Deep image learning of quantitative structure-property relationships of cooper alloys via feature augmentation on Geodesic curve in shape space

arXiv:2404.09515v1 Announce Type: new
Abstract: Understanding how the structure of materials affects their properties is a cornerstone of materials science and engineering. However, traditional methods have struggled to accurately describe the quantitative structure-property relationships for complex structures. In our study, we bridge this gap by leveraging machine learning to analyze images of materials' microstructures, thus offering a novel way to understand and predict the properties of materials based on their microstructures. We introduce a method known as FAGC (Feature Augmentation …

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