A rapid and effective method for alloy materials design via sample data transfer machine learning

A rapid and effective method for alloy materials design via sample data transfer machine learning

Machine learning-guided design and development of metallic structural materials

Tensile and yield strength with variation of heating rate

a) Aging response of the12Zn–1.3Cu–0.3Mn–0.20Cr and 12Zn–1.2

Frontiers Bio-high entropy alloys: Progress, challenges, and opportunities

Machine learning guided alloy design of high-temperature NiTiHf shape memory alloys

Shape memory alloy heat activation: State of the art review

Knowledge-integrated machine learning for materials: lessons from gameplaying and robotics

MLMD: a programming-free AI platform to predict and design materials

PDF) Aging response of Al–Zn–Mg–Cu spray formed alloys and their metal matrix composites

Material machine learning for alloys: Applications, challenges and perspectives - ScienceDirect