[HTML][HTML] Machine-learning synergy in high-entropy alloys: A review
High-entropy alloys (HEAs) have attracted significant attention because of their exceptional
mechanical properties and potential for discovering new compositions. However, owing to …
mechanical properties and potential for discovering new compositions. However, owing to …
Supervised machine learning-based multi-class phase prediction in high-entropy alloys using robust databases
This work evaluated the phase prediction capability of high entropy alloys using four
supervised machine learning models K-Nearest Neighbors (KNN), Multinomial Regression …
supervised machine learning models K-Nearest Neighbors (KNN), Multinomial Regression …
Competitive relationship between the FCC+ BCC dual phases in the wear mechanism of laser cladding FeCoCrNiAl0. 5Ti0. 5 HEAs coating
This work elaborated the microstructure and wear behavior of laser cladding (LC)
FeCoCrNiAl 0.5 Ti 0.5 high-entropy alloys (HEAs) coatings on AISI 1045 steel substrates …
FeCoCrNiAl 0.5 Ti 0.5 high-entropy alloys (HEAs) coatings on AISI 1045 steel substrates …
[HTML][HTML] Stacking ensemble learning assisted design of Al-Nb-Ti-V-Zr lightweight high-entropy alloys with high hardness
Q Chen, Z He, Y Zhao, X Liu, D Wang, Y Zhong, C Hu… - Materials & Design, 2024 - Elsevier
To improve the accuracy and efficiency of machine learning models in predicting and
designing the mechanical properties and designing of lightweight high-entropy alloys, we …
designing the mechanical properties and designing of lightweight high-entropy alloys, we …
Structural evolutions and tribological properties of laser cladded FeCoNiCrMo high-entropy alloy coating by laser remelting and tempering process: TEM and DFT …
Y Lu, Y Peng, X Chang, Z Shi - Tribology International, 2024 - Elsevier
A laser cladded FeCoNiCrMo high-entropy alloy (HEA) coating was treated by laser
remelting and tempering process in sequence to improve its tribological properties. The …
remelting and tempering process in sequence to improve its tribological properties. The …
Hardness prediction of high entropy alloys with periodic table representation of composition, processing, structure and physical parameters
S Li, S Li, D Liu, J Yang, M Zhang - Journal of Alloys and Compounds, 2023 - Elsevier
A rational and information-rich material representation is necessary for a machine learning
model to successfully predict material properties. In this work, the periodic table …
model to successfully predict material properties. In this work, the periodic table …
[HTML][HTML] Machine learning based prediction of Young's modulus of stainless steel coated with high entropy alloys
Abstract The High Entropy Alloy (HEA) coatings exhibit diverse properties contingent upon
their composition and microstructure, addressing current industrial requirements. Machine …
their composition and microstructure, addressing current industrial requirements. Machine …
A Comprehensive Review on Hot Deformation Behavior of High-Entropy Alloys for High Temperature Applications
In contrast to conventional alloys, multicomponent high-entropy alloys (HEAs) have
emerged as promising candidates in the field of advanced materials because of their unique …
emerged as promising candidates in the field of advanced materials because of their unique …
Machine learning accelerated study for predicting the lattice constant and substitution energy of metal doped titanium dioxide
Abstract Currently, titanium dioxide (TiO 2) has been extensively studied for its wide
applications in many fields, and metal do** is regarded as one of the important methods …
applications in many fields, and metal do** is regarded as one of the important methods …
Designing of high entropy alloys with high hardness: a metaheuristic approach
A Poonia, M Kishor, KPR Ayyagari - Scientific Reports, 2024 - nature.com
The near-infinite compositional space of high-entropy-alloys (HEAs) is a huge resource-
intensive task for develo** exceptional materials. In the present study, an algorithmic …
intensive task for develo** exceptional materials. In the present study, an algorithmic …