Artificial intelligence for waste management in smart cities: a review

B Fang, J Yu, Z Chen, AI Osman, M Farghali… - Environmental …, 2023 - Springer
The rising amount of waste generated worldwide is inducing issues of pollution, waste
management, and recycling, calling for new strategies to improve the waste ecosystem, such …

[HTML][HTML] Machine-learning-aided thermochemical treatment of biomass: a review

H Li, J Chen, W Zhang, H Zhan, C He… - Biofuel Research …, 2023 - biofueljournal.com
Thermochemical treatment is a promising technique for biomass disposal and valorization.
Recently, machine learning (ML) has been extensively used to predict yields, compositions …

Applications of machine learning in thermochemical conversion of biomass-A review

SR Naqvi, Z Ullah, SAA Taqvi, MNA Khan, W Farooq… - Fuel, 2023 - Elsevier
Thermochemical conversion of biomass has been considered a promising technique to
produce alternative renewable fuel sources for future energy supply. However, these …

Machine learning for hydrothermal treatment of biomass: A review

W Zhang, Q Chen, J Chen, D Xu, H Zhan, H Peng… - Bioresource …, 2023 - Elsevier
Abstract Hydrothermal treatment (HTT)(ie, hydrothermal carbonization, liquefaction, and
gasification) is a promising technology for biomass valorization. However, diverse variables …

Machine learning predicts and optimizes hydrothermal liquefaction of biomass

A Shafizadeh, H Shahbeig, MH Nadian, H Mobli… - Chemical Engineering …, 2022 - Elsevier
The hydrothermal liquefaction process has recently attracted more attention in biorefinery
design and implementation because of its capability of handling various wet biomass …

Recent advances and future prospects of thermochemical biofuel conversion processes with machine learning

PR Jeon, JH Moon, NO Ogunsola, SH Lee… - Chemical Engineering …, 2023 - Elsevier
Biofuels have been widely recognized as potential solutions to addressing the climate crisis
and strengthening energy security and sustainability. However, techno-economic and …

Machine learning prediction and optimization of bio-oil production from hydrothermal liquefaction of algae

W Zhang, J Li, T Liu, S Leng, L Yang, H Peng… - Bioresource …, 2021 - Elsevier
Hydrothermal liquefaction (HTL) of algae is a promising biofuel production technology.
However, it is always difficult and time-consuming to identify the best optimal conditions of …

[HTML][HTML] Interpretable machine learning to model biomass and waste gasification

S Ascher, X Wang, I Watson, W Sloan, S You - Bioresource Technology, 2022 - Elsevier
Abstract Machine learning has been regarded as a promising method to better model
thermochemical processes such as gasification. However, their black box nature can limit …

Machine learning methods for modeling conventional and hydrothermal gasification of waste biomass: A review

GC Umenweke, IC Afolabi, EI Epelle… - Bioresource Technology …, 2022 - Elsevier
Conventional and hydrothermal gasification are promising thermochemical technologies for
the production of syngas from waste biomass. Both gasification processes are complex, with …

Wet wastes to bioenergy and biochar: A critical review with future perspectives

J Li, L Li, M Suvarna, L Pan, M Tabatabaei… - Science of the Total …, 2022 - Elsevier
The ever-increasing rise in the global population coupled with rapid urbanization demands
considerable consumption of fossil fuel, food, and water. This in turn leads to energy …