Fe(VI) Oxidation of Mixed Trace Phenols: Kinetics, QSAR Modeling, and Cross-Polymerization Mechanisms

  • Mengqiang He
  • , Mingzhu Liu
  • , Xiaolei Teng
  • , Shengnan Zhang
  • , Zunyao Wang
  • , Xiaohong Guan*
  • , Ruijuan Qu
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Phenolic pollutants, frequently detected in aquatic environments as trace-level mixtures, pose significant challenges for water treatment. In this study, we examined the removal of 35 trace phenol mixtures (0.1 μmol/L each) under Fe(VI) oxidation, revealing kinetic differences between single and mixed systems. Fast-reacting phenols with secondary reaction rate constant (kapp) > 350 M−1•s−1 experienced accelerated oxidation upon mixing, whereas slow-reacting ones (kapp ≤ 350 M−1•s−1) exhibited decreased rates. The quantitative structure-activity relationship (QSAR) models were constructed to correlate the kapp of these phenols with molecular descriptors, showing that higher EHOMO and lower Egap were conductive to increasing the reaction rate in the mixed system, while ELUMO had a minimal effect on the reaction. Employing molecular networking for non-targeted screening, we identified the prevalence of cross-polymerization within the mixed system, yielding various cross-polymer products. Reaction pathway analysis, TOC and COD measurements, and theoretical calculations collectively demonstrated that electrophilic attacks of Fe(VI) trigger electron loss in phenols, generating phenoxy radicals that drive cross-polymerization and accelerate reaction rates of fast-reacting phenols, aligning with QSAR model predictions. These findings can deepen our understanding of Fe(VI) oxidation mechanism on mixed trace phenols, offering valuable insights for the advancement of wastewater treatment technologies.

Original languageEnglish
Article number125336
JournalWater Research
Volume292
DOIs
StatePublished - 15 Mar 2026

Keywords

  • Cross-polymerization
  • Ferrate(VI)
  • Mixed trace phenols
  • Molecular networking
  • QSAR modeling

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