[HTML][HTML] Intelligent Algorithms Enable Photocatalyst Design and Performance Prediction

S Wang, P Mo, D Li, A Syed - Catalysts, 2024 - mdpi.com
Photocatalysts have made great contributions to the degradation of pollutants to achieve
environmental purification. The traditional method of developing new photocatalysts is to …

Prediction of antibiotic sorption in soil with machine learning and analysis of global antibiotic resistance risk

J Wang, R Huang, Y Liang, X Long, S Wu, Z Han… - Journal of Hazardous …, 2024 - Elsevier
Although the sorption of antibiotics in soil has been extensively studied, their spatial
distribution patterns and sorption mechanisms still need to be clarified, which hinders the …

Adsorption of uranyl ion on hexagonal boron nitride for remediation of real U-contaminated soil and its interpretation using random forest

BM Jun, SH Chae, D Kim, JY Jung, TJ Kim… - Journal of Hazardous …, 2024 - Elsevier
Acid leaching has been widely applied to treat contaminated soil, however, it contains
several inorganic pollutants. The decommissioning of nuclear power plants introduces …

Multi-channel ceramic catalytic membrane for highly efficient and continuous hydrogenation of p-nitrophenol

G Shao, Y Du, J Zhang, Z Tang, H Jiang… - Separation and …, 2024 - Elsevier
The hydrogenation of p-nitrophenol (4-NP) to p-aminophenol (4-AP) transforms a
detrimental pollutant into a valuable chemical, while conventional powder catalysts face …

Efficient and easily recyclable photocatalytic reduction of Se (IV) from wastewater using stable TiO2/BiOBr/cloth: Mechanism insight and machine learning modeling

Y Liang, Y Yin, Q Deng, S Jiao, X Liang, C Huo… - Separation and …, 2025 - Elsevier
Photocatalytic technology is extensively employed for the reductive removal of water
contaminants; however, it contends with low catalytic efficiency and challenges in catalyst …

Predicting Rate Constants of Alkane Cracking Reactions Using Machine Learning

Y Zhang, M Xia, H Song, M Yang - The Journal of Physical …, 2024 - ACS Publications
Calculating the thermal rate constants of elementary combustion reactions is of great
importance in theoretical chemistry. Machine learning has become a powerful, data-driven …

[HTML][HTML] Determining water and solute permeability of reverse osmosis membrane using a data-driven machine learning pipeline

SH Chae, SW Hong, M Son, KH Cho - Journal of Water Process …, 2024 - Elsevier
Water (A) and solute permeability (B) are the key parameters characterizing the performance
of reverse osmosis (RO) membranes. However, determining A and B requires multiple times …

Programable sewage-cleaning technology: Regenerating chitosan biofilms with anti-bacterial capacity via self-purification of water pollutants

J Wu, S Chen, Q Xu, Q Pang, P Li, Y Li - International Journal of Biological …, 2024 - Elsevier
In this paper, a novel programable sewage-cleaning technology for the regeneration of
antibacterial nanocomposites via the removal of wastewater pollutants is presented …

Predicting the distribution coefficient of cesium in solid phase groups using machine learning

SM Hong, IH Yoon, KH Cho - Chemosphere, 2024 - Elsevier
The migration and retention of radioactive contaminants such as 137 Cesium (137 Cs) in
various environmental media pose significant long-term storage challenges for nuclear …

[HTML][HTML] Z-scheme configured iron oxide/g-C3N4 nanocomposite system for solar-driven H2 production through water splitting

S Bharathkumar, A Murugan, MAW Cordero… - Applied Catalysis O …, 2024 - Elsevier
A nanocomposite composed of α-Fe 2 O 3/gC 3 N 4 is synthesized using a modified
ultrasonication approach, which engineered a robust interfacial contact in the system. Phase …