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Turning brittle mineral to flexible one by the control of solid structure
Yinlin Shen, Zhaoming Liu∗ Submit a Manuscript
Turning brittle mineral to flexible one by the control of solid structure
Yinlin Shen, Zhaoming Liu∗ Submit a Manuscript
Application of topology-based structure features for machine learning in materials science
Shisheng Zheng, Haowen Ding, Shunning Li, Dong Chen*, Feng Pan*
Chin. J. Struct. Chem., 2023, 42: 100120. DOI: 10.1016/j.cjsc.2023.100120
July 15, 2023
Machine learning; Structure feature; Structure graph; Algebraic topology
ABSTRACT
Structure features play an important role in machine learning models for the materials investigation. Here, two topology-based features for the representation of material structure, specifically structure graph and algebraic topology, are introduced. We present the fundamental mathematical concepts underlying these techniques and how they encode material properties. Furthermore, we discuss the practical applications and enhancements of these features made in specific material predicting tasks. This review may provide suggestions on the selection of suitable structural features and inspire creativity in developing robust descriptors for diverse applications.
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