High Entropy Effect Induced In-situ Surface Hydroxylation for Robust Electro-assisted Uranium Mineralization from Real Nuclear Wastewater
Exploring highly active and cost-efficient electrocatalysts with in-situ regeneration of coordination sites is crucial for the large-scale application of electro-assisted uranium extraction technology, which can effectively solve the problem of limited coordination sites for traditional catalysts. Herein, we tailor the charge distribution of La(CrFeCoNiCu)O3 via high-entropy effect to induce in-situ surface hydroxylation, thereby enabling robust uranium recovery from fluoride-containing uranium wastewater. The as-prepared La(CrFeCoNiCu)O3 exhibits high uranium extraction performance, achieving a 97.8% extraction efficiency in fluoride-containing uranium wastewater and still maintaining over 91.3% with real uranium wastewater. Relying on in-situ attenuated total reflection surface-enhanced infrared absorption spectroscopy (ATR-SEIRAS) and quasi-in-situ X-ray photoelectron spectroscopy (XPS), we confirm that Cu sites serve as hydroxylation active sites, enabling precise capture of fluoro-uranium complexes, followed by uranium mineralization via electron reduction-free radical reoxidation pathway. In addition, large-scale application verification of real nuclear wastewater is conducted on the self-designed flow electrolysis device, confirming its cost advantage. A La(CrFeCoNiCu)O3 high-entropy perovskite that drives charge redistribution and in situ surface hydroxylation is reported here, achieving >98% U extraction from real nuclear wastewater. Advanced characterizations identify Cu as the key active site.
Authors
- Zicheng Yao
- Wenkun Zhu (ORCID: https://orcid.org/0000-0002-4116-6213)
- Xiaofang Feng (ORCID: https://orcid.org/0000-0003-0667-6776)
- Hailin Wu
- Xiaoyu Liu
- Xiaochuan Deng
- Tao Chen
- Wenli Zhou
- Wenjie Sun
- Xue Jiang
- Xun Yang
Institutions
- Southwest University of Science and Technology (CN)
Publication Details
- Journal
- Nature Communications
- Published
- 2026-09-01
- DOI
- https://doi.org/10.1038/s41467-026-76781-0
- Primary Topic
- Radioactive element chemistry and processing
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Artificial Intelligence Research Center
- National Natural Science Foundation of China
- Southwest University of Science and Technology
- Southwest University
- Natural Science Foundation of Sichuan Province