A tabela periódica dos elementos químicos prevista por redes neurais artificiais de Kohonen

• Autor(a) principal: Lemes,Maurício Ruv
• Data de Publicação: 2008
• Outros Autores: Pino Júnior,Arnaldo Dal
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Química Nova (Online)
• Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-40422008000500040
• topic: periodic table; neural networks; Kohonen neural network

Although several chemical elements were not known by end of the 18th century, Mendeleyev came up with an astonishing achievement: the periodic table of elements. He was not only able to predict the existence of (then) new elements but also to provide accurate estimates of their chemical and physical properties. This is certainly a relevant example of the human intelligence. Here, we intend to shed some light on the following question: Can an artificial intelligence system yield a classification of the elements that resembles, in some sense, the periodic table? To achieve our goal, we have fed a self-organized map (SOM) with information available at Mendeleyev's time. Our results show that similar elements tend to form individual clusters. Thus, SOM generates clusters of halogens, alkaline metals and transition metals that show a similarity with the periodic table of elements.