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Research Progress on Additively Manufactured Porous Structures of Nickel-Based Superalloys
Shenghang Xu1,2, Yiye Pan1,2, Nanxuan Mei3
1Advanced Materials Additive Manufacturing Innovation Research Center, Hangzhou City University, Hangzhou 310015, China.
Materials (Basel, Switzerland)
|May 27, 2026
Summary
Additive manufacturing enables complex porous nickel-based superalloys for aerospace. This review details structure design, fabrication challenges, and performance impacts for advanced material applications.
Area of Science:
- Materials Science
- Mechanical Engineering
- Additive Manufacturing
Background:
- Nickel-based superalloys are critical for high-temperature applications like aerospace and gas turbines.
- Conventional manufacturing methods limit the creation of intricate porous structures.
- Additive manufacturing offers novel pathways for producing these complex alloys.
Purpose of the Study:
- To review advancements in additively manufactured porous nickel-based superalloys.
- To explore various porous structure designs and fabrication technologies.
- To identify challenges and future research directions in the field.
Main Methods:
- Summarizing research on porous structure designs (disordered, lattice, TPMS, bio-inspired, AI-assisted).
- Introducing common additive manufacturing technologies and their impact on microstructure.
- Discussing defect formation, characterization, and post-processing strategies.
Main Results:
- Additive manufacturing allows for controllable porous structures with complex topologies.
- Non-equilibrium microstructures, segregation, and defects significantly influence mechanical properties (strength, fatigue, creep).
- Porous structures exhibit unique behaviors like anisotropy and defect sensitivity compared to bulk materials.
Conclusions:
- Significant progress has been made in designing and fabricating porous nickel-based superalloys via additive manufacturing.
- Understanding and mitigating defects are crucial for optimizing performance.
- Future research should focus on multi-scale modeling, microstructure control, fatigue prediction, and AI-driven design.
