Statistically Designed Optimization of a Glass Composition

An efficient, statistically based methodology for development and optimization of multicomponent materials is presented. The approach is illustrated with a five‐component nuclear waste glass. A composition field is defined, test compositions are statistically chosen, and their measured property data...

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Bibliographic Details
Published in:Journal of the American Ceramic Society 1984-11, Vol.67 (11), p.763-768
Main Authors: CHICK, L. A., PIEPEL, G. F.
Format: Article
Language:English
Subjects:
Applied sciences
Building materials. Ceramics. Glasses
Chemical industry and chemicals
Exact sciences and technology
Glasses
Structure, analysis, properties
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Summary:An efficient, statistically based methodology for development and optimization of multicomponent materials is presented. The approach is illustrated with a five‐component nuclear waste glass. A composition field is defined, test compositions are statistically chosen, and their measured property data are used to fit empirical models. These models are then used to predict the optimum composition. The following nuclear waste glass components were investigated: SiO2, B2O3, Na2O, CaO, and simulated nuclear waste. The following properties were modeled: viscosity, chemical durability, and crystallinity. Successful models were constructed by using data from 27 test melts. This methodology could be applied to a wide range of ceramic mixture problems.
ISSN:0002-7820
1551-2916
DOI:10.1111/j.1151-2916.1984.tb19514.x