iSCAT‑based NMC battery degradation analysis pipeline
The project provides a full end‑to‑end workflow to analyze interferometric scattering microscopy data of NMC811 cathodes during cycling. It includes data inventory, electrochemical EDA, particle‑level intensity tracing, ML models for remaining‑useful‑life prediction, spatial heterogeneity clustering, and crack‑hazard forecasting. Researchers can run the pipeline on HPC clusters via SLURM, leveraging PyTorch models and HDF5 handling. Its niche focus and ready‑to‑run scripts make it more practical than generic ML toolkits for battery scientists.
View on GitHub →sagarnidhish/nmc-degradation-iscat-analysis