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cond-mat.mtrl-sci2024★ 1 cited
NSGAN: A Non-Dominant Sorting Optimisation-Based Generative Adversarial Design Framework for Alloy Discovery
Zhipeng Li, Nick Birbilis
The design and discovery of new materials is fundamental to advancing scientific and technological innovation. The recent emergence of the materials genome concept holds great prom…
cond-mat.mtrl-sci2023
Revolutionising inverse design of magnesium alloys through generative adversarial networks
Marzie Ghorbani, Zhipeng Li, Nick Birbilis
The utility of machine learning (ML) techniques in materials science has accelerated materials design and discovery. However, the accuracy of ML models - particularly deep neural n…
cond-mat.mtrl-sci2023
A Computational Approach for Mapping Electrochemical Activity of Multi-Principal Element Alloys
Jodie A. Yuwono, Xinyu Li, Tyler D. Doležal +4
Multi principal element alloys (MPEAs) comprise a unique class of metal alloys. MPEAs have been demonstrated to possess several exceptional properties, including, as most relevant…