We utilize a machine-learning force field, trained by a neural network (NN) with bispectrum
coefficients as descriptors, to investigate the chemical short-range order (SRO) influences …

Multi-principal element alloys (MPEAs) with remarkable performances possess great
potential as structural, functional, and smart materials. However, their efficient performance …

Refractory multi-principal element alloys (MPEAs) have exceptional mechanical properties,
including high strength-to-weight ratio and fracture toughness, at high temperatures. Here …

There is intense interest in uncovering design rules that govern the formation of various
structural phases as a function of chemical composition in multi-principal element alloys …

Multi-principal element alloys (MPEAs) continue to gain research prominence due to their
promising high-temperature microstructural and mechanical properties. Recently, machine …

Abstract Multi-Principal Element Alloys (MPEAs) have brought a paradigm shift in the alloy
design process and pose a significant challenge due to the astronomical and compositional …

Multiprincipal element alloys (MPEAs) have gained surging interest due to their exceptional
properties unprecedented in traditional alloys. However, identifying an MPEA with desired …

Multi-principal element alloys (MPEAs), inclusive of so-called high entropy alloys (HEAs),
represent an innovative class of metallic materials that reveal unique properties and …

The recent development of high-entropy alloys (HEAs) has opened a new avenue for alloy
design by incorporating multiple principal elements into a simple crystal lattice. In HEAs …

In this paper, we develop an explainable artificial intelligence (XAI) approach to rapidly
predict and explain the temperature-dependent yield strength (YS) trends of as-cast multi …