[HTML][HTML] Recent advancements and challenges in emerging applications of biochar-based catalysts
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 …
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 …
Recently, machine learning (ML) has been extensively used to predict yields, compositions …
Prediction of soil heavy metal immobilization by biochar using machine learning
Biochar application is a promising strategy for the remediation of contaminated soil, while
ensuring sustainable waste management. Biochar remediation of heavy metal (HM) …
ensuring sustainable waste management. Biochar remediation of heavy metal (HM) …
Applications of machine learning in thermochemical conversion of biomass-A review
Thermochemical conversion of biomass has been considered a promising technique to
produce alternative renewable fuel sources for future energy supply. However, these …
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 …
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
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 …
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 …
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) …
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
Hydrothermal carbonization (HTC) of carbohydrates in general has been reported as a
sustainable and green technique to produce novel carbon materials. Traditional HTC of …
sustainable and green technique to produce novel carbon materials. Traditional HTC of …
Characterizing sludge pyrolysis by machine learning: towards sustainable bioenergy production from wastes
Sludge pyrolysis has sparked the interest of researchers because of its capability to dispose
of hazardous residues while producing valuable bioproducts. Numerous expensive and …
of hazardous residues while producing valuable bioproducts. Numerous expensive and …