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Application of Statistical Methods in Predicting the Properties of Glass-Ceramic Materials Obtained from Inorganic Solid Waste
This paper uses mathematical methods as the basic tool at the stage of experiment planning. The importance of research programming applications was shown using the theory of experiments and the STATISTICA software. The method of experiment planning used in the case of studying the properties of a mi...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8158504/ https://www.ncbi.nlm.nih.gov/pubmed/34070197 http://dx.doi.org/10.3390/ma14102651 |
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author | Zawada, Anna Przerada, Iwona Lubas, Małgorzata Sitarz, Maciej Leśniak, Magdalena |
author_facet | Zawada, Anna Przerada, Iwona Lubas, Małgorzata Sitarz, Maciej Leśniak, Magdalena |
author_sort | Zawada, Anna |
collection | PubMed |
description | This paper uses mathematical methods as the basic tool at the stage of experiment planning. The importance of research programming applications was shown using the theory of experiments and the STATISTICA software. The method of experiment planning used in the case of studying the properties of a mixture, depending on its composition, features considerable complexity. The aim of the statistical analysis was to determine the influence of variable chemical composition of waste materials on selected properties of glass-ceramic materials. A statistical approach to multicomponent systems, such as ceramic sets, enables the selection of appropriate amounts of raw materials through the application of ‘a plan for mixtures’. To utilize the raw waste materials, e.g., slags from a solid waste incinerator, fly or bottom ashes, in the modeling of new materials, a mathematical relationship was developed, which enables estimating, based on the waste chemical composition, selected technological and practical properties of the glass so as to obtain a material featuring the required technological–practical parameters. For the obtained glasses, a comparative analysis of the experimentally and computationally determined properties was carried out: transformation temperature, liquidus temperature, density, and thermal expansion coefficient. The obtained high theoretical approximation (at the level of determination correlation coefficient R(2) > 0.8) confirms the suitability of the polynomial model for mixtures for applications in the design of new glass-ceramic products. |
format | Online Article Text |
id | pubmed-8158504 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-81585042021-05-28 Application of Statistical Methods in Predicting the Properties of Glass-Ceramic Materials Obtained from Inorganic Solid Waste Zawada, Anna Przerada, Iwona Lubas, Małgorzata Sitarz, Maciej Leśniak, Magdalena Materials (Basel) Article This paper uses mathematical methods as the basic tool at the stage of experiment planning. The importance of research programming applications was shown using the theory of experiments and the STATISTICA software. The method of experiment planning used in the case of studying the properties of a mixture, depending on its composition, features considerable complexity. The aim of the statistical analysis was to determine the influence of variable chemical composition of waste materials on selected properties of glass-ceramic materials. A statistical approach to multicomponent systems, such as ceramic sets, enables the selection of appropriate amounts of raw materials through the application of ‘a plan for mixtures’. To utilize the raw waste materials, e.g., slags from a solid waste incinerator, fly or bottom ashes, in the modeling of new materials, a mathematical relationship was developed, which enables estimating, based on the waste chemical composition, selected technological and practical properties of the glass so as to obtain a material featuring the required technological–practical parameters. For the obtained glasses, a comparative analysis of the experimentally and computationally determined properties was carried out: transformation temperature, liquidus temperature, density, and thermal expansion coefficient. The obtained high theoretical approximation (at the level of determination correlation coefficient R(2) > 0.8) confirms the suitability of the polynomial model for mixtures for applications in the design of new glass-ceramic products. MDPI 2021-05-18 /pmc/articles/PMC8158504/ /pubmed/34070197 http://dx.doi.org/10.3390/ma14102651 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Zawada, Anna Przerada, Iwona Lubas, Małgorzata Sitarz, Maciej Leśniak, Magdalena Application of Statistical Methods in Predicting the Properties of Glass-Ceramic Materials Obtained from Inorganic Solid Waste |
title | Application of Statistical Methods in Predicting the Properties of Glass-Ceramic Materials Obtained from Inorganic Solid Waste |
title_full | Application of Statistical Methods in Predicting the Properties of Glass-Ceramic Materials Obtained from Inorganic Solid Waste |
title_fullStr | Application of Statistical Methods in Predicting the Properties of Glass-Ceramic Materials Obtained from Inorganic Solid Waste |
title_full_unstemmed | Application of Statistical Methods in Predicting the Properties of Glass-Ceramic Materials Obtained from Inorganic Solid Waste |
title_short | Application of Statistical Methods in Predicting the Properties of Glass-Ceramic Materials Obtained from Inorganic Solid Waste |
title_sort | application of statistical methods in predicting the properties of glass-ceramic materials obtained from inorganic solid waste |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8158504/ https://www.ncbi.nlm.nih.gov/pubmed/34070197 http://dx.doi.org/10.3390/ma14102651 |
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