Reproducibility package for Machine-Learning Prediction of Optical Band Gaps and Photocatalytic Performance in Rare-Earth-Doped Spinel Ferrites
Year: 2026
Type: software
Abstract: This repository contains the dataset, Python analysis workflow, model-validation outputs, uncertainty analyses, learning-curve analysis, permutation-importance results, sensitivity analyses, and figures supporting the revised Scientific Reports manuscript entitled “Machine-Learning Prediction of Optical Band Gaps and Photocatalytic Performance in Rare-Earth-Doped Spinel Ferrites.” The package enables reproduction of the reported grouped cross-validation, optical-band-gap analysis, performance metrics, uncertainty estimates, validation comparisons, and figures.
Institutions: Rayat Bahra University, Jimma University
Language: English
Subfield: Materials Chemistry
Field: Materials Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7207583643