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Meeting 2026 TMS Annual Meeting & Exhibition
Symposium Thermodynamics and Kinetics of Alloys IV
Presentation Title Microalloying Effects on the Mechanical Behavior of AlCrFeNi-Based Medium Entropy Alloys Optimized by Machine Learning
Author(s) Taner Göktuğ Tekin, Yiğit Can Çavdarlı, Ali Fethi Erdem, Sertaç Altınok, Eren Yunus Kalay
On-Site Speaker (Planned) Taner Göktuğ Tekin
Abstract Scope Low-cost medium entropy alloys (MEAs) based on AlCrFeNi were investigated to develop high-performance materials without costly cobalt. Microalloying with Si and B was applied to produce AlCrFeNi-Si and AlCrFeNi-B alloys alongside the base AlCrFeNi via vacuum arc melting. Their microstructures and compressive properties were characterized, and compositions were further optimized using machine learning to enhance phase stability and mechanical behavior. All alloys exhibited comparable yield strengths (~1500 MPa) in compressive tests, but ductility increased with Si and B additions, increasing elongation from 20% to 24% and 28%, respectively. Reducing Al content in AlₓCrFeNiSi₀.₁ (x = 0.75, 0.5) further enhanced ductility, with Al₀.₇₅CrFeNiSi₀.₁ achieving 1500 MPa yield strength and 40% elongation. The role of microalloying combined with compositional tuning and machine learning-guided design in tailoring the thermodynamic stability and mechanical performance of MEAs will be discussed in detail.
Proceedings Inclusion? Planned:
Keywords Computational Materials Science & Engineering, Machine Learning, Solidification

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