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Alloy synthesis and processing by semi-supervised text mining

Engineering and Technology

Alloy synthesis and processing by semi-supervised text mining

W. Wang, X. Jiang, et al.

Discover how Weiren Wang, Xue Jiang, Shaohan Tian, Pei Liu, Turab Lookman, Yanjing Su, and Jianxin Xie have revolutionized the field of alloy synthesis and processing. Their innovative semi-supervised text mining method extracts crucial parameters from superalloy articles, enhancing predictive models and bridging the gap between synthesis and alloy structure.

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Playback language: English
Abstract
Alloy synthesis and processing are crucial for designing alloys with desired microstructures and properties. This paper introduces a semi-supervised text mining method to extract synthesis and processing parameters from a corpus of superalloy articles. The method automatically extracts 9853 superalloy synthesis and processing actions with chemical compositions, improving the performance of a data-driven γ′ phase coarsening prediction model. This approach complements data-driven methods in exploring the relationship between synthesis and alloy structures.
Publisher
npj Computational Materials
Published On
Oct 06, 2023
Authors
Weiren Wang, Xue Jiang, Shaohan Tian, Pei Liu, Turab Lookman, Yanjing Su, Jianxin Xie
Tags
alloy synthesis
text mining
superalloys
data-driven methods
microstructures
γ′ phase
predictive modeling

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