Startseite Enhanced degradation of malachite green through heterogeneous processes using an iron oxide catalyst
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Enhanced degradation of malachite green through heterogeneous processes using an iron oxide catalyst

  • Sara Belattar , Yazid Mameri , Ala Abdessemed ORCID logo EMAIL logo , Sihem Belaidi , Nassira Seraghni , Belahlou Khalida , Nouar Hayette , Nadra Debbache und Tahar Sehili
Veröffentlicht/Copyright: 20. November 2024

Abstract

This laboratory-scale study investigated the removal of Malachite Green (MG) dye using the goethite composite (α-FeOOH) (GOE). In the dark, an interaction between MG and GOE, attributed to physical adsorption, was observed, reaching 28 % after 4 h and confirmed by FTIR analysis. The addition of hydrogen peroxide (H2O2) enhanced the thermal process in the MG-GOE system. By varying parameters such as pH, GOE concentration, and H2O2 amount, the MG disappearance rate increased with higher GOE and H2O2 concentrations. Alkaline pH favored dye removal. Under UV light (365 nm), GOE effectively degraded MG, especially at pH 9 (97 % degradation in 180 min). The scavenging of hydroxyl radicals (˙OH) by tert-butanol in the GOE-MG-UV365nm system indicated ˙OH-dominated degradation. Fe(II) formation monitoring supported this result. Additionally, H2O2 addition significantly enhanced photodegradation. Partial mineralization of dye molecules was observed via Total Organic Carbon (TOC) analysis. The kinetics of MG degradation followed pseudo-first order behavior. Overall, this promising process holds potential for recalcitrant environmental pollutant removal.


Corresponding author: Ala Abdessemed, Biotechnology Research Centre, BPE 73, Ali Mendjeli, Nouvelle Ville, 25000, Constantine, Algeria, E-mail:

Funding source: Algerian General Directorate of Scientific Research and Technological Development (DGRSDT)

  1. Research ethics: Not applicable.

  2. Informed consent: Informed consent was obtained from all individuals included in this study, or their legal guardians or wards.

  3. Author contributions: The authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  4. Use of Large Language Models, AI and Machine Learning Tools: None declared.

  5. Conflict of interest: The authors state no conflict of interest.

  6. Research funding: The authors thank the Algerian General Directorate of Scientific Research and Technological Development (DGRSDT) for their financial support.

  7. Data availability: The raw data can be obtained on request from the corresponding author.

Appendix A: Supplementary data

Supplementary data associated with this article.

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Supplementary Material

This article contains supplementary material (https://doi.org/10.1515/ijcre-2024-0190).


Received: 2024-09-17
Accepted: 2024-10-18
Published Online: 2024-11-20

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