Machine learning for high-entropy alloys: Progress, challenges and opportunities
High-entropy alloys (HEAs) have attracted extensive interest due to their exceptional
mechanical properties and the vast compositional space for new HEAs. However …
mechanical properties and the vast compositional space for new HEAs. However …
High-entropy energy materials: challenges and new opportunities
The essential demand for functional materials enabling the realization of new energy
technologies has triggered tremendous efforts in scientific and industrial research in recent …
technologies has triggered tremendous efforts in scientific and industrial research in recent …
A machine learning-based alloy design system to facilitate the rational design of high entropy alloys with enhanced hardness
Trapped by time-consuming traditional trial-and-error methods and vast untapped
composition space, efficiently discovering novel high entropy alloys (HEAs) with exceptional …
composition space, efficiently discovering novel high entropy alloys (HEAs) with exceptional …
Material machine learning for alloys: Applications, challenges and perspectives
X Liu, P Xu, J Zhao, W Lu, M Li, G Wang - Journal of Alloys and Compounds, 2022 - Elsevier
Materials machine learning (ML) is revolutionizing various areas in a fast speed, aiming to
efficiently design novel materials with superior performance. Here we reviewed the recent …
efficiently design novel materials with superior performance. Here we reviewed the recent …
Formation ability descriptors for high-entropy diborides established through high-throughput experiments and machine learning
Establishing formation ability descriptors is essential for facilitating the discovery and design
of high-entropy diborides (HEBs) with tailorable properties. In this work, we establish an …
of high-entropy diborides (HEBs) with tailorable properties. In this work, we establish an …
Recent applications of machine learning in alloy design: A review
The history of machine learning (ML) can be traced back to the 1950 s, and its application in
alloy design has recently begun to flourish and expand rapidly. The driving force behind this …
alloy design has recently begun to flourish and expand rapidly. The driving force behind this …
Design high-entropy carbide ceramics from machine learning
High-entropy ceramics (HECs) have shown great application potential under demanding
conditions, such as high stresses and temperatures. However, the immense phase space …
conditions, such as high stresses and temperatures. However, the immense phase space …
Machine-learning and high-throughput studies for high-entropy materials
The combination of multiple-principal element materials, known as high-entropy materials
(HEMs), expands the multi-dimensional compositional space to gigantic stoichiometry. It is …
(HEMs), expands the multi-dimensional compositional space to gigantic stoichiometry. It is …
[HTML][HTML] Scope of machine learning in materials research—A review
This comprehensive review investigates the multifaceted applications of machine learning in
materials research across six key dimensions, redefining the field's boundaries. It explains …
materials research across six key dimensions, redefining the field's boundaries. It explains …
Underpinning the relationship between synthesis and properties of high entropy ceramics: A comprehensive review on borides, carbides and oxides
TC Dube, J Zhang - Journal of the European Ceramic Society, 2024 - Elsevier
This work reviews the recent development of High Entropy Ceramics (HEC), which have five
or more elements combined in equimolar or near equimolar quantities and have …
or more elements combined in equimolar or near equimolar quantities and have …