Conversion of organic solid waste into energy and functional materials using biochar catalyst: Bibliometric analysis, research progress, and directions

Applied Catalysis B Environment and Energy, Год журнала: 2023, Номер 340, С. 123223 - 123223

Опубликована: Сен. 1, 2023

Язык: Английский

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Machine learning applications for biochar studies: A mini-review

Bioresource Technology, Год журнала: 2024, Номер 394, С. 130291 - 130291

Опубликована: Янв. 4, 2024

Язык: Английский

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A machine learning assisted prediction of potential biochar and its applications in anaerobic digestion for valuable chemicals and energy recovery from organic waste

Carbon Neutrality, Год журнала: 2024, Номер 3(1)

Опубликована: Янв. 8, 2024

Abstract The utilization of biochar derived from biomass residue to enhance anaerobic digestion (AD) for bioenergy recovery offers a sustainable approach advance energy and mitigate climate change. However, conducting comprehensive research on the optimal conditions AD experiments with addition poses challenge due diverse experimental objectives. Machine learning (ML) has demonstrated its effectiveness in addressing this issue. Therefore, it is essential provide an overview current ML-optimized processes biochar-enhanced order facilitate more systematic ML tools. This review comprehensively examines material flow preparation impact comprehension reviewed optimize production process perspective. Specifically, summarizes application techniques, based artificial intelligence, predicting yield properties residues, as well their AD. Overall, analysis address challenges recovery. In future research, crucial tackle that hinder implementation pilot-scale reactors. It recommended further investigate correlation between physicochemical process. Additionally, enhancing role throughout entire holds promise achieving economically environmentally optimized efficiency. Graphical

Язык: Английский

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Machine learning in clarifying complex relationships: Biochar preparation procedures and capacitance characteristics

Chemical Engineering Journal, Год журнала: 2024, Номер 485, С. 149975 - 149975

Опубликована: Фев. 24, 2024

Язык: Английский

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Biochar production and its environmental applications: Recent developments and machine learning insights

Bioresource Technology, Год журнала: 2023, Номер 387, С. 129634 - 129634

Опубликована: Авг. 21, 2023

Язык: Английский

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Using automated machine learning techniques to explore key factors in anaerobic digestion: At the environmental factor, microorganisms and system levels

Chemical Engineering Journal, Год журнала: 2023, Номер 475, С. 146069 - 146069

Опубликована: Сен. 15, 2023

Язык: Английский

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Explicable Machine Learning for Predicting High-Efficiency Lignocellulose Pretreatment Solvents Based on Kamlet–Taft and Polarity Parameters

ACS Sustainable Chemistry & Engineering, Год журнала: 2024, Номер 12(19), С. 7578 - 7590

Опубликована: Апрель 29, 2024

Incorporating density functional theory (DFT) and machine learning (ML) methodologies, an intrinsic relationship model was developed utilizing the Kamlet–Taft parameters polarity values of 104 deep eutectic solvents (DES). DES with high lignocellulosic pretreatment efficiency were expected to be screened through synergistic combination hydrogen bond acidity (α), basicity (β), polarization (Π*) molecular index (MPI). Partial least-squares (PLS) models a variety ML used predict cellulose retention delignification. The XGBoost has highest predictive performance R2 0.97 0.91, respectively. Feature importance analysis partial dependence explain variables based on model. showed that α, β, Π* MPI donor determined efficiency. among 4 is nonlinear, there are multiple extreme in different intervals. gave parameter range corresponding Based given this study, composition ratio can selected ensure at least 80% retained 50% lignin removed. Molecular simulation results these highly efficient often contain large number bonds polar groups.

Язык: Английский

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Machine learning application for predicting key properties of activated carbon produced from lignocellulosic biomass waste with chemical activation

Bioresource Technology, Год журнала: 2024, Номер 399, С. 130624 - 130624

Опубликована: Март 21, 2024

Язык: Английский

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Rethinking the biochar impact on the anaerobic digestion of food waste in bench-scale digester: Spatial distribution and biogas production

Bioresource Technology, Год журнала: 2025, Номер unknown, С. 132115 - 132115

Опубликована: Янв. 1, 2025

Язык: Английский

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Machine learning-based analysis of microplastic-induced changes in anaerobic digestion parameters influencing methane yield

Journal of Environmental Management, Год журнала: 2025, Номер 377, С. 124627 - 124627

Опубликована: Фев. 23, 2025

Язык: Английский

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