Potential of Bi2WO6-based heterojunction photocatalysts for environmental remediation

AS Belousov, AA Parkhacheva, EV Suleimanov… - Materials Today …, 2023 - Elsevier
Abstract Bismuth tungstate (Bi 2 WO 6)-based photocatalytic materials have become a
research hotspot in photocatalytic energy conversion and environmental remediation due to …

Recent Advances in gC3N4-Based Materials and Their Application in Energy and Environmental Sustainability

Q Wang, Y Li, F Huang, S Song, G Ai, X Xin, B Zhao… - Molecules, 2023 - mdpi.com
Graphitic carbon nitride (g-C3N4), with facile synthesis, unique structure, high stability, and
low cost, has been the hotspot in the field of photocatalysis. However, the photocatalytic …

Biomass microwave pyrolysis characterization by machine learning for sustainable rural biorefineries

Y Yang, H Shahbeik, A Shafizadeh, N Masoudnia… - Renewable Energy, 2022 - Elsevier
Microwave heating is a promising solution to overcome the shortcomings of conventional
heating in biomass pyrolysis. Nevertheless, biomass microwave pyrolysis is a complex …

AI for nanomaterials development in clean energy and carbon capture, utilization and storage (CCUS)

H Chen, Y Zheng, J Li, L Li, X Wang - ACS nano, 2023 - ACS Publications
Zero-carbon energy and negative emission technologies are crucial for achieving a carbon
neutral future, and nanomaterials have played critical roles in advancing such technologies …

Navigating challenges and opportunities of machine learning in hydrogen catalysis and production processes: Beyond algorithm development

MNI Salehmin, TS Kiong, H Mohamed, DA Umar… - Journal of Energy …, 2024 - Elsevier
With the projected global surge in hydrogen demand, driven by increasing applications and
the imperative for low-emission hydrogen, the integration of machine learning (ML) across …

Enhanced machine learning for nanomaterial identification of photo thermal hydrogen production

G Ramkumar, M Tamilselvi, SDS Jebaseelan… - International Journal of …, 2024 - Elsevier
Instead of using temperature via an outside source, using energy created inside is the most
effective method to improve the efficiency of catalysis. In this research, a novel hollowed TiO …

Integrating experimental and machine learning approaches for predictive analysis of photocatalytic hydrogen evolution using Cu/g-C3N4

B Arabacı, R Bakır, C Orak, A Yüksel - Renewable Energy, 2024 - Elsevier
This study addresses environmental issues like global warming and wastewater generation
by exploring waste-to-energy strategies that produce renewable hydrogen and treat …

Machine learning integrated photocatalysis: progress and challenges

L Ge, Y Ke, X Li - Chemical Communications, 2023 - pubs.rsc.org
Discovering efficient photocatalysts has long been the goal of photocatalysis, which has
traditionally been driven by serendipitous or try-and-error strategies. Recent developments …

Interpretable machine learning model for activation energy prediction based on biomass properties

J Huang, X Wang, L Song, J Wang - Thermal Science and Engineering …, 2024 - Elsevier
A thorough understanding of pyrolysis kinetics for biomass is crucial for the process design,
feasibility assessment, and scale-up in industrial scenarios. To reduce the time and …

Stacked machine learning approach for predicting evolved hydrogen from sugar industry wastewater

R Bakır, C Orak - International Journal of Hydrogen Energy, 2024 - Elsevier
The wastewater generated by the sugar industry contains high levels of organic pollutants,
posing significant environmental and health risks. Traditional treatment methods often fall …