3D Printing parameter optimisation combined with heat treatment for achieving high density and enhanced performance in refractory high-entropy alloys
Deyu Jiang
(State Key Laboratory of Metal Matrix Composites, School of Material Science and Engineering, Shanghai Jiao Tong University, Shanghai, People’s Republic of China)
Miao Luo
(Affiliated Hospital of Youjiang Medical University for Nationalities, Life Science and Clinical Medicine Research Center, Baise, People’s Republic of China)
Changxi Liu
(State Key Laboratory of Metal Matrix Composites, School of Material Science and Engineering, Shanghai Jiao Tong University, Shanghai, People’s Republic of China)
Yashuo Zhang
(School of Materials Engineering, Shanghai University of Engineering Science, Shanghai, People’s Republic of China)
Lai-Chang Zhang
(Centre for Advanced Materials and Manufacturing, School of Engineering, Edith Cowan University, Perth, Australia)
Kuaishe Wang
(School of Metallurgical Engineering, National and Local Joint Engineering Research Center for Functional Materials Processing, Xi’an University of Architecture and Technology, Xi’an, People’s Republic of China)
Wen Wang
(School of Metallurgical Engineering, National and Local Joint Engineering Research Center for Functional Materials Processing, Xi’an University of Architecture and Technology, Xi’an, People’s Republic of China)
Lechun Xie
(Hubei Key Laboratory of Advanced Technology for Automotive Components, Wuhan University of Technology, Wuhan, People’s Republic of China)
Liqiang Wang
(State Key Laboratory of Metal Matrix Composites, School of Material Science and Engineering, Shanghai Jiao Tong University, Shanghai, People’s Republic of China)
Weijie Lu
(State Key Laboratory of Metal Matrix Composites, School of Material Science and Engineering, Shanghai Jiao Tong University, Shanghai, People’s Republic of China)
Di Zhang
(State Key Laboratory of Metal Matrix Composites, School of Material Science and Engineering, Shanghai Jiao Tong University, Shanghai, People’s Republic of China)
Journal: Virtual and Physical Prototyping
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• Taylor & Francis Group
• ISSN: 1745-2767
Abstract
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.
Deyu Jiang, Miao Luo, Changxi Liu, et al. (2025). "3D Printing parameter optimisation combined with heat treatment for achieving high density and enhanced performance in refractory high-entropy alloys". Virtual and Physical Prototyping. https://doi.org/10.1080/17452759.2025.2524524