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 SiO2, B2O3, Na2O, Fe2O3, 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.

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