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

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Materials, Free Full-Text

TEM images of small precipita test in experimental alloys

DSC curve of 7075 aluminum alloy (a) and Liquid fraction ( fl) vs.

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

A physics-informed neural network framework to predict 3D temperature field without labeled data in process of laser metal deposition - ScienceDirect

Jianxin Xie's research works University of Science and Technology Beijing, Beijing (USTB) and other places

a) Aging response of the 8Zn–1.6Cu–4Mn–0.04Ag and 8Zn–1.6Cu–

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

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

Enhancing materials property prediction by leveraging computational and experimental data using deep transfer learning

SEM micrograph of 7075 aluminum alloy isothermally holding at 620 °C