10 citations · 29 across the 8 of their papers we have counts for
4 papers · 1 filter
Machine Learning the Effective Hamiltonian in High Entropy Alloys
Xianglin Liu, Jiaxin Zhang, Markus Eisenbach +1
The development of machine learning sheds new light on the problem of statistical thermodynamics in multicomponent alloys. However, a data-driven approach to construct the effectiv…
Robust data-driven approach for predicting the configurational energy of high entropy alloys
Jiaxin Zhang, Xianglin Liu, Sirui Bi +3
High entropy alloys (HEAs) have been increasingly attractive as promising next-generation materials due to their various excellent properties. It's necessary to essentially charact…
Chemical complexity in high entropy alloys: A pair-interaction perspective
Xianglin Liu, Jiaxin Zhang, Sirui Bi +3
The recently proposed pair-interaction model is applied to study a series of refractory high entropy alloys. The results demonstrate the simplicity, robustness, and high accuracy o…
Machine learning modeling of high entropy alloy: the role of short-range order
Xianglin Liu, Jiaxin Zhang, Markus Eisenbach +1
The development of machine learning sheds new light on the traditionally complicated problem of thermodynamics in multicomponent alloys. Successful application of such a method, ho…