Engineering and Technologynpj Computational Materials
A generative deep learning framework for inverse design of compositionally complex bulk metallic glasses
Z. Zhou, Y. Shang, et al.
Discover a groundbreaking generative deep-learning framework for designing complex bulk metallic glasses, developed by Ziqing Zhou, Yinghui Shang, Xiaodi Liu, and Yong Yang. This innovative approach leverages GANs and Boosted Trees for data generation and evaluation, showcasing the potential for novel BMG compositions through systematic data investigation and experimental validation.
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