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 …
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 …
Emergence of machine learning in the development of high entropy alloy and their prospects in advanced engineering applications
The high entropy alloys have become the most intensely researched materials in recent
times. They offer the flexibility to choose a large array of metallic elements in the periodic …
times. They offer the flexibility to choose a large array of metallic elements in the periodic …
Machine learning guided appraisal and exploration of phase design for high entropy alloys
High entropy alloys (HEAs) and compositionally complex alloys (CCAs) have recently
attracted great research interest because of their remarkable mechanical and physical …
attracted great research interest because of their remarkable mechanical and physical …
A focused review on machine learning aided high-throughput methods in high entropy alloy
L Qiao, Y Liu, J Zhu - Journal of Alloys and Compounds, 2021 - Elsevier
High-entropy alloys (HEAs) have attracted tremendous attention in various fields due to
unique microstructures and many excellent properties. For particular applications, an in …
unique microstructures and many excellent properties. For particular applications, an in …
Searching for high entropy alloys: A machine learning approach
K Kaufmann, KS Vecchio - Acta Materialia, 2020 - Elsevier
For the past decade, considerable research effort has been devoted toward computationally
identifying and experimentally verifying single phase, high-entropy systems. However …
identifying and experimentally verifying single phase, high-entropy systems. However …
High-throughput simulation combined machine learning search for optimum elemental composition in medium entropy alloy
In medium/high entropy alloys, their mechanical properties are strongly dependent on the
chemical-elemental composition. Thus, searching for optimum elemental composition …
chemical-elemental composition. Thus, searching for optimum elemental composition …
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 …
Phase prediction in high entropy alloys with a rational selection of materials descriptors and machine learning models
Materials informatics employs machine learning (ML) models to map the relationship
between a targeted property and various materials descriptors, providing new avenues to …
between a targeted property and various materials descriptors, providing new avenues to …
Machine learning assisted design of high entropy alloys with desired property
We formulate a materials design strategy combining a machine learning (ML) surrogate
model with experimental design algorithms to search for high entropy alloys (HEAs) with …
model with experimental design algorithms to search for high entropy alloys (HEAs) with …