Exploring Insights in Biomass and Waste Gasification via Ensemble Machine Learning Models and Interpretability Techniques

International Journal of Energy Research, Journal Year: 2024, Volume and Issue: 2024(1)

Published: Jan. 1, 2024

This comprehensive review delves into the intersection of ensemble machine learning models and interpretability techniques for biomass waste gasification, a field crucial sustainable energy solutions. It tackles challenges like feedstock variability temperature control, highlighting need deeper understanding to optimize gasification processes. The study focuses on advanced modeling random forests gradient boosting, alongside methods Shapley additive explanations partial dependence plots, emphasizing their importance transparency informed decision‐making. Analyzing diverse case studies, explores successful applications while acknowledging overfitting computational complexity, proposing strategies practical robust models. Notably, finds consistently achieve high prediction accuracy (often exceeding R 2 scores 0.9) gas composition, yield, heating value. These (34% reviewed papers) are most applied method, followed by artificial neural networks (26%). Heating value (12%) was studied performance metric. However, is often neglected during model development due complexity permutation Gini importance. paper calls dedicated research utilizing interpreting models, especially co‐gasification scenarios, unlock new insights process synergy. Overall, this serves as valuable resource researchers, practitioners, policymakers, offering guidance enhancing efficiency sustainability gasification.

Language: Английский

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BCLH2Pro: A novel computational tools approach for hydrogen production prediction via machine learning in biomass chemical looping processes

Energy and AI, Journal Year: 2024, Volume and Issue: 18, P. 100414 - 100414

Published: Aug. 13, 2024

This study optimizes biomass chemical looping processes (BCLpro), a technique for converting to energy, through machine learning (ML) sustainable energy production. The proposes an integrated Fe2O3-based ฺBCLpro combining steam gasification H2 Aspen Plus is used as the primary tool generate extensive datasets covering 24 types with 18 feature inputs in supervised model. A methodology involving K-Nearest Neighbors (KNN), Extreme Gradient Boosting (XGB), Light Machine (LGBM), Support Vector (SVM), Random Forest (RF), and CatBoost (CB) algorithms was employed predict yields BCLpro, utilizing 10-fold cross-validation robust model evaluation. Findings highlight CB algorithm's superior performance, achieving up 98% predictive accuracy, carbon content, reducer temperature, Fe2O3/Al2O3 mass ratio identified crucial features. algorithm has been developed into user-friendly tool, BCLH2Pro, accessible via web server. designed assist reducing costs, optimizing selection, planning operational conditions maximize yield BCLpro systems. Access can be obtained following link: http://bclh2pro.pythonanywhere.com/.

Language: Английский

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Enhancing aromatic hydrocarbon production via catalytic co-pyrolysis of cabbage waste and low-density polyethylene using Fe-modified ZSM-5 catalyst

Biomass Conversion and Biorefinery, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 7, 2025

Language: Английский

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Modelling of biomass gasification for fluidized bed in Aspen Plus: Using machine learning for fast pyrolysis prediction

Energy Conversion and Management, Journal Year: 2025, Volume and Issue: 332, P. 119695 - 119695

Published: March 18, 2025

Language: Английский

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State-of-the-art and perspectives of hydrogen generation from waste plastics

Chemical Society Reviews, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 1, 2025

This review provides a comprehensive analysis of hydrogen production through plastic waste upcycling, covering both established and emerging technologies, addressing their feasibility commercialization challenges.

Language: Английский

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Plastic wastes for carbon-based materials: investigations on recent applications towards environmentally sustainable, carbon dioxide capture and green energy

Environmental Pollution, Journal Year: 2025, Volume and Issue: unknown, P. 125899 - 125899

Published: Feb. 1, 2025

Language: Английский

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Sustainable Hydrogen Production from Plastic Waste: Optimizing Pyrolysis for a Circular Economy

Hydrogen, Journal Year: 2025, Volume and Issue: 6(1), P. 15 - 15

Published: March 7, 2025

Hydrogen is a clean, non-polluting fuel and key player in decarbonizing the energy sector. Interest hydrogen production has grown due to climate change concerns need for sustainable alternatives. Despite advancements waste-to-hydrogen technologies, efficient conversion of mixed plastic waste via an integrated thermochemical process remains insufficiently explored. This study introduces novel multi-stage pyrolysis-reforming framework maximize yield from waste, including polyethylene (HDPE), polypropylene (PP), polystyrene (PS). optimization achieved through integration two water–gas shift reactors pressure swing adsorption unit, enabling rates up 31.85 kmol/h (64.21 kg/h) 300 kg/h wastes, consisting 100 each HDPE, PP, PS. Key parameters were evaluated, revealing that increasing reforming temperature 500 °C 1000 boosts by 83.53%, although gains beyond 700 are minimal. Higher pressures reduce carbon monoxide yields, while steam-to-plastic ratio enhances efficiency. work highlights novel, scalable, thermochemically strategy valorizing into hydrogen, contributing circular economy goals transition.

Language: Английский

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Waste to hydrogen: Steam gasification of municipal solid wastes with carbon capture for enhanced hydrogen production

Biomass and Bioenergy, Journal Year: 2025, Volume and Issue: 198, P. 107855 - 107855

Published: April 9, 2025

Language: Английский

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Machine learning-assisted catalyst synthesis and hydrogen production via catalytic hydrolysis of sodium borohydride

International Journal of Hydrogen Energy, Journal Year: 2025, Volume and Issue: 129, P. 130 - 149

Published: April 24, 2025

Language: Английский

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Plastics Are Paving the Way for a Greener Future and Accelerating Decarbonization

Published: Feb. 29, 2024

This Paper delves into the critical role played by fossil fuel-based polymers in promoting United Nations Sustainable Development Goals (SDGs) face of challenges brought about swift population growth, suburbanization, and mechanization. It sheds light on environmental energy security recompences converting plastic waste biofuels other valuable resources through state-of-the-art processes such as thermochemical conversion pyrolysis. Besides, research investigates utilization solar energy, storage, low carbon transportation, emphasizing inevitability a dual approach that combines advancements bio-based recycling technologies. highlights significance collaborative endeavors involving governments, industries, communities to overcome technical, economic, regulatory complications transitioning towards sustainable circular economy. Eventually, it showcases potential fostering landscape, conducive decarbonization efforts, endorsing sustainability.

Language: Английский

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