Journal
MATERIALS HORIZONS
Volume 9, Issue 5, Pages 1518-1525Publisher
ROYAL SOC CHEMISTRY
DOI: 10.1039/d1mh01912k
Keywords
-
Funding
- National Natural Science Foundation of China [12172123, 12072109, 51871092]
- National Science Foundation [DMR-1611180, 1809640]
Ask authors/readers for more resources
Multi-principal element alloys (MPEAs) have great potential as structural, functional, and smart materials with remarkable performances. However, designing MPEAs with efficient performance in a wide range of compositions and types is challenging. This study proposes a multistage-design approach that integrates machine learning, physical laws, and a mathematical model to develop desired-property MPEAs in a time-efficient way, achieving better efficiency and accuracy compared to existing methods.
Multi-principal element alloys (MPEAs) with remarkable performances possess great potential as structural, functional, and smart materials. However, their efficient performance-orientated design in a wide range of compositions and types is an extremely challenging issue, because of properties strongly dependent upon the composition and composition-dominated microstructure. Here, we propose a multistage-design approach integrating machine learning, physical laws and a mathematical model for developing the desired-property MPEAs in a very time-efficient way. Compared to the existing physical model- or machine-learning-assisted material development, the forward-and-inverse problems, including identifying the target property and unearthing the optimal composition, can be tackled with better efficiency and higher accuracy using our proposed avenue, which defeats the one-step component-performance design strategy by multistage-design coupling constraints. Furthermore, we developed a new multi-phase MPEA at the minimal time and cost, whose high strength-ductility synergy exceeded those of its system and subsystem reported so far by searching for the optimal combination of phase fraction and composition. The present work suggests that the property-guided composition and microstructure are precisely tailored through the newly built approach with significant reductions of the development period and cost, which is readily extendable to other multi-principal element materials.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available