implements:
Multi-output property surrogate Predicts resistivity, TCR, Seebeck coefficient, resistance drift, hardness, strength, ductility, and stability score.
Uncertainty-aware prediction Uses ensemble spread as prediction uncertainty, matching your document’s idea that property prediction models can provide candidate estimates and uncertainty bounds for robust feasibility testing
Scenario robustness testing Perturbs composition, cold work, annealing, test temperature, cyclic strain, and measurement noise.
Robust feasibility scoring Checks whether each alloy route remains inside target property windows across scenarios.
Matroid-style greedy partitioning Assigns candidates into buckets such as:
- electrical stability
- high resistivity
- formability
- robust manufacturing
- experimental validation
Closed-loop update path The code is compatible with the workflow in your PDF: Generate → Predict → Partition → Validate → Update, where new experiments update the database and retrain the surrogate model Important: the script includes synthetic data only for testing the pipeline. For real conclusions, replace it with actual experimental, CALPHAD, phase-field, or published Cu–Ni property data.