[HTML][HTML] Recent advancements and challenges in emerging applications of biochar-based catalysts

X Yuan, Y Cao, J Li, AK Patel, CD Dong, X **… - Biotechnology …, 2023 - Elsevier
The sustainable utilization of biochar produced from biomass waste could substantially
promote the development of carbon neutrality and a circular economy. Due to their cost …

[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 …

Prediction of soil heavy metal immobilization by biochar using machine learning

KN Palansooriya, J Li, PD Dissanayake… - … science & technology, 2022 - ACS Publications
Biochar application is a promising strategy for the remediation of contaminated soil, while
ensuring sustainable waste management. Biochar remediation of heavy metal (HM) …

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 methods for modelling the gasification and pyrolysis of biomass and waste

S Ascher, I Watson, S You - Renewable and Sustainable Energy Reviews, 2022 - Elsevier
Over the past two decades, the use of machine learning (ML) methods to model biomass
and waste gasification/pyrolysis has increased rapidly. Only 70 papers were published in …

Applied Machine Learning for Prediction of CO2 Adsorption on Biomass Waste-Derived Porous Carbons

X Yuan, M Suvarna, S Low… - Environmental …, 2021 - ACS Publications
Biomass waste-derived porous carbons (BWDPCs) are a class of complex materials that are
widely used in sustainable waste management and carbon capture. However, their diverse …

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 assisted predicting and engineering specific surface area and total pore volume of biochar

H Li, Z Ai, L Yang, W Zhang, Z Yang, H Peng… - Bioresource …, 2023 - Elsevier
Biochar produced from pyrolysis of biomass is a platform porous carbon material that have
been widely used in many areas. Specific surface area (SSA) and total pore volume (TPV) …

Bottom-up hydrothermal carbonization for the precise engineering of carbon materials

Y Gong, L **e, C Chen, J Liu, M Antonietti… - Progress in Materials …, 2023 - Elsevier
Hydrothermal carbonization (HTC) of carbohydrates in general has been reported as a
sustainable and green technique to produce novel carbon materials. Traditional HTC of …

Characterizing sludge pyrolysis by machine learning: towards sustainable bioenergy production from wastes

H Shahbeik, S Rafiee, A Shafizadeh, D Jeddi, T Jafary… - Renewable Energy, 2022 - Elsevier
Sludge pyrolysis has sparked the interest of researchers because of its capability to dispose
of hazardous residues while producing valuable bioproducts. Numerous expensive and …