## What is/are Structure Property Linkages?

Structure Property Linkages - In comparison, 3D convolutional neural networks (CNNs) can directly extract geometric features of composites, which have been demonstrated to establish structure-property linkages with high accuracy.^{[1]}In this paper, we critically compare the relative merits of the application of four distinct machine learning approaches for their efficacy in extracting microstructure-property linkages from the finite element simulation data aggregated on high-contrast elastic composites with different microstructures.

^{[2]}Nevertheless, the computational cost restrains the application of full-field simulations in optimizing materials microstructures or in establishing comprehensive structure-property linkages.

^{[3]}Moreover, correlations of structure-property linkages based on homogenization and localization are not easily conceived.

^{[4]}The amelioration via the material flow model inhibits the welding defects and optimizes the parameter intervals, providing references to extracting process-structure-property linkages for friction stir welding.

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