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Separation and purification of Zr from a low-temperature LiCl–KCl–CsCl eutectic by the formation of dendritic crystal

  • Daoqing Ma , Jichen Xu , ZhiXuan Yi , Bin Ma , Ming Fang EMAIL logo and Xiaoli Tan EMAIL logo
Published/Copyright: August 12, 2025

Abstract

Zirconium is widely used in the nuclear industry as a cladding material for nuclear reactors and loading nuclear fuel. From the perspective of safety and the economy, the recovery of zirconium from cladding waste at low temperatures is of strategic significance for nuclear energy. This work studied the electrochemical behavior of Zr(IV) and the separation of Zr metal in a low-temperature LiCl–KCl–CsCl molten salt system at 573 K (300 °C). Zr(IV) ion was reduced to metallic Zr through a two-step four-electron reaction process Zr(IV) → Zr(III) → Zr on the W electrode. The diffusion coefficients of Zr(IV) on the W electrode calculated by cyclic voltammetry and chronoamperometry were 5.805 × 10−5 cm2 s−1 and 2.861 × 10−5 cm2 s−1, respectively. Furthermore, the reaction activation energy of the Zr(III)/Zr(0) pair was measured to be 34.52 kJ mol−1 by the Tafel method. Then, the electrochemical recovery of Zr was accomplished on the W electrode by potentiostatic electrolysis at −2.0 V or galvanostatic electrolysis at 0.01 A, and two zirconium-containing products with the dendritic and flakes morphologies were obtained accordingly. This study provides a new low-temperature molten salt system for the reprocessing of zirconium cladding and shows the application potential of low-temperature molten salts LiCl–KCl–CsCl for spent fuel reprocessing.


Corresponding author: Ming Fang and Xiaoli Tan, MOE Key Laboratory of Resources and Environmental System Optimization, College of Environmental Science and Engineering, North China Electric Power University, Beijing, 102206, P.R. China, E-mail: (M. Feng), (X. Tan)

  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 author states no conflict of interest.

  6. Research funding: This work is funded by the National Natural Science Foundation of China (U2267222).

  7. Data availability: Not applicable.

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Supplementary Material

This article contains supplementary material (https://doi.org/10.1515/ract-2024-0355).


Received: 2024-09-29
Accepted: 2024-12-19
Published Online: 2025-08-12
Published in Print: 2025-09-25

© 2025 Walter de Gruyter GmbH, Berlin/Boston

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