A Comprehensive Extended Review of Advanced Metallic Alloys for Aerospace Structures: Processing, Properties, Recent Advances, and Future Perspectives
Waleed Kadhim Al-Azzawi, Ola Abdullah Abed
The development of advanced metallic alloys for aerospace applications is continuously progressing to meet new requirements for lightweight construction, energy efficiency, high-temperature operation, durability, and sustainability. The state-of-the-art regarding the most common metallic alloy families currently used in aerospace engineering is presented in this review. These alloys include traditional aluminum alloys, aluminum-lithium alloys, titanium alloys, nickel-based superalloys, and advanced high-entropy alloys (HEAs). The compositions, microstructures, processing methods, potential of additively manufactured parts, mechanical properties, and sustainability characteristics of these alloys were critically evaluated. Third-generation Al-Li alloys provide approximately 2-4% decrease in density and up to 10% increase in stiffness compared to conventional 2xxx and 7xxx aluminum alloys, which makes their use very effective in reducing the weight of structural elements. Titanium alloys still cannot be replaced in aerospace structural applications at medium temperatures, whereas nickel-based superalloys are widely used in turbines operating at temperatures higher than 1100-1200°C. High-entropy alloys demonstrate an outstanding combination of strength, ductility, resistance to corrosion, and high-temperature stability, with several lightweight alloys demonstrating compressive yield strengths higher than 1300 MPa at temperatures close to 1000°C. Additive manufacturing techniques have considerably promoted the adoption of topology-optimized aerospace parts; however, fatigue behavior, qualification, and certification remain problematic issues. Moreover, sustainability concerns, including embodied carbon, recyclability, and lifetime impacts, play a more important role in selecting the optimal alloy. Finally, the gaps in the research regarding long-term fatigue behavior, qualification approaches, manufacturing scalability, and machine learning-based alloy design are discussed and prioritized.
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