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Fabrication and characterization of boron doped carbon dots@chitosan/polyvinyl alcohol hydrogels for methylene blue adsorption

  • Guizhen Gong EMAIL logo and Zhe Tang
Published/Copyright: April 2, 2025
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Abstract

In this study, a new boron doped carbon dots@chitosan/polyvinyl alcohol (B-CDs@CS/PVA) hydrogel was prepared for methylene blue (MB) removal from aqueous solution. The B-CDs were first synthesized using orange peel with the addition of boric acid by microwave heating process and then the B-CDs were embedded with chitosan and PVA. The structure and characterization of B-CDs and B-CDs@CS/PVA hydrogel were performed by Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), scanning electron microscope (SEM), differential scanning calorimetry (DSC), thermogravimetric analysis (TG), UV–Vis spectrophotometer and fluorescence spectrophotometer. The results showed that B-CDs solution with an abundance hydroxyl and carbonyl functional groups exhibited UV absorption and fluorescence properties. There is a strong interaction between B-CDs and CS/PVA, which improved the crystallinity and thermal stability of B-CDs@CS/PVA hydrogels. The adsorption performance of B-CDs@CS/PVA hydrogels for MB was studied through batch experiments. The maximum adsorption capacity of the B-CDs/PVA hydrogel for MB was 3.573 mg/g for 12 h. In addition, it was found that the adsorption behavior obeyed the pseudo-second-order kinetic and Freundlich models. The composite hydrogels are promising adsorbent for dye wastewater purification.


Corresponding author: Guizhen Gong, School of Materials and Chemical Engineering, Xuzhou University of Technology, Xuzhou 221018, China, E-mail:

Funding source: Xuzhou University of Technology

Award Identifier / Grant number: XKY2018124

Funding source: China Building Materials Federation

Award Identifier / Grant number: 2014-M3-4

  1. Research ethics: Not applicable.

  2. Informed consent: Not applicable.

  3. Author contributions: All 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 research presented in this paper was supported by China Building Materials Federation (grant number 2014-M3-4) and Xuzhou University of Technology (grant number XKY2018124).

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

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Received: 2025-01-03
Accepted: 2025-03-10
Published Online: 2025-04-02
Published in Print: 2025-05-26

© 2025 Walter de Gruyter GmbH, Berlin/Boston

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