Fig. 2: Assessment of indicator property covariance and model performance using the pool of 163 IPs. | npj Computational Materials

Fig. 2: Assessment of indicator property covariance and model performance using the pool of 163 IPs.

From: Cross-scale covariance for material property prediction

Fig. 2

a Scatter plots of correlations of small-scale indicator properties and strength were evaluated on the pool of 163 IPs for nine FCC metals. C44 = shear modulus (GPa), rVFE = relaxed vacancy formation energy (eV), uSFE = unstable stacking fault energy (ev/A2), iSFE = intrinsic stacking fault energy (ev/A2). b Heatmap of correlation coefficients showing highly correlated (C44), moderately correlated (rVFE and uSFE), and minimally correlated (iSFE) properties. Highly correlated properties approach values of 1 or −1. c Predicted strength (using multi-linear regression and leave-one-out cross-validation, see text for details) vs strength computed in MD simulations for the 163 IP models. d r2 and adjusted r2 goodness of fit as each of the 35 predictor properties are added in the order shown. Each point represents r2 and adjusted r2 of a model including the corresponding predictor and all predictors to its left. Here, the predictors are added in decreasing order of individual correlation with strength.

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