RESEARCH PAPER · Industrial & Engineering Chemistry Research · 2025
Establishing Quantitative Structure–Activity Relationships for the Degradation of Aromatic Organics by UV–H 2 O 2 Using Machine Learning
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Machine learning-based prediction of rate constants in UV/TiO2 degradation of organic compounds
Journal of Water Process Engineering · 2026-01-26
Yanlin Zhang
Read original paper ↗ ·Triatomic-doped MXene based catalyst with sodium alginate encapsulation their molecular and DFT calculation study for efficient photocatalytic removal of disinfected by-product from drinking water
Chemical Engineering Journal · 2026-01-26
Saleem Raza, Ata Ur Rehman, Zhao Zhiyu, Hua Li, Cheng Chen, Wei Yu, Ying Liu, Yan Xu, Liguo Shen, Hongjun Lin
Read original paper ↗ ·Explainable machine learning reveals how molecular descriptors govern micropollutant degradation in UV/H2O2 oxidation
Water Research · 2026-03-22
Mita Nurhayati, Sangsik Kim, Byung Joon Lee, Byung Joon Lee, Ho Kyong Shon, Jaeweon Cho, Sungyun Lee
Read original paper ↗ ·Harnessing Machine Learning to Enhance UV-based Advanced Oxidation Processes for Sustainable Micropollutant Abatement
Environmental Science & Technology · 2026-08-19
Bohan Li, Zhongyan Zhang, Xinyuan Yi, Chii Shang, Yingzheng Fan, Jinfeng Wang, Ran Yin, Xinkun Ren
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