Dataset for Mechanistic Machine Learning for Biomass Pyrolysis

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Authors: ohn zin lin, Aye Hnin Yee, Libor Štěpanec
Cited by: 0

Abstract

This dataset supports the article “Mechanistic Machine Learning for Biomass Pyrolysis: Integrating Lignocellulosic Structure, Thermal Severity, and Multi-Objective Optimization for Organic Bio-Oil Yield.” It contains experimental and derived data related to biomass pyrolysis, including lignocellulosic structural characteristics, thermal severity parameters, and resulting product yields. The data were used to develop and validate mechanistic machine learning models and to perform multi-objective optimization aimed at maximizing organic bio-oil yield. The dataset is provided in Excel format (Data.xlsx) and is intended to facilitate reproducibility, model benchmarking, and further research in biomass conversion and data-driven process optimization. This is a derived dataset created from the original dataset published by https://doi.org/10.1016/j.fuel.2025.135000. The data were processed, additional features were added, and reformatted; no new data were collected.

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
9 January 2026
Language
EN
Document type
Dataset