Simulating La₁₋ₓSrₓMnO₃ Superconductor with LAMMPS
Simulating Sr-doped La₁₋ₓSrₓMnO₃ (LSMO) using Python + LAMMPS with XRD, density, and composition analysis.
Simulating Sr-Doped La₁₋ₓSrₓMnO₃ (LSMO) Superconductor Using LAMMPS
This project demonstrates a Python-based workflow to simulate the synthesis and analyze the structural properties of Sr-doped La₁₋ₓSrₓMnO₃ (LSMO), a complex perovskite material known for its rich magnetic and electronic behavior.
Using LAMMPS, we:
- Created doped crystal structures by replacing La with Sr
- Performed atomistic relaxation
- Analyzed the structure using X-ray diffraction (XRD), density, and elemental composition plots
The workflow offers a foundation for high-throughput simulation studies of doped perovskites and can be extended for advanced material discovery pipelines.
Explore the complete code on GitHub
For a deeper dive into the process and results, read the Medium article.
Here are some visualizations from the project:
Simulation of Sr-doped La₁₋ₓSrₓMnO₃ with structural relaxation and XRD analysis.
Smoothed XRD pattern showing diffraction peaks after atomic relaxation.
Elemental composition pie chart showing La, Sr, Mn, and O distribution.
