Dense nanocrystalline UO2+x fuel pellets synthesized by high pressure spark plasma sintering

Nanocrystalline UO2+x powders are prepared by high‐energy ball milling and subsequently consolidated into dense fuel pellets (>95% of theoretical density) under high pressure (750 MPa) by spark plasma sintering at low sintering temperatures (600°C‐700°C). The grain size achieved in the dense nano...

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Bibliographic Details
Published in:Journal of the American Ceramic Society Vol. 101; no. 3; pp. 1105 - 1115
Main Authors: Yao, Tiankai, Scott, Spencer M., Xin, Guoqing, Gong, Bowen, Lian, Jie
Format: Journal Article
Language:English
Published: Columbus Wiley Subscription Services, Inc 01-03-2018
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Summary:Nanocrystalline UO2+x powders are prepared by high‐energy ball milling and subsequently consolidated into dense fuel pellets (>95% of theoretical density) under high pressure (750 MPa) by spark plasma sintering at low sintering temperatures (600°C‐700°C). The grain size achieved in the dense nano‐ceramic pellets varies within 60‐160 nm as controlled by sintering temperature and duration. The sintered fuel pellets are single phase UO2+x with hyper‐stoichiometric compositions as derived by X‐ray diffraction, and micro‐Raman measurements indicate that random oxygen interstitials and Willis clusters dominate the single phase nano‐sized oxide pellets of UO2.03 and UO2.11, respectively. The thermal conductivities of the densified nano‐sized oxide fuel pellets are measured by laser flash, and the fuel stoichiometry displays a dominant effect in controlling thermal transport properties. A reduction in thermal conductivity is also observed for the dense nano‐sized pellets as compared with micron‐sized counterparts reported in the literature. The correlation among the SPS sintering parameters—microstructure control—properties is established, and the nano‐sized UO2+x pellets with controlled microstructure can serve as the model systems for fundamental understandings of fuel behaviors and obtaining critical experimental data for multi‐physics MARMOT model validation.
ISSN:0002-7820
1551-2916
DOI:10.1111/jace.15289