
This repository contains the datasets and computational scripts supporting the study on feedstock-driven hydrochar design for sludge biorefinery optimization. The repository includes: 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. 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.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
