Resolve the species-specific effects of iron (hydr)oxides on the performance of underlying zerovalent iron for metalloid removal: Identification of their key properties

  • Peng Fan
  • , Xuechen Wu
  • , Jianrong Zeng
  • , Lina Li
  • , Kun Qian
  • , Hejie Qin*
  • , Xiaohong Guan
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Despite the importance of surface iron (hydr)oxides (Fe-(hydr)oxides) for the decontamination performance of zerovalent iron (ZVI) -based technologies has been well recognized, controversial understandings of their exact roles still exist due to the complex species distribution of Fe-(hydr)oxides. Herein, we re-structured the surface of ZVI using eight distinct Fe-(hydr)oxides and analyzed their species-specific effects on the performance of ZVI for Se(IV) under well-controlled conditions. The kinetics-relevant performance indicators (Se(IV) removal rates, Fe2+ release rates, and the utilization ratio of ZVI) under the effect of each Fe-(hydr)oxide roughly followed the order: δ-FeOOH > Fe5HO8·4H2O > α-FeOOH > β-FeOOH > γ-FeOOH > γ-Fe2O3 > Fe3O4 > α-Fe2O3. Multiple linear regression analysis shows that the large pore volume and size (instead of specific surface area), low open-circuit potential, and low electrochemical impedance are key positive properties for kinetics-relevant performance. Besides, for electron efficiency of ZVI, only Fe3O4 increased the value to 50.0%, due to the contribution of its ferrous components, while others did not change it (∼20%). Additional experiments with commercial ZVI covered by individual Fe-(hydr)oxides confirmed the observed species-specific trends. All these results not only provide new basis for mechanism explanation but also have practical implications for the production or modification of ZVI.

Original languageEnglish
Article number135378
JournalJournal of Hazardous Materials
Volume477
DOIs
StatePublished - 15 Sep 2024

Keywords

  • Corrosion
  • Electron efficiency
  • Iron oxides
  • Multiple linear regression analysis
  • Passivation

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