Pseudo-classification of natural elements and atomic total energy prediction

Abstract

Abstract Technological development requires the search for new materials with specific properties. Moreover, the forecasting of physical and chemical compound formation and proprieties can be based on Datamining methods. In this paper, one of the unsupervised methods of Datamining is used, like Principal Component Analysis (PCA). The first goal is to make pseudo-classification of natural and synthetic elements of the periodic table based on all physicochemical and energy available properties. Likewise, the second goal is to test the effectiveness of this statistical method to estimate correlations and appreciate the relationships between the variables and properties. A pseudo-classification of periodic elements is a new way of seeing Mendeleev's table. At the end of this work, a predictive polynomial has been presented that can allow the scientific community to make atomic total energy predictions for each natural periodic element, from Z=2 to Z=103.