Publications

1. Simulation analysis on the irradiation effect of hydrogen ions on the electrostatic residual ion dump in NNBI

Published in Radiation Effects and Defects in Solids, 2025

Status: Minor revision submitted, awaiting final decision.

2. Immobilization of uranium tailings by phosphoric acid-based geopolymer with optimization of machine learning

Published in Journal of Radioanalytical and Nuclear Chemistry, 2022

To decrease the contaminant leaching and radon exhalation from uranium tailings, a phosphoric acid-based geopolymer (PAG) precursor was selected as a solidifying agent to bind coarse sands to achieve compact structures. Machine learning was applied to explore the optimal ratio of geopolymer preparation, aimed at achieving a higher compressive strength of solidified bodies. Results showed that the maximum compressive strength of 18.964 MPa appeared at the mass ratio of 2.8 for phosphoric acid/kaolin. The uranium leaching rate of 0.70 × 10−6 cm/d on the 42nd day was three orders of magnitude less than the clay mixture-based geopolymer solidified bodies. The successful synthesis of geopolymer was evidenced by the X-ray diffraction (XRD) and Fourier transform infrared spectroscopy (FTIR), the homogeneous and dense structure of solidified bodies was characterized by the scanning electron microscopy (SEM).

Recommended citation: Zhao T, Wu H, Sun J, et al. Immobilization of uranium tailings by phosphoric acid-based geopolymer with optimization of machine learning[J]. Journal of Radioanalytical and Nuclear Chemistry, 2022, 331(9): 4047-4054.
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