pySSpredict is a Python-based tool for Solid-solution Strengthening prediction for complex-concentrated alloys. It can be easily installed on the high-throughput computation resources and integrated with TC-Python for desiging high-temperature high-strength structural materials. Contact email: [email protected].
Solid solution strengthening models:
FCC edge dislocation-solute interaction C. Varvenne, G.P.M. Leyson, M. Ghazisaeidi, W.A. Curtin (2017)
BCC edge dislocation-solute interaction F. Maresca, W.A. Curtin (2019)
BCC screw dislocation-solute interaction F. Maresca, W.A. Curtin (2019)
BCC screw dislocation-solute Suzuki model S.I. Rao, C. Woodward, B. Akdim, O.N. Senkov, D. Miracle (2021)
Jupyter notebooks:
Simple calculations and plots
FCC_edge
BCC_edge
BCC_screw
Pseudo-ternary FeMnCoNi+Al FCC complex concentrated alloys predicted by the edge dislocation model. Adapted from study
Ternary NbMoW BCC alloys predicted by the screw dislocation-solute interaction model.
Yield stress-tempreature relationship of BCC TiNbZr alloy predicted by the Suzuki model.
See this example Jupyter Notebook for high-throughput calculations.
You can use pySSpredict together with TC-python for both mechanical properties and phase stability predictions. See this Jupyter Notebook that runs on the cluster.
- Clone the project.
- In the project directory:
pip install .
- Ductility model for BCC materials.