Abstract

—The aim of the present study was to discriminate between distinct types of clay units by applying multivariate statistical techniques, which have seldom been applied to the exploitation of ceramic clays. At the outcrop scale, texturally similar argillaceous or clayey layers of different ceramic types cannot be effectively distinguished, which can result in the misuse and loss of raw materials. Representative samples of clayey raw materials from central Portugal Cenozoic deposits with potential use in the manufacture of structural clay products were first assessed for granulometric, mineralogical, chemical, and technological properties. Based on those properties and the use of multivariate statistical techniques, i.e., factor analysis (FA) and cluster analysis (CA), a novel statistical approach that combined all these variable properties was produced. This approach made it possible to distinguish the ceramic suitability and perceive which parameters most influence that suitability. The use of R-mode FA made it feasible to differentiate and group samples based on the most influential variables: the contents of Al2O3, Fe, illite, quartz, feldspars, and K2O. The use of R-mode CA substantiated the FA results in the identification of influential variables, such as Al2O3, Fe, and illite. The use of Q-mode CA established two main clusters: clayey-silt samples and sandy and/or feldspathic samples, the clayey-silt samples encompassed three sub-clusters. These three sub-clusters match ceramic types with different suitabilities and relate sample stratigraphic setting to the encompassing stratigraphic units. Diagrams that relate the grain size, the content of different oxides, the content of different minerals, and the plasticity to the ceramic suitability illustrate the CA groupings. An adequate blend of sand and clay for red stoneware (bricks and tiles) manufacture was indicated as a major requirement for most raw materials of the clayey-silt cluster. Raw materials represented by the sandy and/or feldspathic cluster can either be used to blend with materials that lack sand or to blend with excessively plastic samples.

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