Biogas production prediction model of food waste anaerobic digestion for energy optimization using mixup data augmentation-based global attention mechanism DOI
Zhiqiang Geng, Xinwei Shi, Bo Ma

et al.

Environmental Science and Pollution Research, Journal Year: 2024, Volume and Issue: 31(6), P. 9121 - 9134

Published: Jan. 6, 2024

Language: Английский

Recent advances in hydrogen production from biomass waste with a focus on pyrolysis and gasification DOI
Van Giao Nguyen, Thi Thanh Xuan Nguyen, Phuoc Quy Phong Nguyen

et al.

International Journal of Hydrogen Energy, Journal Year: 2023, Volume and Issue: 54, P. 127 - 160

Published: May 21, 2023

Language: Английский

Citations

114

Recent advances and perspectives in roles of humic acid in anaerobic digestion of waste activated sludge DOI

Zhang-Wei He,

Fei Wang,

Zheng-Shuo Zou

et al.

Chemical Engineering Journal, Journal Year: 2023, Volume and Issue: 466, P. 143081 - 143081

Published: April 23, 2023

Language: Английский

Citations

47

Comprehensive review on recent production trends and applications of biochar for greener environment DOI

Sivasubramanian Manikandan,

Sundaram Vickram,

Ramasamy Subbaiya

et al.

Bioresource Technology, Journal Year: 2023, Volume and Issue: 388, P. 129725 - 129725

Published: Sept. 7, 2023

Language: Английский

Citations

43

Production and modifications of biochar to engineered materials and its application for environmental sustainability: a review DOI Creative Commons
Gokulan Ravindiran,

Sivarethinamohan Rajamanickam,

Gorti Janardhan

et al.

Biochar, Journal Year: 2024, Volume and Issue: 6(1)

Published: June 21, 2024

Abstract Biochar, a carbon-rich material produced from biomass waste through thermal conversion, holds great environmental promise. This article offers comprehensive overview of the various feedstocks used in biochar production, different types degradation processes, characterization, properties, modifications to engineered materials, and their applications environment. The quality biochar, including surface area, pore size volume, functional group formation, is significantly influenced by specific conditions under which conversion takes place. Each diverse processes employed produce yields distinct set properties final product. In recent years, has gained widespread recognition utilization fields such as wastewater treatment, carbon sequestration, reduction greenhouse gas emissions, biogas catalysis biofuel industries, construction, soil enhancement. summary, promising mitigation tool achieve sustainable addition its benefits, application presents several challenges, selection feedstocks, methods biochar. current review summarizes factors that could lead significant advancements future applications. Graphical

Language: Английский

Citations

25

Machine learning for the management of biochar yield and properties of biomass sources for sustainable energy DOI
Van Giao Nguyen, Prabhakar Sharma, Ümit Ağbulut

et al.

Biofuels Bioproducts and Biorefining, Journal Year: 2024, Volume and Issue: 18(2), P. 567 - 593

Published: Feb. 5, 2024

Abstract Biochar is emerging as a potential solution for biomass conversion to meet the ever increasing demand sustainable energy. Efficient management systems are needed in order exploit fully of biochar. Modern machine learning (ML) techniques, and particular ensemble approaches explainable AI methods, valuable forecasting properties efficiency biochar properly. Machine‐learning‐based forecasts, optimization, feature selection critical improving techniques. In this research, we explore influences these techniques on accurate yield range sources. We emphasize importance interpretability model, improves human comprehension trust ML predictions. Sensitivity analysis shown be an effective technique finding crucial characteristics that influence synthesis Precision prognostics have far‐reaching ramifications, influencing industries such logistics, technologies, successful use renewable These advances can make substantial contribution greener future encourage development circular biobased economy. This work emphasizes using sophisticated data‐driven methodologies synthesis, usher ecologically friendly energy solutions. breakthroughs hold key more environmentally future.

Language: Английский

Citations

23

Techno-economic assessment and logistics management of biomass in the conversion progress to bioenergy DOI Open Access
Viet Duc Bui, Hoang Phuong Vu, Hoang Phuong Nguyen

et al.

Sustainable Energy Technologies and Assessments, Journal Year: 2022, Volume and Issue: 55, P. 102991 - 102991

Published: Dec. 27, 2022

Language: Английский

Citations

44

Nanotechnology- A ray of hope for heavy metals removal DOI

V. Mohanapriya,

R. Sakthivel,

Nguyen Dang Khoa Pham

et al.

Chemosphere, Journal Year: 2022, Volume and Issue: 311, P. 136989 - 136989

Published: Oct. 25, 2022

Language: Английский

Citations

40

A critical review of improving mainstream anammox systems: Based on macroscopic process regulation and microscopic enhancement mechanisms DOI
Xiaonong Zhang, Xingxing Zhang,

Junjiang Chen

et al.

Environmental Research, Journal Year: 2023, Volume and Issue: 236, P. 116770 - 116770

Published: July 28, 2023

Language: Английский

Citations

35

Precise Prediction of Biochar Yield and Proximate Analysis by Modern Machine Learning and SHapley Additive exPlanations DOI
Lê Anh Tuấn, Ashok Pandey,

Ranjan Sirohi

et al.

Energy & Fuels, Journal Year: 2023, Volume and Issue: 37(22), P. 17310 - 17327

Published: Oct. 28, 2023

Biochar is found to possess a large number of applications in energy and environmental areas. However, biochar could be produced from variety sources, showing that yield proximate analysis outcomes change over wide range. Thus, developing high-accuracy machine learning-based tool very necessary predict characteristics. In this study, hybrid technique was developed by blending modern learning (ML) algorithms with cooperative game theory-based Shapley Additive exPlanations (SHAP). SHAP employed help improve interpretability while offering insights into the decision-making process. ML models, linear regression as baseline method, more advanced methodologies like AdaBoost boosted tree (BRT) were employed. The prediction models evaluated on battery statistical metrics, all observed robust enough. Among three BRT-based model delivered best performance R2 range 0.982 0.999 during training phase 0.968 0.988 test. value mean squared error also quite low (0.89 9.168) for models. quantified each input element expected results provided in-depth understanding underlying dynamics. helped reveal temperature main factor affecting response predictions. proposed here provides substantial manufacturing process, allowing improved control properties increasing use sustainable flexible material numerous applications.

Language: Английский

Citations

31

Performance and emission characteristics of diesel engines running on gaseous fuels in dual-fuel mode DOI
Van Nhanh Nguyen, Swarup Kumar Nayak,

Huu Son Le

et al.

International Journal of Hydrogen Energy, Journal Year: 2023, Volume and Issue: 49, P. 868 - 909

Published: Sept. 29, 2023

Language: Английский

Citations

29