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 …

Multi-principal element alloys exhibit excellent physical, chemical and mechanical
properties, and they are used as novel structural materials for potential applications in …

Refractory high-entropy alloys (RHEAs), particularly NbMoTaW RHEAs, exhibit outstanding
softening resistance and thermal stability at ultra-high temperatures, but suffer from room …

Owing to competitive behavior between oxidation products, complex oxidation commonly
exists for MAX phases applied at high temperatures. Two major challenges remain to …

Multi-component alloys have demonstrated excellent performance in various applications,
but the vast range of possible compositions and microstructures makes it challenging to …

High toughness is highly desired for low-alloy steel in engineering structure applications,
wherein Charpy impact toughness (CIT) is a critical factor determining the toughness …

High-strength iron-based alloys serving in hydrogen-containing environments often faces a
critical problem of hydrogen embrittlement, which involves intricate mechanisms across …

The study of piezocatalysis has become an important topic in piezoelectric research,
especially for addressing environmental issues. However, the reliance on nanofabrication …

As an implementation tool of data intensive scientific research methods, machine learning
(ML) can effectively shorten the research and development (R&D) cycle of new materials by …

An equiatomic FeCoCrNi high entropy alloy (HEA) with high strength and excellent
hydrogen embrittlement (HE) resistance is manufactured by the precipitation of nano-sized …