ABSTRACT Additive manufacturing (AM) of heat‐resistant high‐strength aluminum (Al) alloys for load‐bearing components faces a fundamental dichotomy: traditional high‐strength compositions suffer from hot cracking, while printable alloys lack sufficient high‐temperature strength. This inherent conflict severely restricts the design space for novel alloys in demanding applications like aerospace. Addressing this challenge, a data‐driven design strategy leveraging quantum machine learning (QML) and high‐throughput computing identifies an ultrastrong Al 85 Cu 5 Li 4 Mg 3 Zn 3 lightweight Al‐based entropy alloy (LAEA) tailored for AM. The AM process transforms potentially brittle microsized intermetallic compounds into deformable hierarchical nanostructures of cellular eutectics, quasicrystals, and dense nanosized planar defects (stacking faults, nanotwin boundaries, and 9R phases). This intricate microstructure endows the as‐printed alloy with exceptional properties: an ultrastrong compressive strength exceeding 1000 MPa coupled with considerable plasticity (∼20%), outstanding high‐temperature strength (>800 MPa at 200°C), and a specific strength (350 × 10 3 N m/kg) rivaling titanium alloys. Furthermore, a controllable quasicrystal‐to‐crystal phase transformation activated by thermal exposure offers an additional mechanism for precisely tuning mechanical properties post‐fabrication. This work presents a novel design paradigm for AM‐compatible high‐performance lightweight Al‐based entropy alloys (LAEAs), effectively bridging advanced computational material design and advanced manufacturing.
Wang et al. (2026) studied this question.