The oxidative kinetics of uranium at different stages

Wang, Shuaipeng; Li, Haibo; Gan, Li; Tang, Tao; Gu, Yuejiao; Hu, Yin; Chen, Xianglin; Wang, Yun; Lv, Junbo; Luo, Wenhua

doi:10.1016/j.corsci.2022.110487

Cited by 6 publications

(2 citation statements)

References 25 publications

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“…The UO 2 → U 4 O 9 transition is still an exothermic process with a moderate amount of released heat (0.19−0.39 eV/cation), and the U 4 O 9 → U 3 O 7 transition may be a mild exothermic or endothermic process associated with a small amount of energy change (−0.06−0.14 eV/cation). Therefore, when the kinetics is sufficiently activated (e.g., by heating), 1,5,9,[15][16][17]101,108 these metastable oxide phases will not hinder the oxidation process from UO 2 to U 3 O 8 . The associated microscopic kinetic mechanisms therein (e.g., defect diffusion and lattice transformation) still require more firstprinciples calculations in the future, for which the accurate thermodynamic energies here, as well as the accurate electronic structures discussed above (Figure 4), can be used as the stringent references to calibrate the theoretical methods to be used.…”

Section: = | |=mentioning

confidence: 99%

Environmental Stability of Actinide Oxides Mapped by Integrated and Accurate First-Principles Calculations

Sun,

Ye,

Zhang

et al. 2024

J. Phys. Chem. C

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The synthesis, storage, application, and disposal of various actinide materials in the fields of nuclear-fuel-based clean energy and actinide-metal-based metallurgy always closely correlate with the stabilities of U and Pu oxides in many atmospheric and aqueous environments. It is technologically important to jointly evaluate both the thermodynamic and electrochemical stabilities of actinide oxides there, for which free energy of formation (Δf G) is the key physical quantity. Due to various unavoidable technical and physical challenges in experiments, the Δf G data for these polyvalent oxides have long-standing inaccurate and incomplete problems. Here, we design an integrated first-principles approach to carry out efficient structural screenings, accurate energetic calculations by considering both the exact electronic potential and phononic contribution, and reliable mappings of the thermodynamic and electrochemical phase diagrams for anhydrous and hydrous actinide oxides in different environments (e.g., dry air, humid air, and aqueous solution). Based on the accurate and complete stability-composition-environment relationships constructed here, the established thermodynamic and electrochemical understandings can successfully explain versatile experimental observations on the hydration, oxidation, and corrosion behaviors of actinide oxides. Finally, the isotope effects on Δf G values are quantitatively predicted, revealing that any oxide will have nearly the same stability in environments with light and heavy waters. The systematically accurate electronic structure, thermodynamic stability, and electrochemical stability of actinide oxides as obtained in this work can provide many related theoretical and experimental studies in the future with reliable and desirable numerical references, as well as the comprehensively revealed physical and chemical mechanisms.

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Section: = | |=mentioning

confidence: 99%

Environmental Stability of Actinide Oxides Mapped by Integrated and Accurate First-Principles Calculations

Sun,

Ye,

Zhang

et al. 2024

J. Phys. Chem. C

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“…Wang et al [ 4 ] investigated the oxidative performance of U–2.5Nb alloys at different temperatures in air using the thick weight and weight gain methods. Wang et al [ 5 ] researched the oxidation kinetics of uranium at different times by using a combination of oxygen depletion and reflectance spectroscopy methods. The above studies were instructive for the data collection and study of corrosion mechanisms of uranium and uranium alloys in this paper.…”

Section: Introductionmentioning

confidence: 99%

A Machine Learning Method for Predicting Corrosion Weight Gain of Uranium and Uranium Alloys

et al. 2023

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As an irreplaceable structural and functional material in strategic equipment, uranium and uranium alloys are generally susceptible to corrosion reactions during service, and predicting corrosion behavior has important research significance. There have been substantial studies conducted on metal corrosion research. Accelerated experiments can shorten the test time, but there are still differences in real corrosion processes. Numerical simulation methods can avoid radioactive experiments, but it is difficult to fully simulate a real corrosion environment. The modeling of real corrosion data using machine learning methods allows for effective corrosion prediction. This research used machine learning methods to study the corrosion of uranium and uranium alloys in air and established a corrosion weight gain prediction model. Eleven classic machine learning algorithms for regression were compared and a ten-fold cross validation method was used to choose the highest accuracy algorithm, which was the extra trees algorithm. Feature selection methods, including the extra trees and Pearson correlation analysis methods, were used to select the most important four factors in corrosion weight gain. As a result, the prediction accuracy of the corrosion weight gain prediction model was 96.8%, which could determine a good prediction of corrosion for uranium and uranium alloys.

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UH3 produced at the initial stage of U-H2O corrosion

Wang

Gan

et al. 2023

Corrosion Science

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The oxidative kinetics of uranium at different stages

Cited by 6 publications

References 25 publications

Environmental Stability of Actinide Oxides Mapped by Integrated and Accurate First-Principles Calculations

Environmental Stability of Actinide Oxides Mapped by Integrated and Accurate First-Principles Calculations

A Machine Learning Method for Predicting Corrosion Weight Gain of Uranium and Uranium Alloys

UH3 produced at the initial stage of U-H2O corrosion

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