Supplementary Information and codes for "Prediction of Ionic Conductivity in Solid-State Electrolytes Using Machine Learning"

Supplementary information (Tables and Figures) and codes for Prediction of Ionic Conductivity in Solid-State Electrolytes Using Machine LearningThis repository contains all datasets, supplementary informaion, and code used in the study. The materials are organized as follows:Ion conductivitiy.ipynb - Jupiter notebook containing the code used for regression modeling.materialformula_Li_afterSD.csv - Curated dataset of room-temperature ionic conductivities for Li-based solid electrolytes.materialformula_Na_afterSD.csv - Curated dataset of room-temperature ionic conductivities for Li-based solid electrolytes.materialformula_LiNa_afterSD.csv - Combined dataset ihostmaterialformula_LiNa_afterSD.csv - Dataset using host material featurization with one-hot encoding of the mobile ion.Supplementary Information.xlsx (Tables and Figures) - Additional tables and figures referenced in the manuscript.All datasets were obtained through a combination of large language model-assisted extraction and manual curation. The code provided reproduces the regression and classification models described in the article.