nb1Ta0.5Zr1Mo0.5 (TNTZM) high-entropy alloy was fabricated using laser powder bed fusion (LPBF). By integrating 63 sets of parameter trials with machine learning (ML) models, an optimised process window was identified, achieving a density of up to 99.9%. The combination of relatively high laser power and low scanning speed resulted in the formation of a stable cellular structure. Subsequent heat treatments at 700, 850, and 1000°C showed that while small-angle misorientations developed at cell-wall interfaces and medium-entropy (Ti–Zr–Mo) second-phase particles precipitated preferentially in the cell walls, the overall cellular architecture remained intact. Mechanical testing showed that these heat-treated samples exhibited yield strengths over 150 MPa higher than the as-built samples, while still retaining nearly 50% ductility under short-term heat treatment. In particular, small-angle grain boundaries and nanoscale second-phase particles together reinforce the cell walls and promote intracellular dislocation accumulation, thereby improving the overall mechanical properties of the alloy. These results demonstrate that combining ML-guided process design with targeted heat treatment is an effective method for additive manufacturing of refractory HEAs with high density and mechanical properties.
ISSN:1745-2759
1745-2767