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Improving iron-bearing dust pellets performance through synergistic action of dual-component organic binders: cellulose and starch interactions

  • Tao Yang , Xing-wang Li , Qing-hai Yu , Yi-fan Wang , Jie Lei EMAIL logo and Hong-ming Long EMAIL logo
Published/Copyright: March 10, 2025

Abstract

Iron-bearing dust particles demonstrate poor pelletizing performance, resulting in weak and easily pulverized dust pellets, consequently reducing the efficiency of the rotary hearth furnace process. To address this issue, the partial substitution of bentonite with organic binders to create composite binders offers several advantages and represents a crucial strategy for enhancing pellet performance. In this study, we established a liquid bridge model between iron-bearing dust particles and investigated the mechanism of organic binders (OB-A and OB-B) enhancing the cold strength of iron-bearing dust pellets using infrared spectroscopy and contact angle analysis methods. While OB-A enhanced the hydrophilicity of particle surfaces and promoted denser pellet structures, OB-B significantly improved the compressive strength of dry pellets by forming a sturdy network structure during the drying process. These discoveries underscore the potential of composite binders, notably AH-1 binders (comprising 2 % bentonite, 0.18 % OB-A, and 0.8 % OB-B), to enhance both the green and dry pellet performance of iron-bearing dust pellets. Furthermore, the interaction between OB-A and OB-B was found to result in a denser and stronger pellet structure. Such improvements have far-reaching implications for boosting the efficiency of the rotary hearth furnace process.


Corresponding authors: Jie Lei and Hong-ming Long, School of Metallurgical Engineering, Anhui University of Technology, Ma’anshan, Anhui 243032, China; and Key Laboratory of Metallurgical Emission Reduction & Resources Recycling, Anhui University of Technology, Ministry of Education, Ma’anshan, Anhui 243002, China, E-mail: (J. Lei), (H. Long)

Funding source: Outstanding Youth Fund of Anhui Province

Award Identifier / Grant number: 2208085J19

Award Identifier / Grant number: 2022YFC3901405

  1. Research ethics: The local Institutional Review Board deemed the study exempt from review.

  2. Informed consent: Not applicable.

  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: All other authors state no conflict of interest.

  6. Research funding: This work was supported by the National Key Research and Development Program of China (Grant No. 2022YFC3901405) and the Outstanding Youth Fund of Anhui Province (Grant No. 2208085J19).

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

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Supplementary Material

This article contains supplementary material (https://doi.org/10.1515/ijcre-2024-0139).


Received: 2024-07-12
Accepted: 2025-02-22
Published Online: 2025-03-10

© 2025 Walter de Gruyter GmbH, Berlin/Boston

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