Uranium detection by 3D-printed titanium structures: Towards decentralized nuclear forensic applications

Veronika Urbanová, Martin Pumera

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

Uranium can cause significant pollution of the ecosystem as well as it can have immense hazardous effect on human health due to its chemical and radioactive toxicity. Uranyl ions (UO22+) are considered as the most common and stable ionic form of uranium and additionally, UO22+ can spread easily through the environment owing to their high solubility and mobility in water. Hence, the development of appropriate sensors for UO22+ detection is very important for in time revelation of potentially dangerous sources of water or soil contamination. 3D-printing technology is now recognized as effective tool for designing and manufacturing objects of different sizes and shapes. Thus, it might also offer customized solution for design of electrodes to be applied in environmental sensing. In this work, 3D-printed titanium electrode was evaluated toward uranyl ions determination in aqueous samples. This electrode revealed good liner response within the wide concentration range, high stability as well as reproducibility. Good analytical performance of 3D-Ti electrode was further confirmed by low detection limit of 24.5 µg L−1 that also meets the requirement of Maximum Contaminant Level (MCL) for uranium in drinking water (30 µg L−1). The performance of 3D-Ti electrode was also evaluated for its capability of UO22+ determination in spiked tap and mineral water. All results presented in this work, encourage and highlight the exploitation of 3D-printing technology for electrochemical sensing applications since it has strong potential for environmental, nuclear forensic and security applications.

Original languageEnglish
Article number100881
JournalApplied Materials Today
Volume21
DOIs
Publication statusPublished - 2020 Dec

Bibliographical note

Funding Information:
This work was supported by the project Advanced Functional Nanorobots (reg. No. CZ.02.1.01/0.0/0.0/15_003/0000444 financed by the EFRR).

Publisher Copyright:
© 2020 Elsevier Ltd

All Science Journal Classification (ASJC) codes

  • Materials Science(all)

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