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 …

Data to intelligence: The role of data-driven models in wastewater treatment

M Bahramian, RK Dereli, W Zhao, M Giberti… - Expert Systems with …, 2023 - Elsevier
Increasing energy efficiency in wastewater treatment plants (WWTPs) is becoming more
important. An emerging approach to addressing this issue is to exploit development in data …

Machine-learning-based prediction and optimization of emerging contaminants' adsorption capacity on biochar materials

ZH Jaffari, H Jeong, J Shin, J Kwak, C Son… - Chemical Engineering …, 2023 - Elsevier
Biochar materials have recently received considerable recognition as eco-friendly and cost-
effective adsorbents capable of effectively removing hazardous emerging contaminants (eg …

Machine learning approaches to predict the photocatalytic performance of bismuth ferrite-based materials in the removal of malachite green

ZH Jaffari, A Abbas, SM Lam, S Park, K Chon… - Journal of hazardous …, 2023 - Elsevier
This study focuses on the potential capability of numerous machine learning models, namely
CatBoost, GradientBoosting, HistGradientBoosting, ExtraTrees, XGBoost, DecisionTree …

New use for Lentinus edodes bran biochar for tetracycline removal

X Liu, Z Shao, Y Wang, Y Liu, S Wang, F Gao… - Environmental …, 2023 - Elsevier
The abuse of antibiotics poses a threat to the ecological environment and biological health,
and how to effectively reduce the residue of tetracycline (TC) in the environment has …

Insights into the adsorption of pharmaceuticals and personal care products (PPCPs) on biochar and activated carbon with the aid of machine learning

X Zhu, M He, Y Sun, Z Xu, Z Wan, D Hou… - Journal of Hazardous …, 2022 - Elsevier
The science-informed design of 'green'carbonaceous materials (eg, biochar and activated
carbon) with high removal capacity of recalcitrant organic contaminants (eg …

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) …

Machine learning predicting and engineering the yield, N content, and specific surface area of biochar derived from pyrolysis of biomass

L Leng, L Yang, X Lei, W Zhang, Z Ai, Z Yang, H Zhan… - Biochar, 2022 - Springer
Biochar produced from pyrolysis of biomass has been developed as a platform
carbonaceous material that can be used in various applications. The specific surface area …

Machine learning aided supercritical water gasification for H2-rich syngas production with process optimization and catalyst screening

J Li, L Pan, M Suvarna, X Wang - Chemical Engineering Journal, 2021 - Elsevier
Hydrogen production from wet organic wastes through supercritical water gasification
(SCWG) promotes sustainable development. However, it is always time-consuming and …

Construction of a novel double S-scheme heterojunction CeO2/g-C3N4/Bi2O4 for significantly boosted degradation of tetracycline: Insight into the dual charge transfer …

S Zhao, J Jiang, C Zhang, F Chen, Y Song… - Chemical Engineering …, 2024 - Elsevier
Constructing dual S-scheme heterojunction, as one kind of new strategy for the
reinforcement of photocatalytic property, shows significant advantages in facilitating the …