This work is part of the five-year "Accelerated Materials Development for Manufacturing" programme with start date 24 Sep 18 funded by S$24.8M from the AME Programmatic Fund. This programme aims to develop a machine learning platform to substantially cut the development cycle for new materials from 20 years to ~3 years.
IHPC's focus in this programme is the development of high throughput computational algorithms to produce a large-quantity, high-quality materials database and a machine learning-guided design platform to accelerate the development of high-entropy alloys (HEAs), which are attractive structural materials due to their outstanding structural stability and excellent balance between strength and ductility. The increase in yield strength of metals and metal alloys with decreasing microstructure grain size is referred to as the Hall-Petch relation. While understanding effects of composition and processing on microstructure and properties is critical for rationally-designed composition and processing 'recipes' for HEAs with enhanced mechanical properties, there have only been a few studies investigating Hall-Petch effects in HEAs.
Through extensive molecular dynamics simulations of the CoNiFeAlxCu1-x HEA, the team discovered that CoNiFeAlxCu1-x follows the Hall-Petch relation as the average grain size decreases until 10-20nm, beyond which the yield strength decreases with decreasing grain size, i.e. the inverse Hall-Petch relation. Detailed analysis of the molecular dynamics results also uncovered, for the first time, the dominant deformation mechanism(s) for different concentrations of Al (i.e. different values of x in CoNiFeAlxCu1-x).
These findings provide two clear directions for the development of HEAs with enhanced yield strength, i.e. engineer the microstructure such that the average grain size is 10-20nm, and the relevant dominant deformation mechanism(s) is promoted or suppressed. These results also contribute to the overall HEA materials development platform by demonstrating how a suitable atomic scale simulation methodology could reveal the deformation mechanisms and predict the structure-property relations of HEAs.
The article titled "Hall-Petch and inverse Hall-Petch relations in high-entropy CoNiFeAlxCu1-x alloys
" was published in Materials Science & Engineering A (impact factor of 4.081) by researchers from IHPC, City University of Hong Kong, and University of North Texas. The IHPC researchers involved in this work are Dr Chen Shuai, Dr Zachary Aitken, Dr Yu Zhigen, and Prof Zhang Yong Wei.