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Exploring the Pareto front of strength-conductivity trade-off: interpretable machine learning for property prediction and composition design in high-strength high-conductivity Cu alloys

Figure 1. Workflow of ML-assisted copper alloy design. ML: Machine learning; EC: electrical conductivity; UTS: ultimate tensile strength; SHAP: Shapley additive explanations; SVM: support vector machine; GPR: Gaussian process regression; EXP-GPR: experimentally trained Gaussian process regression; MOGWO: multi-objective grey wolf optimizer.

Journal of Materials Informatics
ISSN 2770-372X (Online)
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