A research team has developed a reusable magnetic sensor that detects trace amounts of uranyl ions, a mobile form of uranium, in water. The sensor captures the ions near gold nanoparticles, where their Raman signal becomes easier to measure. In tests, it detected uranyl at concentrations as low as 1×10 -7 moles per liter after 20 minutes of enrichment, remained selective in the presence of several other dissolved ions, and could be used repeatedly. Paired with machine learning, the approach could support faster, more practical monitoring around nuclear and environmental sites.
Uranium monitoring is essential for managing nuclear materials and assessing contamination in aquatic environments. Established analytical methods can measure uranium accurately, but they often require costly instruments, extensive sample preparation, and trained operators. Surface-enhanced Raman scattering (SERS) offers a way to identify substances through their molecular “fingerprints” using potentially portable equipment. Its performance, however, depends on whether the sensing surface can reliably capture sparse uranyl ions and produce a strong signal, even when other substances are present. A surface that loses effectiveness after one use also increases the effort and cost of repeated monitoring.
A study ( DOI:10.48130/scm-0026-0023 ) published in Sustainable Carbon Materials on 27 July 2026 by Zhenli Sun's team, North China Electric Power University, reports a regenerable sensor that concentrates uranyl ions for Raman measurement and supports automated identification of their spectral signature.
To build the sensor, the team coated magnetic iron oxide particles with silica and attached gold nanoparticles to their surfaces. They then added a covalent organic polymer layer, producing a material called FA@tPF. The magnetic core lets the particles be collected with a magnet; the polymer helps capture uranyl; and the gold nanoparticles amplify Raman signals from material brought close to their surfaces. Microscopy and chemical analyses confirmed the layered structure, while measurements showed that the finished particles retained their magnetic response. In a test using standard uranyl solutions, the researchers mixed the sensor with water, collected it magnetically, and measured its Raman spectrum with a portable instrument. A characteristic signal near 850 inverse centimeters remained detectable down to 1×10 -7 moles per liter after 20 minutes. The signal also tracked concentration across the tested range from 1×10 -7 to 1×10 -4 moles per liter. By comparison, particles without the polymer layer produced no identifiable uranyl peak even at 1×10 -4 moles per liter. A flow-cell experiment, designed to test enrichment from moving water, reached the same detection limit after 20 minutes. Common coexisting ions had little effect on the uranyl signal in the interference tests. The team also released captured uranyl using a sodium carbonate solution: the characteristic peak disappeared after cleaning and returned when the particles captured uranyl again. It remained detectable through six cycles, although its intensity declined slightly. Finally, the researchers analyzed the spectra with principal component analysis and a convolutional neural network. The model achieved 100% classification accuracy on the reported dataset, and an interpretation method showed that its decisions relied chiefly on the uranyl-associated peak near 850 inverse centimeters.
Together, the findings show how chemical capture, magnetic enrichment, Raman measurement, and spectral analysis can be combined in one reusable platform. The results point toward portable uranyl monitoring, while performance across a wider range of real environmental samples remains to be established.
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References
DOI
Original Source URL
https://doi.org/10.48130/scm-0026-0023
Funding information
This work was supported by the National Natural Science Foundation of China (Grant No. U21A20290).
About Sustainable Carbon Materials
Sustainable Carbon Materials (e-ISSN 3070-3557) is a multidisciplinary platform for communicating advances in fundamental and applied research on carbon-based materials. It is dedicated to serving as an innovative, efficient and professional platform for researchers in the field of carbon materials around the world to deliver findings from this rapidly expanding field of science. It is a peer-reviewed, open-access journal that publishes review, original research, invited review, rapid report, perspective, commentary and correspondence papers.
Sustainable Carbon Materials
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Reusable magnetic SERS platform functionalized with covalent organic polymers for trace-level and machine-learning-assisted uranyl detection
27-Jul-2026
The authors declare that they have no competing interests.