Flexocatalytic Effect Enables Uranyl Separation by the Organic–Inorganic Hybrid Material
Source abstract
Abstract
Abstract The development of novel technologies for efficient uranyl separation from wastewater is highly desirable, addressing uranium recovery challenges and environmental remediation. Herein, the hybrid material Co[C 4 H 4 N 2 ]V 4 O 10 is reported as a novel flexoelectric catalyst for highly efficient uranyl separation from wastewater. The material demonstrates robust flexocatalytic activity under demanding conditions, including high‐salinity environments, a broad pH range (1.52–11.02), and low ultrasonic power input (20 W). Notably, Co[C 4 H 4 N 2 ]V 4 O 10 achieved outstanding uranium extraction performance in various water matrices, including mining wastewater, seawater, and river water, highlighting its potential for practical applications. By combining DFT calculations, FEM simulations, and comprehensive experimental characterizations, the flexoelectric uranyl separation mechanism is elucidated, which proceeds through the efficient conversion of soluble U(VI) into insoluble UO 2 and (UO 2 )O 2 ·2H 2 O. The anisotropic bonding environments in Co[C 4 H 4 N 2 ]V 4 O 10 enhance deformability along the predominant crystal growth axis, which is identified as the primary origin of its flexocatalytic capability for uranyl separation. This work establishes a structure‐activity relationship for flexoelectric‐driven uranyl separation, offering a promising strategy for wastewater remediation.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Radioactive element chemistry and processing · Pickering emulsions and particle stabilization · Calcium Carbonate Crystallization and Inhibition
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Jiangxi Province Key Laboratory of Functional Organic Polymers East China University of Technology Nanchang 330013 China
National Key Laboratory of Uranium Resources Exploration‐Mining and Nuclear Remote Sensing East China University of Technology Nanchang 330013 China
School of Applied Engineering Gandong University Fuzhou 344000 China
Funding
National Natural Science Foundation of China · Natural Science Foundation of Jiangxi Province
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