Data and Code Repository for "Feedstock-Driven Hydrochar Design for Enhanced Sludge Biorefinery: A Meta-Analysis and Experimental Validation Study"

This repository contains the datasets and computational scripts supporting the study on feedstock-driven hydrochar design for sludge biorefinery optimization.

The repository includes:

1. A processed meta-analysis dataset compiled from published literature, containing feedstock characteristics, hydrothermal parameters, and hydrochar physicochemical properties used for Random Forest (RF) modeling and SHAP feature importance analysis.

2. Python scripts used for:

   • Random Forest model construction and evaluation

   • SHAP-based feature importance analysis

The meta-analysis dataset includes only processed numerical data extracted from published studies and does not contain copyrighted materials.