Laser additive manufacturing (LAM) is revolutionizing the design of high-temperature components for demanding applications like aero-engines. By enabling complex microstructures, LAM offers a way to meet the growing need for materials that can withstand extreme heat. However, predicting the long-term performance of these materials under stress (creep) is crucial. Developing efficient methods to predict creep behavior will be key to wider adoption of LAM in critical applications.
Challenges
While promising, LAM of high-temperature alloys faces key challenges, including material cracking during printing, reduced creep performance compared to traditionally made parts, slow and costly testing that hinders rapid data collection, and a limited ability to predict the full evolution of creep behavior.
Methods & Findings
Fig. 1. Repairing laser additive manufacturing cracks using Liquid Phase Induced Healing (LIH) technology
Building on this, they developed a high-throughput creep testing technology that increases data acquisition efficiency by 8 times while ensuring consistent compressive creep temperature and load (Fig. 2). The results showed that the minimum compressive creep rate of the LIH-treated alloy is comparable to or better than many representative high creep performance engineering alloys (cast) (Fig. 3).
Figure 2. (a) Highthroughput compression creep test system CC801; (b) Compression creep curves of IN738LC under different temperature and stress conditions
Figure 3. Comparison of minimum compressive creep rates between LPBF-IN738LC alloy (LIH treated) and commonly used high-performance superalloys (cast).
Furthermore, they constructed a mapping relationship between minimum creep rate, temperature, and stress based on optimization algorithms. Finally, they integrated deep learning technology to build a predictive model capable of accurately predicting the creep behavior of IN738LC alloy under any temperature and stress condition, providing a powerful tool for material service performance evaluation and optimized design (Fig. 4).
This research used laser additive manufacturing to create a crack-resistant superalloy with excellent creep performance. By combining high-throughput testing with machine learning, the study also developed a new method for accurately predicting creep behavior, accelerating the development of high-temperature materials.
Fig. 5. Precipitates in the sample after creep at 850 °C/280 MPa. (a) MC carbides in γ matrix (EDS, SAED, HRTEM, FFT). (b) MC carbides surrounded by ZrO2 (EDS). (c) M23C6 carbides trapping dislocations (EDS, HAADF, EDS mapping). Dislocations act as channels for element diffusion.
Figure 6. TEM images of LPBF IN738LC before and after creep at 850 °C/280 MPa. (a) initial γ/γ' microstructure; (b-c) atomic structure of γ and γ'; (d) deformation features (dislocation networks, pile-ups, stacking faults) in γ'/γ structure and SAED pattern; (e-f) magnified dislocation pile-up and network; (g) stacking fault formation; (h) twinning blocking dislocations; (i) SAED pattern confirming twinning.
