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Testing of kaolinite/TiO2 nanocomposites for methylene blue removal: photodegradation and mechanism

  • Karim Fendi , Nedjima Bouzidi , Reguia Boudraa , Amira Saidani , Amar Manseri , Dolores Eliche Quesada , Tran Nguyen Hai ORCID logo , Jean-Claude Bollinger ORCID logo , Stefano Salvestrini , Mohamed Kebir , Nacer Belkessa and Lotfi Mouni ORCID logo EMAIL logo
Published/Copyright: January 6, 2025

Abstract

This study investigated the effect of different treatment conditions on kaolinite-halloysite type as a support for TiO2 and their potential application in photocatalysis. These nanocomposites are used to study the photodegradation of methylene blue, a dye widely used in the textile industry and released into the environment. Crystal structure, specific surface area, pore structure and the morphology of kaolinite were all studied using XRD, attenuated total reflectance (ATR), Brunauer-Emmett-Teller (BET), scanning electron microscopy (SEM) and ultraviolet-visible light. The optical band gap increased with increasing kaolin loading from 2.93 to 3.14 eV. Compared with pure TiO2 photocatalyst, the morphology and structure of kaolinite/TiO2 composites can significantly improve their ability to adsorb organic pollutants and their photocatalytic activity: The photocatalytic efficiency of kaolinite/TiO2 was evaluated by degrading the textile dye methylene blue (MB) under UV-light irradiation. The results showed an improvement from 71 % using TiO2 to 98 % for nanocomposites kaolinite/TiO2 using samples amount of 1 g/L and Co = 20 mg/L.


Corresponding author: Lotfi Mouni, Laboratoire de Gestion et Valorisation des Ressources Naturelles et Assurance Qualité, Faculté SNVST, Université de Bouira, Bouira 10000, Algeria, E-mail:

  1. Research ethics: Not applicable.

  2. Informed consent: Not applicable.

  3. Author contributions: Conceptualization, K.F., L.M., A.I., B.N. and R.B; methodology, K.F., A.S., and N.B.; validation, L.M., and A.A.; formal analysis, M.A , S.S., Q.E., K.M and A.S, investigation, K.F ; resources, S.S., A.A., and B.N.; data curation, S.A., R.B., B.N, and K.F.; writing – original draft preparation, K.F; L.M.; writing – review and editing, K.F., B.J, L.M., T.N and A.A.; visualization, K.F., I.A.; B.J, L.M., T.N and A.A supervision, B.J, L.M., T.N and A.A project administration, K.F.,I.A.; B.J, L.M., T.N and A.A All authors have read and agreed to the published version of the manuscript.

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

  5. Conflict of interest: The author states no conflict of interest.

  6. Research funding: None declared.

  7. Data availability: Not applicable.

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Supplementary Material

This article contains supplementary material (https://doi.org/10.1515/ijcre-2024-0145).


Received: 2024-07-20
Accepted: 2024-12-20
Published Online: 2025-01-06

© 2024 Walter de Gruyter GmbH, Berlin/Boston

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