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Radioactive Waste Immobilization Using Vitreous Materials for Facilities in a Safe and Resilient Infrastructure Classified by Multivariate Exploratory Analyses.

Authors :
Nascimento, Marcio Luis Ferreira
Cassar, Daniel Roberto
Ciolini, Riccardo
de Souza, Susana Oliveira
d'Errico, Francesco
Source :
Infrastructures; Sep2022, Vol. 7 Issue 9, pN.PAG-N.PAG, 20p
Publication Year :
2022

Abstract

A database of 479 glass formulations used to immobilize radioactive wastes for facilities in a safe and resilient infrastructure was analyzed, searching for underlying statistical patterns and associated glass performance features. The analyzed data cover many oxides, including SiO<subscript>2</subscript>, B<subscript>2</subscript>O<subscript>3</subscript>, Na<subscript>2</subscript>O, Fe<subscript>2</subscript>O<subscript>3</subscript>, and some fluorides. Borosilicates were the most common glasses (60.1%), while silicates were only 11.9%. In addition to these two families, five radioactive waste vitrification matrices were identified: Boroaluminosilicates, iron phosphates, aluminosilicates, sodium iron phosphates, and boroaluminates, totaling seven glass families. Almost all compositions (97.7%) contained sodium oxide, followed by silica (91.4%), iron (82.7%), boron (73.7%), phosphorus (54.9%), and cesium oxides (26.1%). Multivariate exploratory methods were applied to analyze and classify glass compositions using hierarchical and non-hierarchical (K-means) clusters and principal component analysis. Four main clusters were observed, the largest comprising 417 formulations containing mainly silicates, borosilicates, aluminosilicates, and boroaluminosilicates; two principal components, representing 73.75% of all compositions, emerge from these four clusters derived from a covariance analysis. The principal components and four clusters may be associated with the following glass features in terms of glass compositions: liquidus temperature, glass transition temperature, density, resistivity, microhardness, and viscosity. Some general underlying properties emerged from our classification and are discussed. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
24123811
Volume :
7
Issue :
9
Database :
Complementary Index
Journal :
Infrastructures
Publication Type :
Academic Journal
Accession number :
159301552
Full Text :
https://doi.org/10.3390/infrastructures7090120