Machine learning helps ultra-strong alloys take off

Due to the vast compositional space of multi-principal element alloys (MPEAs), the rational design of MPEAs for optimised microstructures is difficult. Therefore, a research team in A*STAR did a high-throughput first-principles study of Mo-V-Nb-Ti-Zr, a refractory MPEA, was conducted to gain insights into the underlying microstructures. 

"The seemingly limitless potential of this novel alloy design paradigm is exciting. Next-generation HEAs could produce unprecedented combinations of material properties, spurring significant developments in advanced manufacturing and the aerospace industry", said Dr Leong Zhidong, a Research Scientist from A*STAR’s Institute of High Performance Computing (IHPC).

The A*STAR-affiliated researchers contributing to this research are from the Institute of Materials Research and Engineering (IMRE) and the Institute of High Performance Computing (IHPC).

Read the full article published on A*STAR Research.