脱酚配体络合从含氟废水中高效回收铀

IF 12.8 1区 环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL Water Research Pub Date : 2025-03-01 Epub Date: 2024-11-29 DOI:10.1016/j.watres.2024.122884
Juanlong Li , Yezi Hu , Zewen Shen , Huihui Jin , Rong He , Wenkun Zhu , Guixia Zhao , Zhuoyu Ji , Bin Ma , Xiangke Wang
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引用次数: 0

摘要

从富氟放射性废水中提取铀(U(VI))对核能发展和环境修复具有重要意义。富氟含U(VI)废水中存在热力学稳定的[UO2Fn]2−n (n= 0,1,2,3,4)水溶液配合物,严重影响了传统方法提取和回收铀酰的效率。在这项研究中,我们报告了一种直接沉淀法,利用去铁配体从富氟废水中高效提取铀酰,从而抵消了固体材料的制备。去铁配体表现出与F−竞争的特殊螯合能力。在模拟的2.1 × 10-4 mol/L、F−浓度为1 ~ 10 g/L的U(VI)废水中,调节去铁配体的用量,可使U(Ⅵ)的析出率达到97.60% ~ 86.90%。在2小时内,从实际的富氟碱性废水中,U(Ⅵ)的回收率达到99.71%。详细研究表明,在π-π叠加相互作用、静电吸引和分子间氢键的驱动下,不溶性的U(VI)-去铁络合物([(UO2)(H2O)(C7NO2H8)2]·4H2O)在去铁配体的竞争螯合中形成。考虑到去铁配体的成本效益和优异的耐辐射性,这种高效、直接的沉淀方法在富氟废水的U(VI)修复和资源回收中具有很大的实际应用前景。
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Efficient uranium(VI) recovery from fluorinated wastewater via deferiprone ligand complexation
Extracting uranium (U(VI)) from fluoride-rich radioactive wastewater is of great significance for the development of nuclear energy and environmental remediation. The presence of thermodynamically stable [UO2Fn]2−n (n = 0, 1, 2, 3, 4) aqueous complexes in fluoride-rich U(VI)-containing wastewater significantly hinders the efficiency of uranyl extraction and recovery using conventional methods. In this study, we report a direct precipitation method using deferiprone ligands for efficient uranyl extraction from fluoride-rich wastewater that offsets the preparation of solid materials. The deferiprone ligands exhibited exceptional chelating ability competing toward F. In simulated 2.1 × 10–4 mol/L U(VI) wastewater with F concentrations ranging from 1 to 10 g/L, adjusting the amount of deferiprone ligands enabled a high U(Ⅵ) precipitation rate of 97.60 % to 86.90 %, correspondingly. A remarkable 99.71 % recovery of U(Ⅵ) from real fluoride-rich alkaline wastewater was achieved within 2 h. Detailed investigations revealed that the competitive chelating by deferiprone ligands results in the formation of insoluble U(VI)-deferiprone complexes ([(UO2)(H2O)(C7NO2H8)2]·4H2O), driven by π-π stacking interactions, electrostatic attractions, and intermolecular hydrogen bonds. Given the cost-efficiency and excellent radiation resistance of deferiprone ligands, this efficient and straightforward precipitation approach holds great promise for practical applications in U(VI) remediation and resource recovery from fluoride-rich wastewater.
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来源期刊
Water Research
Water Research 环境科学-工程:环境
CiteScore
20.80
自引率
9.40%
发文量
1307
审稿时长
38 days
期刊介绍: Water Research, along with its open access companion journal Water Research X, serves as a platform for publishing original research papers covering various aspects of the science and technology related to the anthropogenic water cycle, water quality, and its management worldwide. The audience targeted by the journal comprises biologists, chemical engineers, chemists, civil engineers, environmental engineers, limnologists, and microbiologists. The scope of the journal include: •Treatment processes for water and wastewaters (municipal, agricultural, industrial, and on-site treatment), including resource recovery and residuals management; •Urban hydrology including sewer systems, stormwater management, and green infrastructure; •Drinking water treatment and distribution; •Potable and non-potable water reuse; •Sanitation, public health, and risk assessment; •Anaerobic digestion, solid and hazardous waste management, including source characterization and the effects and control of leachates and gaseous emissions; •Contaminants (chemical, microbial, anthropogenic particles such as nanoparticles or microplastics) and related water quality sensing, monitoring, fate, and assessment; •Anthropogenic impacts on inland, tidal, coastal and urban waters, focusing on surface and ground waters, and point and non-point sources of pollution; •Environmental restoration, linked to surface water, groundwater and groundwater remediation; •Analysis of the interfaces between sediments and water, and between water and atmosphere, focusing specifically on anthropogenic impacts; •Mathematical modelling, systems analysis, machine learning, and beneficial use of big data related to the anthropogenic water cycle; •Socio-economic, policy, and regulations studies.
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