1 citations · 1 across the 4 of their papers we have counts for
4 papers
Quantum-Annealing Enhanced Machine Learning for Interpretable Phase Classification of High-Entropy Alloys
Diego Ibarra Hoyos, Gia-Wei Chern, Israel Klich +1
High entropy alloys (HEAs) offer unprecedented compositional flexibility for designing advanced materials, yet predicting their crystallographic phases remains a key bottleneck due…
Integrated Design of Aluminum-Containing High-entropy Refractory B2 Alloys with Synergy of High Strength and Ductility
Jie Qi, Xuesong Fan, Diego Ibarra Hoyos +3
Refractory high-entropy alloys, RHEAs, are promising high-temperature structural materials. Their large compositional space poses great design challenges for phase control and high…
High Strength Refractory AlHfNbTiV B2 High Entropy Alloys with High Fracture Strains
Jie Qi, Xuesong Fan, Diego Ibarra Hoyos +2
We demonstrate the development of a series of refractory high-entropy alloys containing aluminum AlRHEAs in the ordered BCC-B2 phase by varying the aluminum content within 10 to 25…
Machine Learning-Based Classification, Interpretation, and Prediction of High-Entropy-Alloy Intermetallic Phases
Jie Qi, Diego Ibarra Hoyos, S. Joseph Poon
The design of high-entropy alloys (HEA) with desired properties is challenging due to their large compositional space. While various machine learning (ML) models can predict specif…